基于独立分量分析的声发射信号去噪方法

Research on Denoising in Acoustic Emission Signals Based on Independent Component Analysis

针对声发射信号比较微弱,实际检测信号中常含有强背景噪声的问题,提出了基于独立分量分析(ICA)的信号去噪方法.该方法首先对观测信号进行FastICA分解,得出多导独立分量;再根据一定的时域及频域先验知识,将独立分量中的噪声信号通道置零,利用解混矩阵反演出去噪后的信号.文中通过断铅声模拟发射信号去噪仿真和埋地水管泄漏声发射信号去噪实验,对该方法进行定性和定量分析.结果表明,与常规的去噪方法比较,ICA去噪方法受噪声强度影响较小,能够得到更高的信噪比和更好的相关系数,有利于提高埋地水管泄漏点的定位精度.

A method based on Independent Component Analysis （ICA） to denoise the acoustic emission signals is presented to overcome the disadvantage of AE signals that they are always very weak and strongly affected by the background noises. Firstly, the observed signals are decomposed of several independent components by FastlCA, then, set the noise component to be zero according to some priori knowledge in time domain or frequency domain of the signals. Finally, the denoised signals are figured out using the decompose matrix. The examples of denoising the acoustic emission signals of pencil break and water pipe leak using the ICA are shown to evaluate the effect of this method. The simulation and experiments indicated that the denoising method based on ICA can get higher signal-noise rate and better correlation coefficient compared with wavelet denoising method and thus improved the precision of water pipe leak location.