Abstract:
Well-being of power transformer is crucial to the reliable operation of power system. Dissolved gas analysis is an important tool for online monitoring of transformer insulation. Although IEC codes were developed to diagnose transformer faults, there are situations of errors and misleading results occurring due to borderline and multiple faults. Methods were developed to solve this problem by using fuzzy membership functions to map the IEC codes and heuristic experience to adjust the fuzzy rules. This paper proposes a fuzzy-neural method to perform self-learning and auto rule-adjustment for producing the best rules. Tests using the hybrid diagnosis system are satisfactory.
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