Smart Diagnosis of Incipient Faults Using Dissolved Gas Analysis-Based Fault Interpretation Matrix (FIM)
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An intelligent transformer fault diagnostic model is the urgent need of reliable power system. To achieve this goal, a diagnostic system using a dissolved gas analysis (DGA)-based fault interpretation matrix (FIM) is proposed. FIM overcomes the issues of contradictory decisions of independent methods and provides low-complexity solution in comparison with the previous literature for transformer fault diagnosis. The developed system has accuracy enhancement and decision-making stages. In the first stage, fuzzy augmentation of three important DGA methods, namely Rogers’, IEC and Duval triangle, is carried out followed by the FIM stage and an intermediate normalisation stage. The output of fuzzy models serves as input to the matrix which smartly interprets the fault along with its criticality by exploiting the advantages of individual methods in diagnosing particular fault. This matrix integrates fuzzy augmented methods as per priorities assigned to their outputs. The rules of integration are constructed based on performance assessing factors of individual fuzzy models, and overall decision is made on sensitivity of method for the particular fault type. The performance evaluation of FIM shows its improved diagnostic ability which is intended to improve reliability of DGA-based condition monitoring.
KeywordsFault diagnosis Dissolved gas analysis Fuzzy logic Decision-making
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Authors would like to thank UGC for providing grants under Maulana Azad National Fellowship.
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