基于随机波长幅值采样的大动态范围分布式声波传感研究

近年来我国的高速铁路飞速发展，因此建设高铁智能化状态监测与灾害预警系统，进一步提升高铁安全应急保障能力成为亟待解决的国家重大需求。高铁健康状态监测需要实时监测长距离铁路沿线上随机发生的宽频带、大动态振动信号，分布式光纤声波传感器(DAS)通过提取传输光纤沿线上任意位置的瑞利散射信号的相位波动，实现了长距离无盲区的高灵敏振动信号测量，开始在高铁智能监测系统中扮演不可替代的作用。然而，现有的DAS技术存在大动态应变信号的相位缠绕问题，极大限制了其对高频振动信号的测量范围，制约其在高铁轨道健康监测中的应用。本项目基于申请人及其团队在多波长复用DAS系统和压缩感知算法的研究基础上，提出基于多波长随机幅值采样和压缩感知解缠绕算法解决现有DAS技术中存在的相位缠绕问题，扩展DAS系统的动态测量范围。本项目研究成果将在国家重大交通设施和高铁轨道的健康状态监测领域发挥重要作用。

Recently, with the rapidly increasing of the high-speed railway mileage in China, the track monitoring and disaster early warning system for high-speed railways became a top priority. High-speed railway health monitoring application requires real-time monitoring of broadband and large dynamic vibration signals that randomly occur along long-distance railways. Optical fiber distributed acoustic sensor (DAS) can demodulate the phase fluctuation of Rayleigh scattering signals at any position along the transmission fiber with long sensing range, high sensitivity and wideband frequency response, which has begun to play an irreplaceable role in the high-speed rail intelligent monitoring system. However, the phase wrapping in traditional DAS technology restricts the strain sensing range of high-frequency vibration signals. To solve the phase wrapping problem in the DAS technology, we propose a large sensing dynamic rage phase-sensitivity optical time domain reflectometer based on random multiple wavelengths multiplexing and compressive sensing phase unwrapping algorithm. With the help of the novel phase unwrapping algorithm, the strain sensing dynamic range of the DAS can extend greatly, which can further improve the safety and emergency support capacity of high-speed railway.