Analysis and Diagnosis of Optical and UHF Partial Discharges in GIS Based on Guided Filtering Fusion

Abstract

The optical method and ultrahigh frequency (UHF) method are important techniques for detecting partial discharge (PD) in gas-insulated switchgear (GIS). However, optical signals and UHF signals may suffer from different degrees of signal loss or interference for different PD types, which leads to incomplete feature information in the optical or UHF patterns and reduces the accuracy of pattern recognition. In this article, a PD detection device in GIS based on the UHF and light guide rod (LGR) technologies is designed. An experimental platform for electrical and optical PD detection in GIS is set up, and measurements of typical PD are carried out. Optical and UHF time-domain signals of corona discharge, floating discharge, and particle discharge are obtained. Then, an image fusion algorithm based on guided filtering fusion (GFF) is proposed to fuse the optical and UHF phase-resolved pulse sequence (PRPS) patterns. Subsequently, a feature extraction method based on speeded-up robust features (SURFs) for PD images is proposed. Finally, the recognition effects of multiple classifiers are compared. The results show that the image fusion and feature extraction method for UHF and optical PD proposed in this article can improve the accuracy of fault diagnosis up to 97.1%.