基于机器学习的电力电子电路可靠性评估研究

Q2 Energy

International Journal of Power Electronics and Drive Systems Pub Date : 2021-03-01 DOI:10.11591/IJPEDS.V12.I1.PP558-566

Soumya Rani Mestha, Pinto Pius A.J

{"title":"基于机器学习的电力电子电路可靠性评估研究","authors":"Soumya Rani Mestha, Pinto Pius A.J","doi":"10.11591/IJPEDS.V12.I1.PP558-566","DOIUrl":null,"url":null,"abstract":"Recent advances in power electronics (PE) and machine learning (ML) have prompted the technologists to adapt these new technologies to improve the reliability of PE systems. During the process, a lot of investigations on the performance and reliability of PE systems is carried out. The intention of this paper is to present a comprehensive study of advances in the field of reliability of PE systems using machine learning. Recent publications in this regard are analysed and findings are tabulated. In addition to this, literatures published in the prediction of remaining useful life (RUL) of power electronic components is discussed with emphasis on its limitations.","PeriodicalId":38280,"journal":{"name":"International Journal of Power Electronics and Drive Systems","volume":"12 1","pages":"558-566"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Investigation of reliability assessement in power electronics circuits using machine learning\",\"authors\":\"Soumya Rani Mestha, Pinto Pius A.J\",\"doi\":\"10.11591/IJPEDS.V12.I1.PP558-566\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent advances in power electronics (PE) and machine learning (ML) have prompted the technologists to adapt these new technologies to improve the reliability of PE systems. During the process, a lot of investigations on the performance and reliability of PE systems is carried out. The intention of this paper is to present a comprehensive study of advances in the field of reliability of PE systems using machine learning. Recent publications in this regard are analysed and findings are tabulated. In addition to this, literatures published in the prediction of remaining useful life (RUL) of power electronic components is discussed with emphasis on its limitations.\",\"PeriodicalId\":38280,\"journal\":{\"name\":\"International Journal of Power Electronics and Drive Systems\",\"volume\":\"12 1\",\"pages\":\"558-566\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Power Electronics and Drive Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/IJPEDS.V12.I1.PP558-566\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power Electronics and Drive Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/IJPEDS.V12.I1.PP558-566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}

引用次数: 1

摘要

电力电子（PE）和机器学习（ML）的最新进展促使技术人员采用这些新技术来提高PE系统的可靠性。在此过程中，对PE系统的性能和可靠性进行了大量的研究。本文旨在利用机器学习对PE系统可靠性领域的进展进行全面研究。对这方面的最新出版物进行了分析，并将调查结果制成表格。除此之外，还讨论了发表在电力电子元件剩余使用寿命预测（RUL）中的文献，并强调了其局限性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Investigation of reliability assessement in power electronics circuits using machine learning

Recent advances in power electronics (PE) and machine learning (ML) have prompted the technologists to adapt these new technologies to improve the reliability of PE systems. During the process, a lot of investigations on the performance and reliability of PE systems is carried out. The intention of this paper is to present a comprehensive study of advances in the field of reliability of PE systems using machine learning. Recent publications in this regard are analysed and findings are tabulated. In addition to this, literatures published in the prediction of remaining useful life (RUL) of power electronic components is discussed with emphasis on its limitations.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Power Electronics and Drive Systems Energy-Energy Engineering and Power Technology

CiteScore

3.50

自引率

0.00%

发文量

期刊介绍： International Journal of Power Electronics and Drive Systems (IJPEDS) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of power electronics and electrical drive systems from the global world. The scope of the journal includes all issues in the field of Power Electronics and drive systems. Included are techniques for advanced power semiconductor devices, control in power electronics, low and high power converters (inverters, converters, controlled and uncontrolled rectifiers), Control algorithms and techniques applied to power electronics, electromagnetic and thermal performance of electronic power converters and inverters, power quality and utility applications, renewable energy, electric machines, modelling, simulation, analysis, design and implementations of the application of power circuit components (power semiconductors, inductors, high frequency transformers, capacitors), EMI/EMC considerations, power devices and components, sensors, integration and packaging, applications in motor drives, wind energy systems, solar, battery chargers, UPS and hybrid systems and other applications.