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 T2 - Proceedings 27th International Conference on Optical Fiber Sensors 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 - 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 T2 - POF conference proceedings 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 - 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 JF - Sensors N2 - Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks). KW - Destructive testing KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547451 DO - https://doi.org/10.3390/s22093434 VL - 22 IS - 9 SP - 3434 PB - MDPI AN - OPUS4-54745 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Johann, Sergej A1 - Baensch, Franziska A1 - Sturm, Patrick A1 - Tiebe, Carlo A1 - Pötschke, Samuel A1 - Lay, Vera ED - Holl, H. T1 - HF RFID-based measurement comparison for method optimization in M2 concrete and alkali-activated mortars JF - Materials today: Proceedings N2 - Monitoring of repositories for radioactive waste requires techniques which can be applied long-term under harsh conditions. In this work, the reliability and suitability of materials and a capacitive sensor for measuring relative humidity are investigated, which are to be embedded in the special concrete components for the closure structures of underground repository. Preliminary tests with accelerated aging of the materials used, validation of the sensors under difficult conditions, investigations of the surfaces after aging by pH 14 solution, defined exposure of the sensors in a climatic chamber and the microscope images are discussed. The results will be used for further development and optimization of the RFID based sensor systems which can be applied to monitor the condition of different building structures without cabling. T2 - 37th Danubia - Adria Symposium on Advances in Experimental Mechanics CY - Linz, Austria DA - 21.09.2021 KW - Alkali-activated mortars KW - Passive sensor interface KW - RFID KW - Structural health monitoring KW - Smart structures PY - 2022 DO - https://doi.org/10.1016/j.matpr.2022.03.465 SN - 2214-7853 VL - 62 IS - 5 SP - 2571 EP - 2576 PB - Elsevier CY - Amsterdam AN - OPUS4-54697 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - 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 T2 - International Symposium on Non-Destructive Testing in Civil Engineering (NDT-CE 2022), 16-18 August 2022, Zurich, Switzerland (NDTCE 2022), e-Proceedings 2022 September 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 A1 - Bernauer, F. A1 - Igel, H. A1 - Hadziioannou, C. 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 - 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 JF - Bautechnik N2 - Die Infrastruktursysteme der Industriestaaten erfordern heute und in Zukunft ein effizientes Management bei alternder Bausubstanz, steigenden Lasten und gleichbleibend hohem Sicherheitsniveau. Digitale Technologien bieten ein großes Potenzial zur Bewältigung der aktuellen und künftigen Herausforderungen im Infrastrukturmanagement. Im BMBF-geförderten Projekt Bewertung alternder Infrastrukturbauwerke mit digitalen Technologien (AISTEC) wird untersucht, wie unterschiedliche Technologien und deren Verknüpfung gewinnbringend eingesetzt werden können. Am Beispiel der Maintalbrücke Gemünden werden ein sensorbasiertes Bauwerksmonitoring, bildbasierte Inspektion mit durch Kameras ausgestatteten Drohnen (UAS) und die Verknüpfung digitaler Bauwerksmodelle umgesetzt. Die aufgenommenen Bilder dienen u. a. als Grundlage für spätere visuelle Anomaliedetektionen und eine 3D-Rekonstruktion, welche wiederum für die Kalibrierung und Aktualisierung digitaler Tragwerksmodelle genutzt werden. Kontinuierlich erfasste Sensordaten werden ebenfalls zur Kalibrierung und Aktualisierung der Tragwerksmodelle herangezogen. Diese Modelle werden als Grundlage für Anomaliedetektionen und perspektivisch zur Umsetzung von Konzepten der prädiktiven Instandhaltung verwendet. Belastungsfahrten und historische Daten dienen in diesem Beitrag der Validierung von kalibrierten Tragwerksmodellen. N2 - Infrastructure systems of industrialised countries today and in the future require efficient management with an ageing stock, increasing loads while simultaneously maintaining a high level of safety. Digital technologies offer great potential for the current and future challenges in infrastructure management. The BMBF-funded project AISTEC is investigating how the individual technologies and their interconnection can be used beneficially. With the Maintalbrücke in Gemünden as an exemplary application, sensor-based structural monitoring, image-based inspection using unmanned aircraft systems (UAS) equipped with cameras and the integration of digital structural models are being implemented. The recorded images serve, among others, as basis for subsequent anomaly detection and a 3D reconstruction, which in turn are used for updating digital structural models. Continuously recorded sensor data is used to update the parameters of the structural models, which in turn provide the basis for predictive maintenance. Load tests are used to validate the models. KW - Bauwerksüberwachung KW - Strukturmonitoring KW - Structural Health Monitoring KW - Modell-Update KW - UAS KW - Belastungstest KW - Structural system identification KW - Structural health monitoring KW - Model update KW - UAS KW - Load tests PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554924 DO - https://doi.org/10.1002/bate.202100102 SN - 0932-8351 VL - 99 IS - 3 SP - 163 EP - 172 PB - Ernst & Sohn CY - Berlin AN - OPUS4-55492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick 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 T2 - Bridge safety, maintenance, management, life-cycle, resilience and sustainability - Proceedings of the eleventh International Conference on Bridge Maintenance, Safety and Management (IABMAS 2022), Barcelona, Spain, July 11-15, 2022 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 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 AN - OPUS4-55494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -