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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.21 No.3
- 발행연도
- 2023.9
- 수록면
- 233 - 238 (6page)
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This study presents a method for identifying partial discharge defects in an eco-friendly gas insulated system using a backpropagation algorithm. Four partial discharge (PD) electrode systems, namely, a free-moving particle, protrusion on the conductor, protrusion on the enclosure, and voids, were designed to simulate PD defects that can occur during the operation of eco-friendly gas-insulated switchgear. The PD signals were measured using an ultrahigh-frequency sensor as a nonconventional method based on IEC 62478. To identify the types of PD defects, the PD parameters of single PD pulses in the time and frequency domains and the phase-resolved partial discharge patterns were extracted, and a back-propagation algorithm in the artificial neural network was designed using a virtual instrument based on LabVIEW. The backpropagation algorithm proposed in this paper has an accuracy rate of over 90% for identifying the types of PD defects, and the result is expected to be used as a reference database for asset management and maintenance work for eco-friendly gas-insulated power equipment.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. EXPERIMENTAL METHOD
Ⅲ. RESULTS AND ANALYSIS
Ⅳ. DISCUSSION AND CONCLUSIONS
REFERENCES
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