Abstract

This paper presents the design of a Hilbert fractal antenna for the purpose of detecting and classifying different 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 designed antenna is connected to a high frequency spectrum analyzer to acquire PD samples in the frequency domain. The different PD types showed unique frequency patterns for each type. In addition, the collected samples are processed using pattern recognition techniques to automatically identify their corresponding PD types. A recognition rate of 95% was achieved when classifying the different PD types.

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