Performance enhancement of Dissolved Gas Analysis using ANFIS

Author

Yadaiah, Narri ; Ravi, Nishkam

Author_Institution

Dept. of Electr. & Electron. Eng., Jawaharlal Nehru Technol. Univ., Hyderabad, India

fYear

2013

fDate

18-19 Oct. 2013

Firstpage

570

Lastpage

577

Abstract

This paper presents a method for performance enhancement of Dissolved Gas Analysis through Adaptive Neuro - Fuzzy Inference System for fault detection and classification of incipient faults in power transformers. The proposed method is evaluated and results indicate that it is an effective tool for classification of incipient faults. The performance of the proposed method is compared with existing methods namely Rogers ratio method, artificial neural network method.

Keywords

fault diagnosis; finite element analysis; fuzzy reasoning; neural nets; power engineering computing; power transformer protection; transformer oil; ANFIS; Rogers ratio method; adaptive neuro fuzzy inference system; artificial neural network method; dissolved gas analysis; fault classification; fault detection; power transformers; Adaptive Neuro - Fuzzy Inference System; Dissolved Gas Analysis; Doernenburg Ratio; Fault Classification; Fault Detection; Incipient Fault; Partial Discharge Fault; Power Transformer; Rogers Ratio; Temperature Fault;

fLanguage

English

Publisher

iet

Conference_Titel

Computational Intelligence and Information Technology, 2013. CIIT 2013. Third International Conference on

Conference_Location

Mumbai

Type

conf

DOI

10.1049/cp.2013.2648

Filename

6950932