HIGH VOLTAGE INSULATOR REAL-TIME CONDITION CLASSIFICATION

Abstract

Insulators have a dual purpose of mechanically supporting and electrically isolating live phase conductors from the support tower in power systems. Due to experiencing harsh weather conditions, insulators may become contaminated or damaged. As a result, electrical and mechanical properties of insulator may deteriorate. Thus, it is significant to automize the process of condition classification of High Voltage insulator to prevent accidents and there fore ensuring secure service of transmission lines. This paper examines the effect of pollution at insulator’s surfaces to the Dielectric Dissipation Factor and therefore research was conducted in 2 different disciplines: 1) Calculation of dielectric dissipation factor using Ansys Maxwell software; 2) High voltage insulators contamination type classification using Convolutional Neural Networks. Ansys Maxwell software is used to simulate the Dielectric Dissipation Factor of insulator under different types of contamination. In this part, three contamination levels (light, medium and heavy) will be considered which include soil, cement, iron, calcium and aluminum as pollutants. The results show trend in which DDF increases with an increase of contamination level. In image classification part, Convolutional Neural Networks will be used to create a classifier. Insulators will be classified be tween 4 types and these are: clean, contaminated with soil, contaminated with water and contaminated with snow. Validation set assessment results in 91% of accuracy.