Abstract：Early fault signal of the rolling bearing which submerged by the system noise signal is weak and difficult to identify. Singular value decomposition (SVD) technology can reduce the noise effectively and extract periodical signal availably, blind signals separation(BSS) can separate fault source signals and extract fault characteristics. Using the advantages of SVD and BSS for the rolling bearing fault diagnosis in this paper, the composite noise of system signals were eliminated by the SVD algorithm, the signals after processing were separated by the BSS algorithm, then the original fault signals characters were extracted. The numerical simulation examples and experimental results show that this method is successful in separating typical fault for rolling bearings, which improved the effect of rolling bearing fault diagnosis.
2012, Vol. 31 
