可维修系统的故障率分析

采用蒙特卡洛方法对可维修系统的故障率进行模拟,讨论了元件的抽样方法.在已知元件寿命分布的条件下直接应用蒙特卡洛方法抽样,对单元件的故障率进行了定量的研究,并对两元件的串联系统的故障率进行仿真,得出了可维修系统故障率的变化规律,验证了随着时间的增加故障率趋于常数--平均故障间隔时间的倒数.     

有限制条件的异类元件构成系统的元件维修率分布确定

为了研究不同类型元件组成系统后,元件各自的维修率;同时考虑工作环境因素对维修率的影响,提出了元件维修率分布的概念。元件维修率分布是通过将SFT中故障概率分布代替Markov链中失效率实现的。给出了不同元件组成的并联和串联系统的元件维修率分布推导过程。实现维修率分布的计算关键在于状态转移概率 范围的确定,及不同元件故障率与维修率的比值,即为计算过程所需的限制条件。给出了 范围和比例限定的计算方法和依据。对一个混联系统进行分析,说明了 范围依赖于系统结构并计算得到 ,也得到了系统中三个不同元件的维修率分布。     

基于Markov和SFT的同类元件系统中元件维修率分布确定

为了扩展空间故障树SFT理论,研究可表示工作环境影响的元件维修率,借助Markov链理论对元件维修率分布进行推导。所研究系统的特点为由相同元件所构成,进而使Markov链中失效率和维修率相同。用SFT中的特征函数代替Markov链中失效率,并根据实际情况设定状态转移概率,从而可得SFT下的元件维修率分布。维修率分布是由工作环境因素作为自变量的函数。考虑工作时间t和工作温度c影响下,对一混联系统进行元件维修率分布计算。最终得到了元件维修率分布和正常状态转移概率范围,其具体计算要依赖于实例系统结构。最后论述了方法的不足及其原因。     

基于蒙特卡洛仿真的使用与保障费用风险分析

装备的使用与保障费用风险分析是对影响使用与保障费用的不确定因素进行辨识,为控制和降低装备使用与保障费用提供决策依据.蒙特卡洛仿真方法能够随机模拟各种变量间的动态关系,解决具有不确定性的复杂问题.在设计Excel工作表的费用计算模型基础上,选用蒙特卡洛仿真方法得出了使用与保障费用的频率分布和风险概率分布,并分析了组件故障率、基地级平均修复时间、维修周转时间等因素对使用与保障费用的影响.仿真结果表明,提出的使用与保障费用风险分析的蒙特卡洛方法,能提供更为丰富的费用决策信息并且有利于费用不确定性因素的识别.     

彩色显示器维修方法和维修实例

显示器是计算机的重要组成部分,随着使用年限的增加,故障率会越来越多。但一般计算机管理人员难以排除,往往送专门的维修部门。这样不但维修期长,而且浪费财力,降低了计算机的利用率。笔者通过自己对显示器的维修经验,认识到,只要做到胆大心细,敢于动手,许多故障便可迎刃而解。 显示器的检修方法: 一、常规观察法 根据故障现象,首先检查印刷线路有无断裂,元件是否烧焦,元件之间有无相碰短路等现象。通过仔细观察,对一     

用PC诊断其控制系统内元件故障的方法

由于ＰＣ的高可靠性，ＰＣ控制系统的故障率主要取决于外接的检测元件和执行元件。本文提出了不对原控制系统作多大改动，利用ＰＣ自身来对连接到ＰＣ上的检测元件和执行元件的故障进行诊断的方法     

控制系统动态马尔可夫过程可靠性分析

针对特定试验条件下小子样控制系统可靠性评定的特点,引入故障率分析,介绍了基于马尔可夫过程可维修控制系统的可靠性分析方法,推导了n个部件组成的串联可维修系统可用度的表达式,并针对具体工程用控制系统进行了可用度仿真计算。最后借助可靠性分析软件验证了该方法的合理性。两种方法结论一致,为其他结构可修系统的可靠性分析提供了重要的理论依据。     

一种估计网络可靠性的蒙特卡洛方法

将K—终端剩余连通可靠度的概念推广到链路存在失效状态的网络模型上，并提出了计算该可靠度的基于RVR的蒙特卡洛方法。首先对网络链路的状态进行抽样。在网络所有链路状态确定的前提下计算网络的K—终端剩余连通可靠度，即等价于计算相同拓扑结构，链路完全可靠网络的K—终端剩余连通可靠度，对于后者可采用H.Cancela等提出的基于RVR的蒙特卡洛算法。实践证明该估计方法是无偏的，且与原始的蒙特卡洛方法相比具有较小的方差。     

可修复系统事后维修可靠性仿真

指出了Markov方法和Monte-Carlo方法在可修复系统可靠性仿真中存在的问题,并提出了一种新的方法,称为RSS方法,从理论上系统地阐述了RSS方法的基本原理及算法过程,并在理论上验证了其正确性.利用RSS方法可以对事后维修可修复元件和系统的可靠性进行仿真.RSS方法不受系统元件寿命分布类型限制,计算量小,仿真时间短,精度高,仿真结果具有确定性,弥补了Markov方法和Monte-Carlo方法的不足,具有实际可靠性工程应用价值.给出了并联和串联可修复系统事后维修可靠性仿真实例.     

TCAS系统元件级深度维修测试设备研发

目前TCAS处理器测试系统可以进行板卡级测试,不能进行元件级的深度测试与维修。本文分析对TCAS系统故障板卡的元件级深度测试和维修,实现对TCAS系统主要板卡的元件级故障测试、定位与维修,测试系统经调试与运行,效果良好。     

On a repairable system with detection,imperfect coverage and reboot: Bayesian approach

System characteristics of a repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the system consists of one active component and one standby component. The detection of standby, the coverage factor and reboot delay of failed components are possibly considered. Time to failure of the components is assumed to follow exponential distribution. Time to repair and time to reboot of the failed components also follow exponential distributions. When time to failure, time to repair and time to reboot have uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and the steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.     

Numerical method for Weibull generalized renewal process and its applications in reliability analysis of NC machine tools

In generalized renewal process (GRP) reliability analysis for repairable systems, Monte Carlo (MC) simulation method instead of numerical method is often used to estimate model parameters because of the complexity and the difficulty of developing a mathematically tractable probabilistic model. In this paper, based on the conditional Weibull distribution for repairable systems, using negative log-likelihood as an objective function and adding inequality constraints to model parameters, a nonlinear programming approach is proposed to estimate restoration factor for the Kijima type GRP model I, as well as the model II. This method minimizes the negative log-likelihood directly, and avoids solving the complex system of equations. Three real and different types of field failure data sets with time truncation for NC machine tools are analyzed by the proposed numerical method. The sampling formulas of failure times for the GRP models I and II are derived and the effectiveness of the proposed method is validated with MC simulation method. The results show that the GRP model is superior to the ordinary renewal process (ORP) and the power law non-homogeneous Poisson process (PL-NHPP) model.     

Numerical method for Weibull generalized renewal process and its applications in reliability analysis of NC machine tools

In generalized renewal process (GRP) reliability analysis for repairable systems, Monte Carlo (MC) simulation method instead of numerical method is often used to estimate model parameters because of the complexity and the difficulty of developing a mathematically tractable probabilistic model. In this paper, based on the conditional Weibull distribution for repairable systems, using negative log-likelihood as an objective function and adding inequality constraints to model parameters, a nonlinear programming approach is proposed to estimate restoration factor for the Kijima type GRP model I, as well as the model II. This method minimizes the negative log-likelihood directly, and avoids solving the complex system of equations. Three real and different types of field failure data sets with time truncation for NC machine tools are analyzed by the proposed numerical method. The sampling formulas of failure times for the GRP models I and II are derived and the effectiveness of the proposed method is validated with MC simulation method. The results show that the GRP model is superior to the ordinary renewal process (ORP) and the power law non-homogeneous Poisson process (PL-NHPP) model.     

马尔可夫系统瞬态不可用度计算的高效率蒙特卡罗方法

当马尔可夫系统规模较大时,需要采用蒙特卡罗方法计算其瞬态不可用度,如果系统的 不可用度很小,则需要采用高效率的蒙特卡罗方法.本文在马尔可夫系统寿命过程的积分方程的 基础上,给出了系统瞬态不可用度计算的蒙特卡罗方法的统一描述,由此设计了马尔可夫系统瞬 态不可用度计算的直接统计估计方法和加权统计估计方法.用直接仿真方法、拟仿真方法、基于 直接仿真的统计估计方法、基于拟方仿真的统计估计方法和加权统计估计方法计算了-可修 Con/3/30:F系统的瞬态不可用度.结果表明,由于同时采用了偏倚的抽样空间和逐次事件估计 量,加权统计估计方法的方差最小,当系统不可用度很小时,该方法效率最高.     

A repairable system with imperfect coverage and reboot: Bayesian and asymptotic estimation

System characteristics of a two-unit repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the coverage factor for an operating unit failure is possibly considered. Time to failure and time to repair of the operating units are assumed to follow exponential distributions. In addition, the recovery time and reboot time of the failed units also follow exponential distributions. When time to failure, time to repair, recovery time and reboot time are with uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and the steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.     

Bayesian assessing for a repairable system with standby imperfect switching and reboot delay

System performance measures of a repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the system consists of two active components and one warm standby. There is a failure probability q that switches from standby state to active state. Time-to-failure of components is assumed to be an exponential distribution. The reboot time and repair time are also exponential distributions. When time-to-failure, time-to-repair and reboot time are with uncertain parameters, a Bayesian assessing is adopted to evaluate system performance measures. Monte Carlo simulation is used to derive the posterior distribution for the steady-state availability and the mean time-to-system failure. Some numerical experiments are performed to illustrate the results derived in this article.     

可修K/N(G)系统可靠性指标的仿真算法研究

利用Monte Carlo随机抽样技术,采用而向事件和面向固定时间间隔的双推进机制,提出了基于事件模块的可修K/N(G)系统可靠性指标仿真算法,算法能有效解决非指数分布类情况下,考虑部件已工作时间和不同维修策略等因素影响时,解析方法难以处理的系统可靠性分析难题,并且算法能同时对系统可靠性的平均指标和瞬时指标进行分析,从而可为指导装备的使用与维修管理提供有力的依据.算法采取的双推进机制保证了算法的仿真效率,基于事件模块的设计思想保证了算法的可扩展性,而且,经与解析算法比较,验证了仿真算法的正确性.     

System reliability-based design optimization using the MPP-based dimension reduction method

The system probability of failure calculation of the series system entails multi-dimensional integration, which is very difficult and numerically expensive. To resolve the computational burden, the narrow bound method, which accounts for the component failures and joint failures between two failure modes, has been widely used. For the analytic calculation of the component probability of failure, this paper proposes to use the most probable point (MPP)-based dimension reduction method (DRM). For the joint probability of failure calculation, three cases are considered based on the convexity or concavity of the performance functions. Design sensitivity analysis for the system reliability-based design optimization (RBDO), which is the major contribution of this paper, is carried out as well. Based on the results of numerical examples, the system probability of failure and its sensitivity calculation show very good agreement with the results obtained by Monte Carlo simulation (MCS) and the finite difference method (FDM).     

基于信息熵的多电飞机供电可靠度评估

由于多电飞机拓扑结构复杂且发生故障的概率较低,采用传统的蒙特卡罗采样方法进行可靠度评估时存在采样次数多,仿真时间长等缺点。通过信息熵引入多元件系统的近似概率分布,从而提出一种适用于多电飞机供电可靠度评估方法,在信息熵中引入最优参数,改变了元件的故障概率分布,构造了元件零方差概率密度函数的近似函数,然后利用差分进化求解最优参数。结合对偶抽样的信息熵法可进一步降低采样过程的方差,提高了传统蒙特卡罗方法的采样效率。最后使用一个多电飞机电源系统为应用案例,对几种可靠度分析方法进行收敛性和准确性分析,其结果表明本文方法在小概率事件评估问题上优势明显。     

Component and system reliability-based topology optimization using a single-loop method

We perform reliability-based topology optimization by combining reliability analysis and material distribution topology design methods to design linear elastic structures subject to random inputs, such as random loadings. Both component reliability and system reliability are considered. In component reliability, we satisfy numerous probabilistic constraints which quantify the failure of different events. In system reliability, we satisfy a single probabilistic constraint which encompasses the component events. We adopt the first-order reliability method to approximate the component reliabilities and the inclusion-exclusion rule to approximate the system reliability. To solve the probabilistic optimization problem, we use a variant of the single loop method, which eliminates the need for an inner reliability analysis loop. The proposed method is amenable to implementation with existing deterministic topology optimization software, and hence suitable for practical applications. Designs obtained from component and system reliability-based topology optimization are compared to those obtained from traditional deterministic topology optimization and validated via Monte Carlo simulation.