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논문 기본 정보

자료유형
학술저널
저자정보
Geetha Mani (PSG College of Technology) Jovitha Jerome (PSG College of Technology)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.9 No.6
발행연도
2014.11
수록면
2,058 - 2,064 (7page)

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초록· 키워드

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In transformer fault diagnosis, dissolved gas analysis (DGA) is been widely employed for a long period and numerous methods have been innovated to interpret its results. Still in some cases it fails to identify the corresponding faults. Due to the limitation of training data and non-linearity, the estimation of key-gas ratio in the transformer oil becomes more complicated. This paper presents Intuitionistic Fuzzy expert System (IFS) to diagnose several faults in a transformer. This revised approach is well suitable to diagnosis the transformer faults and the corresponding action to be taken. The proposed method is applied to an independent data of different power transformers and various case studies of historic trends of transformer units. It has been proved to be a very advantageous tool for transformer diagnosis and upkeep planning. This method has been successfully used to identify the type of fault developing within a transformer even if there is conflict in the results of AI technique applied to DGA data.

목차

Abstract
1. Introduction
2. Preliminaries
3. Proposed IFS Based Transformer Fault Diagnosis
4. Results and Discussions
5. Conclusion
References

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