基于延迟时间理论的两部件并联系统检测区间模型

延迟时间理论广泛应用于系统维修领域,更为细致和准确的反映了系统的运行状态,对于系统的维修建模及确定系统的检测区间起到了重要的作用.但是,以往关于延迟时间理论的应用几乎都是关于单部件系统或串联系统的,而并联系统在实际中也有很广泛的应用.应用延迟时间理论对两部件并联系统的检测区间进行研究,在部件缺陷发生的初始时间为非指数分布的情况下,提出了两种不同的维修措施,并以单位时间期望维修费用最小为目的,对每一种维修措施分别进行研究.文章最后给出了数值案例及模拟运算结果,并对未来的工作做了展望.     

基于延迟时间理论的两部件并联系统检测区间模型北大核心

延迟时间理论广泛应用于系统维修领域,更为细致和准确的反映了系统的运行状态,对于系统的维修建模及确定系统的检测区间起到了重要的作用.但是,以往关于延迟时间理论的应用几乎都是关于单部件系统或串联系统的,而并联系统在实际中也有很广泛的应用.应用延迟时间理论对两部件并联系统的检测区间进行研究,在部件缺陷发生的初始时间为非指数分布的情况下,提出了两种不同的维修措施,并以单位时间期望维修费用最小为目的,对每一种维修措施分别进行研究.文章最后给出了数值案例及模拟运算结果,并对未来的工作做了展望.     

考虑不完美检测的两阶段点检与备件订购策略联合优化

针对设备维修与备件管理相互影响与制约的问题, 在基于延迟时间理论的基础上, 提出了两阶段点检与备件订购策略联合优化。点检是不完美的, 当点检识别设备的缺陷状态时, 进行预防更新; 设备故障时, 进行故障更新。结合设备更新时备件的状态, 采用更新报酬理论建立了以第一阶段点检时间、第二阶段点检周期和备件订购时间为决策变量, 以最小化单位时间期望成本为目标的模型。最后, 通过人工蜂群算法对模型求解, 并在数值分析中将两阶段点检策略与定期点检策略进行比较, 结果表明:两阶段点检策略始终优于定期点检策略, 验证了所建模型的有效性。     

于改进UGF算法的线性拓扑WSN系统可靠性评估

提出了面向感知数据融合的通用发生函数(UGF)改进算法,并使用该算法对线性拓扑结构的无线传感网络(WSN)可靠性进行了评估。首先对PEGASIS协议下WSN的线性拓扑结构及数据传输过程进行抽象,建立了双向连续k/n:F系统模型。然后根据WSN感知数据传输及融合方式,在改进算法中重新定义了传感节点的UGF表达式和组合算子。最后对双向连续k/n:F模型进行单向化分解,根据得到的单向模型可靠性推导出双向模型的可靠性表达式。通过具体实例对提出的改进算法进行了验证,计算结果显示改进的算法可有效解决传感网络线性拓扑结构可靠性评估问题。     

考虑共因失效和负载分担的表决系统维修优化分析

随着仪器设备的大型化、精密型和复杂化,传统的单一故障模型很难精确地描述系统。针对可修的表决系统,考虑了负载分担和共因失效两种失效模式,提出了不完美的故障检测策略,并对模型进行了可靠性和维修性分析,求得了系统的瞬时可用度、稳态可用度和平均维修费用。最后通过数值案例给出了同时考虑可用度和维修费用的最优检测策略,能够为设备管理者提供决策依据。     

基于CBM-HTM的复杂系统预防性维修时机优化

针对目前复杂系统因多采用定周期预防性维修而造成维修费用过高、管理效率较低的情况,综合定周期维修(HTM)和基于状态的维修(CBM)两类技术,提出基于CBM-HTM的复杂系统预防性维修时机优化思路.并在此基础上,以费用最小为目标,建立基于CBM-HTM的复杂系统预防性维修时机优化模型.最后以由6个设备组成的复杂系统为例,进行了预防性维修时机优化算例说明.以期借助自主式保障中PHM、CBM技术,优化地面设备预防性维修时机,降低地面设备的预防性维修费用,提高地面设备维修管理的效率和效益.     

线性Consecutive-k-out-of-γ-from-n:F System可靠性精确解的母函数计算方法

本文利用概率母函数法给出了 Consecutive-k-out-of-γ-from-n:F系统的可靠性精确解.这种方法适用于较复杂的系统可靠性计算,易于在计算机上实现.     

生产系统的检修时间间隔及关键备件采购的联合优化研究

研究了检修间隔时间与零备件库存采购的联合优化问题.利用带有吸收状态的连续时间马尔科夫链表示有m个生产状态以及一个损坏状态的生产系统,这个系统的再生点是生产系统的维修或检修完成的时刻点.利用更新过程报酬定理给出单位时间维修成本,利用概率分析技术给出备件库存的单位时间成本,进而得到整个生产系统的单位时间的总成本.最后,通过...     

线性和环型Consecutive-k-out-of-r-from-n:F系统可靠性的精确解

本文利用马氏链嵌入法给出了工程上被称为Consecutive k out of r from n :F系统的可靠性精确解。这种方法适用于较复杂的系统可靠性计算 ,且易于在计算机上实现。     

考虑非周期检测的视情维修与备件订购联合策略优化

针对单部件系统/关键部件提出视情维修与备件订购联合策略,其中系统退化服从两阶段延迟时间过程且采用非周期检测策略,退化初期以检测间隔T₁检查系统状态,而在第一次识别缺陷状态时,缩短检测周期为T₂、订购备件且进行不完美维修;若系统在随后的退化中被识别处于缺陷状态,执行不完美维修直至超过阈值次数N_max并采取预防性更换,但若在检测周期内发生故障则进行更换。根据系统状态和备件状态分析各种可能更新事件及相应的联合决策,利用更新报酬理论构建最小化单位时间内期望成本的目标函数,优化T₁,T₂, N_max。与对比模型策略相比,算例结果表明所提出的联合策略能有效降低单位时间内的期望成本。     

Linear Systems Associated with Numerical Methods for Constrained Optimization

Linear systems associated with numerical methods for constrained optimization are discussed in thia paper ,It is shown that the corresponding subproblems arise in most well-known methods,no matter line search methods or trust region methods for constrained optimization can be expressed as similar systems of linear equations.All these linear systems can be viewed as some kinds of approximation to the linear system derived by the Lagrange-Newton method .Some properties of these linear systems are analyzed.     

Reliability analysis of k-out-of-n: F balanced systems with multiple functional sectors

In this paper, new concepts of balanced systems are proposed based on real engineering problems. The system under study consists of l groups and each group has n functional sectors. The conception of balance difference is proposed for the first time. It is assumed that unbalanced systems are rebalanced by either forcing down some working units into standby or resuming some standby units into operation. In addition, a case that the forced-down units are subject to failure during standby is studied in this paper. Based on different balanced cases and system failure criteria, two reliability models for balanced systems are developed. The proposed systems have widespread applications in aerospace and military industries, such as wing systems of airplane and unmanned aerial vehicles with balanced engine systems. Markov process imbedding method is used to analyze the number of working units in each sector for each model. Finite Markov chain imbedding approach and universal generating function technique are used to obtain the system reliability for different models. Several case studies are finally presented to demonstrate the new models.     

被检测系统的可靠性和最优检测策略

研究被检测系统的一个模型,假定系统有4种运行状态(正常工作、异常工作、正常故障和异常故障)．系统故障时不需检测,系统工作时必须经过检测才能知道它是正常还是异常．系统开始工作后,每隔一段随机时间对它检测一次,直到系统故障或检测出系统处于异常状态为止．利用概率分析和随机模型的密度演化方法,导出了系统的一些新的可靠性指标和最优检测策略．     

Optimization of Stability Robustness Bounds for Linear Discrete-Time Systems

In this paper, existing stability robustness measures for the perturbation of both continuous-time and discrete-time systems are reviewed. Optimized robustness bounds for discrete-time systems are derived. These optimized bounds are obtained reducing the conservatism of existing bounds by (a) using the structural information on the perturbation and (b) changing the system coordinates via a properly chosen similarity transformation matrix. Numerical examples are used to illustrate the proposed reduced conservatism bounds.     

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In this paper we focus on the sequential k-out-of-n model with covariates. We assume that the lifetime distribution given covariates belongs to the exponential family, and deal with log-linear model of the scale parameter of the exponential distribution. The maximum likelihood estimators (MLEs) of the model parameters with order restrictions are derived and some properties of the MLEs are discussed, and we give the algorithm of MLES and the result of simulation.     

Global Solution of Optimization Problems with Parameter-Embedded Linear Dynamic Systems

This paper develops a theory for the global solution of nonconvex optimization problems with parameter-embedded linear dynamic systems. A quite general problem formulation is introduced and a solution is shown to exists. A convexity theory for integrals is then developed to construct convex relaxations for utilization in a branch-and-bound framework to calculate a global minimum. Interval analysis is employed to generate bounds on the state variables implied by the bounds on the embedded parameters. These bounds, along with basic integration theory, are used to prove convergence of the branch-and-bound algorithm to the global minimum of the optimization problem. The implementation of the algorithm is then considered and several numerical case studies are examined thoroughly     

Sequential Systems of Linear Equations Algorithm for Nonlinear Optimization Problems with General Constraints

In Ref. 1, a new superlinearly convergent algorithm of sequential systems of linear equations (SSLE) for nonlinear optimization problems with inequality constraints was proposed. At each iteration, this new algorithm only needs to solve four systems of linear equations having the same coefficient matrix, which is much less than the amount of computation required for existing SQP algorithms. Moreover, unlike the quadratic programming subproblems of the SQP algorithms (which may not have a solution), the subproblems of the SSLE algorithm are always solvable. In Ref. 2, it is shown that the new algorithm can also be used to deal with nonlinear optimization problems having both equality and inequality constraints, by solving an auxiliary problem. But the algorithm of Ref. 2 has to perform a pivoting operation to adjust the penalty parameter per iteration. In this paper, we improve the work of Ref. 2 and present a new algorithm of sequential systems of linear equations for general nonlinear optimization problems. This new algorithm preserves the advantages of the SSLE algorithms, while at the same time overcoming the aforementioned shortcomings. Some numerical results are also reported.     

自保护相依多部件系统的预防维修建模及策略优化

自保护技术作为自愈技术的一种,能够使系统在环境或工况条件变化的干扰下以较高可靠性运行。本文构建了一个新的具有相依主要部件和辅助部件的系统可靠性模型,其中主要部件的退化速率与工作中的辅助部件的数量有关。此外,基于定期检测和预防维修策略,本文利用半再生过程技术求解了系统的长期运行平均成本,并以长期运行平均成本最小化为目标给出了系统的最优预防维修策略。最后,以镗刀系统为例,利用所提方法给出了预防更换阈值和检测周期的最优值,以期望为实际维修行为决策提供理论参考。     

Bounds for an Optimization Problem with a Linear Programming Structure

The problem of estimating the value of a quadratic cost indexminimized with respect to a linear system constraint arisesin many design studies in control theory and regression analysis.In particular, the assessment of several choices of system inputscould lead to inefficient procedures based on the executionof an optimization routine for each input subset. To avoid suchpitfalls, a set of bounds on the optimal cost have been constructedusing information resident in a set of system moments. The momentsare easily calculated for systems in weighting function formand the bounds obtained from explicit formulae. The derivationof these bounds is presented in some detail using Hilbert spaceanalysis to obtain a canonical form, and randomized solutionsto give the subsequent bound formulae. A simple example is presentedto illustrate the results.