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Deep Learning Model for Railroad Structural Health Monitoring via Distributed Acoustic Sensing | IEEE Conference Publication | IEEE Xplore

Deep Learning Model for Railroad Structural Health Monitoring via Distributed Acoustic Sensing


Abstract:

Railway infrastructure plays a vital role in modern transportation systems, facilitating the efficient movement of people and goods. However, the integrity and performanc...Show More

Abstract:

Railway infrastructure plays a vital role in modern transportation systems, facilitating the efficient movement of people and goods. However, the integrity and performance of railroad structures are subject to various external forces and aging processes, which necessitate continuous monitoring to ensure safety and operational efficiency. This research focused on the structural health monitoring of the railroad using Distributed Acoustic Sensing (DAS) data collected from a High Tonnage Loop (HTL). An investigation on applying a deep learning model, long-shot-term memory (LSTM), and gated recurrent Unit(GRU) is presented to identify and classify railroad conditions.
Date of Conference: 05-07 July 2023
Date Added to IEEE Xplore: 28 August 2023
ISBN Information:
Conference Location: Taiyuan, China

References

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