A new diagnosis method based on continuous wavelet transform for incipient fault of rolling bearing

The feature signal of rolling bearing is weak and affected by transfer path attenuation and environmental noise in early failure period, so it is difficult to identify fault. In order to solve this problem, a diagnosis method based on continuous wavelet transform for incipient fault of bearing was proposed. Firstly, the original signal was processed by continuous wavelet transform and different scale of wavelet coefficients were used to reconstruct the signal, then the corresponding scale signal components could be obtained, in order to acquire signal component which contains fault information as much as possible, merging process, which was guided by kurtosis criterion, was performed on reconstructed signals and correlation coefficent criterion was used to eliminate redundant signals. The signal component whose kurtosis was maximum was selected from the reserved signal components and was regarded as the best component. Envelope demodulation operation was performed on the best component further. Finally, the fault type of bearing could be judged by analyzing the envelope spectrum. Both simulated and measured signals were processed by proposed method and weak feature information was extracted successfully. The results show the proposed method could diagnose the incipient fault of rolling bearing precisely. © 2016, Editorial Department of Journal of Propulsion Technology. All right reserved.