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A Complex Multi-level System Reliability Distribution Estimation Method Based on Bayesian Melding Method

机译:基于贝叶斯融合方法的复杂多级系统可靠性分布估计方法

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As the complexity of system structure increases, system reliability estimation is challenging for lack of time and cost. How to enhance the system reliability distribution for complex multi-level structures is of great value. Besides, when there exists reliability distribution information of subsystems or components, how to fully use the limited information of different system levels for the system reliability distribution estimation has great significance. Therefore, considering that Bayesian Networks can construct complex system structures intuitively as well as evaluate the system reliability effectively, and the Bayesian Melding Method can integrate the multi-level information adequately, a complex multi-level system reliability distribution estimation method is proposed. The complex system structure is first decomposed to many blocks by BN. The single block system reliability distribution is obtained based on the Bayesian Melding Method with information integrated and Bayesian Networks with reliability estimated. The final system reliability distribution is estimated by merging the distributions obtained in different blocks so as to enhance the system reliability distribution with more information from different levels. To demonstrate and verify the effectiveness of the proposed method, one numerical example is employed.
机译:随着系统结构的复杂性增加,由于缺乏时间和成本,系统可靠性估计具有挑战性。如何增强复杂多层结构的系统可靠性分布具有重要的价值。此外,当存在子系统或组件的可靠性分布信息时,如何充分利用不同系统级别的有限信息进行系统可靠性分布估计具有重要意义。因此,考虑到贝叶斯网络可以直观地构造复杂的系统结构并有效地评估系统可靠性,并且贝叶斯融合方法可以充分集成多级信息,提出了一种复杂的多级系统可靠性分布估计方法。 BN首先将复杂的系统结构分解为许多块。基于集成信息的贝叶斯融合方法和估计可靠性的贝叶斯网络,获得了单块系统的可靠性分布。通过合并在不同块中获得的分布来估计最终的系统可靠性分布,以便利用来自不同级别的更多信息来增强系统可靠性分布。为了证明和验证所提方法的有效性,采用了一个数值示例。

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