Identification of insulation defects in gas-insulated switchgear by chaotic analysis of partial discharge

Abstract

The recent increase in the number of failures during the installation and insulation of gas-insulated switchgear (GIS) has led to a need for a reliable risk assessment technique. Accordingly, in this study, a fundamental database of UHF partial discharge (PD) patterns corresponding to different types of defects is presented for risk assessment and for the observation and diagnosis of the state of insulation of GIS at field sites; the patterns have been obtained by modelling a number of defects that have been reported to be the most critical in GIS. For the realisation of a system that can simultaneously detect and analyse UHF PD (it is internationally accepted that the use of such a system is the most effective method to diagnose GIS insulation), a wideband UHF sensor and amplifier are designed and fabricated. The system operation is then investigated. In addition, a chaotic analysis of partial discharge (CAPD) is proposed. This analysis can identify the type of defect by means of PD pattern classification without employing the phase information of the applied voltage signal. The proposed CAPD can replace the conventional phase-resolved partial discharge (PRPD) analysis and can be employed at field sites when the phase information is unavailable. Especially, the PD patterns of free-moving conducting particles, known to be very important in GIS, can be distinguished from those of other defects when using the CAPD method, which is not the case when the PRPD analysis is being performed.