某高炮GSA MK3型瞄准具控制系统可靠性分析

应用可靠性工程理论,通过对某高炮GSAMK3型瞄准具控制系统的结构原理分析,构建了进行可靠性分析的可靠性框图。应用冷贮备系统全概率法,建立了某高炮GSAMK3型瞄准具控制系统的可靠度函数,并计算推导了控制系统的平均寿命,采用这些公式可以进行某高炮GSAMK3型瞄准具控制系统的可靠性预计和分析。     

油料装备增速器可靠性研究

军用油料装备动力系统的高可靠性是装备可靠性的重要保证。根据机械可靠性设计理论,建立了装备动力系统重要零件——增速器的可靠性设计数学模型,并且分析了模型中参数的选择。运用此方法,为设计人员提供了油料装备可靠性的理论依据。     

基于FMECA的某型雷达系统故障分析

故障模式、影响及危害性分析 (简称FMECA)是提高系统可靠性的一种有效的工具。在雷达系统故障分析中运用FMECA方法 ,通过计算机辅助程序实现了故障分析的预测分析和定量分析。与传统的故障分析方法相比 ,该方法能够避免分析中的盲目性和主观性 ,可以获得更为准确的分析结果     

火炮身管寿命分析与计算

分析了射击时弹丸挤进过程 ,建立了弹丸初速下降量与炮膛内膛磨损量计算模型 ,并以某火炮为实例计算了该炮弹丸初速下降量与炮膛内膛磨损量之间变化关系 ,分析了弹道峰现象 ,为身管寿命预测提供理论依据     

Estimating distribution functions from partially observed samples

Suppose that some components are initially operated in a certain condition and then switched to operating in a different condition. Working hours of the components in condition 1 and condition 2 are respectively observed. Of interest is the lifetime distribution F of the component in the second condition only, i.e., the distribution without the prior exposure to the first condition. In this paper, we propose a method to transform the lifetime obtained in condition 1 to an equivalent lifetime in condition 2 and then use the transformed data to estimate F. Both parametric and nonparametric approaches each with complete and censored data are discussed. Numerical studies are presented to investigate the performance of the method. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 521–530, 2000     

考虑故障影响的机构可靠性建模

对影响机构可靠性的主要因素、机构可靠性变化的基本过程以及表征机构可靠性变化的指标参数进行了分析 ,针对机构可靠性问题的特点 ,提出了基于机构输出参数的目标函数与实现函数的叠覆进行机构可靠性分析的方法以及考虑故障等级影响、对不同故障等级进行加权的机构可靠性失效判据 ,建立了与此相对应的机构可靠性分析的数学模型 ,给出了利用Monte Carlo方法对数学模型进行求解的计算流程 ,并对某实际工程问题进行了实例分析。     

气体灭火系统联动可靠性探讨

气体灭火系统用在特殊、重要的场所,其联动控制可靠性是成功灭火的关键.但由于设计单位、建设单位重视不够,影响了联动可靠性.为此针对气体灭火系统联动控制模式规范设计,严把施工质量关,搞好配套设备的控制,以确保系统联动控制可靠性.     

地(舰)空导弹弹体结构可靠性分析

对地(舰)空导弹弹体结构可靠性进行了分析,介绍了弹体结构可靠性的工程计算方法,提出了改进弹体结构可靠性的技术途径。     

Sequential and systematic sampling plans for the Markov‐dependent production process

Acceptance sampling plans are used to assess the quality of an ongoing production process, in addition to the lot acceptance. In this paper, we consider sampling inspection plans for monitoring the Markov‐dependent production process. We construct sequential plans that satisfy the usual probability requirements at acceptable quality level and rejectable quality level and, in addition, possess the minimum average sample number under semicurtailed inspection. As these plans result in large sample sizes, especially when the serial correlation is high, we suggest new plans called “systematic sampling plans.” The minimum average sample number systematic plans that satisfy the probability requirements are constructed. Our algorithm uses some simple recurrence relations to compute the required acceptance probabilities. The optimal systematic plans require much smaller sample sizes and acceptance numbers, compared to the sequential plans. However, they need larger production runs to make a decision. Tables for choosing appropriate sequential and systematic plans are provided. The problem of selecting the best systematic sampling plan is also addressed. The operating characteristic curves of some of the sequential and the systematic plans are compared, and are observed to be almost identical. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 451–467, 2001     

Reliability of a 2‐dimensional k‐within‐consecutive‐r × s‐out‐of‐m × n:F system

A 2‐dimensional rectangular (cylindrical) k‐within‐consecutive‐r × s‐out‐of‐m × n:F system is the rectangular (cylindrical) m × n‐system if the system fails whenever k components in a r × s‐submatrix fail. This paper proposes a recursive algorithm for the reliability of the 2‐dimensional k‐within‐consecutive‐r × s‐out‐m × n:F system, in the rectangular case and the cylindrical case. This algorithm requires min ( O (mk^r(n?s)), O (nk^s(m?r))), and O (mk^rn) computing time in the rectangular case and the cylindrical case, respectively. The proposed algorithm will be demonstrated and some numerical examples will be shown. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 625–637, 2001.