可靠性增长试验中一种新的参数估计法

本文在充分利用可靠性增长试验中各阶段试验数据评定现阶段可靠性指标的基础上对成败型和指数寿命型试验下所得的抽样数据,采用一种新的样本空间排序法─字典排序法给出了现阶段可靠性的点估计和置信下限．从理论和实例两个方面论证了它比仅利用现阶段数据的经典方法具有一致的优良性,改进了房祥忠等［４］相应研究中的不足．而文中定理２．４、定理３．４的结论不仅与可靠性增长试验的直观背景相吻合,还大大提高了这种新方法的实际可操作性．     

多台系统可靠性增长试验方法研究

提出了一种解决多台系统同步投试、同步停止试验和同步改进问题的新模型——指数模型．该模型充分考虑了增长过程中的各种可得信息,包括各改进阶段的失效数、未失效数和失效时间等数据．如果多台系统经过多次同步改进,并且单台系统的可靠性增长符合AMSAA模型,就可以合理地认为在每两个相邻的改进时刻之间,每台系统的失效时间服从指数分布．采用非参数方法得到多台系统在各同步停止试验时刻的可靠度,并利用最小二乘法拟合求得该模型中参数a和b的点估计值,以及参数b的置信限．通过在工程实例中对所提模型和几种已有模型计算结果的比较,说明了所提模型在解决多台系统同步可靠性增长问题中的合理性．     

长寿命产品在小子样缺失数据下的Bayes可靠性增长分析

在长寿命产品的可靠性增长试验过程中,由于人员、观测设备或其他方面的原因,可能会造成某些试验数据丢失或未观测到的现象。对这类小子样变总体缺失数据情形,提出了Bayes可靠性增长分析方法。首先利用Box-Tiao技术构造先验分布,然后利用非齐次Poisson过程原理和缺失数据的产生机制,得到可靠性增长缺失数据的似然函数,再用Bayes统计推断方法得到产品各研制阶段结束时的可靠性水平,同时给出了缺失数据下增长模型的拟合优度检验方法。最后通过一个示例说明了该方法在工程上的应用。     

储存可靠性试验数据的保序回归分析法

本文对一类分布，提出一种在储存可靠性试验场合下分布参数的非迭代估计─ISRDF估计，这种估计是相合的，渐近正态的．该方法方便实用，模拟表明对某些分布精度良好．应用于实测数据的分析中，得到了较好的效果．     

结构可靠性分析的支持向量机方法

针对结构可靠性分析中功能函数不能显式表达的问题,将支持向量机方法引入到结构可靠性分析中．支持向量机是一种实现了结构风险最小化原则的分类技术,它具有出色的小样本学习性能和良好的泛化性能,因此提出了两种基于支持向量机的结构可靠性分析方法．与传统的响应面法和神经网络法相比,支持向量机可靠性分析方法的显著特点是在小样本下高精度地逼近函数,并且可以避免维数灾难．算例结果也充分表明支持向量机方法可以在抽样范围内很好地逼近真实的功能函数,减少隐式功能函数分析（通常是有限元分析）的次数,具有一定的工程实用价值．     

噪声实验室供气系统的可靠性分析

文章研究了噪声实验室供气系统的可靠性问题,根据供气系统的工程设计框图绘制了可靠性框图．进而得到了供气系统的可靠性表达式．根据可靠性的评估方法,结合模拟试验的数据得到了供气系统可靠性评估的定量结果．通过时评估结果的分析,给出了改进噪声实验室供气系统的工程设计从而提高其可靠性的方法．     

基于不完全数据的敏感性产品可靠性的综合评定1

敏感性产品是在某种可以度量的刺激下的一次性作用产品 ,一般采用成败型数据或序惯试验所得不完全数据来估计其可靠度 .前者在高可靠性要求下 ,所需样本量太大 ;后者虽需要较少的样本量 ,但是造成的外推误差太大 .本文将这两种数据结合起来 ,经过一定的纠偏后给出了敏感性产品的综合可靠性估计 .蒙特卡洛模拟表明 ,这样的综合评估方法是一种可行的方法 .     

筛选试验情形下可靠性评估

通过改变数据填充方式重新对筛选试验进行可靠性评估.在填充数据的方法上选择等分位点数据填充算法,使得改进后的算法所得的虚拟完全数据更接近于真实的完全数据.最后对所提出的筛选试验情形下可靠性评估方法进行了模拟验证.     

简单步进应力加速寿命试验及其最优设计

仅含有二个高应力的步加试验称为简单步加试验。本文试图在指数分布场合下对截尾数据讨论简单步加试验。给出了常应力下一些可靠性特征的点估计和置信限,还给出了简单步加试验的最优设计。这里最优性是指常应力下对数寿命的渐近方差的极小化,最后的一个例子说明了上述方法的具体应用。     

截尾子样下的检验方法在可靠性中的应用

<正> 由于产品可靠性日益提高,使用寿命不断延长,所以在寿命试验中,一般只能进行截尾试验,不易得到全子样数据,因而如何利用截尾数据对产品的寿命分布和有关参数进行假设检验,是可靠性数学问题中值得研究的课题.本文将讨论几种检验方法,并用实例说明这些方法在可靠性工程中的应用.     

考虑多种类型缺陷的软件可靠性模型研究

本文提出一种考虑多种类型缺陷的软件可靠性模型,并构建了缺陷检测和剔除两个过程的模型。具体分类情况,可以根据模型的检验方法(拟合准则和预测有效性度量)和模型复杂度来具体决定,如果有测试人员的分类建议或者分类数据,可以结合模型共同决定。为了说明问题,本文给出四种类型缺陷的具体模型,并对实际数据集进行了拟合。通过模型比较,验证了多种类型缺陷模型的有效性。最后,通过构建软件最优发布时间策略对模型进行了应用。研究结果为软件开发和测试提供了理论参考。     

数据预处理对替代数据检验方法的影响

替代数据检验法是检验时间序列中是否存在确定性非线性成分的重要统计方法.通过研究差分和数据平滑运算对替代数据检验方法的影响,指出常用的线性滤波等数据预处理步骤破坏了序列的静态性质,从而会导致对零假设的错误拒绝.因此,建议应该直接利用原始时间序列而非应用了差分等非静态滤波运算后的时间序列生成替代数据,再进行假设检验,以免造成对零假设的错误拒绝.     

Interval statistic based reliability analysis method on small sample hot test of satellite thruster

As one of the most important components of satellites, the thruster must maintain high reliability, but the assessment is difficult when lacking test failure data. When conducting hot test of the satellite thruster, we encountered the problem of reliability assessment on type-I censored data with only one failure, which is common for small sample tests. This paper proposes a novel interval statistic based reliability analysis method, which can fulfill the life information from the failure time to the censored time ignored by conventional methods, and improve the assessment accuracy. In this paper, a life distribution model is established by proper failure mechanism analysis and prior test information exploitation. As thrust chamber burning-through has been considered as the main failure mode, life test of the chamber coating was conducted under different thermal conditions to obtain the model parameter. Based on the interval statistic theory, a detailed derivation is illustrated. Then, reliability assessment and life prediction for the satellite thruster in both transfer orbit phase and synchronous orbit phase have been achieved, and the results show that our method performs very well, which provides an important way for dealing with test data with only one failure.     

BAYESIAN ANALYSIS OF DATA WITH ONLY ONE FAILURE

The hearings of a certain type have their lives following a Weibull distribution. In a life test with 20 sets of bearings, only one set failed within the specified time, and none of the remainder failed even after the time of to estimate the reliabilWith a set of testing data like that in Table 1, it is required to estimate the reliability at the mission time, In this paper, we first use hierarchical Bayesian method of determine the prior distribution and the Bayesian estimates of various probabilities of failures, pi‘s, then use the method of least squares to estimate the parameters of the Weibull distribution and the reliability. Actual computation shows that the estimates so obtained are rather robust. And the results have been adopted for practical use.     

Joint spare parts inventory and reliability decisions under a service constraint

Reliability and inventory levels of spare parts are major factors that determine the service level for the maintenance of machines provided by original equipment manufacturers (OEMs). In general, decisions on reliability and stock levels are made separately in practice, and academic literature offers little guidance on how to jointly make these two decisions. In order to fill in the gap in the literature and provide guidance to OEMs, we jointly model reliability and inventory problems. We consider three different service measures: aggregate fill rate, average downtime per system per year and expected total number of long downs in a year. Our models minimize the sum of holding and emergency shipment costs subject to a limited reliability improvement budget and a target service level. We develop an algorithm that considers reliability and inventory decisions simultaneously, test our solution approach on real-life and randomly generated data sets and compare the results with an approach that considers reliability and inventory decisions sequentially. Numerical results show substantial benefits of integrating reliability and inventory decisions.     

基于测试数据的装备贮存可靠性评估

针对无失效数据情形下装备贮存可靠性估计问题,提出了一种利用性能测试数据进行估计的方法.首先利用测试数据估计装备在不同测试时的失效概率,然后利用配分布曲线法估计装备贮存寿命分布函数中的未知参数.由于方法充分利用了装备性能测试数据中所隐含的可靠性变化趋势,使其估计结果具有一定的可信性.     

Markov Chains on Graded Posets

We consider two types of discrete-time Markov chains where the state space is a graded poset and the transitions are taken along the covering relations in the poset. The first type of Markov chain goes only in one direction, either up or down in the poset (an up chain or down chain). The second type toggles between two adjacent rank levels (an up-and-down chain). We introduce two compatibility concepts between the up-directed transition probabilities (an up rule) and the down-directed (a down rule), and we relate these to compatibility between up-and-down chains. This framework is used to prove a conjecture about a limit shape for a process on Young’s lattice. Finally, we settle the questions whether the reverse of an up chain is a down chain for some down rule and whether there exists an up or down chain at all if the rank function is not bounded.     

A simulation based approach to the parameter estimation for the three-parameter gamma distribution

The gamma distribution is one of the commonly used statistical distribution in reliability. While maximum likelihood has traditionally been the main method for estimation of gamma parameters, Hirose has proposed a continuation method to parameter estimation for the three-parameter gamma distribution. In this paper, we propose to apply Markov chain Monte Carlo techniques to carry out a Bayesian estimation procedure using Hirose’s simulated data as well as two real data sets. The method is indeed flexible and inference for any quantity of interest is readily available.     

Duane-LR模型下复杂系统的动态可靠性增长评定

基于复杂系统可靠性增长试验的特点，运用Duane可靠性增长模型结合数理统计中的线性回归方法对新批次产品的可靠性参数进行预测。结合产品的少量现场试验数据，利用Bayes方法对系统的可靠性增长试验结果进行评定。文中首先给出了可靠性增长分析的模型，然后运用历次阶段试验中的可靠性增长数据建立动态参数的递推估计模型，在此基础上，运用随机变量函数的分布，给出各阶段可靠性增长试验中可靠性参数的Bayes估计。文中对Weibull、指数和二项分布三种试验结果进行分析，给出计算公式。     

Nonparametric predictive reliability of series of voting systems

Nonparametric Predictive Inference (NPI) for system reliability reflects the dependence of reliabilities of similar components due to limited knowledge from testing. NPI has recently been presented for reliability of a single voting system consisting of multiple types of components. The components are all assumed to play the same role within the system, but with regard to their reliability components of different types are assumed to be independent. The information from tests is available per type of component. This paper presents NPI for systems with subsystems in a series structure, where all subsystems are voting systems and components of the same type can be in different subsystems. As NPI uses only few modelling assumptions, system reliability is quantified by lower and upper probabilities, reflecting the limited information in the test data. The results are illustrated by examples, which also illustrate important aspects of redundancy and diversity for system reliability.