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Obtaining a high Accurate Fault Classification of Power Transformer based on Dissolved Gas Analysis using ANFIS

Author Affiliations

  • 1 PG Department of Electronics Engg., Bapurao Deshmukh College of Engg, Sewagram, MS, INDIA

Res. J. Recent Sci., Volume 1, Issue (2), Pages 97- 99, February,2 (2012)

Abstract

Power Transformers are a vital link in a power system. Well-being of power transformer is very much important to the reliable operation of the power system. Dissolved Gas Analysis (DGA) is one for the effective tool for monitoring the condition of the transformer. To interpret the DGA result multiple techniques are available.IEC codes are developed to diagnose transformer faults. But there are cases of errors and misleading judgment due to borderline and multiple faults. Methods were developed to solve this problem by using fuzzy membership functions to map the IEC codes and heuristic experience to adjust the fuzzy rule. This paper proposes a neuro-fuzzy method to perform self learning and auto rule adjustment for producing best rules.

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