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Recognition of GIS insulating defect types based on Ultrasonic detection

  • Fang Cheng Lv
  • , Bo Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, high voltage conductor metal protrusions, suspended particles and immobilized metal particles on gas insulated switchgear (GIS) insulators were simulated in the GIS model. The high voltage conductor metal protrusions defect was simulated by a needle-plate model. The GIS model was filled with 0.4MPa SF6 gas. When the voltage was added to 60kV, the three models all had stable discharge. Ultrasonic sensor was used to measure the discharge waveform for 100 groups. The absolute value of difference between the amplitude of adjacent half wave as Udif and the absolute sum of a cycle of the signal as Utal were chosen as the characteristic parameters. The defect types were recognized with BP neural network and the recognition rate is about 80%.

Original languageEnglish
Title of host publicationApplied Material Science and Related Technologies
PublisherTrans Tech Publications
Pages725-729
Number of pages5
ISBN (Print)9783038350361
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 3rd International Conference on Intelligent System and Applied Material, GSAM 2014 - Taiyuan, China
Duration: Jan 18 2014Jan 19 2014

Publication series

NameAdvanced Materials Research
Volume898
ISSN (Print)1022-6680

Conference

Conference2014 3rd International Conference on Intelligent System and Applied Material, GSAM 2014
Country/TerritoryChina
CityTaiyuan
Period01/18/1401/19/14

Keywords

  • BP neural network
  • Gas insulated switchgear
  • The type of insulating defect
  • Ultrasonic detection

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