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.
时培明,苏晓,袁丹真,苏冠华,马晓杰. 基于VMD和变尺度多稳随机共振的微弱故障信号特征提取方法[J]. 计量学报, 2018, 39(4): 515-520.
SHI Pei-ming,SU Xiao,YUAN Dan-zhen,SU Guan-hua,MA Xiao-jie. A New Feature Extraction Method of Weak Fault Signal Based on VMD and Re-scaling Multi-stable Stochastic Resonance. Acta Metrologica Sinica, 2018, 39(4): 515-520.
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2018, Vol. 39 
