基于小波分析与Wigner分布的对旋风机轴承故障诊断

The Bearing Fault Diagnosis of the Counter-rotating Fan Based on the Wavelet Analysis and Wigner Distribution

利用小波信号重构和Wigner时频分布对矿用对旋风机轴承进行了故障诊断,介绍了分析方法。结果表明:基于小波信号重构和Wigner时频分布的故障诊断方法具有较高的时频分辨率,能够在时域上更加合理地判断偶发性故障信号和真实故障信号的区别,更加准确地给出频率分量的分布,从而正确地判断轴承的早期故障。

The wavelet signal reconstruction and Wigner time-frequency distribution were used in the bearing fault diagnosis of the counter-rotating fan. The results showed that the fault diagnosis method based on wavelet signal reconstruction and Wigner time-frequency distribution has a high time and frequency resolving power, and were more reasonable to judge the difference between the haphazard signal and the real fault signal in the time domain. So it can gain frequency distribution of the fault signal more accurately, and estimate the fault more correctly in early stage.