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

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.