Identification and diagnosis of electrical fault of asynchronous motor

摘要

this paper puts forward the method that the wavelet combines with neural network, and applies the method to identify and diagnose the electrical fault of small asynchronous motor. By experiment we can obtain the data when the small asynchronous motor exist the air gap eccentricity and turn-to-turn short circuit fault and then picks up the two fault feature which is used to input vector of the ANN by using the wavelet packet. Effectively, then we can identify the three Conditions of the small asynchronous motor. that is to say, the normal motor, the air gap eccentricity and turn-to-turn short circuit fault motor with pattern classification function of neural network