TY - CONF A1 - Hicke, Konstantin A1 - Hussels, Maria-Teresa A1 - Eisermann, René A1 - Chruscicki, Sebastian A1 - Krebber, Katerina ED - Chung, Y. ED - Jin, W. ED - Lee, B. ED - Canning, J. ED - Nakamura, K. ED - Yuan, L. T1 - Condition monitoring of industrial infrastructures using distributed fibre optic acoustic sensors T2 - Proceedings SPIE: 25th International Conference on Optical Fiber Sensors N2 - Distributed fibre optic acoustic sensing (DAS) can serve as an excellent tool for real-time condition Monitoring of a variety of industrial and civil infrastructures. In this paper, we portray a subset of our current Research activities investigating the usability of DAS based on coherent optical time-domain reflectometry (C-OTDR) for innovative and demanding condition Monitoring applications. Specifically, our application-oriented Research presented here aims at acoustic and vibrational condition monitoring of pipelines and piping systems, of rollers in industrial heavy-duty conveyor belt systems and of extensive submarine power cable installations, respectively. T2 - 25th International Conference on Fiber Optic Sensors CY - Jeju-City, Jeju, Republic of Korea DA - 24.04.2017 KW - Condition monitoring KW - Distributed fibre optic acoustic sensing KW - Fibre optic sensors KW - Industrial monitoring KW - DAS PY - 2017 SN - 978-1-5090-4850-2 DO - https://doi.org/10.1117/12.2272463 SN - 0277-786X SN - 1996-756X VL - 10323 SP - 103230J-1 EP - 103230J-4 PB - SPIE CY - Bellingham, WA, USA AN - OPUS4-40091 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hussels, Maria-Teresa A1 - Chruscicki, Sebastian A1 - Habib, Abdel Karim A1 - Krebber, Katerina T1 - Distributed acoustic fibre-optic sensors for condition monitoring of pipelines T2 - Proceedings of SPIE N2 - Industrial piping systems are particularly relevant to public safety and the continuous availability of infrastructure. However, condition monitoring systems based on many discrete sensors are generally not well-suited for widespread piping systems due to considerable installation effort, while use of distributed fibre-optic sensors would reduce this effort to a minimum. Specifically distributed acoustic sensing (DAS) is employed for detection of third-party threats and leaks in oil and gas pipelines in recent years and can in principle also be applied to industrial plants. Further possible detection routes amenable by DAS that could identify damage prior to emission of medium are subject of a current project at BAM, which aims at qualifying distributed fibre optic methods such as DAS as a means for spatially continuous monitoring of industrial piping systems. Here, first tests on a short pipe are presented, where optical fibres were applied directly to the surface. An artificial signal was used to define suitable parameters of the measurement system and compare different ways of applying the sensor. T2 - Sixth European Workshop on Optical Fibre Sensors CY - Limerick, Ireland DA - 31.05.2016 KW - fibre-optic condition monitoring KW - distributed acoustic sensing (DAS) KW - pipeline monitoring KW - sensor application PY - 2016 SN - 978-1-5106-0219-9 DO - https://doi.org/10.1117/12.2236809 SN - 0277-786X VL - Vol. 9916 SP - Article Number: 99162Y PB - SPIE CY - Bellingham, Washington USA AN - OPUS4-37234 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kowarik, Stefan A1 - Hussels, Maria-Teresa A1 - Chruscicki, Sebastian A1 - Münzenberger, Sven A1 - Lämmerhirt, A. A1 - Pohl, P. A1 - Schubert, M. T1 - Fiber Optic Train Monitoring with Distributed Acoustic Sensing: Conventional and Neural Network Data Analysis JF - Sensors N2 - Distributed acoustic sensing (DAS) over tens of kilometers of fiber optic cables is well-suited for monitoring extended railway infrastructures. As DAS produces large, noisy datasets, it is important to optimize algorithms for precise tracking of train position, speed, and the number of train cars, The purpose of this study is to compare different data analysis strategies and the resulting parameter uncertainties. We present data of an ICE 4 train of the Deutsche Bahn AG, which was recorded with a commercial DAS system. We localize the train signal in the data either along the temporal or spatial direction, and a similar velocity standard deviation of less than 5 km/h for a train moving at 160 km/h is found for both analysis methods, The data can be further enhanced by peak finding as well as faster and more flexible neural network algorithms. Then, individual noise peaks due to bogie clusters become visible and individual train cars can be counted. From the time between bogie signals, the velocity can also be determined with a lower standard deviation of 0.8 km/h, The analysis methods presented here will help to establish routines for near real-time Train tracking and train integrity analysis. KW - Artificial neural networks KW - Distributed fiber optic sensing KW - Distributed acoustic sensing KW - Train tracking PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-502872 DO - https://doi.org/10.3390/s20020450 VL - 20 IS - 2 SP - 450 PB - MDPI CY - Basel, Switzerland AN - OPUS4-50287 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hussels, Maria-Teresa A1 - Chruscicki, Sebastian A1 - Arndt, Detlef A1 - Scheider, Swen A1 - Prager, Jens A1 - Homann, Tobias A1 - Habib, Abdel Karim T1 - Localization of transient events threatening pipeline integrity by fiber-optic distributed acoustic sensing JF - Sensors N2 - Pipe integrity is a central concern regarding technical safety, availability, and environmental compliance of industrial plants and pipelines. A condition monitoring system that detects and localizes threats in pipes prior to occurrence of actual structural failure, e.g., leakages, especially needs to target transient events such as impacts on the pipe wall or pressure waves travelling through the medium. In the present work, it is shown that fiber-optic distributed acoustic sensing (DAS) in conjunction with a suitable application geometry of the optical fiber sensor allows to track propagating acoustic waves in the pipeline wall on a fast time-scale. Therefore, short impacts on the pipe may be localized with high fidelity. Moreover, different acoustic modes are identified, and their respective group velocities are in good agreement with theoretical predications. In another set of experiments modeling realistic damage scenarios, we demonstrate that pressure waves following explosions of different gas mixtures in pipes can be observed. Velocities are verified by local piezoelectric pressure transducers. Due to the fully distributed nature of the fiber-optic sensing system, it is possible to record accelerated motions in detail. Therefore, in addition to detection and localization of threatening events for infrastructure monitoring, DAS may provide a powerful tool to study the development of gas explosions in pipes, e.g., investigation of deflagration-to-detonation-transitions (DDT). KW - Distributed acoustic sensing (DAS) KW - Distributed vibrations sensing (DVS) KW - Fiber-optic sensing KW - Condition monitoring KW - Pipeline integrity KW - Gas explosion PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-488555 DO - https://doi.org/10.3390/s19153322 SN - 1424-8220 VL - 19 IS - 15 SP - 3322, 1 EP - 20 PB - MDPI CY - Basel, CH AN - OPUS4-48855 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -