基于鲁棒性小波包峭度图的滚动轴承故障诊断

Robust Wavelet Transform-Based Kurtogram for the Fault Diagnostics of Rolling Element Bearing

由于基于小波包变换滤波器的设计方法仍然是采用基于样本四阶矩的谱峭度,因此在实际应用中可能会存在非鲁棒性等问题。在此基础上定义了具有鲁棒性的谱峭度系数,提出了基于小波包变换的具有鲁棒性的峭度图算法。滚动轴承的实测信号验证了所提出的方法不仅能够真实地反映谱峭度大小,而且能够准确过滤出故障瞬态冲击成分,有利于基于包络谱分析轴承故障特征频率检测,说明其具有较好的应用前景。

Due to the use of the spectral kurtosis based on the fourth sample moments,the Wavelet packet transform filter based method might suffer from the non-robustness problem in practical application.Therefore,robust spectral kurtosis coefficients are defined firstly.Subsequently,the robust Kurtogram based on wavelet packet transform is proposed.The practical data have been applied to demonstrate that the improved method not only can measure the real spectral kurtosis,but also can precisely detect the fault transient components used for the bearing fault diagnosis.