Improved performance of detection and classification of 3-phase transmission line faults based on discrete wavelet transform and double-channel extreme learning machine
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
http://link.springer.com/content/pdf/10.1007/s00202-020-01133-0.pdf
Reference39 articles.
1. Chen K, Huang C, He JL (2016) Fault detection, classification and location for transmission lines and distribution systems: a review on the methods. High Voltage 1(1):25–33
2. Veerasamy V, Abdul Wahab NI, Ramachandran R, Thirumeni M, Subramanian C, Othman ML, Hizam H (2019) High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers. Neural Comput Appl 31:9127–9143
3. Lopes FV, Dantas KM, Silva KM, Costa FB (2018) Accurate two-terminal transmission line fault location using traveling waves. IEEE Trans Power Deliv 33:873–880
4. Darwish HA, Hesham M, Taalab A-MI, Mansour NM (2010) Close accord on DWT performance and real-time implementation for protection applications. IEEE Trans Power Delivery 25(4):2174–2183
5. Krishnanand KR, Dash PK (2013) A new real-time fast discrete S-transform for cross-differential protection of shunt-compensated power systems. IEEE Trans Power Del 28(1):402–410
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Fault Detection on Power Transmission Line Based on Wavelet Transform and Scalogram Image Analysis;Energies;2023-12-04
2. AI-based fault recognition and classification in the IEEE 9-bus system interconnected to PV systems;Smart Science;2023-11-23
3. Fault distance estimation for transmission lines with dynamic regressor selection;Neural Computing and Applications;2023-11-15
4. A Novel Attention Temporal Convolutional Network for Transmission Line Fault Diagnosis via Comprehensive Feature Extraction;Energies;2023-10-16
5. A Novel Convolutional LSTM Network Based on the Enhanced Feature Extraction for the Transmission Line Fault Diagnosis;Processes;2023-10-12
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3