A New Discharge Pattern for the Characterization and Identification of Insulation Defects in GIS
Rui Yao,
Meng Hui,
Jun Li,
Lin Bai and
Qisheng Wu
Additional contact information
Rui Yao: School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China
Meng Hui: School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China
Jun Li: State Grid Shaanxi Electric Power Research Institute, Xi’an 710049, China
Lin Bai: School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China
Qisheng Wu: School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China
Energies, 2018, vol. 11, issue 4, 1-18
Abstract:
Identification of insulation defects in gas insulated metal-enclosed switchgear (GIS) is important for partial discharge (PD) evaluation. This article proposes a polar coordinate pattern approach to characterize the different kinds of defect types. These defect types include floating electrodes, a fixed protrusion on the enclosure, surface contamination on the spacer, metallic prominence on the high voltage electrode, a void in the insulator, and free metal particles on the enclosure. First, the physical models for the insulation defects in the established GIS model are designed. Second, the phase resolved pulse sequence (PRPS) data sets are obtained using ultra-high frequency (UHF) measurement. Then, the polar coordinate patterns are proposed to characterize the defects. Nine discharge parameters combined with the parameters based on quadrant statistical theory constitute the input feature vector to identify the PD types. The experimental results show that these new parameters could produce a clear, quantitative description of the characteristics of the defect types and could be used to distinguish between the different kinds of defect types.
Keywords: gas insulated metal-enclosed switchgear (GIS); partial discharge; polar coordinate pattern; K-means clustering algorithm; feature vector; classification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/1996-1073/11/4/971/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/4/971/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:4:p:971-:d:141761
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().