Incipient Diagnosis on the Bearing Fault of Rolling Mills Based on Wavelet Denoising Technology

Due to the influence of the strong background noise,the harmonic feature of the shock fault on the rolling bearing can be identified in the frequency field when the fault reaches some severe level.Therefore,the incipient fault feature can not be extracted effectively through frequency spectrum analysis.By using the band pass filtering feature of wavelet transforms,the signal can be decomposed to specific frequency band.Furthermore,the reconstruction of single-level decomposed signal can separate the valuable components from the noise successfully.The same results can be obtained through global reconstruction after threshold denoising on the high frequency decomposition coefficients.The further processing results of the denoisied signal on the rolling mill have showed that the low frequency information containing fault feature is extracted,and the characteristic frequency can be captured from the frequency spectrum of denosied signal.As a result,the incipient fault can be positioned precisely.