Research on Transformer Fault Diagnosis Expert System Based on DGA Database

被引：2

作者：

Peng, Zhenghong ^{[1
]}

Song, Bin ^{[2
]}

机构：

[1] Wuhan Univ, Sch Urban Studies, Wuhan 430072, Peoples R China

[2] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Peoples R China

来源：

ICIC 2009: SECOND INTERNATIONAL CONFERENCE ON INFORMATION AND COMPUTING SCIENCE, VOL 2, PROCEEDINGS: IMAGE ANALYSIS, INFORMATION AND SIGNAL PROCESSING | 2009年

关键词：

transformer; DGA; Expert system;

D O I：

10.1109/ICIC.2009.115

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper analyzes and designs the transformer fault diagnosis system based on dissolved gas analysis (DGA) database in which DGA data is managed by the Oracle database. The fault diagnosis module includes the single analyzing item and the Integrated analyzing item, such as, improvement three-ratio method, grey relational entropy, fuzzy clustering, artificial neural networks, and so on. They reduce the insufficiency in diagnosis method which is used now. The system realizes each function of the modules by using the lamination method, it is able to diagnose problems existing in oil chromatogram analysis data of transformer, and the accuracy of the system is also testified by practical example.

引用

页码：29 / +

页数：2

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