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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 -