Diagnosis of Reverse-Connection Defects in High-Voltage Cable Cross-Bonded Grounding System Based on ARO-SVM.

IF 3.4 3区 综合性期刊 Q2 CHEMISTRY, ANALYTICAL Sensors Pub Date : 2025-01-20 DOI:10.3390/s25020590
Yuhao Ai, Bin Song, Shaocheng Wu, Yongwen Li, Li Lu, Linong Wang
{"title":"Diagnosis of Reverse-Connection Defects in High-Voltage Cable Cross-Bonded Grounding System Based on ARO-SVM.","authors":"Yuhao Ai, Bin Song, Shaocheng Wu, Yongwen Li, Li Lu, Linong Wang","doi":"10.3390/s25020590","DOIUrl":null,"url":null,"abstract":"<p><p>High-voltage (HV) cables are increasingly used in urban power grids, and their safe operation is critical to grid stability. Previous studies have analyzed various defects, including the open circuit in the sheath loop, the flooding in the cross-bonded link box, and the sheath grounding fault. However, there is a paucity of research on the defect of the reverse direction between the inner core and the outer shield of the coaxial cable. Firstly, this paper performed a theoretical analysis of the sheath current in the reversed-connection state and established a simulation model for verification. The outcomes of the simulation demonstrate that there are significant variations in the amplitudes of the sheath current under different reversed-connection conditions. Consequently, a feature vector was devised based on the amplitude of the sheath current. The support vector machine (SVM) was then applied to diagnose the reversed-connection defects in the HV cable cross-bonded grounding system. The artificial rabbits optimization (ARO) algorithm was adopted to optimize the SVM model, attaining an impressively high diagnostic accuracy rate of 99.35%. The effectiveness and feasibility of the proposed algorithm are confirmed through the analysis and validation of the practical example.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 2","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11768697/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.3390/s25020590","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

Abstract

High-voltage (HV) cables are increasingly used in urban power grids, and their safe operation is critical to grid stability. Previous studies have analyzed various defects, including the open circuit in the sheath loop, the flooding in the cross-bonded link box, and the sheath grounding fault. However, there is a paucity of research on the defect of the reverse direction between the inner core and the outer shield of the coaxial cable. Firstly, this paper performed a theoretical analysis of the sheath current in the reversed-connection state and established a simulation model for verification. The outcomes of the simulation demonstrate that there are significant variations in the amplitudes of the sheath current under different reversed-connection conditions. Consequently, a feature vector was devised based on the amplitude of the sheath current. The support vector machine (SVM) was then applied to diagnose the reversed-connection defects in the HV cable cross-bonded grounding system. The artificial rabbits optimization (ARO) algorithm was adopted to optimize the SVM model, attaining an impressively high diagnostic accuracy rate of 99.35%. The effectiveness and feasibility of the proposed algorithm are confirmed through the analysis and validation of the practical example.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
相关文献
Mechanical power during mechanical ventilation of critically ill patients
IF 3.7 3区 医学Journal of critical carePub Date : 2017-12-01 DOI: 10.1016/J.JCRC.2017.09.067
A. Neto, R. Deliberato, Alistair E. W. Johnson, P. Amorim, S. M. Pereira, D. Cazati, R. Cordioli, T. Corrêa, E. Coutinho, G. Schettino, K. Timenetsky, P. Pelosi, M. G. Abreu, M. Schultz
Mechanical power thresholds during mechanical ventilation: An experimental study.
IF 2.5 ACS Applied Bio MaterialsPub Date : 2022-03-01 DOI: 10.14814/phy2.15225
Federica Romitti, Mattia Busana, Maria Michela Palumbo, Matteo Bonifazi, Lorenzo Giosa, Francesco Vassalli, Alessandro Gatta, Francesca Collino, Irene Steinberg, Simone Gattarello, Stefano Lazzari, Paola Palermo, Ahmed Nasr, Ann-Kathrin Gersmann, Annika Richter, Peter Herrmann, Onnen Moerer, Leif Saager, Luigi Camporota, John J Marini, Michael Quintel, Konrad Meissner, Luciano Gattinoni
来源期刊
Sensors
Sensors 工程技术-电化学
CiteScore
7.30
自引率
12.80%
发文量
8430
审稿时长
1.7 months
期刊介绍: Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensors and biosensors. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
期刊最新文献
Physical Activity in Pre-Ambulatory Children with Cerebral Palsy: An Exploratory Validation Study to Distinguish Active vs. Sedentary Time Using Wearable Sensors. A Critical Analysis of Cooperative Caching in Ad Hoc Wireless Communication Technologies: Current Challenges and Future Directions. Hydrogenated Amorphous Silicon Charge-Selective Contact Devices on a Polyimide Flexible Substrate for Dosimetry and Beam Flux Measurements. Predicting Perennial Ryegrass Cultivars and the Presence of an Epichloë Endophyte in Seeds Using Near-Infrared Spectroscopy (NIRS). A Multi-Task Causal Knowledge Fault Diagnosis Method for PMSM-ITSF Based on Meta-Learning.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1