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SNR Enhancement of Far-End Disturbances on Distributed Sensor Based on Phase-Sensitive Optical Time-Domain Reflectometry

基于阶段敏感的光时间域反射计的分布式的传感器上的远端的骚乱的 SNR 改进

作     者:Li, Dandan Lou, Shuqin Xin, Qi Liang, Sheng Sheng, Xinzhi 

作者机构:Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Sci Beijing 100044 Peoples R China 

出 版 物:《IEEE SENSORS JOURNAL》 (IEEE传感器杂志)

年 卷 期:2021年第21卷第2期

页      面:1957-1964页

核心收录:

学科分类:0808[工学-电气工程] 08[工学] 0804[工学-仪器科学与技术] 0702[理学-物理学] 

基  金:National Natural Science Foundation of China 

主  题:Signal-to-noise ratio (SNR) far-end disturbances denoising location accuracy rate phase-sensitive optical time-domain reflectometry (Phi-OTDR) singular value decomposition (SVD) particle swarm optimization (PSO) clustering algorithm 

摘      要:A denoising method based on singular value decomposition (SVD) with particle swarm optimization (PSO) is proposed to improve the signal-to-noise ratio (SNR) of far-end disturbances in distributed sensor system based on phase-sensitive optical time-domain reflectometry (Phi-OTDR). Also, an improved clustering algorithm is introduced to locate the position of disturbance. The effective sensing distance of the Phi-OTDR system is 25.05 km and four kinds of disturbance events, including watering, knocking, climbing and pressing, are applied on the sensing fiber respectively. A series of experiments of single-point far-end disturbances and five-point disturbances are carried out. Experimental results demonstrate that the SNR of far-end disturbance can be effectively improved to over 12dB, the processing time is less than 3 seconds, and the average location accuracy rate is more than 96%. Compared with the commonly used denoising methods, such as empirical mode decomposition (EMD), wavelet-1D and wavelet-2D, the SVD denoising with PSO method has better performance in SNR enhancement and real-time, which is beneficial for accurate positioning.

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