Stator Winding Turn Faults Diagnosis for Induction Motor by Immune Memory Dynamic Clonal Strategy Algorithm

被引：0

作者：

吴洪兵 ^{[1
,2
]}

楼佩煌 ^{[1
]}

唐敦兵 ^{[1
]}

机构：

[1] College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics

[2] Departments of Electric Engineering,Huaian College of Information Technology

来源：

Journal of Donghua University(English Edition) | 2013年 / 30卷 / 04期

基金：

中国国家自然科学基金;

关键词：

artificial immune system; dynamic clonal strategy; fault diagnosis; stator winding; motor;

D O I：

10.19884/j.1672-5220.2013.04.003

中图分类号：

TM343 [异步电机]; TH165.3 [];

学科分类号：

080202 ; 080801 ;

摘要：

Quick detection of a small initial fault is important for an induction motor to prevent a consequent large fault.The mathematical model with basic motor equations among voltages,currents,and fluxes is analyzed and the motor model equations are described.The fault related features are extracted.An immune memory dynamic clonal strategy(IMDCS)system is applied to detecting the stator faults of induction motor.Four features are obtained from the induction motor,and then these features are given to the IMDCS system.After the motor condition has been learned by the IMDCS system,the memory set obtained in the training stage can be used to detect any fault.The proposed method is experimentally implemented on the induction motor,and the experimental results show the applicability and effectiveness of the proposed method to the diagnosis of stator winding turn faults in induction motors.

引用

页码：276 / 281

页数：6

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