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Comparative Analysis of Partial Discharge Pattern Recognition Using Deep Learning and Machine Learning
- Hong, Tae-yoon;
- Ahn, Hyun-mo;
- Jang, Hyun-jae;
- Park, Junkyu;
- Sun, Jong-ho;
- ... Kim, Jingyu
Citations
SCOPUS
1초록
Partial Discharge (PD) defect type analysis is important for evaluating insulation performance. A machine learning feature extraction algorithm is presented for AC PD pattern data collected in the laboratory, along with deep learning algorithms for PD pattern images and PD time series data. In addition, data is collected under conditions different from those used for artificial intelligence (AI) training, and algorithm performance is evaluated and compared. © 2024 The Korean Institute of Electrical Engineers (KIEE).
키워드
deep learning; high voltage; machine learning; partial discharge; phase resolved partial discharge
- 제목
- Comparative Analysis of Partial Discharge Pattern Recognition Using Deep Learning and Machine Learning
- 저자
- Hong, Tae-yoon; Ahn, Hyun-mo; Jang, Hyun-jae; Park, Junkyu; Sun, Jong-ho; Kim, Jingyu
- 발행일
- 2024
- 유형
- Conference paper
- 페이지
- 702 ~ 704
- 언어
- ENG
- 출판사
- Institute of Electrical and Electronics Engineers Inc.
- 분량
- 3 페이지