Failure risk assessment by multi-state dynamic Bayesian network based on interval type-2 fuzzy sets and leaky-weighted sum algorithm: A case study of crude oil pipelines
Failures of the pipelines can not only result in economic losses, but also potentially lead to serious safety accidents. Therefore, it is important to assess the failure risk of pipelines in order to prevent and mitigate pipeline failure accidents. This study proposed a method for failure risk asses...
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| Published in | Expert systems with applications Vol. 250; p. 123942 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
15.09.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4174 |
| DOI | 10.1016/j.eswa.2024.123942 |
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| Abstract | Failures of the pipelines can not only result in economic losses, but also potentially lead to serious safety accidents. Therefore, it is important to assess the failure risk of pipelines in order to prevent and mitigate pipeline failure accidents. This study proposed a method for failure risk assessment in process systems that combines the dynamic Bayesian network (DBN) with interval type-2 fuzzy sets (IT2FS). In this method, the IT2FS were applied to reduce the subjectivity and uncertainty of expert opinions and the bias between individual opinions. Specifically, an IT2FS-based similarity aggregation method (IT2FS-SAM) was introduced to collect and aggregate the prior probabilities of the parent nodes in the DBN, and an improved weighted sum algorithm (namely leaky-weighted sum algorithm, Leaky-WSA) was developed to obtain the conditional probability tables (CPTs) of the DBN, effectively reducing the number of expert opinions required. Finally, the feasibility of the method was demonstrated through the failure risk assessment of a crude oil gathering pipeline. Using prediction and backward inference with the DBN, the failure probability and main failure causes of the pipeline were determined, allowing pipeline managers to take appropriate preventive and maintenance measures. |
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| AbstractList | Failures of the pipelines can not only result in economic losses, but also potentially lead to serious safety accidents. Therefore, it is important to assess the failure risk of pipelines in order to prevent and mitigate pipeline failure accidents. This study proposed a method for failure risk assessment in process systems that combines the dynamic Bayesian network (DBN) with interval type-2 fuzzy sets (IT2FS). In this method, the IT2FS were applied to reduce the subjectivity and uncertainty of expert opinions and the bias between individual opinions. Specifically, an IT2FS-based similarity aggregation method (IT2FS-SAM) was introduced to collect and aggregate the prior probabilities of the parent nodes in the DBN, and an improved weighted sum algorithm (namely leaky-weighted sum algorithm, Leaky-WSA) was developed to obtain the conditional probability tables (CPTs) of the DBN, effectively reducing the number of expert opinions required. Finally, the feasibility of the method was demonstrated through the failure risk assessment of a crude oil gathering pipeline. Using prediction and backward inference with the DBN, the failure probability and main failure causes of the pipeline were determined, allowing pipeline managers to take appropriate preventive and maintenance measures. |
| ArticleNumber | 123942 |
| Author | Wu, Wei Li, Tao Zhang, Yixin Li, Xiufeng Wei, Liping Liu, Jiawei |
| Author_xml | – sequence: 1 givenname: Jiawei surname: Liu fullname: Liu, Jiawei email: 202121395@stumail.nwu.edu.cn organization: School of Chemical Engineering, Northwest University, Xi'an 710069, China – sequence: 2 givenname: Xiufeng surname: Li fullname: Li, Xiufeng email: lixiufeng@csei.org.cn organization: China Special Equipment Inspection and Research Institute, Beijing 100029, China – sequence: 3 givenname: Yixin surname: Zhang fullname: Zhang, Yixin email: zh_angyixin@163.com organization: School of Chemical Engineering, Northwest University, Xi'an 710069, China – sequence: 4 givenname: Tao surname: Li fullname: Li, Tao email: litao5274@163.com organization: School of Chemical Engineering, Northwest University, Xi'an 710069, China – sequence: 5 givenname: Liping surname: Wei fullname: Wei, Liping email: weiliping@nwu.edu.cn organization: School of Chemical Engineering, Northwest University, Xi'an 710069, China – sequence: 6 givenname: Wei orcidid: 0000-0002-4476-7639 surname: Wu fullname: Wu, Wei email: wuwei@nwu.edu.cn organization: School of Chemical Engineering, Northwest University, Xi'an 710069, China |
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| SubjectTerms | Dynamic Bayesian network Interval type-2 fuzzy numbers Interval type-2 fuzzy sets-based similarity aggregation method Leaky-weighted sum algorithm Risk assessment |
| Title | Failure risk assessment by multi-state dynamic Bayesian network based on interval type-2 fuzzy sets and leaky-weighted sum algorithm: A case study of crude oil pipelines |
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