基于故障特征频率的阶比双谱方法及其在滚动轴承故障诊断中的应用

Order Bispectrum Analysis Based on Fault Characteristic Frequency and Its Application to the Fault Diagnosis of Rolling Bearings

当滚动轴承出现故障时,其产生的振动信号往往表现出较强的非线性、非高斯和非平稳特征。为了实现非平稳转速下滚动轴承的故障诊断,提出了一种基于故障特征频率的阶比双谱分析方法(order bispectrum analysis based on fault characteristic frequency,OBBF)。该方法先对滚动轴承故障振动信号进行包络解调,利用线调频小波路径追踪算法估计出轴承振动包络信号中的故障特征频率,再基于故障特征频率对包络信号进行等角度重采样,将非平稳的时域信号转化为平稳的角域信号;最后对重采样后的信号进行双谱分析,并取其对角切片,得出故障结论。诊断实例表明,该方法能有效地提取滚动轴承故障振动信号的特征,对滚动轴承故障进行正确的诊断。

When a roller bearing fails, its vibration signal may be the nonlinear, non-Gauss and non-stationary signal. In order to diagnose the roller beating faults under vary rotating speed, an order bispectrum analysis method based on the fault characteristic frequency is proposed and applied to the bearing fault diagnosis under non-stationary rotating speed. In the proposed method, the vibration signal of a roller bearing with fault is analyzed by envelope analysis, then the envelope signal is decomposed using the algorithm of chirplet path pursuit to get the fault characteristic frequency. Based on the fault characteristic frequency, the even angle resampling on the envelope signal of the roller bearing is carried out and the non-stationary signal in time domain is transformed into stationary signal in angle domain. Finally, the bispectral analysis on the resampled signal can be accomplished and the diagonal slice spectrum of the bispectrum can be obtained. Practical application examples have proved that the proposed method is very effective in extracting the fault features of roller bearings.