Statistical pattern analysis of partial discharge measurements for quality assessment of insulation systems in high voltage electrical machinery

In this paper, we present a new statistical analysis method of phase resolved partial discharge (PD) measurements for the quality assessment of the electrical insulation in high voltage machinery. The method is based on a supervised classification approach which utilizes histogram similarity analysis. The motivation for choosing histogram similarity analysis is twofold: first the phase resolved PD measurement itself is, in fact, a two dimensional histogram. Therefore a histogram matching based approach suits the very nature of the data. Second histogram similarity analysis combines the typical statistical parameters, such as mean, variance and higher order moments, used in the recognition of PD measurements in a statistically powerful and rigorous way. In our study, we utilize various histogram types and similarity analysis, including correlation, chi-square and Kolmogorov Smirnov tests. Our experimental study on the laboratory samples demonstrates that the method shows strong potential in defection and identification of insulation defects. The results from our study suggest that the proposed method provides a powerful, general and mathematically simple approach to the analysis of phase resolved PD measurements.