小波变换与EMD分析在滚动轴承故障诊断中的应用

针对滚动轴承故障信号的非平稳和调制特点,将小波变换与一种新的信号分析方法EMD(经验模态分解)相结合用于滚动轴承故障诊断。该方法首先利用小波分析技术对检测的信号进行分解,并对含有故障特征的信号进行重构。然后对重构信号进行EMD分解,选取能够反映故障特征的IMF分量进行边际谱分析,得出滚动轴承故障信号对应的频谱,由此确定轴承的故障模式。实验研究结果表明该方法正确有效。

Application of Wavelet Transform and EMD Analysis to Rolling Bearing Fault Diagnosis

In allusion to the non-stationarity and modulation feature of rolling bearing fault signals,this paper unifies the wavelet transformation with one kind of recent discovered signal analysis method EMD（experience modality decomposition） in the rolling bearing failure diagnosis.This method first decompose testing signals through a method based on wavelet,and reconstruct the fault signals.And then decompose reconstructed signal through a method based on EMD,through the correct IMF selection spectrum analysis can reflect the breakdown characteristic of rolling bearing,So as to get the frequency of fault signals.So you can estimate what kind of the faultmode is.The experimental study result indicates this method of high accurately and effectivety.