Incipient fault diagnosis of rolling element bearing based on wavelet packet transform and energy operator

Abstract

This paper mainly deals with the issue of incipient fault diagnosis for rolling element bearing. Firstly, an envelope demodulation technique based on wavelet packet transform and energy operator is applied to extract the fault feature of vibration signal. Secondly, the relative spectral entropy of envelope spectrum and the gravity frequency are combined to construct two-dimensional features vector that characterizes each fault pattern. Furthermore, K-nearest neighbors (KNN) is used to perform faults identification automatically. The experimental results prove that the method could avoid inaccurate diagnosis which only depends on the recognition of characteristic frequency, while the effectiveness of the method in the automatic fault diagnosis of bearing has been proved.