@inproceedings{79712ba1426943e39a7d67e35b3a3056,
title = "Reliability Analysis of Power Electronic Topology Based on Bayesian Network",
abstract = "A lot of evidence shows that power electronic is one of the most important and weakest parts of a complex system. Therefore, credible reliability analysis at the system level is necessary for the power electronic part of the equipment. The advantages of Bayesian Network in probability computing, bidirectional reasoning, and the processing of independent relationships of elements and the strong credibility of this method make it ideal for analyzing electronic systems. This paper introduces how to use Bayesian Networks to model power electronics topology, Bayesian inference, and complete the calculation of power electronics mean time to failure (MTTF) and the determination of weak links. Finally, a case study of interleaved DC-DC boost converter will describe in detail how to use Bayesian Network to calculate the reliability and mean time to failure of electronic circuits.",
keywords = "Bayesian Network, Component, Fault Diagnosis, Power Electronic, Reliability",
author = "Weiwei Hu and Ming Li and Tianyu Si and Xulan Zhu and Li Zhao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 12th IEEE Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021 ; Conference date: 15-10-2021 Through 17-10-2021",
year = "2021",
doi = "10.1109/PHM-Nanjing52125.2021.9612940",
language = "英语",
series = "2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Wei Guo and Steven Li",
booktitle = "2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021",
address = "美国",
}