An early composite fault feature extraction method of bearing based on square envelope spectrum negentropy criterion
CHEN Peng1,ZHAO Xiaoqiang1,2,3
1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China;
3.National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Abstract：In view of the problem that it is difficult to extract the early composite fault feature in fault diagnosis of bearing. An optimized Swarm decomposition (OSWD) method based on the criterion of square envelope spectrum negentropy is proposed. Firstly, an optimization criterion based on square envelope spectrum negentropy is constructed and the improved grasshopper optimization algorithm (IGOA) is used to optimize the threshold parameters of the Swarm decomposition (SWD) to obtain optimal threshold. Then the adaptive decomposition of the composite fault vibration signals is realized by using OSWD. The decomposed components are analyzed by using envelope spectrum analysis to extract the fault feature frequencies. So the early composite fault diagnosis of bearing is accurately realized. Finally, the effectiveness of the proposed method is verified by the simulation analysis case and the fact engineering case.
陈鹏1，赵小强1,2,3. 基于平方包络谱负熵准则的轴承早期复合故障特征提取方法[J]. 振动与冲击, 2022, 41(8): 179-187.
CHEN Peng1,ZHAO Xiaoqiang1,2,3. An early composite fault feature extraction method of bearing based on square envelope spectrum negentropy criterion. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(8): 179-187.
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