Detection for Stator Winding Turn Fault by using Fuzzy Neural Network

被引：0
|
作者：
Wang Xu-hong [1 ]
He Yi-gang [2 ]
机构：
[1] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China
[2] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
来源：
MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, PTS 1 AND 2 | 2011年 / 48-49卷
关键词：
stator windings; turn fault detection; fuzzy neural network; Genetic algorithm; MOTORS;
D O I：
10.4028/www.scientific.net/AMM.48-49.415
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：
A fuzzy neural network based on-line turn fault detection approach for induction motors is proposed in this paper. B-spline membership fuzzy neural network is employed to detect turn fault and a genetic algorithm with an efficient search strategy is developed to optimize network parameters. Based on it, Experiments are carried out on a special rewound laboratory induction motor, the results show fuzzy neural network based diagnosis model determines the shorted turns exactly, and is more effective than the parameters estimation method under the condition of detecting a slowly developing turn fault.
引用
收藏
页码：415 / +
页数：2
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