Based on rolling bearing failure diagnosis in wavelet analysis

In this paper, wavelet features of fault-sensitive characteristics of the signal expounded scale - wavelet power spectrum comparison method and time - autocorrelation of wavelet power spectrum analysis,for the rolling bearing fault diagnosis signal complex and difficult to pass the signal to determine the bearing point of failure, given the normal time-domain waveform and the rolling bearing vibration acceleration signals scale - wavelet energy spectrum, Practice shows that the wavelet analysis to deal with non-stationary signals have a very good application effect, which can effectively be used for rolling bearing fault diagnosis.