小波包分析在轴承早期故障诊断中的应用

Application of Wavelet Packet Analysis to Bearing Initial Fault Diagnosis

为了识别轴承早期损伤引起的故障信号 ,利用小波包对轴承的振动信号进行处理。小波包分析的实质是对小波分解的结果作进一步细分 ,因而具有比小波分解高得多的频域分辨能力。文中用小波包分析了两个存在早期轻微损伤的轴承的振动信号 ,并比较了自然序、Gray序以及移频算法的处理结果。这些分析结果表明 ,小波包分析能够有效地将隐藏在正常振动信号之中的早期弱故障信号提取出来 。

In order to detect the initial fault in a bearing,the method of wavelet packets is used to process the bearing vibration signal.The essence of wavelet packet analysis is to make further decomposition of wavelet decomposed result,so the analysis will yield much better frequency localization.The vibration signals of two bearings with initial faults are processed by using wavelet packet analysis,and the processed results are compared with those obtained by natural sequence?Gray sequence and the algorithm of moving frequency. Compared results show that the initial fault information hidden in the vibration signals can be extracted effectively by wavelet packet analysis,so the bearing initial fault can be detected in the early stage.