Aiming at problems of rolling bearings’ weak failures being difficult to identify, a rolling bearing weak fault identification method based on fusion of the variational mode decomposition (VMD) and the singular value entropy was proposed.Firstly, VMD was done for vibration signal of a rolling bearing to obtain 4 intrinsic mode functions (IMFs).According to a mean square deviation-Euclidean distance index, IMF components containing rich fault information were chosen to perform signal reconstruction.Then, the singular value decomposition (SVD) was done for the reconstructed signal to obtain the diagonal matrix of singular values, and the diagonal matrix’s singular value entropy was obtained using the information entropy theory.Finally, the singular value entropy was used to distinguish working state and fault type of the bearing.The new method was verified with rolling bearing vibration signals of American West Storage University.The results showed that compared with the traditional EMD singular value entropy fault diagnosis method, this method can more clearly delineate rolling bearing weak fault classes to correctly identify a bearing’s weak fault.This study provided a reliable basis for weak fault diagnosis of rolling bearings.
张琛 赵荣珍 邓林峰. 基于变分模态分解奇异值熵的滚动轴承微弱故障辨识方法[J]. 振动与冲击, 2018, 37(21): 87-91.
ZHANG Chen, ZHAO Rongzhen, DENG Linfeng. Weak fault identification of rolling bearings based on VMD singular value entropy. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(21): 87-91.
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