Review of Health Prognostics and Condition Monitoring of Electronic Components

IEEE Access

Sanjeevikumar Padmanaban¹  Zbigniew Leonowicz²  Vigna K. Ramachandaramurthy³  Cherry Bhargava⁴  Mohan Senthilkumar⁵  Pardeep Kumar Sharma⁶  Frede Blaabjerg⁷  Massimo Mitolo⁸ 

[1] Department of Energy Technology, Aalborg University, Aalborg, Denmark;Faculty of Electrical Engineering, Wroc&x0142;Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan Ikram-Uniten, Kajang, Malaysia;School of Electrical and Electronics Engineering, Lovely Professional University, Phagwara, India;School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India;School of PS, Lovely Professional University, Phagwara, India;aw University of Science and Technology, Wroc&x0142;aw, Poland;

关键词: Reliability methods;    condition monitoring;    faults and failures;    prognostics;    diagnostics;   

DOI  :  10.1109/ACCESS.2020.2989410

来源: DOAJ

【 摘 要 】

To meet the specifications of low cost, highly reliable electronic devices, fault diagnosis techniques play an essential role. It is vital to find flaws at an early stage in design, components, material, or manufacturing during the initial phase. This review paper attempts to summarize past development and recent advances in the areas about green manufacturing, maintenance, remaining useful life (RUL) prediction, and like. The current state of the art in reliability research for electronic components, mainly includes failure mechanisms, condition monitoring, and residual lifetime evaluation is explored. A critical analysis of reliability studies to identify their relative merits and usefulness of the outcome of these studies' vis-a-vis green manufacturing is presented. The wide array of statistical, empirical, and intelligent tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarized, and the central research gap is highlighted.

【 授权许可】

Unknown