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 - 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 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 - 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 - 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 - 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 - 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 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 - Hicke, Konstantin T1 - Fibre Optic Sensing @BAM N2 - The profile of division 8.6 Fibre Optic Sensors is shown, underlining specific competencies and know-how. Furthermore, several current application examples of the use of distributed fiber optic sensing for condition and state monitoring are presented. T2 - Visit and technical tour of OECD/NEA CODAP working group led by Gesellschaft für Anlagen- und Reaktorsicherheit CY - Berlin, Germany DA - 19.09.2024 KW - Distributed fiber optic sensing KW - Condition monitoring KW - Geomonitoring KW - Structural health monitoring KW - Embedded fiber optic sensor PY - 2024 AN - OPUS4-61080 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hicke, Konstantin T1 - Fibre Optic Sensors (Division 8.6) N2 - Fiber optic sensing technology being researched and developed at BAM and its numerous applications/ use cases is presented briefly after a short introductory part on the fundamentals of (distributed) fiber optic sensing. T2 - BAM - RCNDE (UK) Webinar CY - Online meeting DA - 13.11.2024 KW - Distributed fiber optic sensing KW - Structural health monitoring KW - Condition monitoring KW - DAS KW - Embedded fiber optic sensors PY - 2024 AN - OPUS4-61643 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 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 - JOUR A1 - Liao, Chun-Man ED - Zhang, Jian T1 - Modal and Wave Propagation Analysis of Vibration Tests on a Laboratory Building Model Before and After Damage N2 - Weakened structural stiffness is often a consequence of building damage, particularly after severe events such as earthquakes, where compromised structural performance can pose significant risks. To prevent immediate structural failure, an early warning system is essential, which requires inspection of local components. This research aims to achieve that by exploring the wave propagation analysis method, specifically seismic interferometry. Previous studies have applied this method to building structures, treating them as homogeneous layers of grouped floors. By analyzing the wave travel time along the height of these layers, the fundamental period of the building was estimated. However, this approach did not account for local damage or the variability of structural components, similar to the limitations of vibration‐based damage detection methods, which mainly identify global changes. Thus, the goal of this paper is to improve structural health monitoring by examining the sensitivity of wave screening, bridging the gap between nondestructive testing and vibration‐based damage detection. A half‐scale, seven‐story building model, characterized by vertical stiffness irregularity and transverse plan asymmetry, was tested in a laboratory setting. Two vertical sensor arrays were placed near corner columns of different sizes, representing both strong and weak structural areas. These arrays recorded floor accelerations in three directions. The study confirmed the effectiveness of wave propagation analysis for detecting damage along the sensor arrays before and after the earthquake. A transmissibility damage indicator was used to correlate changes in wave velocity, providing a quantitative assessment of damage levels along the wave propagation path. KW - Damage location KW - Laboratory test KW - Soft story KW - Stifness irregular structure KW - Structural health monitoring PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-624931 DO - https://doi.org/10.1155/stc/3453150 SN - 1545-2263 VL - 2025 IS - 1 SP - 1 EP - 17 PB - John Wiley & Sons Ltd. AN - OPUS4-62493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Pitters, S. A1 - Wedel, F. A1 - Hindersmann, I. T1 - Developing a guideline for structural health monitoring of road bridges in Germany N2 - In recent years, Structural Health Monitoring (SHM) has become a useful and increasingly widely used tool for supporting lifetime extensions of existing bridges with known structural deficiencies or indications of potentially critical damages or damage processes. At the same time, methods and tools are emerging, which enable monitoring-informed predictive maintenance of new and existing bridges based on digital twins. The monitoring process – starting from the definition of monitoring actions and ending with decisions based on monitoring outcomes – is complex and requires expertise in structural engineering, operation and maintenance of bridges, metrology, and data analytics. To support German road authorities, engineering consultancies, building contractors and other stakeholders of the bridge management, the Federal Highway Research Institute (BASt) has initiated the development of a new guideline for applying SHM as part of the management of road bridges. The guideline will present various use cases and for each identified use case, it will propose a proven monitoring scheme. In addition, the guideline will provide guidance on assessing the benefits of SHM as well as a common approach to managing monitoring data as a systematic basis for integrating monitoring data in the bridge management. This contribution discusses the motivation, objectives, and scope of the guideline, describes its use case centric structure and outlines the proposed data management. T2 - IABMAS 2024 CY - Kopenhagen, Danmark DA - 24.06.2024 KW - Guideline KW - Structural health monitoring KW - Road bridges KW - Infrastructure PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613947 SN - 978-1-032-77040-6 DO - https://doi.org/10.1201/9781003483755-236 SP - 2009 EP - 2017 PB - CRC Press AN - OPUS4-61394 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej T1 - Implementation and validation of robot-enabled embedded sensors for structural health monitoring N2 - In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM. T2 - VDI/VDE-GMA FA 4.52 - Strukturanalyse und- überwachung in der Bautechnik CY - Clausthal-Zellerfeld, Germany DA - 04.09.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors KW - Legged robots KW - Quadruped robots PY - 2024 AN - OPUS4-60978 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej T1 - Investigation of long-term embedded RFID sensors for structural health monitoring N2 - Ensuring the health of civil engineering structures is crucial for the safety and longevity of the built environment. In this direction, structural health monitoring (SHM) has been increasingly employed, providing insight into the structural behavior, based on sensor data representing structural responses. This paper investigates the plausibility of embedding sensors into concrete structures for SHM, leveraging radio frequency identification (RFID) technology, in an attempt to enable the passive operation of sensors without continuous power supply and to reduce potential sources of interference. In contrast to conventional SHM sensors, the uninterrupted operation of embedded sensors must be ensured because post-installation interventions are either impractical or impossible. RFID technology enables wireless data acquisition and energy transmission without mechanical impact on civil engineering structures, although it may be challenging when RFID sensors are embedded in concrete. This study presents a durable passive embedded RFID sensor system (i.e., a system without batteries), including the selection of components, such as housing and cable materials, suitable for withstanding the aggressive environment of concrete without damaging the sensitive electronics or contaminating the data recorded by the sensors. The proposed sensor system is validated in laboratory tests, the results of which provide insights into the influence of each component and are intended to advance the implementation of embedded sensor systems. T2 - IEEE Sensors 2024 CY - Kobe, Japan DA - 20.10.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors PY - 2024 AN - OPUS4-62163 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 - Johann, Sergej A1 - Stührenberg, Jan A1 - Tandon, Aditya A1 - Dragos, Kosmas A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph A1 - Smarsly, Kay T1 - Investigation of long-term embedded RFID sensors for structural health monitoring N2 - Ensuring the health of civil engineering structures is crucial for the safety and longevity of the built environment. In this direction, structural health monitoring (SHM) has been increasingly employed, providing insight into the structural behavior, based on sensor data representing structural responses. This paper investigates the plausibility of embedding sensors into concrete structures for SHM, leveraging radio frequency identification (RFID) technology, in an attempt to enable the passive operation of sensors without continuous power supply and to reduce potential sources of interference. In contrast to conventional SHM sensors, the uninterrupted operation of embedded sensors must be ensured because post-installation interventions are either impractical or impossible. RFID technology enables wireless data acquisition and energy transmission without mechanical impact on civil engineering structures, although it may be challenging when RFID sensors are embedded in concrete. This study presents a durable passive embedded RFID sensor system (i.e., a system without batteries), including the selection of components, such as housing and cable materials, suitable for withstanding the aggressive environment of concrete without damaging the sensitive electronics or contaminating the data recorded by the sensors. The proposed sensor system is validated in laboratory tests, the results of which provide insights into the influence of each component and are intended to advance the implementation of embedded sensor systems. T2 - IEEE Sensors 2024 CY - Kobe, Japan DA - 20.10.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors PY - 2024 SN - 979-8-3503-6351-7 DO - https://doi.org/10.1109/SENSORS60989.2024.10785220 SP - 1 EP - 4 AN - OPUS4-62162 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk T1 - Developing a guideline for SHM of road bridges in Germany N2 - In recent years, Structural Health Monitoring (SHM) has become a useful and increasingly widely used tool for supporting lifetime extensions of existing bridges with known structural deficiencies or indications of potentially critical damages or damage processes. At the same time, methods and tools are emerging, which enable monitoring-informed predictive maintenance of new and existing bridges based on digital twins. The monitoring process – starting from the definition of monitoring actions and ending with decisions based on monitoring outcomes – is complex and requires expertise in structural engineering, operation and maintenance of bridges, metrology, and data analytics. To support German road authorities, engineering consultancies, building contractors and other stakeholders of the bridge management, the Federal Highway Research Institute (BASt) has initiated the development of a new guideline for applying SHM as part of the management of road bridges. The guideline will present various use cases and for each identified use case, it will propose a proven monitoring scheme. In addition, the guideline will provide guidance on assessing the benefits of SHM as well as a common approach to managing monitoring data as a systematic basis for integrating monitoring data in the bridge management. This contribution discusses the motivation, objectives, and scope of the guideline, describes its use case centric structure and outlines the proposed data management. T2 - IABMAS 2024 CY - Kopenhagen, Danmark DA - 24.06.2024 KW - Guideline KW - Infrastructure KW - Structural health monitoring KW - Road bridges PY - 2024 AN - OPUS4-61395 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 - 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 - 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 - 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 - 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 - 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 - 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 - CONF A1 - Johann, Sergej T1 - Implementation and validation of robot-enabled embedded sensors for structural health monitoring N2 - In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM. T2 - VDI Fachausschuss 4.52 CY - Wernigerode, Germany DA - 04.09.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors KW - Legged robots KW - Quadruped robots PY - 2024 AN - OPUS4-62160 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 - 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 - 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 - 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 - 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 - 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 - 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 - CONF A1 - Johann, Sergej A1 - Stührenberg, Jan A1 - Tandon, Aditya A1 - Dragos, Kosmas A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph A1 - Smarsly, Kay T1 - Implementation and validation of robot-enabled embedded sensors for structural health monitoring N2 - In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM. T2 - 11th European Workshop On Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors KW - Legged robots KW - Quadruped robots PY - 2024 SP - 1 EP - 8 AN - OPUS4-60335 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej T1 - Implementation and validation of robot-enabled embedded sensors for structural health monitoring N2 - In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM. T2 - 11th European Workshop On Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors KW - Legged robots KW - Quadruped robots PY - 2024 AN - OPUS4-60336 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Morgenthal, Guido T1 - Parallelized adaptive Bayesian updating with structural reliability methods for inference of large engineering models N2 - The reassessment of engineering structures, such as bridges, now increasingly involve the integration of models with realworld data. This integration aims to achieve accurate ‘as-is’ analysis within a digital twin framework. Bayesian model updating combines prior knowledge and data with models to enhance the modelling accuracy while consistently handling uncertainties. When updating large engineering models, numerical methods for Bayesian analysis present significant computational challenges due to the need for a substantial number of likelihood evaluations. The novelty of this contribution is to parallelize adaptive Bayesian Updating with Structural reliability methods combined with subset simulation (aBUS) to improve its computational efficiency. To demonstrate the efficiency and practical applicability of the proposed approach, we present a case study on the Maintalbrücke Gemünden, a large railway bridge. We leverage modal property data to update a linear-elastic dynamic structural model of the bridge. The parallelized aBUS approach significantly reduces computational time, making Bayesian updating of large engineering models feasible within reasonable timeframes. The improved efficiency allows for a wider implementation of Bayesian model updating in structural health monitoring and maintenance decision support systems. KW - Bayesian model updating KW - Bayesian updating with structural reliability methods KW - Structural health monitoring KW - Parallelization KW - Modal analysis KW - Railway bridge PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-633686 DO - https://doi.org/10.1177/13694332251346848 SN - 1369-4332 SN - 2048-4011 SP - 1 EP - 26 PB - Sage AN - OPUS4-63368 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 - 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 - 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 - JOUR A1 - Epple, Niklas A1 - Schumacher, Thomas A1 - Murtuz, A. K. M. Golam A1 - Niederleithinger, Ernst A1 - Dusicka, Peter T1 - Combined passive and active ultrasonic stress wave monitoring of a full‑scale laboratory reinforced concrete bridge column subject to reverse‑cyclic lateral loading N2 - Effective monitoring of reinforced concrete structures requires techniques that detect early-stage material change and active, localized cracking. This study investigates a combined structural health monitoring approach using passive acoustic emission and active ultrasonic methods on a full-scale reinforced concrete bridge column subjected to reverse-cyclic lateral loading. Active monitoring, based on coda wave interferometry, was used to track changes in wave velocity and waveforms, while passive acoustic emission monitoring was used to detect crack activity. The instrumentation consisted of three embedded ultrasonic transducers and three surface-mounted acoustic emission sensors. The results show that active ultrasonic monitoring is most effective prior to visual damage, successfully detecting the onset of internal cracking via wave velocity decreases exceeding 0.4%, and distinguishing load-induced effects from permanent damage. However, its utility diminished in later stages of damage progression, as strong signal decorrelation hindered further data interpretation. Additionally, active US measurements allowed a comparison of damage severity in different parts of the column. Conversely, passive acoustic emission monitoring effectively tracked the formation of concrete cracks throughout the experiment, with distinct event clusters and high-amplitude signals (> 60 dB) confirming ongoing fracture processes in all damage states. This study confirms that combining these methods results in a more robust structural health monitoring strategy by leveraging their complementary strengths. Active techniques excel at tracking continuous material changes in early damage states, while passive methods are superior for detecting discrete cracking events as damage progresses. Importantly, both methods can utilize the same measurement equipment, enabling a cost-effective approach to continuous damage tracking. KW - Coda wave interferometry KW - Active ultrasonic monitoring KW - Acoustic emission KW - Structural health monitoring KW - Nondestructive evaluation PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-638689 DO - https://doi.org/10.1007/s13349-025-00996-w SN - 2190-5479 SP - 1 EP - 24 PB - Springer Nature AN - OPUS4-63868 LA - eng 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 - 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 - 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 - 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 - 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 - CONF A1 - Liao, Chun-Man T1 - Assessment of prestress loss in a large-scale concrete bridge model under outdoor condition N2 - The presentation shows that subtle variations in coda wave velocity can capture minor temperature effects, offering a good understanding of how a outdoor prestressed concrete structure responds to environmental conditions over time. Ultimately, this work contributes to development of more comprehensive and resilient structural health monitoring strategies for prestressed concrete infrastructure. T2 - EVACES 2025 CY - Porto, Portugal DA - 02.07.2025 KW - Coda wave interferometry KW - Damage detection KW - Prestress loss KW - Seismic interferometry KW - Structural health monitoring PY - 2025 AN - OPUS4-64211 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Brighenti, Francesca A1 - Caspani, Valeria Francesca A1 - Costa, Giancarlo A1 - Giordano, Pier Francesco A1 - Limongelli, Maria Pina A1 - Zonta, Daniele T1 - Bridge management systems: A review on current practice in a digitizing world N2 - Bridges are subject to a plethora of deterioration phenomena, such as corrosion, fatigue, and damaging events (e. g., truck impacts and earthquakes) that can affect their performance and compromise functionality and safety. These challenges, along with the expansion of physical infrastructures and limited economic resources, underscore the need for effective management systems to enhance the efficiency of maintenance activities. To address this need, bridge operators have developed Bridge Management Systems (BMSs), which assist in ensuring safe operations while optimizing budget allocation and intervention strategies. Existing state-of-the-art studies on BMSs, dating back several years, primarily focus on specific aspects of BMSs and do not provide exhaustive insight into the implemented processes. Consequently, a comprehensive analysis of the entire process is currently lacking. This review organizes and discusses the key features of existing BMSs and introduces a novel definition of BMS modules — data management, diagnosis, prognosis, and decision-making — where consensus is currently lacking. The paper covers the historical and current practices of the most common BMSs, outlining the main principles of each phase along with their critical aspects and future trends. KW - Bridge management system KW - Digitalization KW - Automation KW - Inspection KW - Structural health monitoring KW - Digital twin KW - Decision making KW - Life-cycle analysis PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-628380 DO - https://doi.org/10.1016/j.engstruct.2024.118971 SN - 0141-0296 VL - 321 SP - 1 EP - 21 PB - Elsevier CY - Amsterdam AN - OPUS4-62838 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lu, Xin A1 - Königsbauer, Korbinian A1 - Hicke, Konstantin T1 - Improved phase retrieval method for system simplification or fading suppression in interferometer-based φOTDR systems N2 - Phase sensitive optical time domain reflectometry (φOTDR) systems based on different types of interferometers for phase retrieval typically require two or three photodetectors to record the outputs from the interferometer. A novel signal processing principle is proposed for phase retrieval by taking the difference between two outputs as the quadrature component and reconstructing the in-phase component via Hilbert transformation of the Q component for IQ demodulation. Thus, only one balanced photodetector or two standard photodetectors are need, reducing system complexity and data volume. This principle can also be used to suppress fading effect for the traditional three-detector φOTDR systems by selecting optimal phases across detector pairs. Experiments with a φOTDR systems based on an imbalanced Mach-Zehnder interferometer validate the feasibility of this method and demonstrate a high fading suppression of about 90%. KW - Phase retrieval KW - Distributed fiber sensing KW - Structural health monitoring PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-652630 DO - https://doi.org/10.1364/OE.580984 SN - 1094-4087 VL - 33 IS - 26 SP - 54733 EP - 54746 PB - Optica Publishing Group AN - OPUS4-65263 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 -