A hybrid time-frequency method based on improved Morlet wavelet and auto terms window

In this paper, a hybrid time-frequency method (HTM) based on the improved Morlet wavelet and auto terms window (ATW) is presented. The Morlet wavelet, for its shape is similar to the mechanical shock signals, is added two parameters which decide the shape of the mother wavelet. The added parameters and the appropriate scale parameter for continuous wavelet transformation (CWT) are calculated using the cross validation method (CVM) and the minimum Shannon entropy method. The useless noise in the original signal can be filtered by the CWT filter de-noising process. An ATW based on the Smoothed Pseudo Wigner–Ville Distribution (SPWVD) spectrum is designed as a window function to suppress the cross terms in Wigner–Ville Distribution (WVD). The gear fault diagnosis experiment results show that the proposed method has a good de-nosing performance and is effective in removing the cross terms and extracting fault feature.