An Innovative Fuzzy Modeling Technique For Transformer's Failure Modes And Effects Analysis

Failure mode and effects analysis is a compelling tool for boosting the reliability of a power system network. In this paper, a maintenance strategy is proposed based on the prioritization of maintenance work as per the fuzzy values of risk priority number. The fuzzified approach for the computation of risk assessment uproots the paradoxical behavior of the traditional approach under certain circumstances. Failure modes of each component of a transformer are identified and then occurrence, severity, and detection ratings are assigned for the development of a fuzzy inference system. Based on the input data set, the output surface plots for various parameters are plotted which is subsequently used for maintenance prioritization and suggesting recommended actions. Particular attention is given to the comparison between risk priority number values before and after maintenance or overhaul is performed. This paper will be helpful for researchers and utilities working on the development of optimum maintenance plans for any transformer.