Application of RCMDE and ISOMAP in coupling fault identification of planetary gear transmission
The existing fault diagnosis methods for planetary gearbox generally only studied a single fault,but the actual planetary gearbox fault was usually caused by the coupling of multiple faults.The fault mechanism of coupling fault was more complicated than that of a single fault,and the nonlinear factors in vibration signal had more serious interference to feature extraction.To solve this problem,a planetary gearbox coupling fault diagnosis method based on refined composite multiscale diversity entropy(RCMDE),isometric feature mapping(ISOMAP),and genetic algorithm optimized kernel extreme learning machine(GA-KELM)was proposed.Firstly,vibration accelerometer was used to collect vibration signals of planetary gearbox under single fault and coupling fault,and the fault data set was constructed.Secondly,RCMDE was used to extract the fault features of the planetary gearbox vibration signal and establish initial feature samples.Then,ISOMAP was used to reduce the dimension of fault features and visualize them to obtain low-dimensional feature samples.Finally,the new features were input into the GA-KELM classifier to realize the identification of different fault types of planetary gearbox.The reliability of RCMDE method was studied based on multi-point damage samples of planetary gearbox.The research results show that the fault feature extraction method based on RCMDE and ISOMAP can effectively extract the fault feature from the vibration signal,while the fault diagnosis accuracy of GA-KELM is 98.13%,and the average diagnosis accuracy is 96.25%.Comparing with other fault feature extraction methods,the proposed method can diagnose the coupling fault of planetary gearbox better and has higher diagnostic accuracy.