基于期望效益的随机检修系统决策模型研究

本文研究了一类带检修退化可修系统的维修策略问题,为提高系统的安全性和可靠性,在系统故障前增加了随机检修,并在此种情况下对维修模型进行了研究。在假定系统检修"修复如旧"、系统逐次故障后的维修时间构成随机递增的几何过程和系统逐次故障后的工作时间构成随机递增的几何过程的情况下,选择系统的故障次数N为更换策略,利用单调的几何过程,求出了系统经长期运行单位时间内的期望效益的表达式.最后通过数值例子对所得结果进行了分析。     

k/n结构变化的多阶段任务系统维修保障能力评估建模

任务成功性评估是维修保障的关键因素,k/n结构是装备或武器系统中常用的冗余结构系统.考虑装备中外场可更换部件为k/n系统,且k/n结构随阶段任务动态变化,建立了装备多阶段任务系统的任务成功概率评估模型,通过示例表明了模型的正确性.     

一种多目标机系统监视方法

对于嵌入式系统的外部开发人员来说，通常使用的交叉调试工具只能对一段程序或代码进行调试，而对整体系统的运行行为和运行逻辑无法了解，因此对一些系统级行为和逻辑错误的定位和调试变的非常困难。针对这一问题，本文设计了一种针对嵌入式系统的多目标机系统监视方法。该方法通过在嵌入式操作系统中插入记录事件的桩程序，在监视系统运行过程中将各事件发生时间及参数记录下来，并将记录的监视数据发送到宿主机端，由宿主机端的软件解析这些数据，并以图形化的方式展示出来，直观地重现嵌入式操作系统的运行行为和运行逻辑。     

计及电力系统运行风险的电价管理新策略

针对传统电价管理方法的不足,提出了一种计及电力系统短期运行风险的电价管理新策略.该方法在电力系统运行风险评估的基础上对实时电价进行调节,能够以电价为信号刺激用户采取合理的用电结构和方式,从而增强系统运行可靠性.方法只是弥补了传统方法不能考虑系统可靠性的不足,而不是颠覆传统的电价管理方法,所以二者之间具有很好的衔接性.通过对IEEE-RTS可靠性测试系统的计算分析验证了所提算法的有效性.     

600MW火电机组静电除尘系统高压短路原因分析及对策

本文通过对红海湾发电厂#1,#2机组从168试运行至今半年时间内除尘系统的运行状况和常见故障进行分析,找出当前影响红海湾发电厂#1、#2机组除尘系统正常运行的主要原因:高压电路短路故障,并提出相应得对策:调整灰气亮相数比;增加灰斗气化风装置;合理调整输灰循环时间;调整电磁振打器振打高度;加大灰库乏气处理能力;提高仓泵排气阀安装标高;对高灰分煤种进行参烧;更换电极振打传动轴轴封,修复保温箱密封,增加电场本体顶部防雨设施等,以达到机组除尘系统正常运行,满足环保要求的目的。     

具有多阶段任务需求的温备份系统可靠性分析

实际工程中很多系统的任务都具有多个阶段,且不同阶段的外界环境及系统需求均可能发生变化,而工作元件可在任意阶段发生失效,为系统的可靠性分析与建模带来了挑战。为增加系统的可靠性,一种常用的设计方法是配置备份元件。针对多阶段任务下基于需求的温备份系统可靠性建模问题,首先提出了一种基于多值决策图的方法,其次给出了处于不同状态的元件可靠性计算公式,最后通过算例表明该模型适用于具有多阶段任务需求的温备份系统可靠性分析。     

计及电力系统运行风险的电价管理新策略

针对传统电价管理方法的不足,提出了一种计及电力系统短期运行风险的电价管理新策略。该方法在电力系统运行风险评估的基础上对实时电价进行调节,能够以电价为信号刺激用户采取合理的用电结构和方式,从而增强系统运行可靠性。方法只是弥补了传统方法不能考虑系统可靠性的不足,而不是颠覆传统的电价管理方法,所以二者之间具有很好的衔接性。通过对IEEE-RTS可靠性测试系统的计算分析验证了所提算法的有效性。     

高层公共建筑给水系统可靠性管理研究

通过分析高层建筑内给水系统可靠性,运用数学方法对给水方式进行选择,比较不同因素下不同给水方式的可靠性;探讨系统中水源、贮水池、水箱、水泵、管道布置、阀门、喷头、消火栓等组件布置对系统可靠性的影响,分析给水系统超压的原因,给出相应的解决措施,从设计、技术和管理角度提高其可靠性,减少系统工作的故障率。     

线路标准施工在飞机维修中的应用

机务维修手册的正确使用对民航安全起到至关重要的作用。飞机的线路故障问题主要通过WDM与SWPM两本手册进行指导维修。线路标准施工在近年来越发引起机务维修人员的重视。文章以波音飞机连接器插钉更换为例,介绍了WDM与SWPM手册的查询方法。     

计算机仿真技术在煤矿企业的应用

系统仿真,就是通过建立和运行系统的计算机仿真模型,来模仿实际系统的运行状态及其随时间变化的规律,以实现在计算机上对实际系统的结构和行为进行动态实验的全过程。本文是以某矿煤仓容积的实际资料计算为例,对计算机仿真技术在煤矿企业的应用进行了模拟实验。     

某大型装置现场可靠性的贝叶斯分析

可靠性、维修性和可用性是描述复杂装置质量属性的三个重要指标。在某大型装置的现场故障和维修数据的经验分析基础上,运用分段线性模型确定了装置可靠性改进趋势。针对装置现场故障和维修数据的小样本问题,给出了装置现场可靠性和维修性的贝叶斯模型,并用WinBUGS软件对其进行了求解计算。继而分析给出了装置可用性最恰当描述——任务可用度的闭合表达形式。最后,通过与极大似然法进行对比,发现应用贝叶斯方法分析该大型装置现场可靠性更有效。     

多层次激励系统可靠性的敏感分析

多层次激励系统的可靠性由各子系统的可靠性及它们之间的相互关系决定。激励系统可靠性灵敏度是测量激励系统可靠性对激励层次有效概率变化的反应程度。数学模型显示,激励的层次和路径依赖度是影响激励系统可靠性的关键因素。企业可以通过将激励资源优化配置给能带来最大增量效应的对象和改善上下级依赖关系2种方法来提高激励系统可靠性。     

物流系统的可靠度及其优化研究

物流系统是一个由众多物流单元组成的大系统,它的可靠性程度对企业和社会的平稳运行有着重大的影响.本文在建立物流单元的可靠度及其度量方法基础上,研究了物流系统逻辑组成结构对系统可靠度的影响,并探讨了在有物流能力和可靠度约束的情况下,如何优化物流系统逻辑结构和物流成本的方法.     

Reliability analysis of man–machine systems using fuzzy cognitive mapping with genetic tuning

This article offers a method for analyzing the reliability of a man–machine system (MMS) and ranking of influencing factors based on a fuzzy cognitive map (FCM). The ranking of influencing factors is analogous to the ranking of system elements the probabilistic theory of reliability. To approximate the dependence of “influencing factors—reliability,” the relationship of variable increments is used, which ensures the sensitivity of the reliability level to variations in the levels of influencing factors. The novelty of the method lies in the fact that the expert values of the weights of the FCM graph edges (arcs) are adjusted based on the results of observations using a genetic algorithm. The algorithm's chromosomes are generated from the intervals of acceptable values of edge weights, and the selection criterion is the sum of squares of deviations of the reliability simulation results from observations. The method is illustrated by the example of a multifactor analysis of the reliability of the “driver–car–road” system. It is shown that the FCM adjustment reduces the discrepancy between the reliability forecast and observations almost in half. Possible applications of the method can be complex systems with vaguely defined structures whose reliability depends very much on interrelated factors measured expertly.     

Reliability Analysis Based on the Losses from Failures

The conventional reliability analysis is based on the premise that increasing the reliability of a system will decrease the losses from failures. On the basis of counterexamples, it is demonstrated that this is valid only if all failures are associated with the same losses. In case of failures associated with different losses, a system with larger reliability is not necessarily characterized by smaller losses from failures. Consequently, a theoretical framework and models are proposed for a reliability analysis, linking reliability and the losses from failures. Equations related to the distributions of the potential losses from failure have been derived. It is argued that the classical risk equation only estimates the average value of the potential losses from failure and does not provide insight into the variability associated with the potential losses. Equations have also been derived for determining the potential and the expected losses from failures for nonrepairable and repairable systems with components arranged in series, with arbitrary life distributions. The equations are also valid for systems/components with multiple mutually exclusive failure modes. The expected losses given failure is a linear combination of the expected losses from failure associated with the separate failure modes scaled by the conditional probabilities with which the failure modes initiate failure. On this basis, an efficient method for simplifying complex reliability block diagrams has been developed. Branches of components arranged in series whose failures are mutually exclusive can be reduced to single components with equivalent hazard rate, downtime, and expected costs associated with intervention and repair. A model for estimating the expected losses from early-life failures has also been developed. For a specified time interval, the expected losses from early-life failures are a sum of the products of the expected number of failures in the specified time intervals covering the early-life failures region and the expected losses given failure characterizing the corresponding time intervals. For complex systems whose components are not logically arranged in series, discrete simulation algorithms and software have been created for determining the losses from failures in terms of expected lost production time, cost of intervention, and cost of replacement. Different system topologies are assessed to determine the effect of modifications of the system topology on the expected losses from failures. It is argued that the reliability allocation in a production system should be done to maximize the profit/value associated with the system. Consequently, a method for setting reliability requirements and reliability allocation maximizing the profit by minimizing the total cost has been developed. Reliability allocation that maximizes the profit in case of a system consisting of blocks arranged in series is achieved by determining for each block individually the reliabilities of the components in the block that minimize the sum of the capital, operation costs, and the expected losses from failures. A Monte Carlo simulation based net present value (NPV) cash-flow model has also been proposed, which has significant advantages to cash-flow models based on the expected value of the losses from failures per time interval. Unlike these models, the proposed model has the capability to reveal the variation of the NPV due to different number of failures occurring during a specified time interval (e.g., during one year). The model also permits tracking the impact of the distribution pattern of failure occurrences and the time dependence of the losses from failures.     

基于失效情景的应急设施选址评估指标体系与模型

突发事件具有巨大的破坏性、不确定性,应急设施有可能失效,本文研究基于失效情景的应急设施选址评估指标体系与评估模型。首先基于定义的失效情景研究应急设施选址评估指标。构建全局性、可靠性、时效性、均衡性、经济性评估指标。可靠性作为重要评估指标有助于提高应急设施对需求区域的物资保障程度,保证系统的稳定性,采用多重覆盖率刻画。然后,设计具有不同侧重评估目标的一般情景评估指标体系、设施失效情景评估指标体系以及多区域情景评估指标体系。最后,由于应急设施选址评估具有多影响因素特征,涉及输入和输出多个指标的测度,选取处理多输入\多输出问题具有优势的评估方法—数据包络法,对应急设施选址的合理性进行评估。实例验证评估指标体系的实用性和有效性。     

Task Analysis for Industrial Work Process from Aspects of Human Reliability and System Safety

In the design, development, and manufacturing stage of industrial products, engineers usually focus on the problems caused by hardware or software, but pay less attention to problems caused by human error, which may significantly affect system reliability and safety. Although operating procedures are strictly followed, human error still may occur occasionally. Among the influencing factors, the inappropriate design of standard operation procedure (SOP) or standard assembly procedure (SAP) is an important and latent reason for unexpected results found during human operation. To reduce the error probability and error effects of these unexpected behaviors in the industrial work process, overall evaluation of SOP or SAP quality has become an essential task. The human error criticality analysis (HECA) method was developed to identify the potentially critical problems caused by human error in the human operation system. This method performs task analysis on the basis of operation procedure. For example, SOP, analyzes the human error probability (HEP) for each human operation step, and assesses its error effects to the whole system. The results of the analysis will show the interrelationship that exists between critical human tasks, critical human error modes, and human reliability information of the human operation system. To identify the robustness of the model, a case study of initiator assembly tasks was conducted. Results show that the HECA method is practicable in evaluating the operation procedure, and the information is valuable in identifying the means to upgrade human reliability and system safety for human tasks.     

Penalty guided genetic search for redundancy optimization in multi-state series-parallel power system

This paper presents a genetic algorithm (GA) for parallel redundancy optimization in series-parallel power systems exhibiting multi-state behavior, optimizing the reliability subject to constraints. The components are binary and chosen from a list of products available in the market, and are being characterized by their feeding capacity, reliability, cost and weight. System reliability is defined as the ability to satisfy consumer demand and is presented as a piecewise cumulative load curve. In GA, to handle infeasible solutions penalty strategies are used. Penalty technique keep a certain amount of infeasible solutions in each generation so as to enforce genetic search towards an optimal solution from sides of, both, feasible and infeasible regions. We here present a dynamic adaptive penalty function which helps the algorithm to search efficiently for optimal/near optimal solution. To evaluate system reliability, a fast procedure, based on universal generating function, is used. An example considering a multi-state series-parallel power system is solved considering both homogeneous and heterogeneous types of redundancy. Also an example considering price discounts is solved. The effectiveness of the penalty function and the proposed algorithm is studied and shown graphically.     

Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature

The concept of survival signature has recently been introduced as an alternative to the signature for reliability quantification of systems. While these two concepts are closely related for systems consisting of a single type of component, the survival signature is also suitable for systems with multiple types of component, which is not the case for the signature. This also enables the use of the survival signature for reliability of networks. In this article, we present the use of the survival signature for reliability quantification of systems and networks from a Bayesian perspective. We assume that data are available on tested components that are exchangeable with those in the actual system or network of interest. These data consist of failure times and possibly right‐censoring times. We present both a nonparametric and parametric approach.