Fuzzy logic application in DGA methods to classify fault type in power transformer

Assessment of power transformer conditions has become increasingly important in recent years. As an asset that represents one of the largest investments in a utility’s system, detection of incipient faults in power transformers is crucial. Dissolved gas-in-oil analysis (DGA) is a successful technique to detect these potential faults and it provides wealth of diagnostic information. This project used two DGA methods which are Rogers Ratio and IEC Ratio to interpret the DGA results. However, there are situations of errors and misleading results occurring due to borderline and multiple faults. Fuzzy logic is implemented here as an improved DGA interpretation method that provides higher reliability and precision of fault diagnosis. Key-Words: DGA methods, Fault diagnosis of transformer, Fuzzy logic, Fuzzy inference, IEC ratio, Rogers ratio