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     

A new importance sampling Monte Carlo method for a flow network reliability problem

The exact evaluation of the probability that the maximum st‐flow is greater than or equal to a fixed demand in a stochastic flow network is an NP‐hard problem. This limitation leads one to consider Monte Carlo alternatives. In this paper, we propose a new importance sampling Monte Carlo method. It is based on a recursive use of the state space decomposition methodology of Doulliez and Jamoulle during the simulation process. We show theoretically that the resulting estimator belongs to the variance‐reduction family and we give an upper bound on its variance. As shown by experimental tests, the new sampling principle offers, in many cases, substantial speedups with respect to a previous importance sampling based on the same decomposition procedure and its best performances are obtained when highly reliable networks are analyzed. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 204–228, 2002; DOI 10.1002/nav.10004     

利用极大值原理求解飞行器飞行区域

利用现代最优控制理论极大值原理 ,考虑给定约束条件下所有可能的控制方案 ,确定了一定时间内飞行器飞行区域。     

线阵CCD在机械微变距离测量中的应用

介绍了一种应用线阵CCD测量柴油机曲轴臂距差的原理和方法 .讨论了光杠杆原理在此测量系统中的应用 ,并结合实际分析了系统产生非线性误差的原因 ,给出了此测量系统非线性的处理方法 .     

基于最大后验风险的多层Bayes方法

为了对指数型产品进行可靠性鉴定,首先给出了失效率的多层先验分布,然后从最大后验风险的角度,运用Bayes方法,制定出可靠性鉴定试验方案.按照此鉴定试验方案,缩短了试验时间,从而降低了鉴定试验所需的费用.     

зрлaнгa分布及其在保障性数据分析中的应用

首先对（?）分布的特点进行了分析,其次运用极大似然法对其分布参数t_0进行了估计,然后通过2个实例验证了这种分布的可行性和实用性,最后得出几点结论。SS     

相同高度两相邻建筑防火间距设计

防火间距设计是建筑工程消防安全设计中很重要的一项内容。通过相同高度两相邻民用建筑防火间距设计工程实例,结合国家现行《建筑设计防火规范》中的有关规定,探讨了《建筑设计防火规范》对相同高度两相邻建筑防火间距设计要求方面存在的问题。     

一种差分空时分组码及其性能分析

文中介绍了一种差分空时分组码的编译方法及其性能分析,与之对比,先导入单天线时差分调制的概念及其方法,理论分析表明,采用无需信道估值的差分空时分组码与相干检测空时分组码相比其性能差3 dB,但与单天线相比仍有接近于10 dB的分集增益。     

Wasserstein距离在液体火箭发动机故障检测中的应用

健康监控技术能够切实提高液体火箭发动机的可靠性,针对液体火箭发动机健康监控中的故障检测问题,提出基于Wasserstein距离的方法,利用液氢液氧火箭发动机地面热试车数据进行验证。该方法的核心思想是利用Wasserstein生成对抗网络模拟正常数据的样本分布,利用其判别器计算测试样本与模拟分布间的Wasserstein距离,进而实现故障检测。结果表明:该方法能够克服故障数据不足的困难,有效检测稳态过程中的故障,没有发生误报警,且对早期异常有较高敏感性;在训练样本较少的情况下,当Wasserstein距离阈值为3σ时对启动过程的早期异常有较高敏感性,取5σ时仍可有效检测启动过程中的故障,误报警率为12.5%。     

高性能炸药综合性能的多维评估

基于欧几里得几何距离的概念,给出了一种炸药综合性能的多维空间评估方法。这种方法在确定炸药理想方案和最差方案的基础上,综合考虑了各种炸药方案与理想方案和最差方案的欧几里得几何距离,以此评估炸药综合性能。