Analysis and Simulation on Asynchronous Motor Fault Diagnosis
Fazhi Wang · Jisuanji fangzhen · 2010
Motor fault will not only damage itself,but will affect the proper working of the whole system,and even endanger the personal safety,resulting in enormous economic losses.To carry out the motor fault diagnosis well,a new method is put forward to diagnose motor fault,which is based on Elman neural network model and SCG algorithm.Taking Y132S-4 asynchronous motor as the research object,the motor stator current signal is collected for power spectrum estimation to obtain the characteristic frequency of fault.The fault recognition device based on neural network is designed to monitor whether an induction motor is in normal state.The typical faults can be examined.A great deal of simulation work has been carried out and Elman network model obtains more excellent diagnosis results compared to BP network.