Real-time reliability evaluation methodology based on dynamic Bayesian networks: A case study of a subsea pipe ram BOP system.
Real-time reliability evaluation methodology based on dynamic Bayesian networks: A case study of a subsea pipe ram BOP system.
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DOI：
10.1016/j.isatra.2015.06.011
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发表时间：
2015-09
期刊：
影响因子：
7.3
通讯作者：
Bao-ping Cai;Yonghong Liu;Yunpeng Ma;Zengkai Liu;Yuming Zhou;Junhe Sun
中科院分区：
文献类型：
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作者：
Bao-ping Cai;Yonghong Liu;Yunpeng Ma;Zengkai Liu;Yuming Zhou;Junhe Sun
提出了一种新的实时可靠性评估方法，该方法将基于贝叶斯网络的根本原因诊断阶段和基于动态贝叶斯网络的可靠性评估阶段相结合。根本原因诊断阶段可以真实的实时准确定位复杂机电系统故障的根本原因，以提高诊断覆盖率，并通过BN的向后分析来执行。可靠性评估阶段通过DBN的前向推理计算整个系统的实时可靠性。所提出的方法的应用演示使用的情况下，海底管道闸板防喷器系统。研究了实时系统可靠性在元件故障时的大小和变化趋势，并利用互信息和置信方差确定了元件在不同时刻的重要度序列。
A novel real-time reliability evaluation methodology is proposed by combining root cause diagnosis phase based on Bayesian networks (BNs) and reliability evaluation phase based on dynamic BNs (DBNs). The root cause diagnosis phase exactly locates the root cause of a complex mechatronic system failure in real time to increase diagnostic coverage and is performed through backward analysis of BNs. The reliability evaluation phase calculates the real-time reliability of the entire system by forward inference of DBNs. The application of the proposed methodology is demonstrated using a case of a subsea pipe ram blowout preventer system. The value and the variation trend of real-time system reliability when the faults of components occur are studied; the importance degree sequence of components at different times is also determined using mutual information and belief variance.