Linear discriminant analysis for partial discharge classification on high voltage equipment

Abstract

This document is addressing a problem in classifying partial discharge types using linear discriminant analysis. Four PD types generated in the lab are corona at high voltage side in air, corona at low voltage side in air, surface in air, and internal discharge. The independent variables used in this linear discriminant analysis model mainly are from skewness, kurtosis, asymmetry, and cross correlation following the φ - q - n PD patterns obtained from the fingerprint analysis which is a digital signal processing technique for PD measurement. This document also applied stepwise model selection technique to reduce from 10 independent variables to 8 independent variables that not only reduces the complexity of the model estimated but also retains the accuracy of this predictive model to 98.7 percent. © 2006 IEEE.