基于MELMD-ICA的光纤振动信号降噪方法

针对分布式光纤传感系统所采集含噪信号, 提出一种改进集成局部均值分解(MELMD)联合独立成分分析(ICA)的降噪方法, 引入排列熵判决机制提高抑制模态混叠与虚假分量能力。首先使用MELMD方法分解含噪信号得到乘积函数(PF)并进行信号重构; 将含噪信号和重构信号求差得到虚拟噪声, 构造虚拟通道; 然后使用ICA对含噪信号和虚拟通道进行信噪分离, 得到最终结果。通过实验验证, 该方法与EMD-ICA, EEMD-ICA, MELMD相比, 能更好地消除信号中的噪声, 保留信号的特征信息。

Abstract

Aiming at the noisy signals collected by distributed optical fiber sensing systems, a noise reduction method to modified ensemble local mean decomposition (MELMD) combined with independent component analysis (ICA) is proposed. The permutation entropy decision mechanism was introduced to improve the ability to suppress modal aliasing and spurious components. Firstly, the product function (PF) was obtained by decomposing the noisy signal by MELMD method, and the signal reconstruction was carried out. The difference between the noisy signal and the reconstructed signal was calculated to obtain the virtual noise, and the virtual channel was constructed. Then ICA was used to separate the signal-to-noise of the noisy signal and the virtual channel to obtain the final result. Experimental results show that the proposed method can better eliminate the noise in the signal, and retain the characteristic information of the signal.

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