Research On Early Weak Fault Diagnosis Method Of Rolling Bearing Based On Mode Decomposition

The interference noise caused by the non-stationary running state of the rolling bearing and the mutual impact of other components drowns out the weak early fault characteristic information,which brings a great challenge to the early weak fault diagnosis of the rolling bearing.Aiming at the early weak fault diagnosis of rolling bearings,conduct the following studies:Aiming at the problem that the early weak fault signals of rolling bearings are difficult to collect,several sets of related experiments were designed to collect effective rolling bearing acoustic and vibration signals.The traditional modal decomposition method is used for the progressive analysis of the collected signals,which not only verifies the effectiveness of the collected signals,but also exposes various problems existing in the traditional methods,which lays a solid foundation for the next research and points out the research direction.Aiming at the problem that the early weak fault characteristics of rolling bearing is extremely weak under the condition of steady speed,and it is easy to be drowned by all kinds of interference and noise,the multi-layer wavelet decomposition idea is used to propose a method for diagnosing the early weak faults of rolling bearings based on multi-layer reconstruction filters,and through the weak fault simulation experiments of rolling bearings and the accelerated damage experiment of the whole life process fully verified the proposed method.Firstly,the number of modes is determined by empirical wavelet decomposition,then the original signal is segmented,and the frequency band containing fault shock is extracted to effectively eliminate the interference of noise.Input the processed signal to the next layer until the preset decomposition layer number is completed to obtain the optimal mode.In the output layer,with the help of the powerful filtering and signal decomposition ability of variational mode decomposition,the early weak fault characteristics of the rolling bearing are finally extracted,and the fault diagnosis of the rolling bearing is realized.Aiming at the problem that the speed and load of rolling bearing are always changing during the actual operation,the early weak fault diagnosis of rolling bearing under the condition of variable speed is studied.In this paper,the most widely used order ratio tracking theory in the field of variable speed is studied,and it is used as a pretreatment method to stabilize the non-stationary signal,so that the feature information related to the speed can be effectively extracted in the next step.The mode number determination and boundary detection problems of traditional empirical wavelet decomposition in early weak fault diagnosis of rolling bearing are systematically studied.An improved empirical wavelet decomposition is proposed for fault diagnosis of rolling bearing.In this method,an empirical wavelet decomposition algorithm based on envelope demodulation is firstly proposed to overcome the existence of high frequency modulation in bearings,so as to extract the correct boundary.On this basis,a method of source number estimation is proposed,which is adaptive to determine the mode number of decomposition.Finally,compared with the traditional fault diagnosis method,the effectiveness of this method in the early weak fault diagnosis of rolling bearing under the condition of single channel,low signal-to-noise ratio and variable speed acoustic signal is verified.