AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (1.8 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Survey on AI-Assisted Power Transmission Line Fault Detection

Yue Zhang1( )Yonghui Xu2Lizhen Cui2
School of Physics and Electronic Information Engineering, Qinghai Normal University, Xining 810000, China
C-Fair & Software School, Shandong University, Jinan 250000, China
Show Author Information

Abstract

As the main channel for energy transmission, the stable operation of transmission lines is crucial for energy supply and economic development. However, various faults such as short circuits, overloads, and poor grounding contacts inevitably occur during the operation of transmission lines. These faults not only affect the power quality but also cause equipment damage, and even lead to fires and safety accidents. Therefore, the research on transmission line fault detection technology is of great significance. This paper analyzes the advantages and disadvantages of existing artificial intelligence-assisted transmission line fault detection technologies, aiming to provide valuable references for the comprehensive realization of intelligent transmission line fault detection and promote further development in this field.

References

【1】
【1】
 
 
International Journal of Crowd Science
Pages 139-146

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Zhang Y, Xu Y, Cui L. Survey on AI-Assisted Power Transmission Line Fault Detection. International Journal of Crowd Science, 2025, 9(2): 139-146. https://doi.org/10.26599/IJCS.2024.9100016

3310

Views

417

Downloads

3

Crossref

3

Scopus

Published: 13 May 2025
© The author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).