Deep Learning Model for Railroad Structural Health Monitoring via Distributed Acoustic Sensing
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 en...
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| Vydáno v: | 2023 26th ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter) s. 274 - 281 |
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| Jazyk: | angličtina |
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IEEE
05.07.2023
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| 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. |
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| AbstractList | 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. |
| Author | Kim, Jongyeop Rahman, Md Arifur Taheri, Hossein |
| Author_xml | – sequence: 1 givenname: Md Arifur surname: Rahman fullname: Rahman, Md Arifur email: mr26497@georgiasouthern.edu organization: Georgia Southern University,Manufacturing Engineering Department,Statesboro,GA,USA,30460 – sequence: 2 givenname: Hossein surname: Taheri fullname: Taheri, Hossein email: htaheri@georgiasouthern.edu organization: Georgia Southern University,Manufacturing Engineering Department,Statesboro,GA,USA,30460 – sequence: 3 givenname: Jongyeop surname: Kim fullname: Kim, Jongyeop email: jongyeopkim@georgiasouthern.edu organization: Georgia Southern University,Information Technology Department,Statesboro,GA,U.S.A |
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| PublicationTitle | 2023 26th ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter) |
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| Snippet | Railway infrastructure plays a vital role in modern transportation systems, facilitating the efficient movement of people and goods. However, the integrity and... |
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| StartPage | 274 |
| SubjectTerms | Acoustics DAS Deep learning Distributed databases HTL HTL Fiber LSTM Predictive models railroad health railroad monitoring Sensors Structural Health Monitoring Time division multiplexing Transportation |
| Title | Deep Learning Model for Railroad Structural Health Monitoring via Distributed Acoustic Sensing |
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