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| A New Feature Extraction Method of Weak Fault Signal Based on VMD and Re-scaling Multi-stable Stochastic Resonance |
| SHI Pei-ming,SU Xiao,YUAN Dan-zhen,SU Guan-hua,MA Xiao-jie |
| Key Lab Measurement Technol & Instrument Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract To realize the feature extraction of rotating machinery in the strong noise environment, a feature extraction method of weak fault signal based on variational mode decomposition and re-scaling multi-stable stochastic resonance is proposed. The first application of parameter optimization of variational mode decomposition (VMD) algorithm for fault signal is decomposed into several intrinsic mode functions (IMFs), and then through the kurtosis criterion and find the maximum kurtosis of IMF component, finally the characteristic frequency of the IMF component through the re-scaling multi-stable stochastic resonance system will be enhanced, which is easily and clearly detected. The simulation analysis and experiments reveal that, in the strong background noise, the combination of optimized VMD algorithm and the method of re-scaling multi-stable stochastic resonance system, can effectively extract weak feature frequency information and realize the accurate judgment of the rotating machinery fault state.
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Received: 29 July 2017
Published: 06 July 2018
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Corresponding Authors:
Peiming Shi
E-mail: spm@ysu.edu.cn
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2018, Vol. 39 
