Early fault diagnosis method based on time-domain marginal spectrum of S transform and SVMD for rolling bearings

Abstract

Aiming at the problem of early weak fault diagnosis for rolling bearings, an early fault diagnosis method based on time-domain marginal spectrum of S transform and successive variational mode decomposition(SVMD) is proposed. Firstly, the S transform is used to process the bearing fault signal and the time-domain marginal spectrum is extracted. Then time-domain marginal spectrum S transform is decomposed adaptively by using SVMD and the IMF components which are close to the bearing fault feature frequency are automatically selected for reconstruction. Finally, spectrum analysis of the reconstructed time-domain marginal spectrum of S transform is employed to realize bearing fault diagnosis. Experimental results show that the proposed method can extract weak fault feature components effectively, thereby significantly improving early fault diagnosis accuracy for rolling bearings.