Adopting integration of multispectral time resolved analysis and graph-based deep learning method in partial discharge type identification

Abstract

Partial discharge (PD) is treated as one of the major threats for gas insulated switchgear (GIS). By using the new generation multispectral detection sensor named as SiPM-based multispectral discharge sensor (SMDS), the time resolved partial discharge with multispectral information (named as MTRPD) for creeping discharge, suspension discharge and tip discharge, respectively. It indicates that the MTRPD for the specific discharge defect perform unique spectral fingerprints in discharge mode. Based on the graph characteristics of MTRPD, we introduced the convolution neural network (CNN) to implement PD type identification whose overall accuracy of Δqi-Δqi+1 and Δti-Δti+1 were 99.7% and 98.9%, respectively. This paper provides a new technique tool for fine diagnosis of PD independent of phase analysis.

Partial discharge localization method utilizing a 3D optical sensor array

“…After detecting a partial discharge fault, accurate and timely localization of the fault is crucial for subsequent equipment maintenance and troubleshooting 1,2 . it also represents one of the key research areas in gas insulated switcher (GIS) equipment's partial discharge analysis 3,4 . based on different methods used for detecting partial discharges, current approaches to locating such faults primarily include uhf detection and positioning technology 5 , ultrasonic positioning technology 6 , acousto-electric joint positioning technology 7 , uhf-ultrasonic joint positioning technology 8 , electrical positioning technology 9 , and optical positioning technology 10 .…”

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

“…Furthermore, the microscopic information contained in the discharge spectral information has been fully revealed due to the development of spectral acquisition technology 10 . To realize practice discharge spectral analysis, Ren Ming et al proposed a partial discharge (PD) multispectral detection device based on the new generation of silicon optoelectronic semiconductors (SiPM) [11][12][13][14] . In this paper, with reference to the research ideas of the above scholars, we introduce the multi-spectral detection technology into the discharge detection of metal particles, analyze the multispectral evolution characteristics of metal particles in the discharge development process, and provide a basis for the fine diagnosis of free metal particles.…”