基于模糊综合评判的装备软件可靠性分析

可靠性是衡量装备软件质量的重要参数,但由于软件可靠性的特点,在实际对装备软件可靠性定量分析往往很难,甚至不可能。从软件质量框架模型出发,结合装备软件的特点,分析了影响装备软件可靠性的几个参数,提出了一种运用模糊综合评判方法对装备软件可靠性进行定性分析的方法。该方法简单,可行性强。最后,给出了一个实例。     

军用软件的测试与实践方法

首先分析了民用软件存在的问题,然后结合军用软件的特点,对影响军用软件可靠性的因素进行分析,最后提出提高军用软件质量的几种测试与实践方法.     

舰空导弹武器系统软件靶场综合测试分析

针对舰空导弹武器系统的特点以及舰空导弹武器系统软件定型试验的现状,指出了舰空导弹武器系统软件靶场测试的必要性、特殊性。通过靶场软件测试综合试验,总结了舰空导弹武器系统软件靶场定型的试验方法。并指出了靶场软件测试的发展方向。     

Transient analysis of Markov models of fault‐tolerant systems with deferred repair using split regenerative randomization

The (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well‐controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability‐like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C₂, including typical failure/repair reliability‐like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and, for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C₂ model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization‐based methods. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Component importance for linear consecutive‐ k ‐Out‐of‐ n and m ‐Consecutive‐ k ‐Out‐of‐ n systems with exchangeable components

Measuring the relative importance of components in a mechanical system is useful for various purposes. In this article, we study Birnbaum and Barlow‐Proschan importance measures for two frequently studied system designs: linear consecutive k ‐out‐of‐ n and m ‐consecutive‐ k ‐out‐of‐ n systems. We obtain explicit expressions for the component importance measures for systems consisting of exchangeable components. We illustrate the results for a system whose components have a Lomax type lifetime distribution. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Nonparametric bayesian lifetime data analysis using dirichlet process lognormal mixture model

We propose a nonparametric Bayesian lifetime data analysis method using the Dirichlet process mixture model with a lognormal kernel. A simulation‐based algorithm that implements the Gibbs sampling is developed to fit the Dirichlet process lognormal mixture (DPLNM) model using rightly censored failure time data. Five examples are used to illustrate the proposed method, and the DPLNM model is compared to the Dirichlet process Weibull mixture (DPWM) model. Results indicate that the DPLNM model is capable of estimating different lifetime distributions. The DPLNM model outperforms the DPWM model in all the examples, and the DPLNM model shows promising potential to be applied to analyze failure time data when an appropriate parametric model for the data cannot be specified. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

混合不确定条件下的飞行器级间分离可靠性分析

为量化飞行器级间分离过程随机不确定性和认知不确定性的综合影响,结合概率和区间理论混合模型特点,提出了一种基于随机和区间理论混合模型的飞行器级间分离可靠性分析方法。面向高超声速飞行器分离任务需求,建立分离动力学仿真模型,针对级间分离结构的几何特点,设计了一种快速碰撞检测方法,进而构建了分离任务的可靠性分析混合模型。通 过将该模型转化为随机可靠性分析的无约束优化问题,考虑分离过程中复杂外力及力矩导致功能函数高度非线性的特点,利用高效全局优化和主动学习Kriging方法实现无约束优化问题高效求解。结合实例表明,该方法能够准确描述混合不确定性因素对飞行器分离过程的影响,给出了飞行器分离任务可靠性区间,可为飞行器分离方案的精细化设计提供决策支持。     

节点非独立失效下的局域网可靠性建模与分析

以具有层次结构的局域网作为拓扑模型,考虑共因失效和关联失效这2类节点非独立失效事件发生的情况,建立了交换机节点失效模型来模拟交换机失效,利用Monte-Carlo仿真算法近似计算出网络的两端可靠性,研究2种共因失效事件和3种关联失效事件对网络端端可靠性的影响。结果表明:因资源节点出现故障和协议层出现错误而导致交换机失效的共因失效事件均会降低网络可靠性,且资源节点失效概率或协议层失效概率越大,网络可靠性越低;而由于使用了热备份技术、堆叠技术以及发生广播风暴导致的关联失效事件,即使节点独立失效概率很小,只要相关因数足够大,故障都会快速传播,导致网络可靠性迅速下降。     

基于Monte Carlo的军事物流结点可靠性评估方法

军事物流网络结点是构成军事物流网络的基本要素。战场环境瞬息万变,结点的可靠性往往受许多不确定因素的影响,计及不确定因素的评估方法可以更客观、真实地评估结点的可靠性。基于此,提出了刻画物流结点可靠性的评估指标体系,建立了计及不确定因素的军事物流结点可靠性评估模型,给出了Monte Carlo求解算法。对影响结点可靠性的因素进行了分析,在此基础上提出了改善军事物流结点可靠性的措施。以某战役级军事物流网络为例进行算例分析,验证了该方法的可行性和正确性。     

VLMC控制流软件可靠性度量方法

针对现有软件可靠性模型普遍不适用于实际软件的问题,分析了软件内部模块间控制转移机理,通过分离入口模块,提取一阶控制转移概率矩阵;弱化内部模块与出口模块间差异,重构二阶以上转移概率矩阵,在改进Cheung模型的基础上建立一个更符合软件实际的可靠性度量模型。针对变阶依赖（ VLMC）控制转移导致的可靠性度量难问题,通过对导致复杂依赖的多入多出模块进行节点扩展,将VLMC控制流转化为Markov链,利用所建立的软件可靠性模型对VLMC控制流软件进行可靠性度量。研究利用演绎推理对所建立模型进行了正确性形式化证明。最后给出了方法的实例验证。