An Application of Support Vector Machines for Induction Motor Fault Diagnosis with Using Genetic Algorithm
Author:
Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-85984-0_24
Reference15 articles.
1. Widodo, A., Yang, B.S., Han, T.: Combination of Independent Component Analysis and Support Vector Machines for Intelligent Faults Diagnosis of Induction Motors. Expert Systems with Applications 32, 299–312 (2007)
2. Yuan, S.F., Chu, F.L.: Fault Diagnostics Based on Particle Swarm Optimization and Support Vector Machines. Mechanical Systems and Signal Processing 21, 1787–1798 (2007)
3. Yang, Y., Yu, D., Cheng, J.: A Fault Diagnosis Approach for Roller Bearing Based on IMF Envelope Spectrum and SVM. Measurement 40, 943–950 (2007)
4. Jack, L.B., Nandi, A.K.: Fault Detection Using Support Vector Machines and Artificial Neural Networks, Augmented by Genetic Algorithms. Mechanical Systems and Signal Processing 16, 373–390 (2002)
5. Samanta, B., Al-Balushi, K.R., Al-Araimi, S.A.: Artificial Neural Networks and Support Vector Machines with Genetic Algorithm for Bearing Fault Detection. Engineering Applications of Artificial Intelligence 16, 657–665 (2003)
Cited by 14 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. Induction motor failures detection using Motor Current Signal Analysis (MCSA) and two-step Support Vector Machine (SVM) classifier;PRZEGLĄD ELEKTROTECHNICZNY;2024-02-19
2. An overview of Artificial Intelligence applications to electrical power systems and DC microgrids;E3S Web of Conferences;2024
3. Fault Prediction in Induction Motor Using Artificial Neural Network Algorithms;Mechanisms and Machine Science;2024
4. State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions;Energies;2023-09-01
5. Inverter-Fed Motor Drive System: A Systematic Analysis of Condition Monitoring and Practical Diagnostic Techniques;Energies;2023-07-26
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