@inproceedings{33ad74c223124108a753d6530fa77776,
title = "Study about health assessment of circuit based on three-state health DBN algorithm",
abstract = "Health grading evaluation is an important technology in health management. Taking the advantage of Bayesian networks in dealing with the issue of uncertainty, this paper puts forward the dynamic Bayesian network model based on the three-state dividing of system which is according to circuits' fault characteristics of hierarchy, correlation and uncertainty. Component-level health quantitative assessment method based on three-level health status is proposed by studying the meanings and basic assumptions of three-level health status division of system. Then, the health status of circuit is divided into health, sub-health and failure state at three levels. Through the analysis of different models and study methods of Bayesian theory, the principle of fault prediction and inference of Bayesian networks are interpreted. At the last, the three states of dynamic Bayesian network health evaluation reasonable method is put forward.",
keywords = "Bayesian model, Dynamic Bayesian networks, Health assessment, Three-state health",
author = "Junyou Shi and Yawei Zhao and Xiaowei Duan",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016 ; Conference date: 19-10-2016 Through 21-10-2016",
year = "2017",
month = jan,
day = "16",
doi = "10.1109/PHM.2016.7819781",
language = "英语",
series = "Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Qiang Miao and Zhaojun Li and Zuo, \{Ming J.\} and Liudong Xing and Zhigang Tian",
booktitle = "Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016",
address = "美国",
}