Partial Discharge Electrical Tree Growth Identification by Means of Waveform Source Separation Techniques

Abstract

Electrical trees are one of the main degradation processes leading to failure of high voltage polymeric insulation. Electrical trees grow under the effect of partial discharges (PD), which can be measured and analyzed for condition monitoring of electrical insulation. In this paper, techniques that are normally used for classification of PD and noise separation were explored in their ability to determine the stage of growth of electrical trees: Spectral Power Clustering Technique (SPCT), Time-Frequency (TF) maps and Chromatic Technique (CT). The techniques allowed to analyze PD signals captured in ultra-high frequency (UHF) range with an antenna during tree growth. Laboratory treeing-samples were made of epoxy resin and trees were generated at six different excitation frequencies: 0.1, 10, 50, 150, 250 and 350 Hz. The results showed that two parameters, part of SPCT and TF maps, were sensitive to the tree progression and showed a consistent relation with the length of the tree: the low-frequency power ratio and the equivalent bandwidth. These two parameters were selected to create a new map, proposed for the characterization of electrical tree growth, which is more consistent and robust than the original separation maps. It was found that the low-frequency content of PD pulses proportionally increased with tree propagation.