Taxonomy of Induction-Motor Mechanical-Fault Based on Time-Domain Vibration Signals by Multiclass SVM Classifiers
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Link
http://link.springer.com/content/pdf/10.1007/s40903-016-0053-x.pdf
Reference29 articles.
1. Siyambalapitiya, D.J.T., McLaren, P.G.: Reliability improvement and economic benefits of on-line monitoring system for large induction machines. IEEE Trans. Ind. Appl. 26(6), 1018–1025 (1990)
2. Zhongming, Y., Bin, W.: A review on induction motor online fault diagnosis. Proceedings of the IEEE Third International Conference on Power Electronics and Motion Control, IPEMC 3, 1353–1358 (2000)
3. Timusk, M., Lipsett, M., Mechefske, C.K.: Fault detection using transient machine signals. Mech. Syst. Signal Process. 22(7), 1724–1749 (2008)
4. Kral, C., Habetler, T.G., Harley, R.G., Pirker, F., Pascoli, G., Oberguggenberger, H., Fenz, C.J.M.: A comparison of rotor fault detection techniques with respect to the assessment of fault severity. In: Proceedings of the 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED, pp. 265–270 (2003)
5. Nguyen, N.T., Lee, H.H.: An application of support vector machines for induction motor fault diagnosis with using genetic algorithm. In: Huang, D.-S., Wunsch II, D.-C., Levine, D.-S., Jo, K.-H. (eds.)International Conference on Intelligent Computing (ICIC-2008), pp. 190–200. Springer, Heidelberg (2008)
Cited by 15 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. Additive fault diagnosis techniques in rotor systems: a state-of-the-art review;Sādhanā;2024-06-27
2. Fault Prediction in Induction Motor Using Artificial Neural Network Algorithms;Mechanisms and Machine Science;2024
3. Classification and Authentication of Induction Motor Faults using Time and Frequency Feature Dependent Probabilistic Neural Network Model;Journal of The Institution of Engineers (India): Series B;2023-03-15
4. Diagnostics of Combined Mechanical and Electrical Faults of an Electromechanical System for Steady and Ramp-Up Speeds;Journal of Vibration Engineering & Technologies;2022-03-26
5. Artificial intelligence application in fault diagnostics of rotating industrial machines: a state-of-the-art review;Journal of Intelligent Manufacturing;2021-11-12
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