步进加速退化试验及其在电子产品可靠性评估中的应用

为快速评估具有高可靠、长寿命特点的电子产品的可靠性,提出了使用步进加速退化试验技术的方法。文中首先给出了步进加速退化的试验方法及基本假设,然后给出了步进退化数据向恒加退化数据的折算方法,在此基础上提出了基于伪失效寿命的步进加速退化可靠性评估算法,最后利用试验数据对该方法进行了验证。该方法与恒加退化试验相比,在保持样本量不变的基础上,可以极大地缩短试验时间,因此,具有更高的效费比。     

按Weibull分布计算滚动轴承的寿命和强度的可靠性

运用weibull分布推导出任意可靠性指标下滚动轴承的寿命和强度计算公式,给出了多列轴承和轴承系统的可靠性计算方法和公式,并按照工程的方法加以简化处理。     

基于退化量分布的某型电连接器寿命预测方法

使用基于退化量分布的方法对某型电连接器进行了寿命预测,得到了其可靠度曲线并预测出其平均寿命为398 895 h。通过对各加速应力水平下所有样品的退化量进行拟合优度检验,得出退化量在各测量时刻最优服从正态分布,进而确定了退化量均值、方差与温度应力之间的关系。为了提高估计精度,使用极大似然法进行整体统计推断获取未知参数的估计值,并基于参数值与温度的关系外推出样品在工作温度下的可靠度函数。通过可靠度曲线的比较,获知样品寿命较好地服从对数正态分布,并基于此进行了平均寿命预测。     

一种寿命分布类——剩余寿命按凸序递减类

在前人研究的寿命分布类的基础上 ,给出一种新的寿命分布类的定义 ,并研究了其有关的性质 (主要是封闭性质 )。     

On the conditional residual lifetime of coherent systems under double regularly checking

In this paper, we consider a coherent system with n independent and identically distributed components under the condition that the system is monitored at time instances t₁ and t₂ (t₁ < t₂). First, various mixture representations for reliability function of the conditional residual lifetime of the coherent system are derived under different scenarios at times t₁ and t₂ (t₁ < t₂). Several stochastic comparisons between two systems are also made based on the proposed conditional random variables. Then, we consider the conditional residual lifetime of the functioning components of the system given that j components have failed at time t₁ and the system has failed at time t₂. Some stochastic comparisons on the proposed conditional residual lifetimes are investigated. Several illustrative graphs and examples are also provided.     

残差GM（1，1）模型在恒加试验中的应用

介绍了目前恒加试验中,正常应力水平下特征寿命点估计的数据统计分析方法及其不足。针对恒加试验的特点和所需解决的问题,基于灰色预测理论的残差GM(1,1)模型,给出了一种新的求解方法。最后分别运用三种不同的方法对给出的应用实例进行正常应力水平下特征寿命值的求解,证明了本文所给出的方法确实可行。     

Signature based analysis of m‐Consecutive‐k‐out‐of‐n: F systems with exchangeable components

In this article, we study reliability properties of m‐consecutive‐k‐out‐of‐n: F systems with exchangeable components. We deduce exact formulae and recurrence relations for the signature of the system. Closed form expressions for the survival function and the lifetime distribution as a mixture of the distribution of order statistics are established as well. These representations facilitate the computation of several reliability characteristics of the system for a given exchangeable joint distribution or survival function. Finally, we provide signature‐based stochastic ordering results for the system's lifetime and investigate the IFR preservation property under the formulation of m‐consecutive‐k‐out‐of‐n: F systems. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

系统的模糊可靠度、模糊故障率和模糊平均寿命之间的关系

讨论了系统的模糊可靠度、模糊故障率和模糊平均寿命之间的关系及串联、并联系统的模糊可靠度、模糊平均寿命与元件的模糊故障率、模糊平均寿命的关系。     

求解传感器网络最大生存时间的最大流算法

节能是传感器网络研究的中心问题之一,目的是延长网络的生存时间。因此对于一个给定网络,很自然地关心它的最大生存时间是多少。从网络最大流的角度分析这个问题,给出了求解传感器网络最大生存时间确切值的算法。     

Estimating component characteristics from system failure‐time data

Suppose that failure times are available from a random sample of N systems of a given, fixed design with components which have i.i.d. lifetimes distributed according to a common distribution F. The inverse problem of estimating F from data on observed system lifetimes is considered. Using the known relationship between the system and component lifetime distributions via signature and domination theory, the nonparametric maximum likelihood estimator _N(t) of the component survival function (t) is identified and shown to be accessible numerically in any application of interest. The asymptotic distribution of _N(t) is also identified, facilitating the construction of approximate confidence intervals for (t) for N sufficiently large. Simulation results for samples of size N = 50 and N = 100 for a collection of five parametric lifetime models demonstrate the utility of the recommended estimator. Possible extensions beyond the i.i.d. framework are discussed in the concluding section. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010