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.

关键词： asynchronous motor fault diagnosis wavelet packet turn-to-turn short circuit air gap eccentricity BP neural network

作者: Li yan Ian Yang jie ming

作者单位: North University Taiyuan, china Taiyuan University of Technology Taiyuan, china

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 602-604

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）