Semi-Supervised Learning-Based Partial Discharge Diagnosis in Gas-Insulated Switchgear-Reference-Cited by-同舟云学术

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Semi-Supervised Learning-Based Partial Discharge Diagnosis in Gas-Insulated Switchgear

Published:2024 Issue: Volume:12 Page:115171-115181
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tai Ho Trong¹^ORCID,Youn Young-Woo²^ORCID,Choi Hyeon-Soo³,Kim Yong-Hwa¹^ORCID

Affiliation:

1. Department of Computer Science and Information, Korea National University of Transportation, Uiwang, Gyeonggi, Republic of Korea

2. Smart Grid Research Division, Korea Electrotechnology Research Institute, Gwangju, Republic of Korea

3. Genad Systems, Naju, Jeollanam, Republic of Korea

Funder

Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10639399.pdf?arnumber=10639399

Reference42 articles.

1. State of the art in insulation of gas insulated substations: main issues, achievements, and trends

2. GIS insulation co-ordination: on-site tests and dielectric diagnostic techniques. A utility point of view

3. The Study on a New Method for Detecting Corona Discharge in Gas Insulated Switchgear

4. Investigation of a comprehensive identification method used in acoustic detection system for GIS

5. Partial Discharge and Movement Characteristics of Micron-sized Metal Particles on Insulator Surface in Gas-Insulated Switchgear with Long-time AC Stress

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