TY - CONF A1 - Wosniok, Aleksander T1 - Distributed polymer optical fiber sensors using digital I-OFDR for geotechnical infrastructure health monitoring N2 - We present a distributed polymer optical fiber sensor system for deformation monitoring of geotechnical infrastructure. The sensor system is based on the digital incoherent optical frequency domain reflectometry (I-OFDR) for the detection of local strain events along a perfluorinated polymer optical fiber (PF-POF) used as a sensing fiber. For the best possible load transfer, the PF-POFs were integrated onto geosynthetics which pose a sensor carrier for the sensing fiber. By using elastic PF-POF instead of a standard glass fiber as a sensing fiber the strain range of geosynthetics-integrated fiber optic sensors could be extended up to 10 % in accordance with the end-user requirements. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Digital I-OFDR KW - Distributed polymer optical fiber sensor KW - Distributed strain sensing KW - Smart geosynthetics KW - Structural health monitoring PY - 2024 AN - OPUS4-60308 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander T1 - Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels N2 - We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for automotive use. The paper deals with the condition monitoring of such composite pressure vessels (CPVs) using the optical backscatter reflectometry (OBR) applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the polymer liner during the manufacturing process of the carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors can be an opportunity for monitoring the material degradation of CPVs under static and cyclic loading. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Fiber optic sensor KW - Distributed strain sensing KW - Composite pressure vessel KW - Structural health monitoring KW - Fiber-reinforced plastics PY - 2024 AN - OPUS4-60307 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Schukar, Marcus A1 - Woody, Paul A1 - Wang, Bin A1 - Breithaupt, Mathias A1 - Kriegsmann, Andreas T1 - Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels N2 - We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for automotive use. The paper deals with the condition monitoring of such composite pressure vessels (CPVs) using the optical backscatter reflectometry (OBR) applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the polymer liner during the manufacturing process of the carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors can be an opportunity for monitoring the material degradation of CPVs under static and cyclic loading. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Fiber optic sensor KW - Distributed strain sensing KW - Composite pressure vessel KW - Structural health monitoring KW - Fiber-reinforced plastics PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-603105 SP - 1 EP - 8 PB - NDT.net AN - OPUS4-60310 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Königsbauer, Korbinian A1 - Nöther, Nils A1 - Färber, Jan A1 - Schaller, M.-Barbara A1 - Krebber, Katerina T1 - Distributed polymer optical fiber sensors using digital I-OFDR for geotechnical infrastructure health monitoring N2 - We present a distributed polymer optical fiber sensor system for deformation monitoring of geotechnical infrastructure. The sensor system is based on the digital incoherent optical frequency domain reflectometry (I-OFDR) for the detection of local strain events along a perfluorinated polymer optical fiber (PF-POF) used as a sensing fiber. For the best possible load transfer, the PF-POFs were integrated onto geosynthetics which pose a sensor carrier for the sensing fiber. By using elastic PF-POF instead of a standard glass fiber as a sensing fiber the strain range of geosynthetics-integrated fiber optic sensors could be extended up to 10 % in accordance with the end-user requirements. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Digital I-OFDR KW - Distributed polymer optical fiber sensor KW - Ddistributed strain sensing KW - Smart geosynthetics KW - Structural health monitoring PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-603096 SP - 1 EP - 7 PB - NDT.net AN - OPUS4-60309 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos A1 - Heimann, Jan A1 - Duffner, Eric A1 - Charmi, Amir A1 - Schukar, Marcus A1 - Hashemi, Seyedreza A1 - Prager, Jens T1 - Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data fusion and digital twin modeling N2 - Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Acoustic emission KW - Ultrasonic guided waves KW - Fiber optic sensors KW - Hydrogen KW - Pressure vessels KW - Structural health monitoring KW - Machine learning PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-602764 UR - https://www.ndt.net/search/docs.php3?id=29702 SP - 1 EP - 8 PB - NDT.net AN - OPUS4-60276 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos A1 - Schukar, Marcus A1 - Breithaupt, Mathias A1 - Duffner, Eric A1 - Ulbricht, Alexander A1 - Prager, Jens A1 - Krebber, Katerina T1 - Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing N2 - We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Hydrogen KW - Fiber optic sensors KW - Composites KW - Machine learning KW - Structural health monitoring PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-602731 UR - https://www.ndt.net/search/docs.php3?id=29701 SP - 1 EP - 7 PB - NDT.net AN - OPUS4-60273 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data fusion and digital twin modeling N2 - Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Hydrogen KW - Ultrasonic guided waves KW - Fiber optic sensors KW - Acoustic emission KW - Machine learning KW - Pressure vessels KW - Structural health monitoring PY - 2024 AN - OPUS4-60277 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing N2 - We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Hydrogen KW - Composites KW - Pressure vessels KW - Fiber optic sensors KW - Machine learning KW - Structural health monitoring PY - 2024 AN - OPUS4-60275 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ghasem Zadeh Khorasani, Media T1 - Federated SHM: a Novel Collaborative ML Approach to Overcome Data Scarcity and Data Privacy Concerns in StructuralHealth Monitoring N2 - The deployment of machine learning (ML) and deep learning (DL) in structural health monitoring (SHM) faces multiple challenges. Foremost among these is the insufficient availability of extensive high-quality data sets essential for robust training. Within SHM, high-quality data is defined by its accuracy, relevance, and fidelity in representing real-world structural scenarios (pristine as well as damaged). Although methods like data augmentation and creating synthetic data can add to datasets, they frequently sacrifice the authenticity and true representation of the data. Sharing real-world data encapsulating true structural and anomalous scenarios offers promise. However, entities are often reluctant to share raw data, given the potential extraction of sensitive information, leading to trust issues among collaborating entities. Our study introduces a novel methodology leveraging Federated Learning (FL) to navigate these challenges. Within the FL framework, models are trained in a decentralized manner across different entities, preserving data privacy. In our research, we simulated several scenarios and compared them to traditional local training methods. Employing guided wave (GW) datasets, we distributed the data among different parties (clients) using IID (independent, identically distributed or in other words, statistically identical) mini batches of dataset, as well as non-IID configurations. This approach mirrors real-world data distribution among varied entities, such as hydrogen refueling stations. In our methodology, the initial round involves individualized training for each client using their unique datasets . Subsequently, the model parameters are sent to the FL server, where they are averaged to construct a global model. In the second round, this global model is disseminated back to the clients to aid in predictive tasks. This iterative process continues for several rounds to reach convergence. Our findings distinctly highlight the advantages of FL over localized training, evidenced by a marked improvement in prediction accuracy . This research underscores the potential of FL in GW-based SHM, offering a remedy to similar challenges tied to data scarcity in other SHM approaches and paving the way for a new era of collaborative, data-centric monitoring systems. T2 - QI Digital Forum CY - Berlin, Germany DA - 10.10.2023 KW - Machine learning KW - Federated learning KW - Structural health monitoring KW - Artificial intelligence KW - Hydrogen safety KW - Data privacy PY - 2023 AN - OPUS4-59415 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos ED - Krebber, Katerina T1 - Machine learning for strain, temperature and humidity discrimination in Brillouin optical frequency domain analysis N2 - We propose to our knowledge for the first time an ensemble of probabilistic machine learning models for strain, temperature and humidity discrimination in Brillouin optical frequency domain analysis (BOFDA) applying a two-fiber configuration. T2 - 28th International Conference on Optical Fiber Sensors CY - Hamamatsu, Japan DA - 20.11.2023 KW - Multiparameter sensing KW - Machine learning KW - Fiber optic sensors KW - Structural health monitoring PY - 2023 SP - 1 EP - 4 PB - Optica Publishing Group AN - OPUS4-59397 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Machine learning for strain, temperature and humidity discrimination in Brillouin optical frequency domain analysis N2 - We propose to our knowledge for the first time an ensemble of probabilistic machine learning models for strain, temperature and humidity discrimination in Brillouin optical frequency domain analysis (BOFDA) applying a two-fiber configuration. T2 - 28th International Conference on Optical Fiber Sensors CY - Hamamatsu, Japan DA - 20.11.2023 KW - Multiparameter sensing KW - Fiber optic sensors KW - Machine learning KW - Structural health monitoring PY - 2023 AN - OPUS4-59396 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Niederleithinger, Ernst T1 - ridge Monitoring by Ultrasonic Coda Wave Interferometry N2 - The built infrastructure ages and requires regular inspection and, when in doubt, monitoring. To ensure that older concrete bridges showing signs of deterioration can be used safely, several innovative monitoring tools have been introduced, including but not limited to optical, fiber-optic, or acoustic emission techniques. However, there are gaps in the portfolio. A sensing technique that covers a wide range of damage scenarios and larger volumes, while still being sensitive and specific, would be beneficial. For about 15 years, research has been conducted on ultrasonic monitoring of concrete structures that goes beyond the traditional ultrasonic pulse velocity test (PV test), mostly using a very sensitive data evaluation technique called coda wave interferometry. At BAM we have developed sensors and instrumentation specifically for this method. We have instrumented a 70-year-old, severely damaged prestressed concrete bridge in Germany in addition to a commercial monitoring system. We have now collected data for almost 3 years. We can show that we can provide information about the stress distribution in the bridge. We have also been able to confirm that there has been no significant additional damage to the bridge since the installation. T2 - ISNT NDE 2023 CY - Pune, India DA - 07.12.2023 KW - Coda wave interferometry KW - Structural health monitoring KW - Ultrasound KW - Concrete KW - Bridges PY - 2023 AN - OPUS4-59346 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Bartolac, M. A1 - Bien, J. A1 - Górski, M. A1 - Keßler, S. A1 - Küttenbaum, Stefan A1 - Kuzawa, M. A1 - Ley, J. A1 - Maack, Stefan A1 - Mendler, A. A1 - Ryjáček, P. A1 - Santos, L. A1 - Verstrynge, E. ED - Keßler, S. ED - Limongelli, M. P. ED - Apostolidi, E. T1 - Chapter 2: Condition survey - Testing and monitoring methods N2 - The through-life management of our constantly ageing infrastructure is a basic requirement in order to ensure their structural safety and serviceability. Each structure experiences deterioration processes with time leading to a decrease of structural safety and serviceability. The design of new structures considers the expected deterioration for a defined period, the design service life. However, a frequent survey of structural safety controlling structural condition should be mandatory and a maintenance plan should be an integral part of the design. In addition, many structures have exceeded their design service life already or are very close to it leading to an increasing demand for condition assessment. On the one hand, assumptions made during design are not valid any more due to change of the loads, e.g., increasing traffic loads in terms of number and weights. On the other hand, design codes evolved over time in such a way that existing structures do not comply with today’s standards. In all these cases, the through-life management is an important tool to maintain the accessibility of existing structures with known reliability. In line with the new Model Code for Concrete Structures, which includes guidance for both – design of new structures and assessment of existing structures, the Task Group 3.3 focused on the compilation of a state-of-the-art guideline for the through-life management of existing concrete structures, including: Data acquisition by testing and monitoring techniques; Condition assessment for the evaluation of existing structures; Performance prediction using advanced methods; Decision-making procedures to perform a complete assessment of existing structure. The overall objective of the through-life management is the assessment of the current condition and the estimation of the remaining service life under consideration of all boundary conditions. KW - Life management KW - Concrete KW - Non-destructive testing KW - Structural health monitoring KW - State-of-the-art PY - 2023 UR - https://doi.org/10.35789/fib.BULL.0109 SN - 978-2-88394-172-4 DO - https://doi.org/10.35789/fib.BULL.0109.Ch02 SN - 1562-3610 VL - fib Bulletin 109 SP - 16 EP - 38 PB - Fédération internationale du béton (fib) CY - Lausanne AN - OPUS4-59110 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yilmaz, Bengisu A1 - Heimann, Jan A1 - Mustapha, S. A1 - Charmi, Amir A1 - Prager, Jens T1 - Guided wave ultrasonic feature determination in Type IV composite overwrapped pressure vessels towards the digital twin N2 - The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations. T2 - 13th European Conference on Non-Destructive Testing (ECNDT) CY - Lisbon, Portugal DA - 03.07.2023 KW - Industry 4.0 KW - Composite overwrapped pressure vessels KW - Structural health monitoring KW - Ultrasonic guided waves KW - Predictive maintenance PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-591094 DO - https://doi.org/10.58286/28072 SN - 2941-4989 VL - 1 IS - 1 SP - 1 EP - 6 PB - NDT.net CY - Mayen AN - OPUS4-59109 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Charmi, Amir A1 - Mustapha, Samir A1 - Yilmaz, Bengisu A1 - Heimann, Jan A1 - Prager, Jens T1 - A Machine Learning Based-Guided Wave Approach for Damage Detection and Assessment in Composite Overwrapped Pressure Vessels N2 - The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy. T2 - 13th European Conference on Non-Destructive Testing (ECNDT) 2023 CY - Lisbon, Portugal DA - 03.07.2023 KW - Machine learning KW - Structural health monitoring KW - COPV KW - Guided waves KW - Damage localization PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-590789 DO - https://doi.org/10.58286/28079 SN - 2941-4989 VL - 1 IS - 1 SP - 1 EP - 6 PB - NDT.net CY - Mayen AN - OPUS4-59078 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander T1 - POF-based monitoring system using digital I-OFDR for strain detection in road construction N2 - We present a prototype of a distributed POF sensing system for strain detection in road construction and civil engineering ready to be used in practical applications. The system is based on a cost-efficient digital incoherent optical frequency domain reflectometry (I-OFDR). In this approach, the strain-induced changes in the Rayleigh backscattering profile along a perfluorinated polymer optical fiber (PF-POF) are determined by measuring the complex transfer function of the sensing fiber using a compact digital data acquisition unit. The digital unit replaces an oversized vector network analyzer (VNA) enabling suitability of the measurement system for out-door use and providing a significant reduction of the total system costs at the same time. The entire sensor con-cept includes the use of geosynthetics with integrated PF-POFs as two-dimensional sensor structures for geotech-nical applications. The robustness and the functionality of the distributed POF I-OFDR sensors were proven in the field. The field test involved embedding of two geomats, each with two polymer optical sensor loops, into the embankment of the federal road B 91 in a section near Leipzig. The measurements conducted after the sensor-based geomats had been installed confirmed both the potential of such smart geosynthetics and the functionali-ty of the digital I-OFDR prototype. T2 - POF2023 CY - Cork, Irland DA - 17.09.2023 KW - Digital I-OFDR KW - Distriubuted polymer optical fiber sensor KW - Smart geosynthetics KW - Strain detection KW - Structural health monitoring PY - 2023 AN - OPUS4-58423 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Krebber, Katerina T1 - Novel fading suppression method for distributed optical fiber acoustic sensing N2 - A universal method based on alternating pulse widths is proposed to suppress the signal fading for all distributed acoustic sensors (DASs) and experimentally demonstrated by one DAS system based on a Mach-Zehnder interferometer. T2 - Optica Sensing Congress CY - Munich, Germany DA - 30.07.2023 KW - Distributed fiber sensing KW - Acoustic sensing KW - Structural health monitoring KW - Fading suppression PY - 2023 AN - OPUS4-58049 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Krebber, Katerina T1 - Novel fading suppression method for distributed optical fiber acoustic sensing N2 - A universal method based on alternating pulse widths is proposed to suppress the signal fading for all distributed acoustic sensors (DASs) and experimentally demonstrated by one DAS system based on a Mach-Zehnder interferometer. T2 - Optica Sensing Congress CY - Munich, Germany DA - 30.07.2023 KW - Distributed fiber sensing KW - Acoustic sensing KW - Fading suppression KW - Structural health monitoring PY - 2023 SP - 1 EP - 2 AN - OPUS4-58048 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Zustandsbewertung von Bauwerken unter veränderlichen Umgebungsbedingungen mittels Structural Health Monitoring N2 - Brücken sind Teil der alternden Verkehrsinfrastruktur. Um die Nutzungsdauer zu verlängern und plötzliche Schäden zu detektieren kann Bauwerksmonitoring ("Structural Health Monitoring") eingesetzt werden. Der Einfluss von Umgebungsbedingungen, beispielsweise der Temperatur, auf das Bauwerksverhalten ist meist größer als der Einfluss von Schäden. Diese Einflüsse bestmöglich voneinander zu trennen und Veränderungen im Tragverhalten korrekt Schäden oder Umgebungsbedingungen zuzuordnen ist eine offene Forschungsfrage. Diese Arbeit zeigt eine mögliche Lösung, bei der gekoppelte Modelle von Umwelteinflüssen, Schäden und Tragverhalten des Bauwerks auf Grundlage von Monitoringdaten aktualisiert werden. Das Framework dazu wird vorgestellt und an einem Laborexperiment eines Stahlbetonbalkens in der Klimakammer angewandt. Die Ergebnisse bestätigen die Vorgehensweise. In nächsten Schritten müssen komplexere Tragwerke und die Sensitivität des Ansatzes untersucht werden. T2 - Forschungskolloquium, Institut für Konstruktiven Ingenieurbau, Bauhaus-Universität Weimar CY - Weimar, Germany DA - 28.06.2023 KW - Structural health monitoring KW - Bauwerksmonitoring KW - Umwelteinflüsse KW - Brücken PY - 2023 AN - OPUS4-58005 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Yilmaz, Bengisu A1 - Heimann, Jan A1 - Mustapha, Samir A1 - Charmi, Amir A1 - Prager, Jens T1 - Guided wave ultrasonic features in composite overwrapped pressure vessels towards digital twin N2 - The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations. T2 - European Conference on Non-Destructive Testing (ECNDT) 2023 CY - Lisbon, Portugal DA - 03.07.2023 KW - NDT4.0 KW - CComposite overwrapped pressure vessels KW - Structural health monitoring KW - Ultrasonic guided waves KW - Predictive maintenance PY - 2023 AN - OPUS4-57950 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Hicke, Konstantin A1 - Krebber, Katerina T1 - Dual-functionality of WS-COTDR for ground movement monitoring N2 - Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system. T2 - European Workshop on Optical Fibre Sensors (EWOFS 2023) CY - Mons, Belgium DA - 23.05.2023 KW - Distributed fiber sensing KW - Acoustic sensing KW - Structural health monitoring PY - 2023 AN - OPUS4-57591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Königsbauer, Korbinian A1 - Wosniok, Aleksander A1 - Nöther, N. A1 - Schaller, M. B. T1 - POF-based digital I-OFDR for strain detection in road construction N2 - We report on the development of a field-proven distributed fiber optic sensing system for structural health monitoring in road construction and civil engineering. The system is based on a cost-efficient digital incoherent optical frequency domain reflectometry (I-OFDR) for distributed strain detection along a polymer optical fiber. In this method, the strain-induced backscatter increase in a graded-index multimode perfluorinated polymer optical fiber (PF-POF) is determined by measuring the complex transfer function of the sensing fiber using a compact digital data acquisition unit. T2 - European Workshop on Optical Fibre Sensors (EWOFS 2023) CY - Mons, Belgium DA - 23.05.2023 KW - Digital I-OFDR KW - Perfluorinated polymer optical fiber KW - Smart geosynthetics KW - Structural health monitoring KW - Road construction KW - Civil engineering PY - 2023 DO - https://doi.org/10.1117/12.2678436 SP - 1264326-1 PB - SPIE AN - OPUS4-57592 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Hicke, Konstantin A1 - Krebber, Katerina T1 - Dual functionality of wavelength scanning coherent optical time domain reflectometer N2 - Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system. T2 - European Workshop on Optical Fibre Sensors (EWOFS 2023) CY - Mons, Belgium DA - 23.05.2023 KW - Structural health monitoring KW - Distributed fiber sensing KW - Acoustic sensing PY - 2023 DO - https://doi.org/10.1117/12.2678098 VL - 12643 SP - 1 EP - 4 PB - SPEI AN - OPUS4-57590 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin T1 - Introduction to group 8.6 N2 - A brief introduction of group 8.6 and the research work on the application of fiber sensing. T2 - DIU Besuch CY - Berlin, Germany DA - 05.05.2023 KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing KW - Practical application PY - 2023 AN - OPUS4-57430 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schnur, C. A1 - Moll, J. A1 - Lugovtsova, Yevgeniya A1 - Schütze, A. A1 - Schneider, T. ED - Kundu, T. ED - Reis, H. ED - Ihn, J.-B. ED - Dzenis, Y. T1 - Explainable Machine Learning for Damage Detection: in Carbon Fiber Composite Plates Under Varying Temperature Conditions N2 - Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics. T2 - 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation CY - Online meeting DA - 28.07.2021 KW - Explainable machine learning KW - Guided waves KW - Damage detection KW - Structural health monitoring KW - Composite structures PY - 2021 SN - 978-0-7918-8552-9 DO - https://doi.org/10.1115/QNDE2021-75215 VL - QNDE2021-75215 SP - 1 EP - 6 PB - The American Society of Mechanical Engineers (ASME) CY - New York, USA AN - OPUS4-56723 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bulling, Jannis A1 - Jurgelucks, B. A1 - Prager, Jens A1 - Walther, A. T1 - Defect Characterization in Plate Models Facilitated by Algorithmic Differentiation N2 - In non-destructive testing and structural health monitoring with ultrasonic waves, the quantification of damage in components is one of the main tasks. In many shell-like structures, such as plates, pipes, or laminate components, ultrasonic waves propagate as guided waves. Although guided waves enable the testing of large areas, their multimodal and dispersive properties make it challenging to analyze signals. So, there is a need for more advanced algorithms to handle these properties, especially when reconstructing damage position and geometry. The reconstruction can be formulated as an inverse problem where the measured signals are fitted with a simulative forward model. Due to the small wavelength of ultrasonic waves, classic forward models based on, e.g., the Finite Element Method are computationally intensive. In contrast, the authors use the semi-analytical Scaled Boundary Finite Element Method (SBFEM) to reduce the computational effort. The SBFEM approximates arbitrary long, undamaged parts of the structure with only a few degrees of freedom. This contribution summarizes a general inverse procedure based on algorithmic differentiation in combination with the SBFEM. Results are presented for damaged 2D cross-sectional models of waveguides. These results include an analysis of the robustness of the proposed algorithms against noise. T2 - DAGA 22 CY - Stuttgart, Germany DA - 21.03.2022 KW - Structural health monitoring KW - Inverse Methods KW - SBFEM KW - Algorithmic Differentiation KW - Non-destructive testing PY - 2022 VL - 2022 SP - 871 EP - 874 AN - OPUS4-56547 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus A1 - Weege, S. A1 - Roske, T. A1 - Krebber, Katerina T1 - Leakage detection at a borehole simulator using distributed acoustic sensing N2 - A distributed acoustic sensing system is used to detect the leakage in a borehole simulator by measuring the leakage induced vibration. The leakage location can be clearly determined by frequency spectrum analysis. T2 - 27th International Conference on Optical Fiber Sensors (OFS-27) CY - Alexandria, VA, USA DA - 29.08.2022 KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing KW - Leakage detection PY - 2022 AN - OPUS4-56098 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus A1 - Weege, S. A1 - Roske, T. A1 - Krebber, Katerina T1 - Leakage detection at a borehole simulator using distributed acoustic sensing N2 - A distributed acoustic sensing system is used to detect the leakage in a borehole simulator by measuring the leakage induced vibration. The leakage location can be clearly determined by frequency spectrum analysis. T2 - 27th International Conference on Optical Fiber Sensors (OFS-27) CY - Alexandria, VA, USA DA - 29.08.2022 KW - Leakage detection KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing PY - 2022 SP - 1 EP - 4 PB - Optica CY - Washington D.C., USA AN - OPUS4-56097 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Königsbauer, Korbinian A1 - Nöther, N. A1 - Schaller, M. B. A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Distributed POF sensors for structural health monitoring in civil construction applications N2 - In this paper, a cost-efficient distributed fiber optic measurement system based on Rayleigh scattering is presented. The distributed digital incoherent optical frequency domain reflectometry (I-OFDR) method is developed for detection of significantly large strain in the range from 3 % up to 10 % as required by end users. For this purpose, a vector network analyzer used in the I-OFDR is replaced by a compact and cost-effective digital data acquisition system. This digital emitting/receiving unit enables the recording of the complex transfer function carrying information about the local deformations along the entire sensing fiber. T2 - POF 2022 The 30th International Conference on Plastic Optical Fibers CY - Bilbao, Spain DA - 26.09.2022 KW - I-OFDR KW - PF-POF KW - Structural health monitoring KW - Rayleigh backscatter measurement KW - Strain detection PY - 2022 VL - 2022 SP - 152 EP - 155 AN - OPUS4-56060 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liao, Chun-Man A1 - Bernauer, F. A1 - Igel, H. A1 - Hadziioannou, C. A1 - Niederleithinger, Ernst T1 - Real-time bridge monitoring using ultrasonic techniques combined with six-component (6-C) measurements N2 - This study aims to develop a real time structural health monitoring method by ultrasonic tests combined with advanced six component (6C) translation and rotation measurements. Conventionally, the investigation of the velocity and acceleration response in the translation direction is used to obtain the eigenfrequencies of structures. Recently the measurement of rotation has been considered to fully characterize the dynamic behavior of structures. This research undertakes the evaluation of a novel 6C sensor (IMU50-iXblue) with components originally developed for navigation for the purpose of bridge monitoring. However, as for all vibration recordings, there is a certain influence of environmental conditions (mainly temperature) which may affect evaluation and the results of structural assessment. We propose applying the cross-correlation function to the 6C ambient vibration signals to reconstruct wave propagation and using coda wave interferometry (CWI) to obtain internal velocity variation from waveforms. A field experiment on a large-scale prestressed concrete bridge model is presented. To verify that we are able to identify the pre-stress loss even in presence of temperature effects, we perform measurements in two different scales: the ultrasonic and output-only, vibration measurements. The change in the structural properties due to the pre-stress loss should be detected by the pulse velocity change. The results reveal both the performance and advantages of ultrasonic techniques and the capabilities of 6C sensors. To conclude, the application of CWI to wave signals contributes to a comprehensive assessment for bridge monitoring. T2 - NDT-CE 2022 CY - Zurich, Switzerland DA - 16.08.2022 KW - Structural health monitoring KW - Ultrasonic KW - Coda wave interferometry PY - 2022 SP - 1 EP - 10 AN - OPUS4-55660 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas T1 - A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling N2 - Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - Support structures KW - Building information modelling KW - Structural health monitoring KW - Structural integrity maintenance PY - 2022 AN - OPUS4-55651 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liao, Chun-Man A1 - Niederleithinger, Ernst T1 - Real time bridge monitoring using ultrasonic techniques combined with six component (6-c) measurements N2 - This study aims to develop a real-time monitoring method for the structural performance by ultrasonic testing in combination with six-component (6-C) translation and rotation measurements. So far, the recordings of the velocity and acceleration response in the translation direction have been used to obtain the eigenfrequencies of structures. Recently, measurement of rotation has been used to fully characterize the dynamic behavior of structures. In this research, 6-C sensors consisting of a three-component rotational seismometer and a three-component broadband seismometer are evaluated for their suitability for bridge monitoring. Since changes in environmental conditions such as temperature during vibration recordings affect the structural evaluation results, cross-correlation function is applied here to the 6-C ambient vibration signals to reconstruct the wave propagation on the one hand, and coda wave interferometry (CWI) is applied to obtain the internal velocity variation from waveforms on the other hand. In field tests on a large-scale prestressed concrete bridge model, it was verified whether the prestress loss can also be determined in presence of temperature effects. For this purpose, measurements were performed in two scales, ultrasonic and output-only vibration measurements. The change in structural properties due to the prestress loss should be detected by the pulse velocity change. The results demonstrate both the performance and advantages of ultrasonic techniques and the capabilities of 6-C sensors. Thus, the application of CWI to wave signals can contribute comprehensively to bridge monitoring. T2 - NDT-CE 2022 CY - Zurich, Switzerland DA - 16.08.2022 KW - 6-C vibration signals KW - Coda wave interferometry KW - Cross-correlation function KW - Prestressed bridge KW - Structural health monitoring KW - Ultrasonic PY - 2022 AN - OPUS4-55646 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 SN - 978-1-032-35623-5 SN - 978-1-003-32264-1 DO - https://doi.org/10.1201/9781003322641-127 SP - 1061 EP - 1068 PB - CRC Press CY - Boca Raton AN - OPUS4-55493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Helmrich, M. A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Lorelli, S. A1 - Morgenthal, G. T1 - Maintalbrücke Gemünden: Bauwerksmonitoring und -identifikation aus einem Guss T1 - Maintalbrücke Gemünden – Integrated structural health monitoring and UAS diagnostics N2 - Die Infrastruktursysteme der Industriestaaten erfordern heute und in Zukunft ein effizientes Management bei alternder Bausubstanz, steigenden Lasten und gleichbleibend hohem Sicherheitsniveau. Digitale Technologien bieten ein großes Potenzial zur Bewältigung der aktuellen und künftigen Herausforderungen im Infrastrukturmanagement. Im BMBF-geförderten Projekt Bewertung alternder Infrastrukturbauwerke mit digitalen Technologien (AISTEC) wird untersucht, wie unterschiedliche Technologien und deren Verknüpfung gewinnbringend eingesetzt werden können. Am Beispiel der Maintalbrücke Gemünden werden ein sensorbasiertes Bauwerksmonitoring, bildbasierte Inspektion mit durch Kameras ausgestatteten Drohnen (UAS) und die Verknüpfung digitaler Bauwerksmodelle umgesetzt. Die aufgenommenen Bilder dienen u. a. als Grundlage für spätere visuelle Anomaliedetektionen und eine 3D-Rekonstruktion, welche wiederum für die Kalibrierung und Aktualisierung digitaler Tragwerksmodelle genutzt werden. Kontinuierlich erfasste Sensordaten werden ebenfalls zur Kalibrierung und Aktualisierung der Tragwerksmodelle herangezogen. Diese Modelle werden als Grundlage für Anomaliedetektionen und perspektivisch zur Umsetzung von Konzepten der prädiktiven Instandhaltung verwendet. Belastungsfahrten und historische Daten dienen in diesem Beitrag der Validierung von kalibrierten Tragwerksmodellen. N2 - Infrastructure systems of industrialised countries today and in the future require efficient management with an ageing stock, increasing loads while simultaneously maintaining a high level of safety. Digital technologies offer great potential for the current and future challenges in infrastructure management. The BMBF-funded project AISTEC is investigating how the individual technologies and their interconnection can be used beneficially. With the Maintalbrücke in Gemünden as an exemplary application, sensor-based structural monitoring, image-based inspection using unmanned aircraft systems (UAS) equipped with cameras and the integration of digital structural models are being implemented. The recorded images serve, among others, as basis for subsequent anomaly detection and a 3D reconstruction, which in turn are used for updating digital structural models. Continuously recorded sensor data is used to update the parameters of the structural models, which in turn provide the basis for predictive maintenance. Load tests are used to validate the models. KW - Bauwerksüberwachung KW - Strukturmonitoring KW - Structural Health Monitoring KW - Modell-Update KW - UAS KW - Belastungstest KW - Structural system identification KW - Structural health monitoring KW - Model update KW - UAS KW - Load tests PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554924 DO - https://doi.org/10.1002/bate.202100102 SN - 0932-8351 VL - 99 IS - 3 SP - 163 EP - 172 PB - Ernst & Sohn CY - Berlin AN - OPUS4-55492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 AN - OPUS4-55494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lu, Xin A1 - Chruscicki, Sebastian A1 - Schukar, Marcus A1 - Münzenberger, Sven A1 - Krebber, Katerina T1 - Application of Intensity-Based Coherent Optical Time Domain Reflectometry to Bridge Monitoring N2 - Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks). KW - Destructive testing KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547451 DO - https://doi.org/10.3390/s22093434 VL - 22 IS - 9 SP - 3434 PB - MDPI AN - OPUS4-54745 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Johann, Sergej A1 - Baensch, Franziska A1 - Sturm, Patrick A1 - Tiebe, Carlo A1 - Pötschke, Samuel A1 - Lay, Vera ED - Holl, H. T1 - HF RFID-based measurement comparison for method optimization in M2 concrete and alkali-activated mortars N2 - Monitoring of repositories for radioactive waste requires techniques which can be applied long-term under harsh conditions. In this work, the reliability and suitability of materials and a capacitive sensor for measuring relative humidity are investigated, which are to be embedded in the special concrete components for the closure structures of underground repository. Preliminary tests with accelerated aging of the materials used, validation of the sensors under difficult conditions, investigations of the surfaces after aging by pH 14 solution, defined exposure of the sensors in a climatic chamber and the microscope images are discussed. The results will be used for further development and optimization of the RFID based sensor systems which can be applied to monitor the condition of different building structures without cabling. T2 - 37th Danubia - Adria Symposium on Advances in Experimental Mechanics CY - Linz, Austria DA - 21.09.2021 KW - Alkali-activated mortars KW - Passive sensor interface KW - RFID KW - Structural health monitoring KW - Smart structures PY - 2022 DO - https://doi.org/10.1016/j.matpr.2022.03.465 SN - 2214-7853 VL - 62 IS - 5 SP - 2571 EP - 2576 PB - Elsevier CY - Amsterdam AN - OPUS4-54697 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kudela, P. A1 - Radzienski, M. A1 - Moix-Bonet, M. A1 - Willberg, C. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Tschöke, K. A1 - Moll, J. T1 - Dataset on full ultrasonic guided wavefield measurements of a CFRP plate with fully bonded and partially debonded omega stringer N2 - The fourth dataset dedicated to the Open Guided Waves platform presented in this work aims at a carbon fiber composite plate with an additional omega stringer at constant temperature conditions. The dataset provides full ultrasonic guided wavefields. Two types of signals were used for guided wave excitation, namely chirp signal and tone-burst signal. The chirp signal had a frequency range of 20-500kHz. The tone-burst signals had a form of sine modulated by Hann window with 5 cycles and carrier frequencies 16.5kHz, 50kHz, 100kHz, 200kHz, 300kHz. The piezoceramic actuator used for this purpose was attached to the center of the stringer side surface of the core plate. Three scenarios are provided with this setup: (1) wavefield measurements without damage, (2) wavefield measurements with a local stringer debond and (3) wavefield measurements with a large stringer debond. The defects were caused by impacts performed from the backside of the plate. As result, the stringer feet debonds locally which was verified with conventional ultrasound measurements. KW - Lamb waves KW - Composite panel KW - Impact damage KW - Damage detection KW - Scanning laser Doppler vibrometry KW - Structural health monitoring KW - Non-destructive evaluation KW - Open data PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-545242 DO - https://doi.org/10.1016/j.dib.2022.108078 SN - 2352-3409 VL - 42 SP - 1 EP - 13 PB - Elsevier CY - Amsterdam AN - OPUS4-54524 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Chakraborty, J. A1 - Wang, Xin A1 - Stolinski, M. T1 - Analysis of Sensitivity of Distance between Embedded Ultrasonic Sensors and Signal Processing on Damage Detectability in Concrete Structures N2 - Damage detection of reinforced concrete (RC) structures is becoming a more attractive domain due to the safety issues arising in the last few decades. The damage in concrete can be caused by excessive exploitation of the structure or environmental effects. The cracks in concrete can be detected by different nondestructive testing methods. However, the available methods used for this purpose have numerous limitations. The technologies available in the market nowadays have difficulties detecting slowly progressive, locally limited damage. In addition, some of These methods cannot be applied, especially in hard-to-reach areas in the superstructures. In order to avoid these deficiencies, an embedded ultrasonic methodology can be used to detect cracks in RC structures. In this study, the methodology of crack detection supported with the advanced Signal processing algorithm was proposed and verified on RC structures of various types, and cracks occurring between embedded sensors can be detected. Moreover, different pairs of ultrasonic sensors located in the considered structures are used for the analysis of the sensitivity of distance between them. It is shown that the ultrasonic sensors placed in the range of 1.5–2 m can detect cracks, even when the other methods failed to detect changes in the structure. The obtained results confirmed that diffuse ultrasonic sensor methodology is able to monitor real structures more effectively than traditional techniques. KW - Ultrasound KW - Coda wave interferometry KW - Structural health monitoring PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543624 DO - https://doi.org/10.3390/acoustics4010007 VL - 4 IS - 1 SP - 89 EP - 110 PB - MDPI CY - Basel, Schweiz AN - OPUS4-54362 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schnur, C. A1 - Moll, J. A1 - Lugovtsova, Yevgeniya A1 - Schütze, A. A1 - Schneider, T. T1 - Explainable machine learning for damage detection - In carbon fiber composite plates under varying temperature conditions N2 - Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics. T2 - 48th Annual Review of Progress in Quantitative Nondestructive Evaluation CY - Online meeting DA - 28.07.2021 KW - Explainable machine learning KW - Guided waves KW - Damage detection KW - Structural health monitoring KW - Composite structures PY - 2021 SN - 978-0-7918-8552-9 DO - https://doi.org/10.1115/QNDE2021-75215 SP - 1 EP - 6 PB - American Society of Mechanical Engineers (ASME) CY - New York, NY AN - OPUS4-54219 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schnur, C. A1 - Goodarzi, P. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Prager, Jens A1 - Tschöke, K. A1 - Moll, J. A1 - Schütze, A. A1 - Schneider, T. T1 - Towards interpretable machine learning for automated damage detection based on ultrasonic guided waves N2 - Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand. Here, this toolbox is applied to a guided wave-based SHM dataset for varying temperatures and damage locations, which is freely available on the Open Guided Waves platform. A classification rate of 96.2% is achieved, demonstrating reliable and automated damage detection. Moreover, the ability of the ML model to identify a damaged structure at untrained damage locations and temperatures is demonstrated. KW - Composite structures KW - Structural health monitoring KW - Carbon fibre-reinforced plastic KW - Interpretable machine learning KW - Automotive industry PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-542060 DO - https://doi.org/10.3390/s22010406 SN - 1424-8220 VL - 22 IS - 1 SP - 1 EP - 19 PB - MDPI CY - Basel AN - OPUS4-54206 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Niederleithinger, Ernst A1 - Wang, Xin A1 - Epple, Niklas A1 - Schumacher, T. A1 - Ahmend, S. A1 - Klikowicz, P. ED - Yokota, H. ED - Frangopol, D. W. T1 - Ultrasonic coda wave monitoring of concrete structures: First experiences with large-scale experiments and real structures N2 - Ultrasonic monitoring, making use of the sensitivity of the coda of repeated transmission meas-urements to changes in stress, temperature, moisture, as well as localized or distributed damage, has gotten at-tention in structural health monitoring (SHM) research recently. Analysis methods such as coda wave inter-ferometry (CWI), including its nonlinear extension, have been shown to be able to measure ultrasonic wave velocity changes with a 1∙10-5 resolution, while indicators such as cross-correlation or cross-coherence have been used to distinguish between reversible and irreversible changes. Several small- and large-scale laboratory experiments have demonstrated that stress changes in structures can be captured or damage detected in a very early stage. The use of this technique for pre-warning before failure are currently under investigation, as well as detailed research on the physical causes and the connection between ultrasonic wave properties and materi-al/structural behavior. Recently, several of large-scale laboratory and real structures have been instrumented with embedded ultrasonic transducers to gather experience and evidence on how to use this technology in re-al-world applications. Preliminary results from installations on a new bridge, an existing bridge, a tunnel, a la-boratory earthquake test as well as a historic stadium in Germany, Poland, and the United States, respectively, are presented. Environmental influences (mainly temperature) and validation by load tests are discussed. KW - Coda wave interferometry KW - Structural health monitoring KW - Ultrasound KW - Concrete KW - Bridges PY - 2021 SN - 978-0-367-23278-8 DO - https://doi.org/10.1201/9780429279119-345 SP - 2525 EP - 2531 PB - Taylor & Francis CY - London, UK AN - OPUS4-54168 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Recknagel, Christoph ED - Cunha, Á. ED - Caetano, E. T1 - Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations N2 - Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) CY - Online meeting DA - 30.06.2021 KW - Digital twin KW - Structural health monitoring KW - Material tests KW - Bayesian updating PY - 2021 SN - 2564-3738 SP - 1537 EP - 1544 AN - OPUS4-54126 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations N2 - Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) CY - Online meeting DA - 30.06.2021 KW - Digital twin KW - Structural health monitoring KW - Material tests KW - Bayesian updating PY - 2021 AN - OPUS4-54130 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Braml, T. A1 - Wimmer, J. A1 - Varabei, Y. A1 - Maack, Stefan A1 - Küttenbaum, Stefan A1 - Kuhn, T. A1 - Reingruber, M. A1 - Gordt, A. A1 - Hamm, J. T1 - Digitaler Zwilling: Verwaltungsschale BBox als Datenablage über den Lebenszyklus einer Brücke T1 - Digital twin: Asset administration shell BBox as data storage over the life cycle of a bridge N2 - Auf dem Weg zur digitalen Brücke existieren bereits erste Lösungen, die den Lebenszyklus einer Brücke abbilden können. Für die Planung, den Bau und den Unterhalt stehen unterschiedlichste Werkzeuge, z. B. BIM, DIN 1076, SIB-Bauwerke, Monitoring etc. zur Verfügung, die jeweils mit unterschiedlichen Datenformaten arbeiten. Für ein intelligentes Erhaltungsmanagement müssen aber alle Daten mit den verschiedenen Datenformaten zusammengeführt, abgelegt und so verwaltet werden können, dass über den gesamten Lebenszyklus einer Brücke die Abbildung eines ganzheitlichen digitalen Zwillings eines Bauwerks möglich ist. Die Autoren haben dafür mit BBox den Prototyp einer Verwaltungsschale (VWS) auf Grundlage von Industrie 4.0 entwickelt. Damit wird das physikalisch-ingenieurtechnische Modell zur Zustandsbewertung der Brücke in den Mittelpunkt gestellt und der gesamte Lebenszyklus einer Brücke kann unabhängig von Datenformaten digital erfasst werden. Da der Aufbau der VWS durch die Granularität optimal strukturiert ist, bietet die Ablage und Einspeisung von Messdaten sowohl die Grundlage eines Live-Monitorings als auch den Grundstein für maschinelles Lernen (ML). Der Datenzugriff via S3-Schnittstelle erleichtert die Entwicklung von eigenen Prognosemodellen mit Informationsmustern (SHIP – Structural Health Information Pattern). Am Beispiel der Heinrichsbrücke Bamberg wird die praktische intelligente Umsetzung des Bauwerksmonitorings inkl. VWS mit Informationsmustern und ML gezeigt. N2 - On the way to the digital bridge, initial solutions already exist that can map the life cycle of a bridge. A wide variety of tools are available for planning, construction and maintenance, e. g. BIM, DIN 1076, SIB structures, monitoring etc., each of which works with different data formats. For an intelligent maintenance management, however, all data with the different data formats must be merged, stored, and managed in such a way that the mapping of a holistic digital twin of a structure is possible over the entire life cycle of a bridge. For this purpose, the authors have developed BBox, a prototype of an asset administration shell (AAS) based on Industry 4.0. This places the physical-engineering model for assessing the condition of the bridge at the center, and the entire life cycle of a bridge can be digitally recorded independently of data formats. Since the structure of the AAS is optimally structured through granularity, the storage and feeding of measurement data provides both the basis of live monitoring and the cornerstone for machine learning (ML). The data access via S3 interface facilitates the development of own prognosis models with information patterns (SHIP – Structural Health Information Pattern). Using the Heinrichsbrücke Bamberg as an example, the practical intelligent implementation of structural monitoring incl. AAS with information patterns and ML is shown. KW - Digitaler Zwilling KW - Lebenszyklus KW - Bauwerksmonitoring KW - Industrie 4.0 KW - Maschinelles Lernen KW - Digital twin KW - Life cycle KW - Structural health monitoring KW - Industry 4.0 KW - Machine learning PY - 2021 DO - https://doi.org/10.1002/bate.202100094 SN - 1437-0999 SP - 1 EP - 9 PB - Ernst & Sohn CY - Berlin AN - OPUS4-54017 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liao, Chun-Man A1 - Hille, Falk A1 - Fontoura Barroso, Daniel A1 - Niederleithinger, Ernst ED - Papadrakakis, M. ED - Fragiadakis, M. T1 - Monitoring of a prestressed bridge model byultrasonic measurement and vibration recordings N2 - The aim of this work is to improve the current structural health monitoring (SHM) methods for civil structures. A field experiment was carried out on a two-span bridge with a built-in un-bonded prestressing system. The bridge is a 24-metre long concrete beam resting on three bear-ings. Cracks were formed subsequently when a prestressing force of 350 kN was changed to 200 kN, so that different structural states could be demonstrated. The structural assessment of this reference bridge was accomplished by the non-destructive testing using ultrasonic devices and vibration measurements. The ultrasonic velocity variations were investigated by using the coda wave interferometry method. The seismic interferometry technique was applied to the vi-bration recordings to reconstruct the wave propagation field in the bridge. This investigation shows that the wave velocity is sensitive to the current structural state and can be considered as the damage indicator. Overall, the implementation of coda cave interferometry and seismic interferometry technique facilitates structural health monitoring (SHM) in civil engineering. T2 - COMPDYN 2021 8th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering CY - Online meeting DA - 28.06.2021 KW - Structural health monitoring KW - Non-destructive testing KW - Coda wave interferometry KW - Seismic interferometry KW - Ultrasonic measurement KW - Prestress PY - 2021 SP - 1 EP - 9 PB - European Community on Computational Methods in Applied Sciences (ECCOMAS) AN - OPUS4-52957 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strangfeld, Christoph T1 - Adaption of fluidic devices for SHM of hydrogen tanks N2 - Frequency analysis of the tank during every filling Passive actuator is integrated inside filling nozzle/ pressure vessel Frequency from 5 kHz to 150 kHz Frequency sweep (Chirp) can be performed Works with every fluid: air, hydrogen, oxygen, argon, water. T2 - H2Safety Kompetenzzentrum CY - BAM Berlin, Germany DA - 07.07.2021 KW - Fluidic device KW - Structural health monitoring KW - Hydrogen tank KW - Ultrasound PY - 2021 AN - OPUS4-52930 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Bayesian system identification of a reinforced concrete beam subject to temperature variations based on static response data N2 - Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data. T2 - Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020) CY - Online meeting DA - 11.04.2021 KW - Bayesian system identification KW - Reinforced concrete KW - Damage identification KW - Environmental effects KW - Structural health monitoring KW - Structural systems PY - 2021 AN - OPUS4-52812 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias ED - Yokota, H. ED - Frangopol, D. M. T1 - Bayesian system identification of a reinforced concrete beam subject to temperature variations based on static response data N2 - Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data. T2 - Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020) CY - Online meeting DA - 11.04.2021 KW - Structural systems KW - Bayesian system identification KW - Damage identification KW - Environmental effects KW - Structural health monitoring PY - 2021 DO - https://doi.org/10.1201/9780429279119-125 SP - 934 EP - 941 PB - CRC Press AN - OPUS4-52809 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Epple, Niklas T1 - Monitoring Reinforced Concrete Structures with Coda Waves The Influence of Temperature on Ultrasound Velocity Changes calculated with Coda Wave Interferometry N2 - Monitoring of reinforced concrete structures to ensure their stability and increase their service-life is a crucial element of a modern infrastructural concept. With classical methods of non-destructive testing and inspection, repeated measurements under comparable conditions are difficult to conduct. Therefore, DFG research unit FOR 2825 CoDA researches the assessment of concrete damage using ultrasound coda wave interferometry and embedded sensors. Embedding the sensors into the monitoring target reduces human and non-human factors influencing repeatability. Using Coda Wave Interferometry (CWI), small velocity changes in the material can be detected by comparison of repeated measurements. The technique is sensitive to damaging changes like cracking as well as to reversible influences like material temperature. The understanding of these different influences on the signal is crucial for the analysis of long-term monitoring data to make an educated assessment of the structure and its integrity. With several laboratory experiments in a climate chamber and a long-term experiment recording an annual cycle in a large model on an outdoor test site in Horstwalde close to Berlin, we try to understand the influence of temperature on the CWI results. The results show that the velocity change calculated by CWI does closely follow the trend of concrete temperature. After one year of data recording with the large model being exposed to environmental variations only, the calculated velocity change resembles the annual temperature curve. The data shows a linear dependency between velocity and temperature change in a range of -0.03 percent per °K to -0.06 percent per °K - regardless of specimen size. An approach to remove temperature influence from the yearly cycle recorded in the large-scale experiment using this linear relation is unable to remove high-frequency variations - especially daily influences. Low-pass filtering the data can eliminate these variations while preserving permanent shifts caused by damages. Although we have shown that the influence of temperature on long term monitoring can be removed to a significant extent, there is still an influence of environmental changes remaining in the data. Possible nonlinear effects and influences not related to temperature need to be investigated in the future. T2 - DGG 81. Jahrestagung 2021 CY - Online meeting DA - 01.03.2021 KW - Ultrasound KW - Bridge Monitoring KW - Coda Wave Interferometry KW - Structural health monitoring PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-522401 DO - https://doi.org/10.23689/fidgeo-3975 AN - OPUS4-52240 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Long, Lijia A1 - Alcover, I. F. A1 - Thöns, Sebastian T1 - Utility analysis for SHM durations and service life extension of welds on steel bridge deck N2 - Optimization of the duration of Structural Health Monitoring (SHM) campaigns is rarely performed. This article provides a utility-based solution to posteriorly determine: i) optimal monitoring Durations and ii) the extension of the service life of the welds on a steel bridge deck. The approach is Illustrated with a case study focusing on remaining fatigue life estimation of the welds on the orthotropic steel deck of the Great Belt Bridge, in Denmark. The identification of the optimal monitoring duration and the decision about extending the service life of the welds are modelled by maximizing the expected benefits and minimizing the structural risks. The results are a parametric analysis, mainly on the effect of the target probability, benefit, cost of failure, cost of rehabilitation, cost of monitoring and Discount rate on the posterior utilities of monitoring strategies and the choice of service life considering the risk variability and the costs and benefits models. The results show that the decision on short-term monitoring, i.e., 1 week every six months, is overall the most valued SHM strategy. In addition, it is found that the target probability is the most sensitive parameter affecting the optimal SHM Durations and service life extension of the welds. KW - Fatigue KW - Monitoring strategy KW - Orthotropic steel deck KW - Structural health monitoring KW - Utility and decision theory PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-521719 DO - https://doi.org/10.1080/15732479.2020.1866026 SN - 1573-2479 VL - 18 IS - 4 SP - 492 EP - 504 PB - Taylor Francis Online AN - OPUS4-52171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Epple, Niklas A1 - Fontoura Barroso, Daniel A1 - Niederleithinger, Ernst ED - Rizzo, P. ED - Milazzo, A. T1 - Towards Monitoring of Concrete Structures with Embedded Ultrasound Sensors and Coda Waves – First Results of DFG for CoDA N2 - Due to the importance of reinforced concrete structures for modern society, damage assessment during the entire life-cycle of such structures has become a special interest in non-destructive testing. Using embedded ultrasound sensors in combination with other measurement methods, numerical modeling and self-made data collectors, tailored specifically for monitoring tasks, the German research group DFG FOR CoDA aims to investigate and develop novel methods for damage detection and rapid model updating in reinforced concrete structures. In the first stage of the project, besides the development of custom-built, low-cost data collectors, ultrasonic transducers are embedded in a large, reinforced concrete specimen on a BAM test site near Berlin. In this experiment, the influence of changing environmental conditions (mainly temperature) on the ultrasound signal is investigated using coda-wave interferometry. The results show a correlation between changes in temperature and ultrasonic velocity. Such changes must be taken into consideration in a long-term monitoring setup to distinguish between reversible and permanent changes. By correcting the data using a linear relation between concrete temperature and velocity change to remove the seasonal trends and by low-pass filtering the data to remove daily variations can remove most of the temperature influence on the ultrasound measurements. KW - Ultrasound KW - Coda Wave Interferometry (CWI) KW - Embedded sensors KW - Structural health monitoring PY - 2021 SN - 978-3-030-64593-9 SN - 978-3-030-64594-6 DO - https://doi.org/10.1007/978-3-030-64594-6_27 VL - 127 SP - 266 EP - 275 PB - Springer Nature CY - Cham, Switzerland AN - OPUS4-52012 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Vibration-based Structural Health Monitoring of a Reinforced Concrete Beam Subjected to Varying Ambient Conditions Using Bayesian Methods N2 - Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection. T2 - EURODYN 2020, XI International Conference on Structural Dynamics CY - Online meeting DA - 23.11.2020 KW - Bayesian methods KW - Environmental effects KW - Structural health monitoring PY - 2020 AN - OPUS4-51732 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Munzke, Dorit A1 - Duffner, Eric A1 - Eisermann, René A1 - Schukar, Marcus A1 - Schoppa, André A1 - Szczepaniak, Mariusz A1 - Strohhäcker, J. A1 - Mair, Georg W. T1 - Monitoring of type IV composite pressure vessels with multilayer fully integrated optical fiber based distributed strain sensing N2 - We present the results of distributed fiber optic strain sensing for condition monitoring of a hybrid type IV composite fully wrapped pressure vessel using multilayer integrated optical fibers. Distributed strain sensing was performed for a total number of 252,000 load cycles until burst of the vessel. During this ageing test material fatigue could be monitored and spatially localized. Critical material changes were detected 17,000 cycles before material failure. Results have been validated by acoustic emission analysis. T2 - 12th International Conference on Composite Science and Technology (ICCST12) CY - Sorrento, Italy DA - 08.05.2019 KW - Hybrid composite pressure vessel KW - Distributed fiber optic sensing KW - Acoustic emission analysis KW - Structural health monitoring PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-516772 DO - https://doi.org/10.1016/j.matpr.2020.02.872 SN - 2214-7853 VL - 34 SP - 217 EP - 223 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-51677 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Viefhues, Eva A1 - Said, Samir A1 - Herrmann, Ralf A1 - Baeßler, Matthias ED - Papadrakis, M. ED - Fragiadakis, M. ED - Papadimitriou, C. T1 - Vibration-based Structural Health Monitoring of a Reinforced Concrete Beam Subjected to Varying Ambient Conditions Using Bayesian Methods N2 - Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection. T2 - EURODYN 2020, XI International Conference on Structural Dynamics CY - Online meeting DA - 23.11.2020 KW - Structural health monitoring KW - Bayesian methods KW - Environmental effects PY - 2020 SN - 978-618-85072-2-7 SN - 978-618-85072-0-3 SP - 1254 PB - Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA) CY - Athens, Greece AN - OPUS4-51590 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Long, Lijia A1 - Anh Mai, Q. A1 - Morato, P. G. A1 - Dalsgaard Sorensen, J. A1 - Thöns, Sebastian T1 - Information value-based optimization of structural and environmental monitoring for offshore wind turbines support structures N2 - The use of load and structural performance measurement information is vital for efficient structural integrity management and for the cost of energy production with Offshore Wind Turbines (OWTs). OWTs are dynamically sensitive structures subject to an interaction with a control unit exposed to repeated cyclic wind and wave loads causing deterioration and fatigue. This study focuses on the quantification of the value of structural and environmental information on the integrity management of OWT structures, with the focus on fatigue of welded joints. By utilizing decision analysis, structural reliability methods, measurement data, as well as the cost-benefit models, a Value of Information (VoI) analysis can be performed to quantify the most beneficial measurement strategy. The VoI assessment is demonstrated for the integrity management of a butt welded joint of a monopile support structure for a 3 MW OWT with a hub height of approximately 71m. The conditional value of three-year measured oceanographic information and one-year strain monitoring information is quantified posteriori in conjunction with an inspection and repair planning. This paper provides insights on how much benefits can be achieved through structural and environmental information, with practical relevance on reliability-based maintenance of OWT structures. KW - Structural health monitoring KW - Offshore wind turbine KW - Monopile support structure KW - Value of information KW - Weld fatigue KW - Decision tree KW - Dynamic Bayesian Network PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-514098 DO - https://doi.org/10.1016/j.renene.2020.06.038 VL - 10 IS - 159 SP - 1036 EP - 1046 PB - Elsevier Ltd. AN - OPUS4-51409 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Epple, Niklas T1 - Monitoring of bridges with coda waves - first steps towards an imaging strategy N2 - Monitoring of concrete structures is of utmost importance in maintenance and preservation of infrastructure. As a part of the DFG research group CoDA (Concrete Damage Assessment by Coda Waves), the works within this PhD project aim for identification of damage sensitive parameters extracted from ultrasonic measurements obtained with embedded sensors, the determination of environmental (reversible) influences on the signal and the localisation of damaged areas. The main technique used for the detection of changes in the monitored material is the so-called Coda Wave Interferometry (CWI). It uses the later part of the ultrasonic recording for the detection of small changes in the sensed area and the calculation of a relative velocity change. Using this technique we can show that we are able to detect changes in concrete temperature with ultrasound measurements. This enables temperature correction for ultrasound monitoring with embedded sensors. The crucial point for imaging and localisation with coda waves is the calculation of the so-called sensitivity kernels. We propose the application of numerical wave simulations for the kernel calculations instead of the commonly used diffusivity equation. Using finite-difference wave modelling code from our DFG project partners we are able to calculate those Kernels and first results are shown in this presentation. The major task for the second year will be the development and implementation of the inversion algorithm as well as the preparation of validation experiments. T2 - Doktorandenseminar BAM Abt. 8 CY - Berlin, Germany DA - 30.03.2020 KW - Ultrasound KW - Non-destructive testing KW - Numerical modelling KW - Structural health monitoring PY - 2020 AN - OPUS4-50624 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schukar, Marcus T1 - Monitoring of type IV composite pressure vessels with multilayer fully integrated optical fibre based distributed strain sensing N2 - We present the results of distributed fibre optic strain sensing for condition monitoring of a hybrid type IV composite overwrapped pressure vessel using multilayer integrated optical fibres. During load cycle tests material fatigue could be localised and monitored 17000 load cycles before burst. T2 - TAHYA Workshop "Structural health monitoring" CY - Berlin, Germany DA - 27.11.2019 KW - Distributed fibre optic sensing KW - Hybrid composite pressure vessel KW - Structural health monitoring PY - 2019 AN - OPUS4-49996 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Munzke, Dorit A1 - Kraus, David A1 - Eisermann, René A1 - Kübler, Stefan A1 - Schukar, Marcus A1 - Nagel, Lukas A1 - Hickmann, Stefan A1 - Trappe, Volker T1 - Distributed fiber-optic strain sensing with millimeter spatial resolution for the structural health monitoring of multiaxial loaded GFRP tube specimens N2 - Due to their high strength-to-weight ratio and excellent fatigue resistance, glass fiber reinforced polymers (GFRP) are used as a construction material in a variety of applications including composite high-pressure gas storage vessels. Thus, an early damage detection of the composite material is of great importance. Material degradation can be determined via measuring the distributed strain profile of the GFRP structures. In this article, swept wavelength interferometry based distributed strain sensing (DSS) was applied for structural health monitoring of internal pressure loaded GFRP tube specimens. Measured strain profiles were compared to theoretical calculation considering Classical Lamination Theory. Reliable strain measurements with millimeter resolution were executed even at elongations of up to 3% in the radial direction caused by high internal pressure load. Material fatigue was localized by damaged-induced strain changes during operation, and detected already at 40% of burst pressure. KW - GFRP KW - Swept wavelength interferometry KW - Distributed fiber optic sensing KW - Material degradation KW - Structural health monitoring PY - 2019 DO - https://doi.org/10.1016/j.polymertesting.2019.106085 SN - 0142-9418 VL - 80 SP - 106085 PB - Elsevier Ltd. AN - OPUS4-48950 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Johann, Sergej A1 - Wu, Cheng-Chieh T1 - KonSens - RFID embedded² systems in concrete – validation experiments N2 - Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users. The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively). First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments. Four materials were investigated in pH 13 solution for 14 days - 3D-Printer-Polymer was completely resolved - PVC has no noticeable decrease in weight - (VitaPro) glass filter for the sensor protector, has weight loss 2.7 % - The epoxy resin has increased by 1.8 % due to moisture expansion Different concrete samples were prepared for the validation of the systems. RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring. T2 - 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) CY - Potsdam, Germany DA - 27.08.2019 KW - Passive RFID KW - RFID sensors KW - Sensors in concrete KW - Smart structures KW - Structural health monitoring PY - 2019 AN - OPUS4-48790 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liehr, Sascha A1 - Münzenberger, Sven A1 - Krebber, Katerina T1 - Wavelength-scanning distributed acoustic sensing for structural monitoring and seismic applications N2 - We introduce wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) for dynamic vibration sensing along optical fibers. The method is based on spectral shift computation from Rayleigh backscatter spectra. Artificial neural networks (ANNs) are used for fast and high-resolution strain computation from raw measurement data. The applicability of the method is demonstrated for vibration monitoring of a reinforced concrete bridge. We demonstrate another application example for quasi-static and dynamic measurement of ground deformation and surface wave propagation along a dark fiber in a telecommunication cable. T2 - 7th International Symposium on Sensor Science CY - Napoli, Italy DA - 09.05.2019 KW - Optical fiber sensor KW - Distributed acoustic sensor (DAS) KW - Optical time domain reflectometry KW - Rayleigh scattering KW - Artificial neural networks KW - Structural health monitoring KW - Seismic measurement PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-487733 DO - https://doi.org/10.3390/proceedings2019015030 SN - 2504-3900 VL - 15 SP - Paper 30, 1 EP - 5 PB - MDPI CY - Basel AN - OPUS4-48773 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liehr, Sascha T1 - Wavelength-scanning distributed acoustic sensing for structural monitoring and seismic applications N2 - We introduce wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) for dynamic vibration sensing along optical fibers. The method is based on spectral shift computation from Rayleigh backscatter spectra. Artificial neural networks (ANNs) are used for fast and high-resolution strain computation from raw measurement data. The applicability of the method is demonstrated for vibration monitoring of a reinforced concrete bridge. We demonstrate another application example for quasi-static and dynamic measurement of ground deformation and surface wave propagation along a dark fiber in a telecommunication cable. T2 - 7th International Symposium on Sensor Science CY - Napoli, Italy DA - 09.05.2019 KW - Optical fiber sensor KW - Distributed acoustic sensor (DAS) KW - Optical time domain reflectometry KW - Rayleigh scattering KW - Artificial neural networks KW - Structural health monitoring KW - Seismic measurement PY - 2019 AN - OPUS4-48774 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Döhler, M. A1 - Lecieux, Y. A1 - Lupi, C. A1 - Thomas, J. A1 - Schoefs, F. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical Subspace-based Damage Localization on Saint-Nazaire Bridge Mock-Up N2 - The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure. T2 - International Operational Modal Analysis Conference CY - Copenhagen, Danmark DA - 13.05.2019 KW - Structural health monitoring KW - Damage localization KW - Cable-stayed bridge KW - Cable failure PY - 2019 SP - 1 EP - 9 AN - OPUS4-48243 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Döhler, M. A1 - Lecieux, Y. A1 - Lupi, C. A1 - Thomas, J.-C. A1 - Schoefs, F. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical subspace based damage localization on Saint-Nazaire bridge mock-up N2 - The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure. T2 - 8. International Operational Modal Analysis Conference CY - Kopenhagen, Denmark DA - 12. Mai 2019 KW - Damage localization KW - Cable-stayed bridge KW - Cable failure KW - Structural health monitoring PY - 2019 SP - 1 EP - 9 AN - OPUS4-48183 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Munzke, Dorit T1 - Monitoring of type IV composite pressure vessels with multilayer fully intregrated optical fibre based distributed strain sensing N2 - We present the results of distributed fibre optic strain sensing for condition monitoring of a hybrid type IV composite fully wrapped pressure vessel using multilayer integrated optical fibres. During load cycle tests material fatigue could be localised and monitored 17,000 load cycles before burst. Results have been validated by acoustic emission analysis. T2 - 12th International Conference on Composite Science and Technology CY - Sorrento, Italy DA - 08.05.2019 KW - Hybrid composite pressure vessel KW - Distributed fibre optic sensing KW - Acoustic emission analysis KW - Structural health monitoring PY - 2019 AN - OPUS4-47995 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bassil, A. A1 - Wang, Xin A1 - Chapeleau, X. A1 - Niederleithinger, Ernst A1 - Abraham, O. A1 - Leduc, D. T1 - Distributed fiber optics sensing and coda wave interferometry techniques for damage monitoring in concrete structures N2 - The assessment of Coda Wave Interferometry (CWI) and Distributed Fiber Optics Sensing (DFOS) techniques for the detection of damages in a laboratory size reinforced concrete beam is presented in this paper. The sensitivity of these two novel techniques to micro cracks is discussed and compared to standard traditional sensors. Moreover, the capacity of a DFOS technique to localize cracks and quantify crack openings is also assessed. The results show that the implementation of CWI and DFOS techniques allow the detection of early subtle changes in reinforced concrete structures until crack formation. With their ability to quantify the crack opening, following early detection and localization, DFOS techniques can achieve more effective monitoring of reinforced concrete structures. Contrary to discrete sensors, CWI and DFOS techniques cover larger areas and thus provide more efficient infrastructures asset management and maintenance operations throughout the lifetime of the structure. KW - Distributed fiber optic sensors KW - Coda wave interferometry KW - Reinforced concrete KW - Cracks KW - Damage detection KW - Structural health monitoring PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-472549 DO - https://doi.org/10.3390/s19020356 SN - 1424-8220 VL - 19 IS - 2 SP - 356, 1 EP - 15 PB - MDPI AN - OPUS4-47254 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hu, Wei-Hua A1 - Tang, De-Hui A1 - Teng, Jun A1 - Said, Samir A1 - Rohrmann, Rolf T1 - Structural health monitoring of a prestressed concrete bridge based on statistical pattern recognition of continuous dynamic measurements over 14 years N2 - This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons. KW - Bridge KW - Structural health monitoring KW - Statistical pattern recognition KW - Temperature effect PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-468126 DO - https://doi.org/10.3390/s18124117 SN - 1424-8220 VL - 18 IS - 12 SP - 4117, 1 EP - 28 PB - MDPI CY - 4052 Basel, Schweiz AN - OPUS4-46812 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hu, W.-H. A1 - Said, Samir A1 - Rohrmann, R. A1 - Cunha, À. A1 - Teng, J. T1 - Continuous dynamic monitoring of a prestressed concrete bridge based on strain, inclination and crack measurements over a 14-year span N2 - The Westend Bridge is located on the A100 Highway in Berlin. An integrated continuous dynamic monitoring system, composed of 20 velocity sensors, 5 temperature sensors, 3 strain gauges, 1 crack sensor and 2 inclination sensors, was implemented by the Federal Institute for Materials Research and Testing in 2000. The system runs continuously with occasional intermittence and led to a huge amount of data over a 14-year span. In this article, variations of the strain, crack and inclination measurements during the last 14 years are presented. It is noted that the observed crack and inclination of the bridge are strongly influenced by seasonal temperature variation. It further induces change in the relationship between the strains measured in both concrete and prestressed tendon. Application of k-means cluster Analysis technique in both the crack and strain measurements can partition them into different seasonal phases by identifying ‘turning points’ that indicate annual periodical bridge change. In the period of these two ‘turning points’, a strong linear relation of the strains in two materials is observed. In the rest of the year, a nonlinear relationship between the strains recorded in both the concrete and the prestressed tendon is noted. The possible reason is the additional thermal load due to the change in temperature difference between the bridge’s surface and soffit. Finally, a health index in a Framework of regression model and process control theory is proposed by investigating the linear relationship between the strains in concrete and prestressed tendon. The tendency of the health index in the 14 years may suggest the long-term bridge change during that time frame. KW - Detection of structural change KW - Structural health monitoring KW - Strain KW - Crack KW - Inclination KW - Bridge PY - 2017 DO - https://doi.org/10.1177/1475921717735505 VL - 17 IS - 5 SP - 1073 EP - 1094 PB - SAGE CY - USA/UK AN - OPUS4-45990 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Liehr, Sascha ED - Peng, G.D. T1 - Polymer fiber sensors for structural and civil engineering applications N2 - This chapter gives an overview about polymer optical fiber (POF) sensors with the focus on structural and civil engineering applications. POF properties such as the high-strain range, the low Young’s modulus, and specific scattering effects open new fields for fiber-optic sensing applications. POF properties, sensitivities, and cross-sensitivities that are relevant for sensing are introduced. Advantages and limitations are discussed. State-of-the-art POF sensors and application examples are presented in subsections with regard to their underlying measurement principles. KW - Optical fiber sensors KW - Polymer optical fibers (POF) KW - Structural health monitoring KW - Distributed sensor PY - 2018 UR - https://link.springer.com/referenceworkentry/10.1007%2F978-981-10-1477-2_3-1 SN - 978-981-10-1477-2 DO - https://doi.org/10.1007/978-981-10-1477-2_3-1 SP - 1 EP - 36 PB - Springer Nature CY - Singapore AN - OPUS4-45754 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Niederleithinger, Ernst T1 - Buildings: Seismology and Strctural Health Monitoring N2 - Overview of seismological concepts unsed in nondestructive testing in civil engineering T2 - Fourth TIDES Advanced Training School CY - Prague, Czech Repubilc DA - 01.07.2018 KW - Geophysics KW - Seismology KW - Interferometry KW - Structural health monitoring KW - Nondestructive testing PY - 2018 AN - OPUS4-45361 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Döhler, Michael A1 - Hille, Falk A1 - Mevel, Laurent ED - Ottaviano, Erika ED - Pelliccio, Assunta ED - Gattulli, Vincenzo T1 - Vibration-based monitoring of civil structures with subspace-based damage detection N2 - Automatic vibration-based structural health monitoring has been recognized as a useful alternative or addition to visual inspections or local non-destructive testing performed manually. It is, in particular, suitable for mechanical and aeronautical structures as well as on civil structures, including cultural heritage sites. The main challenge is to provide a robust damage diagnosis from the recorded vibration measurements, for which statistical signal processing methods are required. In this chapter, a damage detection method is presented that compares vibration measurements from the current system to a reference state in a hypothesis test, where data9 related uncertainties are taken into account. The computation of the test statistic on new measurements is straightforward and does not require a separate modal identification. The performance of the method is firstly shown on a steel frame structure in a laboratory experiment. Secondly, the application on real measurements on S101 Bridge is shown during a progressive damage test, where damage was successfully detected for different damage scenarios. KW - Structural health monitoring KW - Subspace methods KW - Damage detection KW - Statistical tests KW - Vibrations PY - 2018 SN - 978-3-319-68645-5 DO - https://doi.org/10.1007/978-3-319-68646-2 SP - 307 EP - 326 PB - Springer International Publishing CY - Cham ET - 1. AN - OPUS4-45127 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Johann, Sergej A1 - Strangfeld, Christoph ED - Chan, T. ED - Mahini, S, T1 - Embedded wireless sensor systems for long-term SHM and corrosion detection in concrete components N2 - State-of-the-art communication standards like RFID and Bluetooth Low Energy enable the development of sensor systems which can be completely embedded into concrete components for long-term SHM and early damage detection. Objective of the project KonSens which is carried out at BAM is the development, implementation, and validation of sensors for measuring of Parameters relevant for corrosion, like moisture, pH value, and electrical conductivity, inside steel reinforced concrete components. The primarily addressed application is detection and evaluation of corrosion processes in concrete bridges. In contrast to cable connected sensors, embedded wireless sensors avoid any pathways for intrusion of moisture and chemicals, e.g., chlorides which could trigger corrosion activity. To allow for long-term, ideally life-time operation, the once embedded sensor systems must work highly energy efficient. One option are passive RFID sensor systems, which work without battery. The energy is transmitted to the system through the electromagnetic field, even to operate sensors. A crucial parameter is the transmission depth in concrete. First experiments with RFID sensors working at frequencies of 13.56 MHz (HF) and 868 MHz (UHF) embedded in concrete specimen resulted positive for transmission depths of up to 13 cm, which is quite promising, considering that corrosion would appear first at the top level of rebars. A second generation of passive RFID sensor systems has been implemented with improved antenna design. Current experiments using these systems focus on the Transmission characteristics in terms of transmission depths and the impact of concrete moisture. Low-energy humidity sensors are used and analysed regarding their capability for measuring the material moisture. Additionally, a relation between transmitted power to the embedded sensor and the moisture content of the concrete specimen caused by energy absorption can be presumed and is under systematic investigation. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure 2017 CY - Brisbane, Australia DA - 05.12.2017 KW - RFID sensors KW - Structural health monitoring KW - Sensors in concrete KW - Smart structures PY - 2017 SN - 978-1-925553-05-5 SP - 1 EP - 7 AN - OPUS4-43492 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias T1 - Embedded wireless sensor systems for long-term SHM and corrosion detection in concrete components N2 - State-of-the-art communication standards like RFID and Bluetooth Low Energy enable the development of sensor systems which can be completely embedded into concrete components for long-term SHM and early damage detection. Objective of the project KonSens which is carried out at BAM is the development, implementation, and validation of sensors for measuring of Parameters relevant for corrosion, like moisture, pH value, and electrical conductivity, inside steel reinforced concrete components. The primarily addressed application is detection and evaluation of corrosion processes in concrete bridges. In contrast to cable connected sensors, embedded wireless sensors avoid any pathways for Intrusion of moisture and chemicals, e.g., chlorides which could trigger corrosion activity. To allow for long-term, ideally life-time operation, the once embedded sensor systems must work highly energy efficient. One option are passive RFID sensor systems, which work without battery. The energy is transmitted to the system through the electromagnetic field, even to operate sensors. A crucial parameter is the transmission depth in concrete. First experiments with RFID sensors working at frequencies of 13.56 MHz (HF) and 868 MHz (UHF)embedded in concrete specimen resulted positive for transmission depths of up to 13 cm, which is quite promising, considering that corrosion would appear first at the top level of rebars. A second generation of passive RFID sensor systems has been implemented with improved antenna design. Current experiments using these systems focus on the transmission characteristics in terms of transmission depths and the impact of concrete moisture. Low-energy humidity sensors are used and analysed regarding their capability for measuring the material moisture. Additionally, a relation between transmitted power to the embedded sensor and the moisture content of the concrete specimen caused by energy absorption can be presumed and is under systematic investigation. T2 - Structural Health Monitoring of Intelligent Infrastructure Conference 2017 CY - Brisbane, Australia DA - 05.12.2017 KW - RFID sensors KW - Structural health monitoring KW - Sensors in concrete KW - Smart structures PY - 2017 AN - OPUS4-43491 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strangfeld, Christoph A1 - Johann, Sergej A1 - Müller, Maximilian A1 - Bartholmai, Matthias T1 - Embedded passive RFID-based sensors for moisture monitoring in concrete N2 - Damages in infrastructure due to moisture amount to billions of Euros every year. For a more predictive structural health monitoring in civil engineering, the detection and monitoring of hazardous moisture in steel reinforced concrete constructions is of high interest. The sensors have to be wireless, elsewise they weaken the concrete cover of the rebars. The lifetime of such constructions is normally decades, thus the sensors have to be battery-free and fully passive. Considering these requirements, passive RFID-based sensors are developed. Communication and energy supply are realized wireless via the electromagnetic field of a RFID transmitter. The passive RFIDbased sensors are embedded into the concrete to enable the monitoring of moisture transport in porous materials. Results of the hydration process are shown. T2 - IEEE Sensors 2017 CY - Glasgow, Scotland, UK DA - 30.10.2017 KW - Embedded sensors KW - Wireless sensors KW - Passive sensors KW - RFID-based sensors KW - Structural health monitoring KW - Moisture PY - 2017 SN - 978-1-5386-4056-2 DO - https://doi.org/10.1109/ICSENS.2017.8234166 SP - 870 EP - 872 PB - IEEE AN - OPUS4-43033 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moldenhauer, Laura T1 - Experimental modeling approach for determining the moisture damping exponent of a bluetooth low energy signal in moist building material N2 - We investigated, the damped Received Signal Strength Indicator (RSSI) of a Bluetooth Low Energy (BLE) signal, transmitted from the BLE-module embedded in building materials with changing moisture content, Fig. 1. The BLE-module communicates with a mobile Smart Device as tablet via 2.45 GHz-ISM-frequency band where water dipoles start to oscillate, Fig. 2. The damping model demonstrates this damping effect on RSSI by the abstraction of the reality observed in a real system. Through the reproduction of the active relationships, the system behavior is decomposed in such a way that a separate consideration of the required system parameters is possible. T2 - 34th DANUBIA ADRIA SYMPOSIUM on Advances in Experimental Mechanics (DAS 2017) CY - Trieste, Italy DA - 18.09.2017 KW - Structural health monitoring KW - Long-term monitoring KW - Bluetooth Low Energy KW - BLE KW - Moisture KW - Network Communication KW - Experimental study KW - Modellierung PY - 2017 AN - OPUS4-42966 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - Entwicklung von Verfahren zur wiederkehrenden Prüfung und zur Zustandsüberwachung von Composite-Druckbehältern N2 - Composite-Druckbehälter werden für Speicherung und Transport von Gasen unter hohem Druck verwendet. Durch die gewichtssparende Struktur, die aus einem dünnwandigem Metallgefäß und Faserverbundwerkstoff-Ummantelung besteht, sind solche Behälter insbesondere für die Automobilindustrie interessant, z.B. als Wasserstoffspeicher. Die Druckprüfung ist ein konventioneller Test, um die Integrität von Metalldruckbehältern zu bewerten. Im Falle des Composite-Druckbehälters könne eine solche Prüfung jedoch den Faserverbundwerkstoff überbeanspruchen und somit die verbleibende Lebensdauer der getesteten Komponente verringern. Infolgedessen, es ist notwendig, die Verfahren zur zerstörungsfreie Prüfung und möglicherweise zur Zustandsüberwachung von Composite-Druckbehältern zu entwickeln. Unser Vorgehen verwendet geführte Ultraschallwellen und hat das Potenzial, kritische Schäden wie Risse im Metall, Faserbrüche und Matrixrisse in Faserverbundwerkstoff zu detektieren. In diesem Beitrag wurde die Finite Elemente Methode benutzt, um die multimodale, geführte Wellenausbreitung in einer Metall-Faserverbundwerkstoffstruktur zu analysieren. Dadurch wurden die geeigneten Wellenmoden identifiziert und deren Wechselwirkung mit verschiedenen Fehlertypen analysiert. Diese Kenntnisse sollen für die Entwicklung von Verfahren zur wiederkehrenden Prüfung und zur Zustandsüberwachung von Composite-Druckbehältern angewendet werden. T2 - Seminar des FA Ultraschall CY - Berlin, Germany DA - 06.11.2017 KW - Composite-Druckbehälter KW - Geführte Ultraschallwellen KW - Structural health monitoring KW - Finite element modelling KW - Wasserstoffspeicher PY - 2017 AN - OPUS4-42751 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej T1 - RFID sensor system embedded in concrete –validation of UHF antenna geometries in different concrete depths N2 - This paper is a further research on the topic of the complete embedding of radio frequency identification (RFID) sensors in concrete. The Focus is on the antenna of the transponder. Earlier investigations of different RFID technologies, embedded in concrete, showed a difference in energy transmission. The transmission through concrete at ultra high frequency (UHF), in spite of the large signal range, does not match the targeted application specific task. Therefore, the antenna characteristics have been examined more closely. The antenna is an important component for the application of RFID. Through the antenna, energy and data Transfer takes place, so it is important to design an optimal antenna to accomplish a maximum embedding depths in concrete. To identify the optimal antenna geometry, different UHF antenna types were selected and investigated. An experimental comparison was performed to gain more information about the damping behavior and antenna characteristics in concrete. T2 - 34th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Trieste, Italy DA - 19.09.2017 KW - RFID sensors KW - Structural health monitoring KW - Passive RFID KW - UHF antenna KW - Sensors in concrete KW - Smart structures PY - 2017 AN - OPUS4-42094 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej A1 - Strangfeld, Christoph A1 - Bartholmai, Matthias ED - Cosmi, Francesca T1 - RFID sensor system embedded in concrete –validation of UHF antenna geometries in different concrete depths N2 - This paper is a further research on the topic of the complete embedding of radio frequency identification (RFID) sensors in concrete. The focus is on the antenna of the transponder. Earlier investigations of different RFID technologies, embedded in concrete, showed a difference in energy transmission. The transmission through concrete at ultra high frequency (UHF), in spite of the large signal range, does not match the targeted application specific task. Therefore, the antenna characteristics have been examined more closely. The antenna is an important component for the application of RFID. Through the antenna, energy and data transfer takes place, so it is important to design an optimal antenna to accomplish a maximum embedding depths in concrete. To identify the optimal antenna geometry, different UHF antenna types were selected and investigated. An experimental comparison was performed to gain more information about the damping behavior and antenna characteristics in concrete. T2 - 34th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Trieste, Italy DA - 19.09.2017 KW - RFID sensors KW - Structural health monitoring KW - Passive RFID KW - UHF antenna KW - Sensors in concrete KW - Smart structures PY - 2017 SN - 978-88-8303-863-1 SP - 114 EP - 115 CY - Trieste AN - OPUS4-42093 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Johann, Sergej A1 - Strangfeld, Christoph A1 - Müller, Maximilian A1 - Mieller, Björn A1 - Bartholmai, Matthias T1 - RFID sensor systems embedded in concrete – Validation experiments for long-term monitoring T1 - RFID Sensorsysteme eingebettet in Beton – Validierungsexperimente zum Langzeitmonitoring N2 - Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users. The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively). First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments. Four materials were investigated in pH13 solution for 14 days - 3D-Printer-Polymer was completely resolved - PVC has no noticeable decrease in weight - (VitaPro) glass filter for the sensor protector, has weight loss 2.7% - The epoxy resin has increased by 1.8% due to moisture expansion Different concrete samples were prepared for the validation of the systems. RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring. KW - RFID sensors KW - Structural health monitoring KW - Sensors in concrete KW - Smart structures KW - Sensor requirements PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-418331 UR - http://www.ndt.net/?id=21499 SN - 1435-4934 VL - 22 IS - 9 SP - Artikel 8, 1 EP - 7 PB - NDT.net CY - Bad Breisig AN - OPUS4-41833 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Johann, Sergej A1 - Strangfeld, Christoph A1 - Müller, Maximilian A1 - Mieller, Björn A1 - Bartholmai, Matthias ED - Emri, I. T1 - RFID sensor systems embedded in concrete – requirements for long–term operation N2 - Structural Health Monitoring (SHM) is an important topic for Industry 4.0. More and more systems are embedded in different materials and are connected to each other. To embed sensors for a long time in concrete, an exact preparation is required. In this paper, we identify Radio-Frequency Identification (RFID) as promising technology for monitoring of concrete structures. This paper present the concept for long term monitoring, defines the requirements and shows first development steps, for example, the system design, the possibilities of sensor connection, and an encapsulation for embedding in concrete. T2 - 33nd Danubia Adria Symposium on Advances in Experimental Mechanics CY - Portoroz, Slovenia DA - 20.09.2016 KW - RFID sensors KW - Long-term requirements KW - Structural health monitoring KW - Passive RFID KW - Sensor requirements KW - Sensors in concrete KW - Smart structures PY - 2017 UR - http://www.sciencedirect.com/science/article/pii/S2214785317308283 DO - https://doi.org/10.1016/j.matpr.2017.06.053 SN - 2214-7853 VL - 4 IS - 5, Part 1 SP - 5827 EP - 5832 PB - Elsevier Ltd. AN - OPUS4-41581 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph A1 - Van Bocxlaer, A. T1 - RFID-Sensor-Transponder in Beton N2 - Sensor-Transponder-Lösung der BAM ermöglicht automatisiertes Brückenmonitoring und Predictive Maintenance und detektiert Korrosion in Beton. KW - RFID-Sensorsysteme KW - Bauteilintegrierte Sensoren KW - Betonkorrosion KW - Structural health monitoring PY - 2017 SN - 1860-5907 VL - 2017 IS - 5 SP - 46 EP - 49 PB - Verlag & Freie Medien, Lüneburg CY - Lüneburg AN - OPUS4-40873 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eisermann, René T1 - Akustische Überwachung von Transformatoren mit Glasfasern?! N2 - Vorstellung aktueller Ergebnisse der Quasi-verteilten faseroptische Sensorik für die Echtzeit-Diagnostik von Hochspannungstransformatoren. T2 - Seminar Hochspannungstechnik und Energieversorgung CY - Technische Universität Berlin, Germany DA - 30.05.2017 KW - C-OTDR KW - Distributed acoustic sensing KW - Quasi-distributed vibration sensing KW - Structural health monitoring PY - 2017 AN - OPUS4-40637 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eisermann, René T1 - Advanced distributed acoustic monitoring N2 - New progress of developments of distributed acoustic monitoring. Review of previous results and lastest improvements. T2 - Seminar Angewandte Photonik CY - Goslar, Germany DA - 15.06.2017 KW - Distributed acoustic sensing KW - Structural health monitoring KW - Quasi-distributed sensing KW - Fibre optic sensors PY - 2017 AN - OPUS4-40640 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eisermann, René T1 - Applications of distributed acoustic sensing N2 - Review of early AIP related early developments. Overview of distributed methods at BAM. Examples of applications of distributed acoustic sensing for infrastructure monitoring. T2 - innoFPSEC Photonik Seminar CY - Potsdam, Germany DA - 07.06.2017 KW - Fibre-optic sensing KW - Distributed acoustic sensing KW - Structural health monitoring PY - 2017 AN - OPUS4-40641 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beck, Uwe T1 - LAYER-based Sensors for Monitoring: Surface Plasmon Resonance, Air-coupled UltraSonics, Magneto-optical Coupling N2 - The talk addresses layer-based sensors for monitoring applications. In particular, sensor principles surface plasmon resonance (SPR), air-coupled ultrasonic, and magneto-optical coupling are discussed. Optical sensors on planar substrates are prepared by sol-gel, CVD- and PVD deposition techniques, ultrasonic sensors on planar and curved substrates are made by means of PVD processes, and magnetostrictive coatings for magneto-optical sensors are deposited on fibre-based Bragg gratings (FBGs) using PVD and ECD techniques. For all kinds of sensors design and function are explained and discussed, i.e. regarding sensitivity. It is shown that a) SPR enhanced ellipsometry is a promising tool for gas monitoring of hazardous gases, that b) thermos-acoustic and piezo-electric pulse-echo techniques are relevant for damage inspection of hidden volume defects of CFRPs, and that c) magnetostrictive-optical sensors with self-calibrating (magnetic reference field) function are useful for structural health monitoring in terms of strain sensors. T2 - Vortrag im National Institute of Standards and Technology, Ceramics Division, Nanoscale Strength Measurement and Standards CY - NIST Gaithersburg, Maryland, USA DA - 28.04.2017 KW - Layer-based sensors KW - Surface plasmon resonance (SPR), KW - Air-coupled ultrasonics KW - Magneto-optical coupling KW - Gas monitoring KW - Damage inspection KW - Structural health monitoring PY - 2017 AN - OPUS4-40465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Johann, Sergej A1 - Strangfeld, Christoph A1 - Müller, Maximilian A1 - Mieller, Björn A1 - Bartholmai, Matthias T1 - RFID sensor systems embedded in concrete – validation experiments for long-term monitoring N2 - Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users. The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively). First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments. Four materials were investigated in pH 13 solution for 14 days - 3D-Printer-Polymer was completely resolved - PVC has no noticeable decrease in weight - (VitaPro) glass filter for the sensor protector, has weight loss 2.7 % - The epoxy resin has increased by 1.8 % due to moisture expansion Different concrete samples were prepared for the validation of the systems. RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring. T2 - DGZfP-Jahrestagung 2017 CY - Koblenz, Germany DA - 22.05.2017 KW - Smart structures KW - RFID sensors KW - Long-term requirements KW - Structural health monitoring KW - Passive RFID KW - Sensor requirements KW - Sensors in concrete PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-403496 UR - https://www.ndt.net/?id=21499 SN - 1435-4934 VL - 22 IS - 9 SP - 1 EP - 7 PB - NDT.net CY - Kirchwald AN - OPUS4-40349 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Johann, Sergej T1 - RFID sensor systems embedded in concrete – validation experiments for long-term monitoring N2 - Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users. The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively). First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments. Four materials were investigated in pH 13 solution for 14 days - 3D-Printer-Polymer was completely resolved - PVC has no noticeable decrease in weight - (VitaPro) glass filter for the sensor protector, has weight loss 2.7 % - The epoxy resin has increased by 1.8 % due to moisture expansion Different concrete samples were prepared for the validation of the systems. RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring. T2 - DGZfP-Jahrestagung 2017 CY - Koblenz, Germany DA - 22.05.2017 KW - RFID sensors KW - Long-term requirements KW - Structural health monitoring KW - Passive RFID KW - Sensor requirements KW - Sensors in concrete KW - Smart structures PY - 2017 AN - OPUS4-40348 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hicke, Konstantin T1 - Distributed fibre optic acoustic sensing for condition and structural health monitoring applications N2 - We present current and previous research projects and activities at BAM related to distributed fibre optic acoustic sensing (DAS) for condition monitoring purposes. Furthermore, we show the experimental capabilities of our DAS equipment and portray other BAM competences in fibre optic sensing that could be combined with DAS. T2 - EAGE/DGG Workshop on Fibre Optics Technology in Geophysics CY - Potsdam, Germany DA - 31.03.2017 KW - Condition monitoring KW - Structural health monitoring KW - Distributed fibre optic acoustic sensing KW - DAS KW - Fibre optic sensors PY - 2017 AN - OPUS4-40086 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zorn, Sebastian A1 - Unger, Jörg F. A1 - Schneider, Ronald ED - Silva Gomes, J. F. ED - Meguid, S. A. T1 - A probabilistic method for identification of vehicle loads and system parameters for reinforced concrete bridges N2 - Growth of vehicle traffic density can be observed in many countries all over the world. This accretion is caused by world-wide population growth on the one hand, but also by increasing freight volumes and, thus, freight transports on the streets on the other hand. This increased exposure becomes more and more of a problem for the civil infrastructure such as bridges. Many of these bridges are nowadays stressed to their limits by higher loads than they were originally designed for and/or operating times beyond the initially predicted life span. This raises questions about structural safety and lifetime prediction, of course, and therefore illustrates the need for accurate structural monitoring. Since the lifetime of bridge structures is primarily influenced by their traffic loading, an accurate identification of load configurations over the whole length of a structure is most desirable. In this paper, a method for vehicle load identification is proposed. It involves Bayesian Analysis and (quasi-)static importance functions in order to estimate vehicle positions, velocities and weights. The structure is modeled with finite elements in order to generate model predictions for different load configurations. The model predictions are compared to the actual measured data to identify the most probable loading configuration for that measurement. This involves the use of enhanced Monte Carlo simulations such as MCMC to reduce the computational effort. The measured data from different kinds of sensors can (and should) be combined for accuracy gain – in this case a combination of measured displacements and inclinations. Since the measurements take place over some time during the passage of the vehicle, these estimations are carried out for several time instants for which the estimation is carried out. The advantage of using Bayesian Updating Method is the embodied learning effect leading to an improvement of the estimation when adding new information in a new calculation step. Using the estimates for the loading conditions of a bridge structure as well as measurements of the structural responses, Bayesian analysis is again used in order to estimate localized structural parameters such as Young's modulus or Moments of Inertia in form of probability density functions yielding most probable values for the parameters. Considering the difficulties for load identification close to the support poles of the bridge and therefore for the proposed structural parameter identification procedure, it is clear that this problem is ill posed. Bayesian regularization methods also have proven to be very effective when handling ill posed problems. T2 - IRF2016 - Integrity Reliability Failure CY - Porto, Portugal DA - 24.07.2016 KW - Vehicle load identification KW - Structural health monitoring KW - Bayesian updating method PY - 2016 SN - 978-989-98832-4-6 VL - 2016 SP - PAPER REF: 6294-575 EP - 576 PB - INEGI-Instituto de Ciencia e Inovacao em Engenharia Mecanica e Gestao Industrial CY - Porto - Portugal AN - OPUS4-39833 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Rohwetter, Philipp T1 - Fibre-optic distributed acoustic and vibration sensing for monitoring of industrial plants and installations N2 - We propose the application of Distributed Acoustic Sensing (DAS) based on Rayleigh Coherent Optical Time-Domain Reflectometry (C-OTDR) to unconventional sensing tasks in industrial condition monitoring. As examples we present results on the way to fibre-optic remote sensing of dielectric damage processes in high voltage cable joints as well as to condition monitoring of passive rollers in large industrial belt conveyor systems. T2 - International Conference on Smart Infrastructure and Construction CY - Cambridge, UK DA - 27.06.2016 KW - Distributed acoustic sensing KW - Fibre-optic sensing KW - Partial discharge KW - Structural health monitoring KW - Industrial condition monitoring PY - 2016 AN - OPUS4-38717 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Rohwetter, Philipp A1 - Eisermann, René A1 - Großwig, S. A1 - Krebber, Katerina T1 - Fibre-optic distributed acoustic and vibration sensing for monitoring of industrial plants and installations N2 - We propose the application of Distributed Acoustic Sensing (DAS) based on Rayleigh Coherent Optical Time-Domain Reflectometry (C-OTDR) to unconventional sensing tasks in industrial condition monitoring. As examples we present results on the way to fibre-optic remote sensing of dielectric damage processes in high voltage cable joints as well as to condition monitoring of passive rollers in large industrial belt conveyor systems. T2 - International Conference on Smart Infrastructure and Construction CY - Cambridge, UK DA - 27.06.2016 KW - Distributed sensing KW - C-OTDR KW - Strain measurement KW - Structural health monitoring PY - 2016 UR - http://www.icevirtuallibrary.com/doi/abs/10.1680/tfitsi.61279.063 SN - 978-0-7277-6127-9 DO - https://doi.org/10.1680/tfitsi.61279.063 SP - 63 EP - 68 PB - ICE Publishing CY - London, UK AN - OPUS4-38411 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Johann, Sergej A1 - Kammermeier, Michael A1 - Müller, Maximilian A1 - Strangfeld, Christoph T1 - Transmission characteristics of RFID sensor systems embedded in concrete N2 - Completely embedded sensor systems for long-term operation offer innovative possibilities for structural health monitoring of concrete structures. Measuring of relevant parameters, e.g., temperature, humidity, or indication of corrosion can be performed with low energy sensors. This allows to implement passive RFID sensor systems without cable connection and battery, which are power supplied exclusively by the electromagnetic field from the external reader device. To evaluate characteristics and conditions of this concept, a systematical investigation of the transmission characteristics with variation of relevant parameters, as communication frequency, installation depth, type of concrete, moisture content, etc. is currently carried out in an interdisciplinary research project at BAM. First results are presented in this paper. T2 - IEEE Sensors 2016 CY - Orlando, FL, USA DA - 30.10.2016 KW - Embedded sensors KW - Energy harvesting KW - Wireless sensors KW - RFID sensors KW - Transmission characteristics KW - Structural health monitoring PY - 2016 SN - 978-1-4799-8287-5 SN - 1930-0395 SP - 1541 EP - 1543 PB - IEEE AN - OPUS4-38388 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias T1 - Transmission characteristics of RFID sensor systems embedded in concrete N2 - Completely embedded sensor systems for long-term operation offer innovative possibilities for structural health monitoring of concrete structures. Measuring of relevant parameters, e.g., temperature, humidity, or indication of corrosion can be performed with low energy sensors. This allows to implement passive RFID sensor systems without cable connection and battery, which are power supplied exclusively by the electromagnetic field from the external reader device. To evaluate characteristics and conditions of this concept, a systematical investigation of the transmission characteristics with variation of relevant parameters, as communication frequency, installation depth, type of concrete, moisture content, etc. is currently carried out in an interdisciplinary Research project at BAM. First results are presented in this paper. T2 - IEEE Sensors 2016 CY - Orlando, FL, USA DA - 30.10.2016 KW - Embedded sensors KW - Energy harvesting KW - Wireless sensors KW - RFID sensors KW - Transmission characteristics KW - Structural health monitoring PY - 2016 AN - OPUS4-38387 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strangfeld, Christoph T1 - Embedded RFID-sensors for concrete bridge structures N2 - In the near future, it will be important to adopt innovative approaches and technologies in order to further guarantee the reliability and availability of the highway network. New tools are therefore needed in order to obtain in-depth information about the condition of bridges and its development early enough before significant, precarious damage cases occur. In 2011, the research program “Intelligente Brücken (Smart Bridges)” was launched by the BASt together with the BMVI to evolve systems for information and holistic evaluation for Bridge structures as a supplement to the current inspection-based maintenance management. Several projects dealt with the topic in the last few years and provided guidelines and a solid basis to move towards a first implementation considering the input of all research projects carried out so far. T2 - International Symposium Non-Destructive Testing in Civil Engineering CY - Berlin, Germany DA - 15.09.2015 KW - RFID based sensors KW - Embedded sensors KW - Structural health monitoring KW - Concrete condition monitoring PY - 2015 AN - OPUS4-37626 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liehr, Sascha T1 - Applications and prospects for distributed sensing using polymer optical fibres N2 - One of the unique advantages of polymer optical fibres (POF) is that they can be used to measure very high strain values up to 100 % and beyond exceeding the strain limits of silica fibre-based sensor principles. In this paper the distributed strain measurement capabilities of POF based on backscatter change evaluation are summarized and distributed backscatter measurement technologies are intro-duced. Application examples in the structural health monitoring (SHM) field are presented: a promising approach is the integration into technical textiles for high-strain measurement in earthwork structures and crack detection in buildings. The potential of POF for future applications in SHM such as distributed relative humidity sensing is discussed. T2 - International Conference on Smart Infrastructure and Construction CY - Cambridge, UK DA - 27.06.2016 KW - Strain measurement KW - Structural health monitoring KW - OTDR KW - Polymer Optical Fibre KW - Distributed sensing PY - 2016 UR - http://www.icevirtuallibrary.com/doi/abs/10.1680/tfitsi.61279.093 DO - https://doi.org/10.1680/tfitsi.61279.093 AN - OPUS4-37231 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liehr, Sascha A1 - Krebber, Katerina T1 - Applications and prospects for distributed sensing using polymer optical fibres N2 - One of the unique advantages of polymer optical fibres (POF) is that they can be used to measure very high strain values up to 100 % and beyond exceeding the strain limits of silica fibre-based sensor principles. In this paper the distributed strain measurement capabilities of POF based on backscatter change evaluation are summarized and distributed backscatter measurement technologies are intro-duced. Application examples in the structural health monitoring (SHM) field are presented: a promising approach is the integration into technical textiles for high-strain measurement in earthwork structures and crack detection in buildings. The potential of POF for future applications in SHM such as distributed relative humidity sensing is discussed. T2 - International Conference on Smart Infrastructure and Construction CY - Cambridge, UK DA - 27.06.2016 KW - Strain measurement KW - Structural health monitoring KW - OTDR KW - Polymer Optical Fibre KW - Distributed sensing PY - 2016 UR - http://www.icevirtuallibrary.com/doi/abs/10.1680/tfitsi.61279.093 SN - 978-0-7277-6127-9 DO - https://doi.org/10.1680/tfi tsi.61279.093 SP - 93 EP - 98 PB - ICE Publishing CY - London, UK AN - OPUS4-37230 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Johann, Sergej A1 - Kammermeier, Michael A1 - Müller, Maximilian A1 - Strangfeld, Christoph T1 - RFID sensor systems embedded in concrete – systematical investigation of the transmission characteristics N2 - Long-term completely embedded sensor systems offer innovative possibilities for structural health monitoring of concrete structures. Measuring of relevant parameters, e.g., temperature, humidity, or indication of corrosion can be performed with low energy sensors. This allows to implement passive RFID sensor systems without cable connection and battery, which are power supplied exclusively by the electromagnetic field from the external reader device. To evaluate characteristics and conditions of this concept, a systematical investigation of the transmission characteristics with variation of relevant parameters, as communication frequency, installation depth, type of concrete, moisture content, etc. is currently carried out in an interdisciplinary research project at BAM. First results are presented in this paper. T2 - 8th European Workshop On Structural Health Monitoring CY - Bilbao, Spain DA - 05.07.2016 KW - Structural health monitoring KW - Embedded sensor KW - Energy harvesting KW - Wireless sensors KW - RFID sensors KW - Transmission characteristics PY - 2016 SP - 1 EP - 5 AN - OPUS4-37129 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph T1 - RFID sensor systems embedded in concrete – systematical investigation of the transmission characteristics N2 - Long-term completely embedded sensor systems offer innovative possibilities for structural health Monitoring of concrete structures. Measuring of relevant parameters, e.g., temperature, humidity, or indication of corrosion can be performed with low energy sensors. This allows to implement passive RFID sensor systems without cable connection and battery, which are power supplied exclusively by the electromagnetic field from the external Reader device. To evaluate characteristics and conditions of this concept, a systematical Investigation of the transmission characteristics with variation of relevant parameters, as communication frequency, installation depth, type of concrete, moisture content, etc. is currently carried out in an interdisciplinary research project at BAM. First results are presented in this paper. T2 - 8th European Workshop On Structural Health Monitoring CY - Bilbao, Spain DA - 05.07.2016 KW - Embedded sensor KW - Energy harvesting KW - Wireless sensors KW - RFID sensors KW - Transmission characteristics KW - Structural health monitoring PY - 2016 AN - OPUS4-37130 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Worzewski, Tamara A1 - Röllig, Mathias A1 - Maierhofer, Christiane A1 - Doroshtnasir, M. A1 - Steinfurth, H. A1 - Krankenhagen, Rainer T1 - Thermographic inspection of a wind turbine rotor blade segment utilizing natural conditions as excitation source, Part I: Solar excitation for detecting deep structures in GFRP N2 - This study evaluates whether subsurface features in rotor blades, mainly made of Glass Fibre Reinforced Plastics (GFRP), can generally be detected with ‘‘solar thermography”. First, the suitability of the sun is tested for acting as a heat source for applying active thermography on a 30 mm thick GFRP test specimen. Second, a defective rotor blade segment is inspected outdoors under ideal natural conditions using the sun as excitation source. Additionally, numerical FEM-simulations are performed and the comparability between experiment and simulation is evaluated for outdoor measurements. KW - NDT KW - Numerical simulation KW - Solar excitation KW - On-site inspection KW - Structural health monitoring PY - 2016 DO - https://doi.org/10.1016/j.infrared.2016.04.011 SN - 1350-4495 VL - 76 SP - 756 EP - 766 PB - Elsevier B.V. AN - OPUS4-36076 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Krebber, Katerina ED - Karabay, G. ED - Kara, S. T1 - Smart geosynthetics for structural health monitoring using fully distributed fiber optic sensors N2 - We report on the development of a complete system for structural health monitaring of large-scale geotechnical structures. The system uses Brillouin frequency domain analysis (BOFDA) for distributed measurement of strain and temperature along glass optical fibers (GOFs) by determining the so-called Brillouin frequency shift (BFS). ln a number of research activities we managed to optimize the BOFDA measurement setup regarding the spatial resolution and the accuracy of the measured quantities. Moreover, we realized a simultaneaus measurement of strain and temperature by using nonzero dispersion-shifted fibers (NZDSFs) with several multiple Brillouin scattering resonances. ln cooperation with our German and ltalian industry partners we finally succeeded in fabricating low-attenuation smart geosynthetics as a sensor component of a fully distributed Brillouin-based fiber optic monitaring system. T2 - 6th International Technical Textiles Congress CY - Izmir, Turkey DA - 14.10.2015 KW - Brillouin scattering KW - Distributed sensor KW - Fiberoptic sensor KW - Optical fiber KW - Structural health monitoring PY - 2015 SN - 978-975-441-448-6 SP - 215 EP - 218 PB - Meta Basim Pr. AN - OPUS4-34772 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -