Abstract
As a need to reduce cost and minimize losses associated with downtime, early fault diagnosis has become necessary for more reliable, efficient, and productive industrial maintenance practices. This research was able to optimize the Enhanced Park Vector Approach (EPVA) by maximizing the advantage of the visualized Park vector plot, whose distortion is directly proportional to the degree of faults, to diagnose and compute the Fault Severity Index (FSI) of an occurred fault. The research was simulated on MATLAB using the mathematical model of an induction motor (IM). Iterative values of 0%, 1%, 3%, 5%, and 10% of inter-turn short circuit (ITSC) fault were used to study the state of the IM. The research was able to contribute to an effective mathematical computational method of computing the severity of fault using standard deviation and variance.
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