Genetic Algorithm Application to Detect Broken Rotor Bar in Three Phase Squirrel Cage Induction Motors

被引：0

作者：

Rashtchi, Vahid ^{[1
,3
]}

Rahimpour, Ebrahim ^{[2
]}

Fazli, Saeid ^{[1
]}

机构：

[1] Univ Zanjan, Fac Elect Engn, Zanjan, Iran

[2] ABB AG, R&D Dept, Power Prod Div, Transformers, Bad Honnef, Germany

[3] Univ Zanjan, Fac Engn, Zanjan, Iran

来源：

INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE | 2011年 / 6卷 / 05期

关键词：

Induction Motors; Fault Detection; Genetic Algorithm; Broken Bar; MACHINES; DIAGNOSIS; FAULTS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

One of the most important faults of a three-phase squirrel cage induction motor is broken rotor bar. The detection of this fault is necessary to avoid outage of motor as swell as subsequent damage to other equipment. Present paper introduces a new systematic straightforward method based on parameter identification for accurate detection of this type of fault in order to help enhance the diagnosis system of induction motors. The proposed method uses a genetic algorithm (GA) with data collected from a simple experiment on the selected motor. The validity of the scheme is shown for a motor with ratings of 1 hp and 380 V, under different operating point conditions. The analysis and decision in the proposed method can be achieved within a proper time. Copyright (C) 2011 Praise Worthy Prize S.r.l. - All rights reserved.

引用

页码：2286 / 2292

页数：7

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