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Abstract

Summary

Railways are highly sensitive to rockfalls, and alarm systems exist to stop traffic when they occur. Existing alarm systems are mechanical triggers that suffer from frequent false alarms related to animal activity or vegetation growth. We introduce an alarm system powered by continuous recording on dense seismic arrays. To maximize the rockfall detection rate, the lines of accelerometers are deployed along the track, directly below the monitored cliff. The continuous data stream can be processed in near real-time for alarm detection thanks to a fast algorithm for impulsive events detection. At this scale, rockfalls are found to be strong impulsive sources of Rayleigh waves, which can be located automatically using Matched Field Processing methods. As rockfalls emit strong signals with distinctive trajectories, seismic processing should be able to reliably identify them, even for small blocks (≈0.01 m----------) which are big enough to cause train derailment. The rockfall magnitude can be estimated from the signal energy. Experimental results suggest that impacts on the rail can be identified as they display a specific signature. This study paves the way towards rockfall alarm systems for railway monitoring powered by real-time automated seismic processing.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.202320079
2023-09-03
2026-02-10

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/content/papers/10.3997/2214-4609.202320079
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Towards Seismic-Powered Rockfall Alarm Systems for Railway Monitoring
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202320079
/content/papers/10.3997/2214-4609.202320079
/content/papers/10.3997/2214-4609.202320079
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