Fault Diagnosis of Rotor Winding Inter-turn Short Circuit in Turbine-Generator Based on BP Neural Network

被引:0
|
作者
Li, Yong-gang [1 ]
Zhao, Yan-jun [1 ]
Chen, Lei [1 ]
Ji, Xuan [1 ]
机构
[1] N China Elect Power Univ, Sch Elect Engn, Baoding 071003, Peoples R China
关键词
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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
The electromagnetic characteristic and rotor vibration characteristic of turbine-generator are analyzed when rotor winding inter-turn short circuit fault has happened. This paper reveals that exciting magnetic force F(f) is constant in a fixed condition whereas the exciting current I(f) increases in case of rotor inter-turn fault. This paper also finds relevant characteristic parameters. Based on the theory, we can get training patterns without doing destructive tests. Then BP (back propagation) neural network can be adequately trained and diagnosis rotor winding inter-turn short circuit. BP neural network is independent on mathematic models and parameters of turbine-generator. Finally practically acquired dynamic experiment data of the MJF-30-6 generator, the results of verification show that the theory analysis is right and the method is efficient and accurate.
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收藏
页码:783 / 787
页数:5
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