Bearing fault feature extraction based on VMD optimized with information entropy

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Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (23) : 219-225.

LI Hua,WU Xing,LIU Tao,CHEN Qing

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Abstract

Aiming at problems of the variational mode decomposition (VMD)’s parameters needing to be determined in advance and how to choose intrinsic mode functions (IMFs) containing fault feature information,a method to determine VMD parameters and the other one to choose IMFs both based on information entropy were proposed.With these methods,the original fault signal was decomposed using VMD,and the VMD parameters were optimized with the minimum information entropy principle to obtain several IMFs.The IMF corresponding to the minimum information entropy was chosen as the effective IMF to do the envelope demodulation analysis,and extract a bearing fault feature frequency.Through analyzing bearing simulated signals and actual signals,it was shown that the proposed methods can be used to effectively extract weak features of the early fault signal of a rolling bearing,and realize accurate fault diagnosis.

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variational mode decomposition / information entropy / rolling bearing / envelope demodulation / fault diagnosis

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LI Hua,WU Xing,LIU Tao,CHEN Qing. Bearing fault feature extraction based on VMD optimized with information entropy[J]. Journal of Vibration and Shock, 2018, 37(23): 219-225

References

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