Diagnosis of power transformer incipient faults using Fuzzy Logic-IEC Based Approach

A power transformer in operation is subjected to different stresses such as electrical stress and thermal stress which lead to liberation of gases from the hydrocarbon mineral oil. Dissolved gas analysis (DGA) is one of the most useful methods to detect power transformers incipient faults. There are different conventional DGA methods developed for analyzing these gases such as key Gas, Rogers Ratio, Doernenburg, International Electrotechnical Commission (IEC) Ratio, and Duval triangle. Artificial Intelligence (AI) can be also used to detect power transformers incipient faults. This paper presents Fuzzy Logic-IEC Based approach (FLIBA) to get the correct diagnosis of the incipient faults and the output simulation results are compared with two techniques multi-layer perception neural network (MLPNN) and radial basic function neural network (RBFNN).