An Application of the Second Generation of Wavelet Transform in the Fault Diagnosis of Rolling Bearings

In dealing with the deficiency of traditional wavelet analysis in extracting fault feature of bearing, the second generation of wavelet transform(SGWT) is adopted in the fault diagnosis of bearing.The prediction operator and update operator of SGWT are constructed based on the interpolating subdivision principle.Furthermore, the first-order smoothing boundary constitution technology is used to solve the mutation problem in the calculating boundary.As a result, the reconstructed signal can be smoothed.The denoising technology based on SGWT can subtract the background noise to obtain the fault feature successfully, and the effect is much better than that of the traditional wavelet denoising.Finally, the incipient fault features have been extracted successfully by integrating the SWGT with correlation analysis and demodulation technology.