Fault diagnosis of induction motor based on information entropy fusion

摘要：

A fault diagnosis method based on information entropy fusion of motor is presented in this paper.Fault feature are extracted though calculating information entropy of collected signal.To improve accuracy of diagnosis,stator current signal,axial vibration signal and radial vibration signal are collected.Based on these eigenvalue of each signal type,primary conclusion is obtained using Neural network.The Dempster combination rule is used to realize information fusion to achieve finally conclusion.The result of experiment shows that information entropy acts well as fault feature and when using multi sensor signal,the reliability of the fault diagnosis method is more accurate and certainty.As a result,the proposed method can improve the accuracy and reliability of fault diagnosis remarkably.

关键词： fault diagnosis induction motor information entropy fusion

作者: A HAN li Shi Li-ping

作者单位: The School of Information and Electronic Engineering,China University of Mining and Technology Xuzhou,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 48-51

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）