Fuzzy-Logic Applications in Transformer Diagnosis Using Individual and Total Dissolved Key Gas Concentrations

Abstract

The gases generated in oil filled transformer can be used for determination of incipient faults. Dissolved gas analysis (DGA) of transformer oil has been one of the most power full methods to detect the faults. The various methods such as liquid chromatography, acoustic analysis, and transformer function techniques are require some experience to interpret observations. The researchers have used artificial intelligence (AI) approach to encode these diagnostic techniques. This paper presents an expert system using AI techniques which can diagnose multiple faults in a transformer theoretical and practical fuzzy-logic information model. We also concluded by identifying limitations, recent advances and promising future research directions over seventy and more power transformers.