给定极小样本量的定量截尾序贯检验法及其应用

对现有截尾序贯检验法作了必要的改进,提出定量截尾序贯检验法。结合导弹命中精度验收试验的工程实际需求,在事先给定几种特小样本量的前提下,针对定量截尾序贯检验法的实际应用展开研究,给出了可应用于实际的检验方案。通过对检验实例的比较分析,说明了方案的优越性。     

运行和修复同时进行的固有可用度定时截尾试验方案

针对如何设计一个试验以完成检验系统固有可用度、平均故障间隔时间和平均修复时间等3个指标参数的问题,将试验分为同时进行的可靠性和维修性定时截尾试验2个项目,假设运行时间和修复时间均服从指数分布,且可靠性和维修性试验方案已知,提出了一种固有可用度定时截尾试验方案．该试验方案通过合理选择累积运行时间和累积修复时间,同时满足检验3个指标参数的承制方和使用方风险,可完成对3个指标参数的检验．     

定时截尾试验的参数估计

本文对可靠性试验中定时截尾试验的参数估计公式进行推证和讨论。认为 GJB 899—90《可靠性鉴定和验收试验》中的个别公式有差错。为避免可靠性计算中发生差错,应予以纠正。     

寿命型产品定数截尾可靠性鉴定试验方案研究

相对于定时截尾可靠性鉴定试验方案来说,寿命型产品定数截尾试验方案方面的研究较少。首先从理论上证明了,寿命服从指数分布的产品,无论对定数截尾试验中的故障产品是否用新产品替换,其鉴定试验方案的设计公式完全相同。之后推导出了同时能满足检验上限、检验下限、生产方风险、使用方风险要求的定数截尾鉴定试验方案设计公式,并用GB5080.7中的数据验证了公式的正确性。给出了指数寿命型产品定数截尾试验中的接收概率公式,并推论出了同一产品在不同试验方案的鉴定结果可能完全相反。最后建议,应在鉴定试验前尽可能知晓产品的可靠性水平,从而可有目的地选择或设计试验方案,以求产品高概率通过鉴定试验。     

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．     

一种改进的指数型序贯抽样检验方法

针对指数型产品的可靠性验收问题,通过分析总结两次序贯概率比检验和序贯网图检验的思想,提出了一种改进的序贯抽样检验方法。通过构造验收风险的马尔可夫链模型,研究了改进的指数型序贯抽样检验方案的风险计算方法。在此基础上,给出了指数型序贯抽样检验方案的制定程序。实例分析表明:改进的指数型序贯抽样检验方案在保证截尾时间的条件下,明显降低了美军标MIL-STD-781C标准方案的验收风险,可以更好地满足双方的风险要求。     

截尾序贯验后加权检验截尾点的优化设计

选取截尾点是截尾序贯验后加权检验很关键的一步,目前理论上尚无有效的选取方法。本文用优化技术确定截尾点Ｃ,克服了实践中确定停时Ｎ和截尾点Ｃ遇到的计算困难,避免了一般取Ｃ＝１的盲目性,使截尾点Ｃ的选取有了理论根据。优选的截尾点不仅使双方承担的风险之和最小,而且使双方承担的风险值相对合理,易于接受。     

枪械可靠性试验统计方案与参数估计研究

为了提高对枪械可靠性指标试验考核的系统性,对枪械故障分布规律进行了建模研究和特征分析,说明在使用寿命内可以用指数分布来近似;以指数分布为基础,运用可靠性工程理论和数学方法,开展了枪械定时截尾和序贯截尾两类试验统计方案的研究,举例说明了各试验要素的量化确定方法;对于定时截尾试验提出了枪械可靠性要求常用特征量故障率的点估计与区间估计公式,以便于定量地把握枪械的可靠性特征;通过实例应用验证了枪械可靠性试验统计方案与参数估计方法的可行性和有效性。     

导弹命中精度的序贯截尾概率圆检验方法

针对圆概率偏差检验难以直接计算的问题,提出序贯截尾概率圆检验方法,以目标点为中心,绘制两个同心圆,其中小圆以内区域为接受域,大圆以外区域为拒绝域,中间区域为继续试验域,在此基础上定义了序贯检验的基本决策规则,给出了双方风险及平均试验次数计算模型,提出了两种不同的决策阈值优化计算模型,通过求解优化问题确定接受域及拒绝域半径。利用数值仿真分析了两种不同决策阈值计算方法下检验方案中的各类参数,其中以平均试验次数最小为优化目标的计算模型具有更好的工程实用性。     

武器系统MTBF的Bayes序贯检验方法

针对武器系统试验鉴定中显著具有的小子样的特点,研究了武器系统平均故障间隔时间(MTBF)的Bayes序贯检验方法,推导了检验模型,平均试验数计算公式、定时和定数截尾实际风险计算公式,并给出了算例。该方法在武器系统可靠性鉴定中具有一定的应用价值。     

Efficient distributions of arms‐control inspection effort

A rule that constrains decision‐makers is enforced by an inspector who is supplied with a fixed level of inspection resources—inspection personnel, equipment, or time. How should the inspector distribute its inspection resources over several independent inspectees? What minimum level of resources is required to deter all violations? Optimal enforcement problems occur in many contexts; the motivating application for this study is the role of the International Atomic Energy Agency in support of the Treaty on the Non‐Proliferation of Nuclear Weapons. Using game‐theoretic models, the resource level adequate for deterrence is characterized in a two‐inspectee problem with inspections that are imperfect in the sense that violations can be missed. Detection functions, or probabilities of detecting a violation, are assumed to be increasing in inspection resources, permitting optimal allocations over inspectees to be described both in general and in special cases. When detection functions are convex, inspection effort should be concentrated on one inspectee chosen at random, but when they are concave it should be spread deterministicly over the inspectees. Our analysis provides guidance for the design of arms‐control verification operations, and implies that a priori constraints on the distribution of inspection effort can result in significant inefficiencies. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

A sequential attribute sampling inspection game for item facilities

The routine inspection of facilities storing large numbers of identical items is modeled as a two‐person, sequential game. Timely detection of illegal activity is parameterized in terms of a critical time to detection, and equilibria are derived which provide inspection strategies. Necessary conditions for deterrence of illegal behavior are discussed. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 496–505, 2001     

MARKOVIAN DETERIORATION WITH UNCERTAIN INFORMATION — A MORE GENERAL MODEL

A model of a deteriorating system with imperfect information is considered. The structures appropriate for such a model include failing machinery and depleted inventory systems. In an effort to add a new dimension to such models, it is assumed that the operator must pay an inspection cost to determine the precise state of the system. At the start of every time period, the operator is faced with three choices: repair, no action, or inspection. Under fairly general assumptions, the optimal policy for repair is found to be straightforward and intuitive. This result has two important areas of application.     

Sequential determination of inspection epochs for reliability systems with general lifetime distributions

The problem of determining the optimal inspection epoch is studied for reliability systems in which N components operate in parallel. Lifetime distribution is arbitrary, but known. The optimization is carried with respect to two cost factors: the cost of inspecting a component and the cost of failure. The inspection epochs are determined so that the expected cost of the whole system per time unit per cycle will be minimized. The optimization process depends in the general case on the whole failure history of the system. This dependence is characterized. The cases of Weibull lifetime distributions are elaborated and illustrated numerically. The characteristics of the optimal inspection intervals are studied theoretically.     

Optimal lot sizing and inspection policy for an EMQ model with imperfect inspections

An EMQ model with a production process subject to random deterioration is considered. The process can be monitored through inspections, and both the lot size and the inspection schedule are subject to control. The “in-control” periods are assumed to be generally distributed and the inspections are imperfect, i.e., the true state of the process is not necessarily revealed through an inspection. The objective is the joint determination of the lot size and the inspection schedule, minimizing the long-run expected average cost per unit time. Both discrete and continuous cases are examined. A dynamic programming formulation is considered in the case where the inspections can be performed only at discrete times, which is typical for the parts industry. In the continuous case, an optimum inspection schedule is obtained for a given production time and given number of inspections by solving a nonlinear programming problem. A two-dimensional search procedure can be used to find the optimal policy. In the exponential case, the structure of the optimal inspection policy is established using Lagrange's method, and it is shown that the optimal inspection times can be found by solving a nonlinear equation. Numerical studies indicate that the optimal policy performs much better than the optimal policy with periodic inspections considered previously in the literature. The case of perfect inspections is discussed, and an extension of the results obtained previously in the literature is presented. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 165–186, 1998     

Using container inspection history to improve interdiction logistics for illicit nuclear materials

Strengthening the United States' ability to prevent adversaries from smuggling nuclear materials into the country is a vital and ongoing issue. The prospect of additional countries, such as Iran, obtaining the know‐how and equipment to produce these special nuclear materials in the near future underscores the need for efficient and effective inspection policies at ports and border crossings. In addition, the reduction of defense and homeland security budgets in recent years has made it increasingly important to accomplish the interdiction mission with fewer funds. Addressing these complications, in this article, we present a novel two‐port interdiction model. We propose using prior inspection data as a low‐cost way of increasing overall interdiction performance. We provide insights into two primary questions: first, how should a decision maker at a domestic port use detection data from the foreign port to improve the overall detection capability? Second, what are potential limitations to the usefulness of prior inspection data—is it possible that using prior data actually harms decision making at the domestic port? We find that a boundary curve policy (BCP) that takes into account both foreign and domestic inspection data can provide a significant improvement in detection probability. This BCP also proves to be surprisingly robust, even if adversaries are able to infiltrate shipments during transit. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 433‐448, 2013     

航空发动机叶片的内窥涡流集成化原位检测

目前内窥检测是航空发动机叶片原位检测的唯一方法,但是内窥检测对于叶片裂纹缺陷的检测效果不理想.为此,提出内窥涡流集成化检测技术,使这两种方法的优势互补,实现对航空发动机叶片的原位检测.研制了一种可用于航空发动机叶片原位检测的内窥涡流集成化检测探头,给出了航空发动机叶片的检测实例.检测结果表明:内窥涡流集成化检测技术的缺陷检测能力高,并且可以实现对裂纹缺陷的定量评估,因此较单一的内窥检测更有优越性.具有很高的实际应用价值.     

Optimal replacement of continuously degrading systems in partially observed environments

Motivated by wind energy applications, we consider the problem of optimally replacing a stochastically degrading component that resides and operates in a partially observable environment. The component's rate of degradation is modulated by the stochastic environment process, and the component fails when it is accumulated degradation first reaches a fixed threshold. Assuming periodic inspection of the component, the objective is to minimize the long‐run average cost per unit time of performing preventive and reactive replacements for two distinct cases. The first case examines instantaneous replacements and fixed costs, while the second considers time‐consuming replacements and revenue losses accrued during periods of unavailability. Formulated and solved are mixed state space, partially observable Markov decision process models, both of which reveal the optimality of environment‐dependent threshold policies with respect to the component's cumulative degradation level. Additionally, it is shown that for each degradation value, a threshold policy with respect to the environment belief state is optimal if the environment alternates between two states. The threshold policies are illustrated by way of numerical examples using both synthetic and real wind turbine data. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 395–415, 2015     

Stochastic allocation of inspection capacity to competitive processes

Optimal allocation and control of limited inspection capacity for multiple production processes are considered. The production processes, which operate independently but share inspection capacity, are subject to random failures and are partially observed through inspection. This study proposes an approach of stochastic allocation, using a Markov decision process, to minimize expected total discounted cost over an infinite time horizon. Both an optimal model and a disaggregate approximation model are introduced. The study provides some structural results and establishes that the control policy is of a threshold type. Numerical experiments demonstrate a significantly decreased amount of computational time required for the disaggregate approach when compared to the optimal solution, while generating very good control policies. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 78–94, 2002; DOI 10.1002/nav.1049