Research On Fault Diagnosis Of Motor Bearings For Electric Vehicles Based On Wavelet Transform

Since our country put forward the new energy electric vehicle as a strategic emerging industry,it has an important impact on the change of people's social life,the concept of energy saving and emission reduction,and also has a very important significance for improving the earth's environment.Electric vehicle is a kind of vehicle,and its safety is an important index.Motor is its power source,and its reliability is very important.Bad working conditions and violent vibration of electric vehicle motor make it easy to break down.Rolling bearing fault is one of the main fault sources of electric vehicle transmission system.Bearing fault causes motor vibration to increase,reduces the comfort of electric vehicle,and even causes safety accidents in serious cases.Therefore,periodic detection of bearing operation status and fault diagnosis have attracted much attention,and become a hot spot in the field of fault diagnosis.Firstly,this paper introduces the development trend of electric vehicle,bearing fault diagnosis technology and the research status of fault feature extraction methods at home and abroad.Secondly,according to the influence of bearing fault on the operation parameters(vibration and current)of permanent magnet synchronous motor,the variation of internal parameters of motor after bearing fault is analyzed in detail,and the corresponding characteristic frequency of stator current spectrum is deduced when bearing fault occurs.Then the motor model with bearing fault is established,and the simulation system of electric drive system of electric vehicle based on permanent magnet synchronous motor is established by using the software of MATLAB/Simulink.The stator current data are obtained by simulation operation,and the correctness of the simulation system is verified by analysis.Finally,based on the characteristics that wavelet transform is suitable for processing transient and non-stationary signals,the stator current of the motor is analyzed,the corresponding relationship between the timefrequency domain characteristic information and the fault of the motor bearing is analyzed,and the hidden fault features in the current are extracted.The simulation experiment of fault diagnosis of the motor bearing proves the validity of the method.