Multispectral characteristic analysis for free metallic particle discharge in SF6 gas conditions

Abstract

Free metallic particle discharge seriously threatens the operation safety of the gas insulated switchgear (GIS). However, limited by the detection sensitivity, anti-interference ability and intelligent diagnosis ability, the traditional electromagnetic detection and chemical detection methods face serious challenges in abnormal discharge detection. In this paper, a practical multispectral detection technology is introduced into free metallic particle discharge diagnosis. According to change the number of the free metallic particle, discharge defects with different risks are simulated. On this basis, phase-based multispectral characteristics such as, phase-resolved partial discharge pattern, pulse phase distribution, and non-phase-based multispectral characteristics such as, time series signal, maximum multispectral pulse intensity, multispectral mean pulse intensity and ternary graph distribution are analyzed to represent the degree of free metallic particle discharge development. Multispectral characteristic analysis provides an effective method to characterize the discharge defects and provides a research basis for the subsequent fine fault diagnosis combined with intelligent algorithms.