Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance
Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance
复制标题
使用具有不完善修复和预防性维护的动态贝叶斯网络进行海底防喷器控制系统的性能评估
DOI:
10.1016/j.engappai.2013.08.011
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发表时间:
2013-11
影响因子:
8
通讯作者:
Xin Dong
中科院分区:
文献类型:
--
作者:
Yunwei Zhang;Shilin Yu;Zengkai Liu;Xin Dong
The work presents a dynamic Bayesian networks (DBN) modeling of series, parallel and 2-out-of-3 (2oo3) voting systems, taking account of common-cause failure, imperfect coverage, imperfect repair and preventive maintenance. Seven basic events of one, two or three component failure are proposed to model the common-cause failure of the three-components-systems. The imperfect coverage is modeled in the conditional probability table by defining a coverage factor. A multi-state degraded component is used to model the imperfect repair and preventive maintenance. Using the proposed method, a DBN modeling of a subsea blowout preventer (BOP) control system is built, and the reliability and availability are evaluated. The mutual information is researched in order to assess the important degree of basic events. The effects of degradation probability, failure rate and mean time to repair (MTTR) on the performances are studied. The results show that the repairs and maintenance can improve the system performance significantly, whereas the imperfect repair cannot degrade the system performance significantly in comparison with the perfect repair, and the preventive maintenance can improve the system performance slightly in comparison with the imperfect repair. In order to improve the performance of subsea BOP control system, the single surface components and the components with all-common-cause failure should given more attention. The influence of degradation probability on the performance is in the order of PLC, PC and ES. The influence of failure rate and MTTR on the performance is in the order of PLC, ES, PC, DO, DI and AI.
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DOI:
10.1016/j.engappai.2010.06.003
发表时间:
2012-06
期刊:
Eng. Appl. Artif. Intell.
影响因子:
--
作者:
M. Neil;D. Marquez
通讯作者:
M. Neil;D. Marquez
影响因子:
7.3
作者:
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通讯作者:
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影响因子:
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影响因子:
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通讯作者:
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影响因子:
0.9
作者:
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通讯作者:
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