Development of partial discharge detection method using an autoregressive model in gas‐insulated switchgears (GIS)

Hiroshi Inujima*, Takeshi Masui, Hiroshi Maekawa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Gas‐insulated switchgears (GIS) are important equipment in electric‐supply stations where advanced techniques for safety and maintenance are required. As a result, a system is being developed that can automatically monitor and diagnose a GIS in service. This article focuses on some problems concerning insulating functions of GIS to discuss a method of signal processing for partial discharge detection and position identification. For sensors, potential detectors were installed on flanges of the GIS. Focusing on the potential fluctuations measured by these detectors, an autoregressive model is designed for potential fluctuation in a state without any partial discharge. This model is called a normal state model. The difference was found between potential fluctuations measured during partial discharge and those of the normal state model. The index of whiteness test method of the residual random process is a useful parameter for representing this difference, and the use of this method allowed detection of partial discharge that could not be found at normal potential levels. These results indicate bright prospects for manufacturing a monitoring system that can detect deterioration in GIS insulation with a high sensitivity in an early stage and that also operates on‐line.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalElectrical Engineering in Japan
Issue number1
Publication statusPublished - 1995 Feb
Externally publishedYes


  • GIS
  • abnormal diagnosis
  • autoregressive model
  • partial discharge
  • signal processing

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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