Research On Fault Diagnosis Technology Of Harmonic Motor Bearings

The motor is the main electromechanical energy conversion equipment,the bearing is an important part of the equipment,and the bearing failure is the main reason that affects the normal operation of the motor.Therefore,in-depth study of motor bearing fault diagnosis technology is of great significance.The information of the rolling bearing of the motor is collected by the harmonic detection method,the vibration detection method and the temperature detection method.For the nonlinear and non-stationary characteristics of the fault signal of the rolling bearing of the motor,the time domain,the frequency domain and the frequency domain feature are extracted.And analysis,and then construct the fault eigenvector.BP artificial neural network is adopted in the fault local diagnosis of motor rolling bearing,and D-S evidence theory is adopted in data fusion.Based on the comprehensive analysis of the failure mode of the rolling bearing and the adaptability of the fault detection method,the fault diagnosis for the motor rolling bearing will be data fusion at the decision level,and the empirical mode decomposition(EMD)?BP artificial neural network and DS evidence The theory is effectively combined to construct a data fusion motor rolling bearing fault diagnosis system with multiple information sources.