多阶段任务系统可靠性分析的二元决策图模型

为了实现计算机自动生成多阶段任务系统的二元决策图可靠性模型,提出了二元决策图可靠性建模的通用方法。定义了嵌套的二元决策图数据结构BDD_Element,给出了二元决策图模型的描述和存储方法,提出了与门、或门和k/n表决门向二元决策图模型的自动转化算法。给出了建立多阶段任务系统二元决策图可靠性模型的2个步骤:基于逻辑门转化算法,将部件逻辑关系结构函数转化为阶段二元决策图模型;基于二元决策图布尔操作规则整合阶段二元决策图模型。卫星姿态调整任务的可靠性分析表明:该方法可以有效应用于多阶段任务系统的可靠性分析。     

The joint signature of coherent systems

We investigate the joint signature of $m$ coherent systems, under the assumption that the components have independent and identically distributed lifetimes. The joint signature, for a particular ordering of failure times, is an $m$‐dimensional matrix depending solely on the composition of the systems and independent of the underlying distribution function of the component lifetimes. The elements of the $m$‐dimensional matrix are formulated based on the joint signatures of numerous series of parallel systems. The number of the joint signatures involved is an exponential function of the number of the minimal cut sets of each original system and may, therefore, be significantly large. We prove that although this number is typically large, a great number of the joint signatures are repeated, or removed by negative signs. We determine the maximum number of different joint signatures based on the number of systems and components. It is independent of the number of the minimal cut sets of each system and is polynomial in the number of components. Moreover, we consider all permutations of failure times and demonstrate that the results for one permutation can be of use for the others. Our theorems are applied to various examples. The main conclusion is that the joint signature can be computed much faster than expected.     

多阶段任务系统可靠性分析的ROBDD算法

针对Markov方法分析多阶段任务系统(Phased-Mission System,PMS)可靠性时的状态空间爆炸问题,基于层次化建模思想,建立了PMS任务可靠性的顶层系统二维决策图(Binary Decision Diagram,BDD)模型和底层部件Markov模型。通过分析BDD中的同构节点和冗余节点,提出顶层模型构造过程中的同构节点合并策略和冗余节点删除策略。利用上述节点压缩策略生成简化模型,提高模型构造和存储效率。基于PMS部件排序规则,给出了层次化模型的递归求解方法,该方法的计算复杂度与顶层模型中的节点总数呈线性关系。通过算例分析,对比采用节点压缩策略前后的模型节点数,以及层次化方法与Markov方法的计算结果,验证了简化层次模型的正确性和有效性。     

概率化认知控制模式下人为差错概率的量化方法

在现有成果的基础上,对CREAM方法中的人为差错概率量化进行了改进.介绍了CREAM基本法量化人为差错概率的基本思想;讨论了两种概率化认知控制模式的确定方法:贝叶斯网络法和模糊逻辑法,强调了概率化认知控制模式下量化人为差错概率的必要性.通过理论推导,构建了概率化认知控制模式下人为差错概率的量化方法.另外,为了提高计算效...     

基于遗传算法的通信网络可靠性优化设计

在可靠性条件约束下 ,使网络成本最低是网络规划NP hard问题 .文章提出一种基于遗传算法的优化方法解决了这类问题 .仿真结果表明这种算法是有效的 .     

基于遗传算法的大系统可靠度优化分配

给出了大系统可靠度优化分配的数学模型 ,设计了大系统可靠度优化分配问题的遗传算法。数值例子表明该方法可以有效地解决大规模的、复杂的非线性规划问题。解决了传统算法的局限性     

一种基于模糊可靠度确定雷达故障检测间隔期的方法

将雷达装备参数漂移的动态范围模糊化 ,并基于数理统计中参数估计的理论 ,建立了雷达装备的参数模糊可靠度预计模型。把该模型应用于确定雷达电参数的故障检测周期 ,并通过实例论证此方法的优越性和实用性。     

证据推理法在C4ISR系统可靠性评价中的应用

首先参考外军NATO COBP阐述了不确定性处理在C4ISR系统评价中的重要性,鉴于ER方法的先进思想,介绍了ER(Evidential Reasoning)方法在不确定条件下的基本评价框架,并对ER方法和AHP方法,D-S证据理论以及模糊综合评价方法进行了比较综合,针对我军C4ISR系统可靠性评价中的数据不完备等实际问题,初步应用此方法进行评价,对决策人员有一定的参考意义.     

系统可靠性模糊分配的熵权方法

采用模糊数来表示不同模糊因素的相对强度,即通过指标得分的比较,用三角模糊数来表示m个模糊因素的权重系数,建立模糊判断矩阵,根据α截集和决策者对模糊判断矩阵的满意乐观程度指标λ进行模糊区间运算,得出各分系统可靠性指标所占的熵权,再根据熵权对系统可靠性指标进行分配。这种方法可以正确把握处理模糊问题的尺度,减少人为干扰。     

Log‐concave and concave distributions in reliability

Nonparametric classes of life distributions are usually based on the pattern of aging in some sense. The common parametric families of life distributions also feature monotone aging. In this paper we consider the class of log‐concave distributions and the subclass of concave distributions. The work is motivated by the fact that most of the common parametric models of life distributions (including Weibull, Gamma, log‐normal, Pareto, and Gompertz distributions) are log‐concave, while the remaining life of maintained and old units tend to have a concave distribution. The classes of concave and log‐concave distributions do not feature monotone aging. Nevertheless, these two classes are shown to have several interesting and useful properties. We examine the closure of these classes under a number of reliability operations, and provide sharp reliability bounds for nonmaintained and maintained units having life distribution belonging to these classes. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 419–433, 1999