Study on fault diagnosis for transformer based on adaptive fuzzy inference system

Author

Hu, Wen-ping ; Wang, Xiao-wei ; Yin, Xiang-gen

Author_Institution

Hebei Electr. Power Res. Inst., Shijiazhuang, China

fYear

2008

fDate

10-13 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

This paper has effectively combined self-study advantage of adaptive neural network and fuzzy reasoning method of fuzzy math, resolved the problem that the fuzzy rule is difficult to be determined in the fault diagnosis for transformer insulation, confirmed the fuzzy rule and the fuzzy subject degree by using self-study function of adaptive neural network and established ANFIS model of transformer fault diagnosis. This model has realized the fault diagnosis for electric equipments and reflected the operation condition of the transformer.

Keywords

condition monitoring; fault diagnosis; fuzzy neural nets; fuzzy reasoning; insulation testing; power engineering computing; power transformer insulation; power transformer testing; ANFIS model; adaptive fuzzy inference system; adaptive neural network; electric equipments; fuzzy math; fuzzy reasoning method; fuzzy rule; self-study function; transformer fault diagnosis; transformer insulation; transformer operation condition; Adaptive systems; Fault diagnosis; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Neural networks; Power transformer insulation; Power transformers; Takagi-Sugeno model; Uncertainty; Fault diagnosis; fuzzy theory; neural network; transformer;

fLanguage

English

Publisher

ieee

Conference_Titel

Electricity Distribution, 2008. CICED 2008. China International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-3373-5

Electronic_ISBN

978-1-4244-3372-8

Type

conf

DOI

10.1109/CICED.2008.5211728

Filename

5211728