小波消噪和盲源分离在转子故障信号分析中的应用方法

Application Method of Blind Source Separation and Wavelet De-noising in Rotor Fault Signal Analysis

针对转子振动信号不可避免地受噪声污染问题,提出了一种基于小波消噪和盲源分离相结合的信号分析方法。该方法首先利用小波滤波器对测试信号进行消噪处理,再利用信号的二阶统计量(SOS)来分离盲源信号。仿真和实验结果表明,相对于直接对测试信号进行盲源分离的方法,本方法可更有效地提取出转子振动的本质信号特征。

In this paper,a new process monitoring method is presented based on wavelet transform and blind source separation.At first,wavelet transform is employed to de-noise measured signals to remove the process noise.Then blind source separation based on second order statistics(SOS) is used to extract blind source signals of the process.The simulation and experiment testing results show that the proposed method compared with other method based on blind source analysis directly with process information can effectively extract the quantitative feature extraction.