Research on the blind source separation method of DAS signal based on the improvement of FastICA algorithm

Tianxiong Li, Fudong Zhang, Jun Lin, Xingye Bai, Haozhuang Liu
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Abstract

Distributed optical fiber acoustic sensing system (DAS) can achieve real-time monitoring of vibration events along the optical fibers by demodulation of back Rayleigh scattered light information in optical fibers. DAS system has a long detection distance, low cost, high sensitivity and other characteristics, and has been playing an important role in various engineering applications. However, in practical engineering detection of DAS system, there are other vibration sound sources in the environment besides target vibration events. However, the number and type of environmental sound sources are usually unknown. This kind of uncertain multi-source interference will have a serious impact on the monitoring of target events.
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基于 FastICA 算法改进的 DAS 信号盲源分离方法研究
分布式光纤声学传感系统(DAS)通过对光纤中的后向瑞利散射光信息进行解调,可实现对光纤沿线振动事件的实时监测。DAS 系统具有探测距离远、成本低、灵敏度高等特点,在各种工程应用中发挥着重要作用。然而,在 DAS 系统的实际工程检测中,除了目标振动事件外,环境中还存在其他振动声源。然而,环境声源的数量和类型通常是未知的。这种不确定的多声源干扰将对目标事件的监测产生严重影响。
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