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• W4385201723 abstract "Distributed acoustic sensors (DAS) utilize optical fibers to monitor vibrations across thousands of independent locations. However, the measured acoustic waveforms experience significant variations along the sensing fiber. These differences primarily arise from changes in coupling between the fiber and its surrounding medium as well as acoustic interferences. Here, a correlation-based method is proposed to automatically find the spatial locations of DAS where temporal waveforms are repeatable. Signal repeatability is directly associated with spatial monitoring locations with both good coupling and low acoustic interference. The DAS interrogator employed is connected to an over 30-year-old optical fiber installed alongside a railway track. Thus, the optical fiber exhibits large coupling changes and different installation types along its path. The results indicate that spatial monitoring locations with good temporal waveform repeatability can be automatically discriminated using the proposed method. The correlation between the temporal waveforms acquired at locations selected by the algorithm proved to be very high considering measurements taken for three days, the first two on consecutive days and the third one a month after the first measurement." @default.
• W4385201723 created "2023-07-25" @default.
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• W4385201723 date "2023-07-22" @default.
• W4385201723 modified "2023-10-14" @default.
• W4385201723 title "Finding Well-Coupled Optical Fiber Locations for Railway Monitoring Using Distributed Acoustic Sensing" @default.
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• W4385201723 doi "https://doi.org/10.3390/s23146599" @default.
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• W4385201723 hasPublicationYear "2023" @default.
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