Open AccessInvestigation of reliability assessement in power electronics circuits using machine learning
Author(s) -
Soumya Rani Mestha,
Pinto Pius A.J
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijpeds.v12.i1.pp558-566
Subject(s) - reliability (semiconductor) , reliability engineering , electronics , computer science , field (mathematics) , power electronics , electronic systems , process (computing) , power (physics) , electronic circuit , emphasis (telecommunications) , artificial intelligence , electrical engineering , engineering , telecommunications , electronic engineering , mathematics , physics , pure mathematics , quantum mechanics , operating system
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.