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http://dx.doi.org/10.5370/KIEEP.2016.65.3.188

Fault Diagnosis of Oil-filled Power Transformer using DGA and Intelligent Probability Model  

Lim, Jae-Yoon (Dept. of Computer Electronics Daeduk College)
Lee, Dae-Jong (Dept. of Electrical Engineering Korea National University of Transportation)
Ji, Pyeong-Shik (Dept. of Electrical Engineering Korea National University of Transportation)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.65, no.3, 2016 , pp. 188-193 More about this Journal
Abstract
It has been proven that the dissolved gas analysis (DGA) is the most effective and convenient method to diagnose the transformers. The DGA is a simple, inexpensive, and non intrusive technique. Among the various diagnosis methods, IEC 60599 has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using DGA and Intelligent Probability Model. To demonstrate the validity of the proposed method, experiment is performed and its results are illustrated.
Keywords
Fault diagnosis; Power transformer; DGA; Intelligent probability model;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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