A new technique to reduce cross terms in the Wigner distribution
Digital Signal Processing
Detecting impulses in mechanical signals by wavelets
EURASIP Journal on Applied Signal Processing
Correcting data from an unknown accelerometer using recursive least squares and wavelet de-noising
Computers and Structures
A novel technique for selecting mother wavelet function using an intelli gent fault diagnosis system
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
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.