武器装备软件的可靠性分析综述

首先论述了武器装备软件可靠性的重要性,指出了软件可靠性与硬件可靠性的主要区别,并依据装备软件研制总要求及武器装备软件的特点分析了装备软件可靠性的内涵、特点,介绍了装备软件可靠性指标的确定、软件可靠性模型以及装备软件可靠性的评估,最后分析讨论了几种提高武器装备软件可靠性的方法与途径。     

一种基于新技术复杂装备的可靠性增长方法

针对新技术复杂装备可靠性增长难的问题,利用可靠性增长理论,结合新技术复杂装备的特点,提出了一种适应于新技术复杂装备可靠性增长的方法。并将其应用于某型无人机系统的可靠性增长,通过2个生产周期达到了预期的可靠性增长目标值。这种方法具有良好的可操作性和经济性,可广泛应用于其他新技术复杂装备的可靠性增长中。     

变异系数在可靠性中的应用

对使用变异系数描述随机变量的离散程度进行分析,推导了可靠性工程中常用的4种概率分布的变异系数与分布参数之间的关系.以机械产品整机及其零部件不同失效模式的寿命变异系数的取值范围为实例,说明了变异系数在可靠性工程中的应用.     

武器雷达装备RCM分析决策系统

详细介绍了武器雷达装备RCM分析决策系统的体系结构、功能模块划分和数据库设计方法,并给出了系统的实现方案以及后续开发的设想。     

Development programs for one‐shot systems using multiple‐state design reliability models

Design reliability at the beginning of a product development program is typically low, and development costs can account for a large proportion of total product cost. We consider how to conduct development programs (series of tests and redesigns) for one‐shot systems (which are destroyed at first use or during testing). In rough terms, our aim is to both achieve high final design reliability and spend as little of a fixed budget as possible on development. We employ multiple‐state reliability models. Dynamic programming is used to identify a best test‐and‐redesign strategy and is shown to be presently computationally feasible for at least 5‐state models. Our analysis is flexible enough to allow for the accelerated stress testing needed in the case of ultra‐high reliability requirements, where testing otherwise provides little information on design reliability change. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

小子样条件下可靠性试验信息的融合方法

小子样条件下,不同状态的多源信息融合是可靠性工程领域的一个热门问题。综述了小子样条件下可靠性试验信息的融合方法。在一定的假设条件之下,利用分离可交换量模型对不同环境下的可靠性信息融合方法进行了研究,仿真算例说明这种融合方法充分利用了信息,评估结论更为合理。     

基于GO法的多阶段共因失效任务系统可靠性评估

为了解决部件阶段依赖性与共因失效给系统可靠性分析带来的复杂性,针对多阶段共因失效任务系统,结合GO法易于处理有时序、含共因失效系统可靠性分析的特点,首先,将前一阶段的输出信号作为后一阶段的输入信号,建模时首尾连接各阶段模型,建立整个任务系统的隐性GO模型;其次,在进行各信号流状态组合运算时,融入阶段代数处理部件的阶段依赖性;再次,用隐性共因失效分析,将共因失效对系统的影响在状态组合的定量分析中表达出来,得到所需系统可靠性指标;最后,与基于二元决策图的算法进行对比验证。结果表明:GO法可以简捷、准确地处理多阶段共因失效任务系统可靠性评估问题。     

基于RBF网络加速模型的可靠性评估

在可靠性加速试验中,由于各种不同的应力引起的失效机理不一样,不同应力之间可能还存在着相互耦合作用,要将它们和寿命结合,找出一个能真实描述客观情况的加速模型是相当困难的,仅仅依据有限的试验数据建立产品的加速模型存在很大难度和风险,为此提出了一种基于RBF网络加速模型的可靠性评估方法．该方法将加速寿命试验中的加速应力和可靠度作为训练网络的输入向量,相应的时间作为目标向量对网络进行训练,根据网络收敛速和误差精度等情况调整隐含层单元个数,直至得到最优的网络．最后,以实例说明了该方法的有效性和实用性．     

基于灰色Verhulst优化模型的电子装备故障预测方法

针对平均故障工作时间数据样本量少的特点,提出利用灰色Verhulst模型预测电子装备故障;又针对灰色Verhulst模型存在预测精度不高的问题,研究了灰色Verhulst模型参数的优化方法。通过实际试验数据对2个模型进行了仿真验证,并基于灰色关联度对2个模型的模拟预测精度进行了比较分析,结果表明：基于灰色Verhulst优化模型适合于电子装备故障预测,并具有较高的拟合预测精度。     

Evaluating cost and reliability integrated performance of stochastic logistics systems

The significance of integrating reliability into logistics performance has been established [The Logistics Performance Index and Its Indicators, World Bank International Trade and Transport Departments, (2010)]. Hence, as a response to the work by the World Bank, the present article aims to evaluate the performance index R_b,d of logistics systems as the probability that a specified demand d can be distributed successfully through multistate arc capacities from the source to the destination under the constraint that the total distribution cost should not exceed the cost limitation b. This article provides a pioneering approach for a straightforward computation of the performance index R_b,d. The proposed algorithm is a hybrid between the polynomial time capacity‐scaling algorithm, which was presented by Edmonds and Karp [JACM 19 (1972)], and the decomposition algorithm, which was presented by Jane and Laih [IEEE (2008)]. Currently, the proposed approach is the only algorithm that can directly compute R_b,d. An illustration of the proposed algorithm is presented. The results of the computational experiments indicate that the presented algorithm outperforms existing algorithms. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012