DocumentCode :
3276732
Title :
Power Transformer Fault Diagnosis Based on Integrated of Rough Set Theory and Evidence Theory
Author :
Zhou Ai-Hua ; Yao Yi ; Song Hong ; Zeng Xiao-Hui
Author_Institution :
Inst. of Autom. & Electron. Inf., Sichuan Univ. of Sci. & Eng., Zigong, China
fYear :
2013
fDate :
16-18 Jan. 2013
Firstpage :
1049
Lastpage :
1052
Abstract :
When using chromatography data analysis in diagnosis of power transformer fault, fault information cannot be make full use, which can\´t effectively discover knowledge hidden in data. In this paper a method integreted of rough set theory and evidence theory for transformer fault diagnosis is presented. In this approach, in order to avoid subjectivity of basic probability assignment", "rough set was induced to calculate the importance degree of condition attribute to decision attribute and act as basic probability assignment of recognition framework. Different evidence in the same reconginition framwork was combinated to obtain information on the fault types of decision classification information. A large number of examples analysis show that the rough set theory and evidence combination used in electric power transformer fault diagnosis, not only can effectively improve the single fault diagnosis accuracy, also give the information about compound fault analysis.
Keywords :
chromatography; fault diagnosis; power transformers; rough set theory; chromatography data analysis; compound fault analysis; decision classification information; electric power transformer fault diagnosis; evidence theory; fault information; rough set theory; single fault diagnosis; Fault diagnosis; Information systems; Partial discharges; Power transformers; Probability; Set theory; Evidence Theory; Fault Diagnosis; Power Transformer; Rough Set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
Type :
conf
DOI :
10.1109/ISDEA.2012.247
Filename :
6456128
Link To Document :
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