Predictive-Adaptive Maintenance Applied for Optimizing the Performance of Industrial Electrical Systems and Equipment

Author:

Munteanu Ionuţ-Cătălin1,Cazacu Emil1,Petrescu Lucian1

Affiliation:

1. 1 National University of Science and Technology POLITEHNICA Bucharest , Romania, Faculty of Electrical Engineering , 313, Splaiul Independentei, 060042, district 6 , Bucharest Romania

Abstract

Abstract In the Industry 4.0 era, predictive maintenance became a crucial element in ensuring the efficiency and reliability of intelligent industrial systems. This paper proposes a critical study on the role and benefits of predictive maintenance in the context of optimizing and enhancing the performance of industrial electrical systems, more specific the on the asynchronous machine, highlighting emerging perspectives and challenges associated with the implementation of this advanced technology. Additionally, it brings to the forefront the latest concepts and solutions in predictive maintenance to provide a more comprehensive and conclusive view at the time of conducting this case study.

Publisher

Walter de Gruyter GmbH

Reference28 articles.

1. S. Nikolic, C. Rados.. Motor Current Signature Analysis in Predictive Maintenance, Journal of Energy – Energija, vol. 67, no.4, pp. 3-6, 2018, https://doi.org/10.37798/201867462.

2. C. Martis, Mentenanța sistemelor industriale, Materiale de curs – Universitatea Tehnică Cluj, https://memm.utcluj.ro/mentenanta.htm

3. A. da Silva, Induction motor fault diagnostic and monitoring methods, A Thesis submitted to the Faculty Of the Graduate School, Marquette University, Milwaukee – Wisconsin, May 2006, https://www.researchgate.net/publication/243055807

4. M. Samiullah, H. Ali, S. Zahoor, A. Ali, Fault Diagnosis on Induction Motor using Machine Learning and Signal Processing, School of Electrical Engineering and Computer Science, (SEECS) National University of Sciences and Technology, Islamabad, Pakistan, January 2024, https://doi.org/10.48550/arXiv.2401.15417

5. O.V. Thorsen, M. Dalva, Failure identification and analysis for high voltage induction motors in petrochemical industry, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242), pp. 291-298, 1998, https://doi.org/10.1109/28.777188

同舟云学术

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