Fault Diagnosis of Induction Machine using Artificial Neural Network and Support Vector Machine

摘要：

This paper presents an artificial neural network ANN) and support vector machine (SVM) approach for on-line fault diagnosis of induction machine. The proposed approach uses motor currents’ measurements as the medium for the motor fault diagnostics, and the faults are classified using a combination of support vector classifiers (SVCs) and feedforward neural networks (FFNNs). A series of experiments carried through a three phase cage induction machine are performed under different fault conditions to provide training and testing data, and the results presented show that the proposed approach of fault diagnosis gives accurate results in terms of the fault classification.

作者: Ruiming Fang

作者单位: Department of Electrical Engineering Huaqiao University Quanzhou, Fujian, 362021, China

会议类型: 国际会议

会议名称: 第三届国际脉冲动力系统及应用学术会议

会议地点: 青岛

会议语种:英文

在线出版日期: 2006-07-21（万方平台首次上网日期，不代表论文的发表时间）