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Organisationseinheit der BAM
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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.
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).
The feasibility study „AGIFAMOR. Ageing infrastructures – distributed acoustic monitoring of pipes” is an interdisciplinary research project at BAM internally financed from 2015 to 2018. Therefore, the quite young fibre optic sensing technology of distributed acoustic sensing (DAS) was investigated to possibly be extended towards a global condition monitoring system for pipelines operating in real time.
DAS is a highly dynamic fibre optic sensing technology based on the method of coherent optical time domain reflectometry (C-OTDR). DAS allows capturing strain changes in the range of kHz. For the experimental work, the most suitable application yielding an optimum sensitivity was proven by wrapping a standard single-mode silica fibre around the pipe.
The DAS sensitivity was investigated regarding the detection of 1) incidents that initiate propagation of acoustic waves in the pipe wall, 2) changes inside the pipeline causing altered flow and 3) damage development in the pipe wall. Therefore, several testing setups in laboratory as well as in real scale were realized. For comparison purposes, experiments were accompanied by acoustic emission analyses and by measurements with accelerometers.
DAS was found to be very sensitive to gas ignition and its propagation across the pipe. Furthermore, the ability of DAS to detect and localize acoustic signals associated with pipeline leakage was demonstrated. The detection of crack formation and propagation within the pipe wall by means of DAS was studied during bending tests on several pipe segments, but was not proven so far with certainty. As expected, these studies turned out as the most difficult challenge due to the random occurrence and transient nature of microscopic damage phenomena.