基于模糊故障树的军用气象物资包装可靠性分析

应用模糊故障树分析方法对军用气象物资包装可靠性进行了系统分析,简要介绍了模糊故障树分析方法的基本理论,利用专家判断和模糊集理论相结合的方法,评估了故障树底事件发生的模糊失效概率。并以"TFS-1通风干湿表包装"为例,建立了包装系统的故障树,采用下行法求解了引起顶事件发生的最小割集,定量分析计算,得出模糊失效率为0.0705,同时计算了各底事件的重要度。模糊故障树分析方法对于提高军用气象物资包装防护能力,确保物资装备质量,具有非常重要的意义。     

Reliability Analysis of a conveyor system using hybrid data

The quantification of a fault tree is difficult without an exact probability value for all of the basic events of the tree. To overcome this difficulty in this paper, we propose a methodology which employs ‘hybrid data’ as a tool to analyse the fault tree. The proposed methodology estimates the failure probability of basic events using the statistical analysis of field recorded failures. Under these circumstances, where there is an absence of past failure records, the method follows a fuzzy set based theoretical evaluation based on the subjective judgement of experts for the failure interval. The proposed methodology has been applied to a conveyor system. The results of the analysis reveal the effectiveness of the proposed methodology and the instrumental role played by the experience of experts in providing reliability oriented information. Copyright © 2006 John Wiley & Sons, Ltd.     

Reliability modelling of repairable systems using Petri nets and fuzzy Lambda–Tau methodology

A methodology is developed which uses Petri nets instead of the fault tree methodology and solves for reliability indices utilising fuzzy Lambda–Tau method. Fuzzy set theory is used for representing the failure rate and repair time instead of the classical (crisp) set theory because fuzzy numbers allow expert opinions, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into the system model. Petri nets are used because unlike the fault tree methodology, the use of Petri nets allows efficient simultaneous generation of minimal cut and path sets.     

不同信息融合方法在结构损伤识别上的应用和分析

在工程结构的损伤探测领域,不同的信息融合方法和方式对结构的损伤敏感程度以及计算的复杂程度往往不同,而且适用条件也不同。为了解决以上问题,描述了基于结构损伤识别的功能信息融合模型,并在此基础之上采用了多种融合方法进行了数值仿真和分析。数值仿真结果表明,采用了信息融合技术的结构多损伤位置识别,可以产生比单一信息源更精确、更完全的估计和判决,而且不同的信息融合算法的应用往往取决于研究对象和实际条件的要求。     

药品智能包装的模糊灰色故障树分析

目的对某款药品智能包装从系统层面进行可靠性分析。方法首先,通过失效分析建立药品智能包装的故障树;其次,利用专家判断知识和模糊数学理论,得到故障树底事件和顶事件的三角形式模糊失效率,以及采用模糊中值法进行底事件模糊重要度计算;最后,运用灰色关联分析求出表征各最小割集与顶事件相关行为关系的灰色关联度。结果定量分析计算显示,药品智能包装模糊失效率为(0.146 59,0.179 69,0.206 91),故障相关性最大的为包装材料本身的功能失效,其次为外界的振动和冲击以及包装尺寸误差等。结论模糊灰色关联故障树同时考虑包装系统的模糊性和灰色性,它可为预防药品智能包装失效、提高智能包装可靠性和安全性提供理论依据。     

基于T-S模糊模型的主动悬架滑模容错控制器设计

针对主动悬架系统的质量参数不确定性以及作动器出现的随机故障对车辆行驶平顺性和控制稳定性带来的重要影响,该文提出一种基于T-S模糊模型的主动悬架滑模容错控制器设计方法。为了描述悬架参数不确定性,基于T-S模糊模型建立1/4车辆的非线性模型,利用故障调节因子表示作动器故障的大小,进而获得考虑悬架系统质量不确定性和作动器故障的车辆主动悬架控制模型。接着,将滑模控制与自适应理论结合,设计合适的滑模面函数和滑模容错控制律,以达到故障悬架系统的容错控制目的;并基于Lyapunov稳定性理论,对所提出控制器稳定性和悬架系统安全约束性能进行了分析。最后,给出一个仿真算例,验证了所设计控制器的有效性和适用性。     

A dynamic fault tree

The fault tree analysis is a widely used method for evaluation of systems reliability and nuclear power plants safety. This paper presents a new method, which represents extension of the classic fault tree with the time requirements. The dynamic fault tree offers a range of risk informed applications. The results show that application of dynamic fault tree may reduce the system unavailability, e.g. by the proper arrangement of outages of safety equipment. The findings suggest that dynamic fault tree is a useful tool to expand and upgrade the existing models and knowledge obtained from probabilistic safety assessment with additional and time dependent information to further reduce the plant risk.     

基于精确T-S模型的LON总线变结构控制系统

详细介绍了包括基于T-S模糊模型的变结构控制节点的整个LON总线系统的硬件组成与软件设计．整个系统由两层组成,上层PC计算机为操作人员提供了良好的人机界面,下层的智能节点完成基本控制．上位机以传送网络变量的形式发布命令信号．系统通过i．Lon1000实现了Internet上的计算机对本系统很容易地进行远程监控．在解决非线性问题上,采用了著名的T—S模糊系统模型,将成熟的线性系统理论与模糊理论有效地结合起来,并得到了稳定性证明．基于T-S模糊模型的变结构控制的引入。使系统具有很强的鲁捧性．通过实验研究,证明了该系统的有效性和可靠性．     

在役钢结构吊车梁剩余疲劳寿命的可靠寿命评估

从Miner累积损伤的定义出发,视累积损伤为随机过程,临界损伤为随机变量,基于疲劳动态可靠性理论,提出了在役钢结构吊车梁疲劳剩余寿命的可靠寿命评估方法。之后与现行《钢结构检测评定与加固技术规程》(YB9257-96)中安全期限寿命评估方法进行了分析比较,说明了安全寿命评估方法的概率意义。最后通过算例分析结果表明,提出的可靠寿命评估方法更加合理。     

基于深度置信网络与信息融合的齿轮故障诊断方法

针对齿轮在复杂运行工况下故障特征提取困难,传统故障诊断方法的识别精度易受人工提取特征的影响,以及单传感器获取信息不全面等问题,提出基于深度置信网络(DBN)与信息融合的齿轮故障诊断方法。通过多传感器信息融合技术对每个传感器采集的振动信号进行数据层融合;利用DBN进行自适应特征提取从而实现故障分类。为了避免因人为选择DBN结构参数,导致模型识别精度下降的问题,利用改进的混合蛙跳算法(ISFLA)对DBN结构参数进行优化。试验表明,与BP神经网络、未经优化的DBN以及单传感器故障诊断相比,该研究提出的信息融合及优化方法具有更高的故障识别精度。     

Improved accuracy in quantitative fault tree analysis

The fault tree diagram defines the causes of the system failure mode or ‘top event’ in terms of the component failures and human errors, represented by basic events. By providing information which enables the basic event probability to be calculated, the fault tree can then be quantified to yield reliability parameters for the system. Fault tree quantification enables the probability of the top event to be calculated and in addition its failure rate and expected number of occurrences. Importance measures which signify the contribution each basic event makes to system failure can also be determined. Owing to the large number of failure combinations (minimal cut sets) which generally result from a fault tree study, it is not possible using conventional techniques to calculate these parameters exactly and approximations are required. The approximations usually rely on the basic events having a small likelihood of occurrence. When this condition is not met, it can result in large inaccuracies. These problems can be overcome by employing the binary decision diagram (BDD) approach. This method converts the fault tree diagram into a format which encodes Shannon's decomposition and allows the exact failure probability to be determined in a very efficient calculation procedure. This paper describes how the BDD method can be employed in fault tree quantification. © 1997 John Wiley & Sons, Ltd.     

A global procedure for the time-dependent reliability assessment of crane structural members

This paper aims at developing a probabilistic fatigue assessment procedure for crane structural members, using a structural reliability method, namely the stress–strength interference method. A crane member strength law is found by fitting fatigue life distribution parameters using finite element results and experimental data. The stress model is developed by using on-site data to determine probabilistic parametric distributions defining crane member loading. The efficiency of the proposed stress–strength interference method for tower crane member reliability assessment in fatigue is demonstrated on a jib chord member connection.     

Mission Reliability Assessment of Space TT&C System by Discrete Event System Simulation

Based on the analysis of system characteristics and mission process, space tracking, telemetry and command (TT&C) system can be viewed as a phased‐mission system (PMS). A general methodology using discrete event system simulation is proposed to quantitatively assess mission reliability of space TT&C system, because the traditional method is difficult to solve such complex problem. By dividing the time sequence of TT&C mission profile into several phases, the fault tree model of PMS is built to represent the system logical structure in each phase. In order to efficiently build simulation models, unified modeling language static class diagram is used to describe simulation model architecture. Extensible markup language is adopted to represent the mission reliability model in standard format for simulation input. By randomly generating the failure and repair events of the system components, the changes of the system state are simulated. The logic structure function of fault tree and observation data of the system state change jointly determines the mission reliability. A case study is given to illustrate the approach and validate its effectiveness. Copyright © 2013 John Wiley & Sons, Ltd.     

Fault trees analysis using expert opinion based on fuzzy‐bathtub failure rates

The main objective of fault tree analysis method is to estimate the “Top Event occurrence probability”. This requires determination of failure time distribution functions also known as “Bathtub Curves” for each of the system elements/events. This paper introduces a novel method to determine the failure time distribution functions using possibility theory. For this purpose, fuzzy‐bathtub distributions using expert opinions are generated for basic events and fuzzy formulas are derived for static and dynamic gates fault tree constructions. This process completed by proposed fuzzy Monte Carlo simulation throughout the preferred operational time and uses the actual time‐to‐failure data. Accordingly, the Top Event failure curve and the reliability profile of the system are depicted based on the defuzzificated basic‐events' bathtub‐failure‐rates. The results show that the proposed method not only is feasible and powerful but can also be accurate more than the other probabilistic and possibilistic techniques because of the component failure rates follow the real failure distributions.     

Posbist fault tree analysis of coherent systems

When the failure probability of a system is extremely small or necessary statistical data from the system is scarce, it is very difficult or impossible to evaluate its reliability and safety with conventional fault tree analysis (FTA) techniques. New techniques are needed to predict and diagnose such a system's failures and evaluate its reliability and safety. In this paper, we first provide a concise overview of FTA. Then, based on the posbist reliability theory, event failure behavior is characterized in the context of possibility measures and the structure function of the posbist fault tree of a coherent system is defined. In addition, we define the AND operator and the OR operator based on the minimal cut of a posbist fault tree. Finally, a model of posbist fault tree analysis (posbist FTA) of coherent systems is presented. The use of the model for quantitative analysis is demonstrated with a real-life safety system.     

Hybrid fault tree analysis using fuzzy sets

In conventional fault tree analysis (FTA), the ambiguous and imprecise events such as human errors tend not to be handled effectively. To overcome this disadvantage, a hybrid approach employing fuzzy set evaluation and probabilistic estimation for FTA is proposed to evaluate abnormal events. The safety problem of unexpected robot motion in an aircraft wing drilling system was analyzed using the proposed method. The results indicated that the proposed approach is very effective in analyzing the reliability of a man-machine system.     

Production reliability in flexible manufacturing systems

A typical flexible manufacturing system, Westland Helicopters' sheet metal detail manufacturing complex, has been analysed for reliability. The techniques of fault tree analysis and event tree analysis are presented and their applicability to this study investigated. Event tree analysis has been found to be a more effective method for analysing manufacturing systems. The failure states of the system have been identified from the construction of an event tree which considers random hardware faults that influence production. Failure rate data have been used to quantify the critical production failure states in terms of machine failures. Estimates are made of the system's MTTF and percentage availability using typical MTTR figures. The probability that a selected production route fails to complete the manufacture of a set of parts is also evaluated. A dependency of systems reliability on the production demand has been discovered, and a possible method for modelling and assessing the reliability of systems capable of producing several products is proposed.     

基于证据理论的结构损伤识别研究

基于多源损伤信息可以有效解决由多种不确定性所导致的损伤误判问题。将证据理论作为理论基础，研究基于多源信息的损伤识别方法。为了充分体现不同证据在重要性、可靠性方面的差异，在考虑实际损伤识别过程的基础上，提出了基于先验和后验可靠性联合校正的证据合成方法。损伤识别试验研究表明，所提出的证据合成方法优于经典的D—S合成法则；相对于传统的基于单一损伤信息的损伤识别而言，基于多源损伤信息能够有效降低损伤误判的可能性，获得准确性、鲁棒性更好的损伤识别结果。     

Dynamic reliability and risk assessment of the accident localization system of the Ignalina NPP RBMK-1500 reactor

The paper presents reliability and risk analysis of the RBMK-1500 reactor accident localization system (ALS) (confinement), which prevents radioactive releases to the environment. Reliability of the system was estimated and compared by two methods: the conventional fault tree method and an innovative dynamic reliability model, based on stochastic differential equations. Frequency of radioactive release through ALS was also estimated. The results of the study indicate that conventional fault tree modeling techniques in this case apply high degree of conservatism in the system reliability estimates.One of the purposes of the ALS reliability study was to demonstrate advantages of the dynamic reliability analysis against the conventional fault/event tree methods. The Markovian framework to deal with dynamic aspects of system behavior is presented. Although not analyzed in detail, the framework is also capable of accounting for non-constant component failure rates. Computational methods are proposed to solve stochastic differential equations, including analytical solution, which is possible only for relatively small and simple systems. Other numerical methods, like Monte Carlo and numerical schemes of differential equations are analyzed and compared. The study is finalized with concluding remarks regarding both the studied system reliability and computational methods used.     

机械设备故障诊断模糊、概率Petri网

根据故障诊断的特点,将概率信息引入模糊Ｐｅｔｒｉ网,提出了模糊,概率Ｐｅｔｒｉ网模型,简称模糊概率网。研究基于模糊概率网模型进行故障诊断的方法,利用概率信息处理反向推理中冲突消解问题,提高了诊断效率;利用模糊信息计算诊断结果的可信度;提出了一种反向推理机制,给出了算法。最后,以机械手掉刀为例,对该诊断方法进行了说明。