Fuzzy logic approach to identify transformer criticality using dissolved gas analysis

Abstract

Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results. However, all of these techniques rely on personnel experience more than standard mathematical formulation. DGA interpretation is yet a challenge in the power transformer condition monitoring research area. This paper introduces a novel fuzzy logic approach to help in standardizing DGA interpretation techniques and to identify transformer critical ranking using DGA. DGA has been performed on several oil samples that have been collected from different transformers. Traditional DGA interpretation techniques are used to analyze the results and then compared with the results of the fuzzy logic model. Results show that the fuzzy logic model is very effective in interpreting DGA results identifying the critical ranking of the power transformer based on DGA.