多信号模型故障模式与信号概率关联算法

为适应复杂装备的测试性建模,多信号模型采用层次化的建模方式.针对建模过程中信号概率和故障模式(功能故障和完全故障)概率的冲突问题,提出了三种概率关联更新算法,并通过某装备模块多信号模型的故障模式及信号概率的更新验证了算法的有效性.算法提高了测试性分析与评估的精度,为模型的修正和故障诊断策略的生成提供了更加可靠的依据.     

模糊支撑半径变量贝叶斯网络多态系统故障概率分析

针对现有隶属函数描述系统及部件故障状态的不足,构建了一种含模糊支撑半径变量的隶属函数来描述部件故障状态,提出了一种基于模糊支撑半径变量的贝叶斯网络多态系统故障概率计算方法。在隶属函数的构造中,用变量代替精确值描述隶属函数模糊支撑半径,建立了含模糊支撑半径变量的隶属函数;并将其引入贝叶斯网络,利用桶消元法对多态系统叶节点故障概率进行分析,得到叶节点故障概率变化曲线。将所提出的方法与文献中基于模糊支撑半径为定值的隶属函数贝叶斯网络方法相比较,验证了方法的有效性。最后,将该方法应用到数控机床主轴系统故障分析实例中,对叶节点故障概率进行计算。结果表明,该方法能够有效解决多态系统故障状态隶属函数选择中的主观性问题。     

测试性建模中故障模式概率更新算法研究

为适应复杂装备全寿命周期内的测试性分析与评估,测试性建模中多采用层次化的建模方式．针对建模过程中信号(功能)概率和故障模式概率的冲突问题,提出了两种故障模式概率更新算法,并通过某装备模块的故障模式概率的更新验证了算法的有效性．提高了测试性分析与评估的精度,为模型的修正和故障诊断策略的生成提供了更加可靠的依据．     

基于HMM的多态系统状态识别模型研究

在分析装备三级工作模式基础上,建立了多态系统的可靠性向量模型,基于隐马尔可夫模型(HMM)原理分析了多态系统的状态转移过程,并建立了多状态系统HMM模型,在此基础上利用MATLAB对系统隐藏状态转移和观察状态之间的关系进行了仿真.仿真结果表明,在一定观察序列的情况下,该模型可以实现较高的状态识别率和状态预测精度,为科学合理地诊断多状态系统的潜在故障提供了技术支持,具有重要的理论意义和应用价值.     

基于贝叶斯网络的组合服务信任度评估方法

对组合服务信任度评估问题进行了研究。基于信任的不确定性和模糊性,给出了信任度的离散化表示方法;借助于贝叶斯网络的强大的推理能力,给出了组合服务的贝叶斯网络模型以及组合服务模型到贝叶斯网络的转换规则,利用贝叶斯网络的正向推理机制设计了基于贝叶斯网络模型的组合服务信任度评估方法。通过一个组合服务的买例,说明了组合服务的贝叶斯网络模型及其基于贝叶斯网络的组合服务信任度评估方法的使用方法。该评估方法基于信任的模糊性和不确定性,更符合信任的本质并易于实现。     

浅谈提高舰船导航电子装备可靠性的对策

随着舰船装备系统性能越来越好,装备系统越来越复杂,由于大型装备系统具有零部件复杂和零部件较多的特点,想要使庞大的系统稳定运行,发挥最佳的性能,就需要保证电子装备的可靠性。本文首先介绍了造成舰船导航电子装备可靠性差的因素,其次分析了提高导航电子装备可靠性的对策,为我国舰船导航电子装备可靠性的提升尽一份力。     

基于贝叶斯网络的汽轮机组轴承工频振动诊断

将贝叶斯网络方法用于汽轮机组轴承振动诊断。根据现场诊断经验,建立了轴承工频振动诊断的质朴型贝叶斯网络,网络中融合了振动频谱、相位和运行工况等诊断信息;提出了网络推理计算方法,并在LabVIEW软件平台上实现。诊断结果的准确性在多个实际案例中得到证实,表明本文的诊断方法能有效地识别轴承振动的单一故障和复合故障。     

基于贝叶斯网络的汽车故障诊断分析研究

贝叶斯（Bayes）网络是基于概率推理的图形化网络、数学模型,针对汽车故障的特点及类型,提出采用贝叶斯（Bayes）网络作为汽车故障诊断分析方法,为汽车故障提供准确和可靠的决策依据。     

基于支持向量回归的装备可靠性评估新方法

针对经典的装备可靠性评估方法在小样本情况下难以得到满意的评估结果的问题,提出了一种综合运用支持向量回归(SVR)算法和自适应重要抽样(AIS)算法进行评估的新方法.该方法通过分析小样本条件下装备可靠性评估原理,建立基于SVR和AIS的装备可靠性评估模型,分析小样本条件下开展装备可靠性评估的过程,给出相应的统一建模语言(...     

基于贝叶斯网络的自由场地震液化沉降评估

基于贝叶斯网络方法,综合考虑地震参数、土体参数和场地条件等12个影响因素,结合场地的液化势和液化潜能指数,建立了地震液化沉降的贝叶斯网络评估模型。通过算例分析,与径向基神经网络方法和IY简化计算方法的评估性能对比,发现地震液化沉降的贝叶斯网络评估模型的优势明显;该模型不仅有较好的评估精度和可靠性,而且还可以进行逆向因果推理。对两个机器学习模型进行敏感因素分析发现,在12个影响因素中,地表峰值加速度、地震持续时间和标准贯入锤击数为较敏感因素,和IY简化算法考虑的参数基本一致。     

Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks

In this paper, we present Radyban (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained.     

Reliability and risk analysis of large systems with ageing components

Applications of limit reliability functions to the reliability evaluation of large multi-state systems composed of independent components are considered. The main emphasis is on multi-state systems with ageing components because of the importance of such an approach in safety analysis, assessment and prediction, and analysing the effectiveness of operation processes of real technical systems. The results concerned with multi-state series systems are applied to the reliability evaluation and risk function determination of a homogeneous bus transportation system. Results on limit reliability functions of a homogeneous multi-state “m out of n” system are applied to durability evaluation of a steel rope. A non-homogeneous series-parallel pipeline systems composed of several lines of pipe segments is estimated as well. Moreover, the reliability evaluation of the model homogeneous parallel-series electrical energy distribution system is performed.     

New insights on multi-state component criticality and importance

In this paper, new importance measures for multi-state systems with multi-state components are introduced and evaluated. These new measures complement and enhance current work done in the area of multi-state reliability. In general, importance measures are used to evaluate and rank the criticality of component or component states with respect to system reliability. The focus of the study is to provide intuitive and clear importance measures that can be used to enhance system reliability from two perspectives: (1) how a specific component affects multi-state system reliability and (2) how a particular component state or set of states affects multi-state system reliability. The first measure unsatisfied demand index, provides insight regarding a component or component state contribution to unsatisfied demand. The second measure multi-state failure frequency index, elaborates on an approach that quantifies the contribution of a particular component or component state to system failure. Finally, the multi-state redundancy importance identifies where to allocate component redundancy as to improve system reliability. The findings of this study indicate that both perspectives can be used to complement each other and as an effective tool to assess component criticality. Examples illustrate and compare the proposed measures with previous multi-state importance measures.     

Optimal allocation of elements in a linear multi-state sliding window system

This paper proposes a new model that generalizes the consecutive k-out-of-r-from-n:F system to multi-state case. In this model (named linear multi-state sliding window system) the system consists of n linearly ordered multi-state elements. Each element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The system fails if the sum of the performance rates of any r consecutive elements is lower than a demand W.An algorithm is suggested that finds the order of elements with different characteristics within linear multi-state sliding window system, which provides the greatest possible system reliability. The algorithm is based on using a universal generating function technique for system reliability evaluation. A genetic algorithm is used as the optimization tool. Illustrative examples are presented.     

A fully Bayesian approach for combining multi-level information in multi-state fault tree quantification

This paper presents a fully Bayesian approach that simultaneously combines non-overlapping (in time) basic event and higher-level event failure data in fault tree quantification with multi-state events. Such higher-level data often correspond to train, subsystem or system failure events. The fully Bayesian approach also automatically propagates the highest-level data to lower levels in the fault tree. A simple example illustrates our approach.     

Extended block diagram method for a multi-state system reliability assessment

The presented method extends the classical reliability block diagram method to a repairable multi-state system. It is very suitable for engineering applications since the procedure is well formalized and based on the natural decomposition of the entire multi-state system (the system is represented as a collection of its elements). Until now, the classical block diagram method did not provide the reliability assessment for the repairable multi-state system. The straightforward stochastic process methods are very difficult for engineering application in such cases due to the “dimension damnation”—huge number of system states. The suggested method is based on the combined random processes and the universal generating function technique and drastically reduces the number of states in the multi-state model.     

Consecutive sliding window systems

This paper proposes a new model that generalizes the linear multi-state sliding window system to the case of m consecutive overlapping windows. In this model the system consists of n linearly ordered multi-state elements. Each element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The system fails if in each of at least m consecutive overlapping groups of r consecutive elements (windows) the sum of the performance rates of elements belonging to the group is lower than a minimum allowable level. An algorithm for system reliability evaluation is suggested which is based on an extended universal moment generating function. Examples of evaluating system reliability and elements' reliability importance indices are presented.     

Multi-state systems with multi-fault coverage

The paper introduces a new model of fault level coverage for multi-state systems in which the effectiveness of recovery mechanisms depends on the coexistence of multiple faults in related elements. Examples of this effect can be found in computing systems, electrical power distribution networks, pipelines carrying dangerous materials, etc. For evaluating reliability and performance indices of multi-state systems with imperfect multi-fault coverage, a modification of the generalized reliability block diagram (RBD) method is suggested. This method, based on a universal generating function technique, allows performance distribution of complex multi-state series–parallel system with multi-fault coverage to be obtained using a straightforward recursive procedure. Illustrative examples are presented.     

Redundancy analysis for repairable multi-state system by using combined stochastic processes methods and universal generating function technique

This paper discusses a type of redundancy that is typical in a multi-state system. It considers two interconnected multi-state systems where one multi-state system can satisfy its own stochastic demand and also can provide abundant resource (performance) to another system in order to improve the assisted system reliability. Traditional methods are usually not effective enough for reliability analysis for such multi-state systems because of the “dimensional curse” problem. This paper presents a new method for reliability evaluation for the repairable multi-state system considering such kind of redundancy. The proposed method is based on the combination of the universal generating function technique and random processes methods. The numerical example is presented to illustrate the proposed method.     

A study on quantitative analysis of human reliability with inspection

This paper is concerned with determining human reliability with inspection. The two-state models of operation-inspection sequence with certain dependence relations are shown where all working units are supposed to have two states: success or failure. Moreover, the multi-state models of operation-inspection are presented on the assumption that operation unit is of multi-state and each inspection unit is in two states.