基于小波包近似熵的轴承故障诊断

Fault Diagnosis of the Bearing based on the Wavelet Transform and Approximate Entropy

将小波包变换与近似熵原理相结合,根据近似熵随着信号复杂程度的增加而变大的特征,可应用于轴承声发射信号分析,判断轴承有无缺陷。通过采集轴承在不同模拟缺陷、不同转速、不同载荷等工况下的声发射信号,将采集到的信号经过小波包降噪与分解后,找出能量最大的子带,进行近似熵计算。结果表明,故障轴承中近似熵随着径向载荷和转速的增加而增加,正常轴承的近似熵则不会随着工况的变化而变化,从而取得了较好的诊断效果。

Combining the wavelet transform and approximate entropy theory, according to the characteris- tic that the approximate entropy will become larger with the increase of signal complexity, it is applied to the a- nalysis of acoustic emission signals of the bearing. In the test, through collecting acoustic emission signals under such working conditions as different stimulated defects, speeds or loads, then, the wavelet packet de - noise and transform is applied to this signals, and the maximum energy subband is found, and the approximate entro- py calculation is carried out. Based on the analysis of the signals collected, it is concluded that the approximate entropy will become larger with the increase of radial load and speed in fault bearings while this phenomenon will not appear in the normal bearing. Thus a good diagnosis effect is achieved.