BP Neural Network and Its Improved Algorithm In the Power System Transformer Fault Diagnosis

被引：4
|
作者：
Zhang, HaoQian [1 ]
机构：
[1] North China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R China
来源：
APPLIED MECHATRONICS AND ANDROID ROBOTICS | 2013年 / 418卷
关键词：
BP network; GABP model; over-fitting operation; transformer fault diagnosis; OPTIMIZATION;
D O I：
10.4028/www.scientific.net/AMM.418.200
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
According to the measured gas content in power transformers, we use BP neural network to accomplish the pattern recognition of transformer fault. The recognition effect of BP network pattern was studied from the aspects of adding over-fitting operation and genetic algorithm. Four kinds of neural network models, BP model,BP & over-fitted identification model,GABP model and GABP & over-fitted identification model, were constructed respectively, making the pattern recognition effect further enhanced.
引用
收藏
页码：200 / 204
页数：5
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