WSEAS Transactions on Power Systems
Print ISSN: 1109-9445, E-ISSN: 2415-1513
Volume 11, 2016
Power Transformer Fault Detection and Isolation Based on Intuitionistic Fuzzy System
Authors: ,
Abstract: Power transformer oil using Dissolved Gas Analysis (DGA) is the most used diagnosis method for power transformer faults. Though various methods have been developed to interpret DGA results, sometimes they fail to determine the faults. Forecasting of the ratios of key-gas in transformer oil is a complicated problem due to its non-linearity and the small amount of training data. This paper presents Intuitionistic Fuzzy System (IFS) to diagnose several faults in a transformer. This proposed approach is recommended for fault transformer diagnosis and the suitable actions to be taken. It has been proved to be a very advantageous tool for transformer diagnosis and upkeep planning. This method is applied to an independent data of different power transformers and various case studies of historic trends of transformer units. This method has been successfully used to identify the type of fault developing within a transformer even if there is conflict in the results of AI technique applied to DGA data.
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Pages: 10-17
WSEAS Transactions on Power Systems, ISSN / E-ISSN: 1109-9445 / 2415-1513, Volume 11, 2016, Art. #2