相似产品信息在导弹可靠性试验评估中的应用

验前分布的确定是运用Bayes方法进行系统可靠性评估的重要前提.在对导弹系统进行可靠性评估时,大量的相似产品信息是不可忽视的重要验前信息.基于相似产品信息的存在性.研究了利用相似产品的信息采用加权融合确定可靠度验前分布的方法.并针对导弹寿命服从Weibull分布的可靠性试验结果,给出应用Bayes方法评估新导弹系统可靠性的计算公式.最后,通过一个实例证明了该方法的有效性.     

应力-强度模型的Bayes可靠性分析

当应力、强度分别服从于正态分布、指数分布和Weibull分布时 ,分析了应力 -强度模型的可靠性评估 ,着重讨论了无信息验前下的Bayes可靠性评估。仿真结果表明 ,无信息验前下的评估结论可以很好地用频率学派的观点来解释。     

贝叶斯方法在某型防空导弹武器系统可靠性评估中的应用

提出采用贝叶斯(Bayes)方法分析防空导弹武器系统的可靠性问题.首先对各种不同分布类型的单元进行Bayes可靠性分析,利用某型防空导弹武器系统的试验信息构造系统可靠性验前分布,再利用Bayes定理和系统试验信息更新系统可靠性的验前分布得到验后分布,最后对系统可靠性进行评估.仿真算例说明了评估方法的合理性.     

验前分布的稳健性

研究Bayes统计分析中运用验前信息的稳健性 ,给出了正态分布期望值验前分布和指数寿命型分布失效率验前分布的稳健性分析。所论方法对于飞行器系统试验的精度分析和可靠性评估 ,具有较普遍的意义     

基于Dirichlet先验分布的模糊可靠性增长模型研究

将模糊理论应用于基于Dirichlet先验分布的Bayes可靠性增长模型,提出了可靠性增长的模糊模型。在对Dirichlet先验分布函数研究的基础上,分析了先验参数的获取方法。针对某水冲压发动机可靠性增长试验使用Dirichlet先验分布模型进行了分析,给出了试验各阶段的先验分布和后验分布,并分析了与先验信息方差有关的参数对后验可靠度的影响。在此基础上,通过引入模糊变量,发展了模糊可靠性增长模型,得到了试验各阶段模糊可靠度。     

指数寿命产品可靠性增长试验的Bayes分析

针对指数寿命产品的定时、定数截尾试验方案,推广了Mazzuchi-Soyer模型的应用范围。首先引入模型假设,以狄氏分布作为先验分布,综合利用产品研制的历史信息和专家信息,结合产品研制各阶段试验数据,给出了各阶段可靠性的联合后验分布。然后利用Gibbs抽样算法解决后验推断计算问题,得到各阶段产品可靠性的Bayes点估计和区间估计。最后给出产品可靠性增长分析实例,表明了模型的优越性。     

基于Bayes理论的固有可用度定时截尾试验方案

为解决小子样条件下进行产品固有可用度试验验证的问题,基于Bayes理论,提出了一种固有可用度定时截尾试验方案．该试验方案在假设故障间隔时间和修复时间均服从指数分布的前提下,将现场试验分为同时进行的可靠性和维修性定时截尾试验2个部分,要求在利用验前试验信息的基础上,使本次试验获得的验后分布还可以作为下一次现场试验的验前分布,提高了试验数据的利用率,具有较好的经济效益．     

验前信息在武器装备试验中的应用研究

针对武器装备定型试验时如何把验前积累大量的先验信息科学合理利用,根据武器装备不同种类的验前信息,确定其分布类型并采用参数和非参数检验方法进行相容性检验,使经过预处理的验前信息能够为试验所用,并通过实例验证了该方法的科学可行性。该方法对验前信息在武器装备试验及结果评定中的应用具有一定意义。     

利用验前信息的一种序贯检验方法——序贯验后加权检验方法

序贯验后加权检验方法是Bayes 统计观点在假设检验中的运用。本文提出了该方法的一般理论,给出了当总体的分布参数具有验前信息时的序贯检验方法。文中确定了决策区的划分,同时讨论了序贯截尾方案,给出了检验中可能犯两类错误的概率的上界,并将一般理论应用于产品的可靠性检验和再入飞行器随机落点的精度鉴定。由于运用了验前信息,因此能有效地在少量试验之下进行统计假设检验。本文所提供的方法对于昂贵产品试验结果的统计评定具有普遍意义。     

维修性试验验前信息融合方法

针对小子样维修性试验因数据异总体而导致验前信息融合精度低的问题,提出了基于信息可用度的验前信息折合模型,解决了因数据异总体无法融合的问题;利用随机加权法对验前分布参数进行了拟合,准确地表述了验前分布;提出了基于支持度的融合权值确定方法,提高了各验前分布融合权值分配的合理性;最后,通过某装备维修性试验验前信息融合实例,表明了该方法具有一定的工程应用价值。     

指数型产品可靠性验收试验的一种贝叶斯方法

采用贝叶斯方法 ,利用大量的历史数据和工程技术人员的丰富经验确定先验分布 ,制定出验收试验的一种新方案 .按照这一方案 ,在确保产品质量的前提下 ,可大大节省试验时间 ,从而得到十分可观的经济效益 .     

A bayesian approach to evaluating military investments in product improvement and testing

Two issues of frequent importance in new product development are product improvement and reliability testing. A question often faced by the developer is: Should the product be distributed in its present state, or should it be improved further and/or tested before distribution? A more useful statement of the question might be: What levels of investment in further improvement and testing are economically permissible? Products for which this question is relevant may vary widely in type and intended use. This paper presents a model for determining these levels for one such product—an equipment modification procedure. The model presented makes use of present value analysis to compare cost streams and of Bayesian statistics to relate the costs to various outcomes under conditions of uncertainty. The model is applied to an actual military problem and a method is described for examining the sensitivity of the results to changes in the prior probabilities and discount rate.     

Sensitivity Test and Data Analysis for Storage Reliability Assessment of Explosive Initiator

The explosive initiator is one kind of sensitivity products with long life and high reliability.In order to improve the storage reliability assessment,the method of storage reliability assessment for explosive initiator was proposed based on time series model using the sensitivity test data.In the method,the up and down test was used to estimate the distribution parameters of threshold.And an approach to design the up and down test was present to draw better estimations.Furthermore,the method of shrinkage estimation was introduced to get a better estimation of scale parameter by combining the sample information with prior information.The simulation result shows that the shrinkage estimation is better than traditional estimation under certain conditions.With the distribution parameters estimations,the time series models were used to describe the changing trends of distribution parameters along with storage time.Then for a fixed storage time,the distribution parameters were predicted based on the models.Finally,the confidence interval of storage reliability was obtained by fiducial inference.The illustrative example shows that the method is available for storage reliability assessment of the explosive initiator with high reliability.     

A model for step‐stress accelerated life testing

Modern technology is producing high reliability products. Life testing for such products under normal use condition takes a lot of time to obtain a reasonable number of failures. In this situation a step‐stress procedure is preferred for accelerated life testing. In this paper we assume a Weibull and Lognormal model whose scale parameter depends upon the present level as well as the age at the entry in the present stress level. On the basis of that we propose a parametric model to the life distribution for step‐stress testing and suggest a suitable design to estimate the parameters involved in the model. A simulation study has been done by the proposed model based on maximum likelihood estimation. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

三参数威布尔分布在寿命分析中的参数估计

威布尔分布在可靠性工程中已得到了广泛的应用.在对己给定的寿命试验数据进行可靠性分析与评估中,因简单易解多采用二参数威布尔分布,但参数估计会带来较大误差.对具有以损耗失效为特征的某些机械零部件,采用三参数威布尔分布进行拟合及参数估计,可以得到更高的精度,因而较二参数威布尔分布,更能反映产品可靠性的实际情况.     

A sequential Bayesian generalization of the Jelinski–Moranda software reliability model

The Jelinski–Moranda model of software reliability is generalized by introducing a negative‐binomial prior distribution for the number of faults remaining, together with a Gamma distribution for the rate at which each fault is exposed. This model is well suited to sequential use, where a sequence of reliability forecasts is made in the process of testing or using the software. We also investigate replacing the Gamma distribution with a worst‐case assumption about failure rates (the worst‐case failure rate in models such as this is not infinite, since faults with large failure rates are immediately discovered and removed). © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006