A method for fault diagnosis of cycloidal gear reducers based on ensemble empirical mode decomposition(EEMD)and order tracking analysis was proposed,in response to the problems of complex components,high noise interference during operation,and difficulty in accurately extracting internal fault characteristics of cycloidal gear reducers,which often operate under complex working conditions such as variable speed and reciprocating.Firstly,the collected time-domain vibration signal and speed signal were subjected to equal angle domain difference sampling to obtain the equal angle domain stationary signal of the vibration signal.Secondly,the ensemble empirical mode decomposition on angular domain signals was performed to obtain several intrinsic mode functions(IMFs),by calculating the kurtosis values of each intrinsic mode component,the target mode component was selected for signal reconstruction.Then,the order diagram of the fault signal was obtained through fast Fourier transform.Finally,based on the transmission mode of the reducer and the modulus of each component,the fault order of its main components was calculated,and the energy peak of the order graph before and after the fault of the reducer for fault diagnosis was compared.The research results show that the proposed method can accurately extract the intrinsic mode components containing fault information,achieve the conversion from equidistant time domain signals to equiangular domain signals,extract the roller fault order(8.37 orders)of the cycloidal pin wheel reducer,and achieve a fault accuracy of 99.6%.It realizes the fault feature recognition of the cycloidal pin wheel reducer under non-stationary working conditions,and verifies the feasibility and effectiveness of the proposed method.
万方数据
维普
