关键词: 变分模态分解；遗传算法；轴承；故障诊断；1.5维谱

Abstract: In order to extract fault features of bearings accurately，a method of parameter optimized variational mode decomposition(VMD)based on genetic algorithm(GA)combining with 1.5-dimensional spectrum was proposed for the fault diagnosis of bearing. Firstly，taking envelope entropy of modal components in the VMD method minimum as the optimization goal，number of modal components and secondary penalty factor were optimized by employing genetic algorithm，and the two input parameters which can realize the optimal decomposition of VMD were determined. Then，a simulated signal and the inner ring faulty signal of a bearing were decomposed using the parameter optimized VMD method，and 1.5-dimensional spectrum diagrams of each modal component were plotted. The parameter optimized VMD method decomposed and gained four modal components which were consistent with the original components of the simulated signal. 1.5-dimensional spectrum eliminated the 10Hz frequency component which was not involved in the quadratic phase coupling. In the meantime，the proposed method in this paper extracted the first to sixth harmonics and the modulation frequencies of the motor’s rotating frequency with them below the 1kHz. It showed that parameter optimized VMD based on genetic algorithm can decompose complex signals into several modal components accurately，and 1.5-dimensional spectrum can detect quadratic phase coupling of signals effectively. Meanwhile，parameter optimized VMD based on genetic algorithm combined with 1.5-dimenaionl spectrum can extract inner ring fault features effectively，which verifies the effectiveness and practicability of the method proposed in the paper.

Key words: Variational mode decomposition；Genetic algorithm；Bearing；Fault diagnosis；1.5-dimentional spectrum