An improved power transformer diagnosis system for incipient fault based on fuzzy rough set theory

被引：0
|
作者：
Xiong Hao [1 ]
Li Weiguo [2 ]
Chang Guanghui [1 ]
Guo Huimin [3 ]
机构：
[1] Wuhan Univ, Wuhan 430072, Peoples R China
[2] North China Elect Power Univ, Beijing, Peoples R China
[3] Power Co Henan Prov, Zhengzhou, Peoples R China
来源：
2006 INTERNATIONAL CONFERENCE ON POWER SYSTEMS TECHNOLOGY: POWERCON, VOLS 1- 6 | 2006年
关键词：
knowledge discovery in database (KDD); Fuzzy rough sets; data mining; dissolved gas-in-oil analysis (DGA);
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Based on fuzzy rough set theory(FRS), the paper is meant to present a new diagnosis system with gas ratios method for transformer incipient fault diagnosis, which not only has the capability of coping with incomplete information inputting and rules reduction just as in conventional rough set theory(RS), but also has the capability of fuzzification of thresholds of continuous values of attributes. Since strict thresholds setting is said to undergo the diagnosis effectiveness, A method of fuzzy subsets extraction from database based on KDD technology is employed to the setting attributes, which improve the power of prevailing IEC/IEEE criteria in fields of strict thresholds setting. Finally, results of testing the proposed diagnosis system on actual dissolved gas records are addressed, which confirmed that rules represented by fuzzy terms and extracted based on FRS allow diagnosis results to be satisfied, and diagnosis system proposed can provide a satisfactory accuracy.
引用
收藏
页码：861 / +
页数：2
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