复杂多态系统的区间值模糊贝叶斯网络建模与分析

随着现代工程系统结构复杂度的增加以及运行环境的复杂化,传统的可靠性分析与评估技术已不能满足现代工程系统需求.针对复杂多态系统可靠性分析与评估的需求,本文从部件状态分析、系统结构分析入手,对存在认知不确定性同时考虑失效相关性的复杂多态系统进行可靠性建模与分析.由于现代复杂多态系统信息输入及系统故障影响因素的多样性,以及系统冗余,使得不确定性和共因失效对复杂多态系统可靠性分析和评估至关重要.本文借助贝叶斯网络对多态系统的图形表达和推理优势,采用模糊理论中区间值三角模糊数对部件概率进行描述;同时利用β因子模型对共因失效进行量化,再将其以新增共因节点的方式实现共因失效的贝叶斯网络建模,从而提出基于区间值模糊贝叶斯网络的复杂多态系统可靠性分析方法.最后,将基于区间值模糊多态贝叶斯网络对具有共因失效的多态卫星天线双轴定位机构传动系统进行可靠性分析.通过对实际工程系统的分析,表明本文建立的多种因素影响下复杂多态系统的可靠性建模和分析方法,进一步完善了复杂系统可靠性分析理论与方法.     

Recursive Algorithm Based Reliability Analysis of Multiphase Satellite Systems with Propagated Failures

Modern satellite systems are generally designed to fulfill multiphase-missions. Component /subsystem redundancies are commonly used to achieve high reliability and long life of modern satellite systems. These characteristics have leaded to a critical issue of reliability analysis of satellites that is how to deal with the reliability analysis with multiphase-missions and propagated failures of redundant components. Traditional methods based on the binary decision diagram( BDD) can hardly cope with these issues efficiently. Accordingly, a recursive algorithm method was introduced to facilitate the reliability analysis of satellites. This method was specified for the analysis of static fault tree and it was implemented by generating combination of component failures and carrying out a backward recursive algorithm. The effectiveness of the proposed method was demonstrated through the reliability analysis of a multiphase satellite system with propagated failures.The major advantage of the proposed method is that it does not need composition of BDD and its computational process is automated.