A novel approach based on fault tree analysis and Bayesian network for multi-state reliability analysis of complex equipment systems

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Xiaofang Luo, Yushan Li, Xutao Bai, Rongkeng Tang, Hui Jin
{"title":"A novel approach based on fault tree analysis and Bayesian network for multi-state reliability analysis of complex equipment systems","authors":"Xiaofang Luo, Yushan Li, Xutao Bai, Rongkeng Tang, Hui Jin","doi":"10.1177/1748006x231171449","DOIUrl":null,"url":null,"abstract":"Due to the complex structure of multi-state complex systems and the lack of data, information, and knowledge, the uncertainty of the logical relationship between the failure states of systems and components and the uncertainty of related failure data become the key issues in the reliability analysis of multi-state complex systems. In this paper, combined with multi-state fault tree (MSFT), a multi-state reliability assessment framework for complex systems considering uncertainty based on multi-source information fusion and multi-state Bayesian network (MSBN) is proposed. The multi-source information fusion method combines historical data and experts’ opinions to solve the uncertainty problem of multi-state failure data in complex equipment systems effectively. Based on the multi-source information fusion method, the calculation method of multi-state prior probability and the construction method of conditional probability are given. By constructing the conditional probability table (CPT), the uncertain logic relationship between the multi-state nodes is effectively expressed, which effectively improves the efficiency of CPT acquisition for MSBN and reduces the workload of experts scoring. Finally, a mud circulating system is taken as an example to prove the proposed method, and the specific calculation process, evaluation results, and some discussions are given. The results show that the proposed method is an effective multi-state reliability analysis method for complex uncertain multi-state systems.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/1748006x231171449","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the complex structure of multi-state complex systems and the lack of data, information, and knowledge, the uncertainty of the logical relationship between the failure states of systems and components and the uncertainty of related failure data become the key issues in the reliability analysis of multi-state complex systems. In this paper, combined with multi-state fault tree (MSFT), a multi-state reliability assessment framework for complex systems considering uncertainty based on multi-source information fusion and multi-state Bayesian network (MSBN) is proposed. The multi-source information fusion method combines historical data and experts’ opinions to solve the uncertainty problem of multi-state failure data in complex equipment systems effectively. Based on the multi-source information fusion method, the calculation method of multi-state prior probability and the construction method of conditional probability are given. By constructing the conditional probability table (CPT), the uncertain logic relationship between the multi-state nodes is effectively expressed, which effectively improves the efficiency of CPT acquisition for MSBN and reduces the workload of experts scoring. Finally, a mud circulating system is taken as an example to prove the proposed method, and the specific calculation process, evaluation results, and some discussions are given. The results show that the proposed method is an effective multi-state reliability analysis method for complex uncertain multi-state systems.
基于故障树分析和贝叶斯网络的复杂设备系统多状态可靠性分析新方法
由于多状态复杂系统结构复杂,缺乏数据、信息和知识,系统和部件失效状态之间逻辑关系的不确定性以及相关失效数据的不确定性成为多状态复杂系统可靠性分析中的关键问题。结合多状态故障树(MSFT),提出了一种基于多源信息融合和多状态贝叶斯网络(MSBN)的考虑不确定性的复杂系统多状态可靠性评估框架。多源信息融合方法结合历史数据和专家意见,有效解决了复杂装备系统中多状态故障数据的不确定性问题。基于多源信息融合方法,给出了多状态先验概率的计算方法和条件概率的构造方法。通过构造条件概率表(CPT),有效地表达了多状态节点之间的不确定逻辑关系,有效地提高了MSBN获取CPT的效率,减少了专家打分的工作量。最后,以一个泥浆循环系统为例,对所提出的方法进行了验证,并给出了具体的计算过程、评价结果和一些讨论。结果表明,该方法是复杂不确定多状态系统的一种有效的多状态可靠性分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信