基于贝叶斯网络和贝叶斯融合的系统可靠性分析多先验集成方法

Yingchun Xu, Wen Yao, Xiaohu Zheng, Xiaoqian Chen
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引用次数: 1

摘要

近年来,随着系统结构在工程领域的迅速发展,往往存在着经验丰富的专家或历史实验的多重先验。贝叶斯融合法是一种基于确定性系统结构的多先验融合方法。然而,当系统模型不能用显式表达式描述时,传统的贝叶斯融合法就不再适用于系统可靠性分析。为了清晰地描述结构关系,本文采用贝叶斯网络构建复杂的系统结构模型,采用节点概率表而不是显式表达式来计算系统的可靠度。结合贝叶斯融合法和贝叶斯网络的优点,提出了一种用于复杂系统结构可靠性分析的多先验集成与更新算法。最后,以卫星姿态控制系统为例进行了验证。采用贝叶斯网络建立了该系统,并详细讨论了自然先验和更新先验的比较。
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Multi-Prior Integration Method for System Reliability Analysis Based on Bayesian Network and Bayesian Melding Method
In recent years, there often exist multiple priors from experienced experts or historical experiments with the rapid development of system structure in engineering fields. Bayesian Melding Method is commonly used for integrating multiple priors, which is based on the deterministic system structure. However, if the system model cannot be described by an explicit expression, the traditional Bayesian Melding Method is not feasible for system reliability analysis anymore. In order to describe the structure relationship clearly, Bayesian Network is applied in this paper to construct the complex system structure model and the system reliability is calculated by node probability tables rather than explicit expressions. Combining the advantages of the Bayesian Melding Method and Bayesian Network, a multi-prior integration and updating algorithm is developed for the system reliability analysis of complex system structures. Finally, a satellite attitude control system is used to demonstrate the proposed method. The system is established by the Bayesian Network and the comparison between natural prior and updated prior is discussed at length.
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