The module fault diagnosis of power transformer based on GA-BP algorithm

被引：0
|
作者：
Sun, HQ [1 ]
Sun, LH [1 ]
Liang, YC [1 ]
Guo, YJ [1 ]
机构：
[1] Hebei Univ Sci & Technol, Shijiazhuang 050054, Peoples R China
来源：
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词：
genetic algorithm; BP algorithm; module; power transformer; fault diagnosis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
According to the parameters of voltage and current of power transformer, the faults of power transformer are divided into interior and exterior modules. Genetic algorithm is adopted to optimize the initial value in neural network. BP (back propagation) algorithm is utilized to search in local part and fast gets the matrix of the weight value and the threshold. Then it realizes the fault diagnosis of power transformer. The result proves that the convergence rate of neural network based on genetic algorithm is faster than BP neural network, and improves the speed of fault diagnosis of power transformer.
引用
收藏
页码：1596 / 1598
页数：3
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