Abstract
This paper presents the design of a wideband Hilbert fractal antenna for the purpose of detecting and classifying different common partial discharge (PD) types in an oil-paper insulated system. Three common types of PDs are considered for the multi-class classification problem, namely, PD from a sharp point to ground plane, surface discharge, and PD from a void in the insulation. The different PD types showed variation in the detected frequency contents. The collected samples were processed using pattern recognition techniques to identify their corresponding PD types. A recognition rate of 95% was achieved when K-nearest neighbors was used as the classifier.
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