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华体会官方网页版-华体会(中国):Traffic Vibration Signal Analysis of DAS Fiber Optic Cables with Different Coupling Based on an Improved Wavelet Thresholding Method

2023-07-17
Title: Traffic Vibration Signal Analysis of DAS Fiber Optic Cables with Different Coupling Based on an Improved Wavelet Thresholding Method

Author(s): An, YH (An, Yuhang); Ma, JH (Ma, Jihui); Xu, TW (Xu, Tuanwei); Cai, YP (Cai, Yunpeng); Liu, HY (Liu, Huiyong); Sun, YT (Sun, Yuting); Yan, WF (Yan, Wenfa)

Source: SENSORS Volume: 23  Issue: 12  Article Number: 5727  DOI: 10.3390/s23125727  Published: JUN 2023 

Abstract: Distributed Acoustic Sensing (DAS) is a novel technology that uses fiber optics to sense and monitor vibrations. It has demonstrated immense potential for various applications, including seismology research, traffic vibration detection, structural health inspection, and lifeline engineering. DAS technology transforms long sections of fiber optic cables into a high-density array of vibration sensors, providing exceptional spatial and temporal resolution for real-time monitoring of vibrations. Obtaining high-quality vibration data using DAS requires a robust coupling between the fiber optic cable and the ground layer. The study utilized the DAS system to detect vibration signals generated by vehicles operating on the campus road of Beijing Jiaotong University. Three distinct deployment methods were employed: the uncoupled fiber on the road, the underground communication fiber optic cable ducts, and the cement-bonded fixed fiber optic cable on the road shoulder, and compared for their outcomes. Vehicle vibration signals under the three deployment methods were analyzed using an improved wavelet threshold algorithm, which was verified to be effective. The results indicate that for practical applications, the most effective deployment method is the cement-bonded fixed fiber optic cable on the road shoulder, followed by the uncoupled fiber on the road, and the underground communication fiber optic cable ducts are the least effective. This has important implications for the future development of DAS as a tool for various fields.

Accession Number: WOS:001015634700001

PubMed ID: 37420892

eISSN: 1424-8220



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