Research on Bearing Intelligent Diagnostic Technology Based on EMD and GA-BP

Zhikai Xing, Qiang Wang, Yongbao Liu, Yansong Guo, Yan Jia, Mo Li, Jun Li


Bearings are the core components of rotating machinery and can have a significant impact on the equipment in the event of a failure. In this paper, an intelligent diagnostic technique based on the combination of EMD and GA-BP algorithm sifts with the rolling bearing fault identification and classification problem. First, the test data is processed by EMD method, the characteristic enhancement and extraction of micro-faults is realized, and the bearings are trouble shoot as training sets and test sets of BPNNs optimized by the built GA. The results show that the accuracy and convergence speed of this method are improved compared with the method of unutilized energy characteristics, and the identification and diagnosis of bearing fault can be effectively carried out.


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