Motor Inverter Fault Diagnosis Using Wavelets Neural Networks

被引：12

作者：

Qiang, Sheng ^{[1
]}

Li, Yingying ^{[1
]}

机构：

[1] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150006, Peoples R China

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) | 2013年

关键词：

Inverter Fault diagnosis; Open switch; Short circuit switch; Wavelet transform; RBF neural network; AUTOMATIC DIAGNOSIS; DRIVES; LOCATION;

D O I：

10.1109/SMC.2013.540

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Diagnosis and location of the power transistor open switch and short circuit switch faults in inverter are studied. Wavelet transform is used to extract diagnostic indices from the current, speed and torque waveforms of brushless DC drive system. RBF neural network is developed to identify and locate the fault. RBF neural networks are trained offline using simulation results under various healthy and faulty conditions from a simulation model. Simulation results confirm the effectiveness of the proposed methodology.

引用

页码：3168 / 3173

页数：6

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