Improved BP neural network in diagnosis of nonlinear fault

被引：0
|
作者：
Xu, Bin [1 ]
Shen, Xiaoju [2 ]
Xue, Weining [3 ]
机构：
[1] North China Inst Sci & Technol, Dept Mech Elect Engn, Sanhe 065201, Peoples R China
[2] North China Inst Sci & Technol, Dept Management, Sanhe 065201, Peoples R China
[3] North China Inst Sci & Technol, Dept Elect & Informat Engn, Sanhe 065201, Peoples R China
来源：
FRONTIERS OF MANUFACTURING SCIENCE AND MEASURING TECHNOLOGY III, PTS 1-3 | 2013年 / 401卷
关键词：
fault diagnosis; neural network; transformer; DISSOLVED-GAS ANALYSIS;
D O I：
10.4028/www.scientific.net/AMM.401-403.1055
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
According to the nonlinear characteristics of transformer fault symptoms and fault types, the application of BP neural network to the problem of transformer fault diagnosis is presented. With a characteristic of the gas content ratio as the input, fault diagnosis model is established by using MATLAB software to achieve improved Newton method. And the simulation experiments show the effectiveness of the model of fault diagnosis.
引用
收藏
页码：1055 / +
页数：2
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