딥러닝 기반 수배전반 내 열화진단 시스템 개발

Translated title of the contribution: Development of a Deep Learning-Based Deterioration Diagnosis System in Switchgear
  • Tae Hyung Kang
  • , Jun Ho Bang
  • , In Ho Ryu*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

The switchgear is a device which receives the high voltage electricity from the generator it into the useable voltage for the consumers. It is an infrastructure can provide the useable voltage from the households to the big facilities throughout our society. But If a blackout emergency occurs, it can cause serious damage. Altuogh the regular inspection of the switchgear is required to prevent the problems and for the safe maintenance, it is very hard because of some factors like non-standardized equipments, dangerous and narrow working spaces and so on. In this paper, we are about to talk about possibility of adapting the thermal imaging camera for the safer and more effecient monitoring and surveillance. We have developed a deep learning-based thermal diagnostic system which can check the information of the main equipments. It also can detect the status data varying by the temperature and notify an alarm to the manager.

Translated title of the contributionDevelopment of a Deep Learning-Based Deterioration Diagnosis System in Switchgear
Original languageKorean
Pages (from-to)1588-1594
Number of pages7
JournalTransactions of the Korean Institute of Electrical Engineers
Volume73
Issue number9
DOIs
StatePublished - 2024.09

Keywords

  • Deep Learning
  • Deterioration Diagnosis
  • Object Detection
  • Status Diagnosis
  • Switchgear

Quacquarelli Symonds(QS) Subject Topics

  • Engineering - Electrical & Electronic
  • Engineering - Petroleum

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