A Hybrid Support Vector Fuzzy Inference System for the Classification of Leakage Current Waveforms Portraying Discharges

Abstract

Several techniques have been applied on leakage current waveforms in order to extract information regarding electrical activity on high-voltage insulators. However, a fully representative value is yet to be defined. In this article, a hybrid support vector fuzzy inference system is introduced as a classification tool. The system incorporates fuzzy logic, genetic algorithms, and support vector machines. Apart from the classification accuracy achieved, the system also produces a set of fuzzy rules under which the classification is made, allowing a further insight of the process. A comparison is made to other classification tools previously applied on the same data set.