An enhanced semi-supervised learning method with self-supervised and adaptive threshold for fault detection and classification in urban power grids-Reference-Cited by-同舟云学术

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An enhanced semi-supervised learning method with self-supervised and adaptive threshold for fault detection and classification in urban power grids

Published:2024-09 Issue: Volume:17 Page:100377
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Zhang Jiahao,Cheng Lan,Yang Zhile,Xiao Qinge,Khan Sohail,Liang Rui,Wu Xinyu,Guo Yuanjun^ORCID

Publisher

Elsevier BV

Reference45 articles.

1. Fault diagnosis for electrical systems and power networks: A review;Furse;IEEE Sens J,2020

2. Power quality disturbance classification using Hilbert transform and RBF networks;Jayasree;Neurocomputing,2010

3. Algoritm of current protection based on three instantaneous-value samples;Buryanina,2019

4. Distance protection based on travelling waves;Crossley;IEEE Trans Power Appar Syst,1983

5. Waveform abnormality detection method for distribution system equipment condition monitoring;Luo;Int J Electr Power Energy Syst,2023

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