论文标题
基于通用生成功能和贝叶斯网络的复杂多国家系统的可靠性分析
Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network
论文作者
论文摘要
在复杂的多国家系统(MSS)中,可靠性分析是一个重要的研究内容,无论是用于设备设计,制造,使用和维护。通用生成函数(UGF)是可靠性分析中的重要方法,该方法通过快速代数程序有效地获得了系统的可靠性。但是,当子系统或组件之间的结构关系不清楚或没有明确表达式时,UGF方法很难使用或根本不适用。贝叶斯网络(BN)在没有明确表达的关系的不确定性推断方面具有自然优势。但是,对于组件的数量非常大,它具有低效率的缺陷。为了克服UGF和BN的各个缺陷,为复杂的MSS提出了一种称为UGF-BN的新型可靠性分析方法。在UGF-BN框架中,UGF方法首先用于分析大量数量的底部组件。然后,获得的概率分布作为BN的输入。最后,复杂MSS的可靠性是通过BN方法建模的。该提出的方法提高了计算效率,尤其是对于具有大量底部组件的MSS。此外,基于UGF-BN方法的基于飞机可靠性的设计优化,并在质量,功率和成本上的预算限制进一步研究。最后,使用两种情况来证明和验证所提出的方法。
In the complex multi-state system (MSS), reliability analysis is a significant research content, both for equipment design, manufacturing, usage and maintenance. Universal Generating Function (UGF) is an important method in the reliability analysis, which efficiently obtains the system reliability by a fast algebraic procedure. However, when structural relationships between subsystems or components are not clear or without explicit expressions, the UGF method is difficult to use or not applicable at all. Bayesian Network (BN) has a natural advantage in terms of uncertainty inference for the relationship without explicit expressions. For the number of components is extremely large, though, it has the defects of low efficiency. To overcome the respective defects of UGF and BN, a novel reliability analysis method called UGF-BN is proposed for the complex MSS. In the UGF-BN framework, the UGF method is firstly used to analyze the bottom components with a large number. Then probability distributions obtained are taken as the input of BN. Finally, the reliability of the complex MSS is modeled by the BN method. This proposed method improves the computational efficiency, especially for the MSS with the large number of bottom components. Besides, the aircraft reliability-based design optimization based on the UGF-BN method is further studied with budget constraints on mass, power, and cost. Finally, two cases are used to demonstrate and verify the proposed method.