@Article{cmes.2021.016870,
AUTHOR = {Fangjun Zuo, Meiwei Jia, Guang Wen, Huijie Zhang, Pingping Liu},
TITLE = {Reliability Modeling and Evaluation of Complex Multi-State System Based on Bayesian Networks Considering Fuzzy Dynamic of Faults},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {129},
YEAR = {2021},
NUMBER = {2},
PAGES = {993--1012},
URL = {http://www.techscience.com/CMES/v129n2/44805},
ISSN = {1526-1506},
ABSTRACT = {In the traditional reliability evaluation based on the Bayesian method, the failure probability of nodes is usually expressed by the average failure rate within a period of time. Aiming at the shortcomings of traditional Bayesian network reliability evaluation methods, this paper proposes a Bayesian network reliability evaluation method considering dynamics and fuzziness. The fuzzy theory and the dynamic of component failure probability are introduced to construct the dynamic fuzzy set function. Based on the solving characteristics of the dynamic fuzzy set and Bayesian network, the fuzzy dynamic probability and fuzzy dynamic importance degree of the fault state of leaf nodes are solved. Finally, through the dynamic fuzzy reliability analysis of CNC machine tool hydraulic system balance circuit, the application of this method in system reliability evaluation is verified, which provides support for fault diagnosis of CNC machine tools.},
DOI = {10.32604/cmes.2021.016870}
}