Partial Discharge Diagnosis Using Semi-Supervised Learning and Complementary Labels in Gas-Insulated Switchgear

Partial Discharge Diagnosis Using Semi-Supervised Learning and Complementary Labels in Gas-Insulated Switchgear

Deep neural networks have proven to be highly efficient in fault detection and classification using partial discharges (PDs) in gas-insulated switchgear (GIS). However, previous studies have not fully addressed the issue of limited labeled training data, which significantly impacts the performance o...

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Bibliographic Details
Main Authors: Ho Trong Tai, Young-Woo Youn, Hyeon-Soo Choi, Yong-Hwa Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Semi-supervised learning (SSL)
complementary labels
contrastive learning
fault diagnosis
phase-resolved partial discharge (PRPD)
gas-insulated switchgear (GIS)
Online Access:https://ieeexplore.ieee.org/document/10945843/
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https://ieeexplore.ieee.org/document/10945843/

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