Research on Transformer Fault Based on Probabilistic Neural Network

被引：2

作者：

Li, Yingshun ^{[1
]}

Li, Jingjing ^{[2
]}

Han, Junfeng ^{[3
]}

机构：

[1] Beijing Inst Petrochem Technol, Beijing, Peoples R China

[2] Guangxi Univ Technol, Liuzhou, Guangxi, Peoples R China

[3] Qinzhou Univ, Qinzhou, Guangxi, Peoples R China

来源：

2015 INTERNATIONAL CONFERENCE ON ENERGY, MATERIALS AND MANUFACTURING ENGINEERING (EMME 2015) | 2015年 / 25卷

关键词：

artificial intelligence; fault diagnosis; expert system; probabilistic neural network;

D O I：

10.1051/matecconf/20152503010

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

With the development of computer science and technology, and increasingly intelligent industrial production, the application of big data in industry also advances rapidly, and the development of artificial intelligence in the aspect of fault diagnosis is particularly prominent. On the basis of MATLAB platform, this paper constructs a fault diagnosis expert system of artificial intelligence machine based on the probabilistic neural network, and it also carries out a simulation of production process by the use of bionic algorithm. This paper makes a diagnosis of transformer fault by the use of an expert system developed by this paper, and verifies that the probabilistic neural network has a good convergence, fault-tolerant ability and big data handling capability in the fault diagnosis. It is suitable for industrial production, which can provide a reliable mathematical model for the construction of fault diagnosis expert system in the industrial production.

引用

页数：4