Sequential diagnosis method for bearing fault of inwheel motor based on CDI and AHNs
1. School of Mechanical Engineering, Jiangsu University, Zhenjiang， Jiangsu 212013, China; 2.School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang， Jiangsu 212013, China
Abstract： To realize the monitoring and safety evaluation of inwheel motor bearing operating state for electric vehicle, a sequential diagnosis method for mechanical failure of inwheel motors was proposed based on compound distinguish index (CDI) and artificial hydrocarbon networks (AHNs). Considering the effects of vehicle speed conditions on the vibration signal of inwheel motor state, the multiple highsensitivity symptom parameters were extracted in the timefrequency domain based on CDI to characterize the operating state of inwheel motor for improving the timeliness of diagnosis, and a bearing fault sequential diagnosis model of inwheel motor was constructed based on AHNs to identify the operating state of inwheel motor. The proposed method was verified by the experiments of the inwheel motor test bench. The results show that the diagnostic accuracy rate of this method is as high as 98.46% with good robustness, and the method can effectively diagnose the bearing fault of inwheel motor.
