Fault Diagnosis of Traction Gear Box Based on Adaptive Morlet Wavelet and WO A Method
In order to improve the early fault diagnosis ability of gear box for rail transit traction transmission system,a Morlet wavelet adaptive parameter dictionary algorithm is developed with the aim to realize the function of local segmentation and global analysis of the whole data.The whale optimization algorithm is used to compute the wavelet dictionary data autonomously.According to the results of orthogonal matching pursuit,the sparse decomposision of the vibration signals is carried out,and the envelope spectrum analysis method is applied to obtain the early signals in the gear box,achieving the efficient fault diagnosis of the gear box.The results show that obvious periodic fault impact features are formed in the simulation signal waveform,and the Morlet wavelet parameters calculated by the method greatly shorten the time required by the algorithm.Compared with CFA method,this method has more accurate identification performance for atomic wavelet parameters,stronger anti-noise ability,and remarkablely improved algorithm efficiency.The research can be extended to other mechanical transmission systems with a high value of popularization.
万方数据
维普
