SA-SVM incremental algorithm for GIS PD pattern recognition

Abstract

With changes in insulated defects, the environment, and so on, new partial discharge (PD) data are highly different from the original samples. It leads to a decrease in on-line recognition rate. Using ultra-high frequency (UHF) cumulative energy and its corresponding apparent discharge as inputs, a support vector machine (SVM) incremental method based on simulated annealing (SA) is constructed. Examples show that the new method speeds up the data update rate and improves the adaptability of the classifier.