Fiber Monitoring System Applied to Railway Bridge Structures in a Near-Fault Region

Bridges are widely used for train transportation. Some bridges must be constructed close to geologic faults or across them due to the constraints of travel route alignment and the geographical environment. Taiwan is located at the junction of the Eurasian Plate and the Philippine Plate, where geological joints are present and earthquakes are frequent. In Taiwan, the monitoring and early warning of structural displacements is increasingly important, especially in the mutual control and monitoring of bridges and railways. This study utilizes fiber as a continuous sensor to monitor the safety of railway bridges in a near-fault region. This research builds upon the theory of Brillouin frequency shift (BFS) and applies it to a practical scenario of a fault-crossing railway bridge. BFS is related to the strain and temperature change in a single-mode fiber. Distributed fiber optic sensing (DFOS) systems enable us to detect shifts in frequency on the sensing fiber. A systemic approach to installing DFOS systems will be discussed. Data from a DFOS system are collected, and through data processing, they are converted into strain with regard to the deformations (bending, tension, compression) of a box girder bridge. Changes in the geometric structure of the box girder bridge throughout the year are measured and processed into graphical data. This system can be effectively applied to the structural safety monitoring of railway bridges. Through this research, several functions have been achieved, including continuous displacement, automatic monitoring, and real-time automatic alarm functions, without the need for human intervention.

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Publication Details

Journal
Applied Sciences
Published
2024-09-04
DOI
https://doi.org/10.3390/app14177883
Primary Topic
Advanced Fiber Optic Sensors
Type
article
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article

Fiber Monitoring System Applied to Railway Bridge Structures in a Near-Fault Region

Tseng-Hsing Hsu, Wen-Kuei Hsu, Yu-Lin Lee, Ning-Hsuan Chang et al.
Applied Sciences
Advanced Fiber Optic Sensors
article

Fiber Monitoring System Applied to Railway Bridge Structures in a Near-Fault Region

Tseng-Hsing Hsu, Wen-Kuei Hsu, Yu-Lin Lee, Ning-Hsuan Chang, Nien-Tsu Yang, Hsiao-Chen Su
article en

Abstract

Bridges are widely used for train transportation. Some bridges must be constructed close to geologic faults or across them due to the constraints of travel route alignment and the geographical environment. Taiwan is located at the junction of the Eurasian Plate and the Philippine Plate, where geological joints are present and earthquakes are frequent. In Taiwan, the monitoring and early warning of structural displacements is increasingly important, especially in the mutual control and monitoring of bridges and railways. This study utilizes fiber as a continuous sensor to monitor the safety of railway bridges in a near-fault region. This research builds upon the theory of Brillouin frequency shift (BFS) and applies it to a practical scenario of a fault-crossing railway bridge. BFS is related to the strain and temperature change in a single-mode fiber. Distributed fiber optic sensing (DFOS) systems enable us to detect shifts in frequency on the sensing fiber. A systemic approach to installing DFOS systems will be discussed. Data from a DFOS system are collected, and through data processing, they are converted into strain with regard to the deformations (bending, tension, compression) of a box girder bridge. Changes in the geometric structure of the box girder bridge throughout the year are measured and processed into graphical data. This system can be effectively applied to the structural safety monitoring of railway bridges. Through this research, several functions have been achieved, including continuous displacement, automatic monitoring, and real-time automatic alarm functions, without the need for human intervention.

Applied SciencesVol. 14(17)
Chung Hua University (TW)
Sustainable cities and communities
Openalex Percentile: Top 88%
Advanced Fiber Optic Sensors
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