基于模糊故障树的动车组塞拉门系统可靠性分析

塞拉门系统作为动车组的重要组成部分,在动车组的运营过程中,其可靠性的高低直接关系到列车运营的安全性。通过对CHR5型动车组塞拉门系统历史故障数据统计及分析的基础上,将模糊数学理论与故障树方法相结合,对塞拉门系统可靠性进行分析。首先建立了以塞拉门发生故障为顶事件的模糊故障树;然后采用定量分析法,得到了顶事件的故障概率;最后对故障树各个底事件进行重要度分析,得到会影响塞拉门系统的薄弱环节。该分析结果为动车组安全可靠的运营提供了数据分析基础。     

基于贝叶斯网络的多态故障树分析方法

针对多态系统故障树分析的难点,通过一个多态雷达系统的实例给出了一种基于贝叶斯网络的多态故障树分析方法.首先根据多态故障树的结构建立贝叶斯网络的拓扑结构,然后根据多态逻辑算子对其进行定量化,进而利用贝叶斯网络分析多态故障树顶事件概率、部件重要度及其它结果.最后通过对实例的分析说明了基于贝叶斯网络的多态故障树分析方法有更强的建模分析能力.     

基于GSPN的实施延迟策略生产系统建模与性能分析

延迟策略是协调市场需求变化的绝对性和生产系统相对稳定性矛盾的一个重要战略手段。为分析实施延迟策略生产系统的性能,利用随机广义Petri-net(GSPN)的建模分析方法,并根据GSPN与马尔科夫链的同构关系,将GSPN模型转化成为等价的马尔科夫链模型。通过马尔科夫链及相关数学方法获得实施延迟策略生产系统的主要性能指标。该方法不仅可以分析实施延迟策略生产系统的整体性能,而且能够对系统的各个环节运作效率做出定量分析。最后,通过算例分析验证了该方法的科学性与有效性,丰富了延迟策略研究方面的方法理论。     

基于MCMC稳态模拟的指数回归模型及其应用

讨论了加速失效模型族中最简单而又十分重要的指数回归模型，利用贝叶斯方法提高了该模型的有效性。为了较好的解决高维数值积分在实际应用中的难题，提出了对寿命服从指数分布的产品，运用基于Gibbs抽样的马尔科夫链蒙特卡洛（Markov Chain Monte Carlo，MCMC）方法动态模拟出参数后验分布的马尔科夫链，在回归参数的先验分布为多元正态分布时，给出随机截尾条件下，回归参数在指数回归模型中的贝叶斯估计，提高了计算的精度。借助数据仿真分析说明了利用WinBUGS（Bayesian inference Using Gibbs Sampling）软件包进行建模分析的过程，证明了该模型在可靠性应用中的直观性与有效性。     

基于模糊故障树的高速列车电流互感器可靠性分析

针对目前高速列车差动保护系统所使用的直通式电流互感器的结构与运行方式,结合主要元件的故障模式和机理,构建故障树模型,采用下行法计算其最小割集为84个,利用专家评分法与梯度模糊数相结合的方法计算故障树各个底事件与中间事件的发生概率及其权重,进而计算出顶事件的失效概率,发现其可靠度较高,其中绕组故障对顶事件(电流互感器失效)的贡献度最高,通过与传统的模糊故障树分析法作比较,体现出了本文所提算法的优越性。可为高速列车电力牵引系统的可靠性量化分析与评估奠定基础,为动车组电流互感器的运营维护决策提供依据。     

基于动态数据驱动的改进灰色马尔科夫模型黄金价格预测

将黄金数据的尖峰厚尾、异方差性及杠杆效应等统计特征与马尔科夫概率转移矩阵所具有的动态变化规律结合,提出一种改进的灰色马尔科夫模型.模型首先对数据进行统计分析,建立相应的概率统计模型并用此模型对系统发展变化趋势进行拟合.在拟合序列的基础上利用马尔科夫链的动态转移变化建立状态转移概率矩阵,采用动态数据驱动原理对未来每一步数据进行动态预测.模型既是统计方法与数据动态驱动的结合,克服了传统的灰色马尔科夫模型中对数据内在统计规律的忽视,实证表明其预测精度较灰色马尔科夫模型预测高,具有较好的实用性.     

考虑多失效行为的平衡系统可靠性建模与计算

平衡系统的可靠性建模与相关指标计算是可靠性理论与工程领域的研究热点之一。针对由多部件构成的串联平衡系统,假设每个部件受环境冲击影响逐渐退化,呈现出多种状态;系统的性能平衡取决于部件的状态及其排列位置,即当系统中退化程度超过某一阈值的部件分布在某一特定区域时,系统失去性能平衡。考虑单部件失效导致系统失效和三类系统性能失衡导致系统失效四类失效行为,构建了考虑多失效行为的平衡系统可靠性模型。运用有限马尔可夫链嵌入法推导了部件的相关概率指标以及系统可靠度。最后以液压支架系统为例,验证了所提出模型与方法的有效性。     

基于故障树分析的堰塞湖溃坝概率估计方法

堰塞湖排险的一个关键问题是如何针对实施不同应对措施情况下的堰塞湖溃坝概率进行估计,这是一个值得关注的重要研究课题。本文提出了一种基于故障树分析(FTA)的堰塞湖溃坝概率估计方法。首先,通过堰塞湖排险问题的实际背景分析,基于FTA构建了堰塞湖溃坝故障树的基本架构;然后,通过相关领域知识、历史案例分析、专家主观判断和多位专家主观判断信息的融合,可以确定实施某一应对措施情形下故障树中各基本事件在不同时段内发生的概率;进一步地,依据构建的故障树和基本事件发生的概率,给出了在不同时段内堰塞湖溃坝事件发生的概率的估计方法。最后,通过一个实例分析说明了本文所提出方法的可行性与有效性。     

基于模糊故障树的动车组空调系统性能可靠性

空调系统是动车组上的车载设备之一,其可靠性程度直接关系到乘客的生命安全。本文在对CRH5型动车组空调系统的故障数据统计与分析的基础上,结合模糊数学理论以及故障树方法,对空调系统可靠性进行了分析。首先建立空调系统的模糊故障树,以定量分析的方法进行分析计算,可得系统的故障概率区间,然后计算了28个底事件的重要度,得到影响空调系统的薄弱环节,最后通过对比分析,证明该方法的有效性,为动车组空调系统的故障预测和诊断提供参考。     

基于无故障概率的多参数多工序工艺系统可靠性评估模型与方法

通过对工艺要素、工艺过程、工艺输出参数、性能参数和产品可靠性等的影响分析,建立了多参数多工序工艺系统可靠性影响关系模型;基于制造质量和生产效率两个维度,提出了多参数工艺系统故障判据与工作能力状态准则;分串联、并联和混联三种模式,建立了多工序工艺系统可靠性逻辑框图;考虑设置检验和不设置检验两种状态,研究了基于无故障概率的多参数多工序工艺系统可靠性评估方法、数学表述和算例.     

Fuzzy temporal fault tree analysis of dynamic systems

Fault tree analysis (FTA) is a powerful technique that is widely used for evaluating system safety and reliability. It can be used to assess the effects of combinations of failures on system behaviour but is unable to capture sequence dependent dynamic behaviour. A number of extensions to fault trees have been proposed to overcome this limitation. Pandora, one such extension, introduces temporal gates and temporal laws to allow dynamic analysis of temporal fault trees (TFTs). It can be easily integrated in model-based design and analysis techniques. The quantitative evaluation of failure probability in Pandora TFTs is performed using exact probabilistic data about component failures. However, exact data can often be difficult to obtain. In this paper, we propose a method that combines expert elicitation and fuzzy set theory with Pandora TFTs to enable dynamic analysis of complex systems with limited or absent exact quantitative data. This gives Pandora the ability to perform quantitative analysis under uncertainty, which increases further its potential utility in the emerging field of model-based design and dependability analysis. The method has been demonstrated by applying it to a fault tolerant fuel distribution system of a ship, and the results are compared with the results obtained by other existing techniques.     

Reliability analysis of non‐repairable systems modeled by dynamic fault trees with priority AND gates

Many real‐life systems are typically involved in sequence‐dependent failure behaviors. Such systems can be modeled by dynamic fault trees (DFTs) with priority AND gates, in which the occurrence of the top events depends on not only combinations of basic events but also their failure sequences. To the author's knowledge, the existing methods for reliability assessment of DFTs with priority AND gates are mainly Markov‐state‐space‐based, inclusion–exclusion‐based, Monte Carlo simulation‐based, or sequential binary decision diagram‐based approaches. Unfortunately, all these methods have their shortcomings. They either suffer the problem of state space explosion or are restricted to exponential components time‐to‐failure distributions or need a long computation time to obtain a solution with a high accuracy. In this article, a novel method based on dynamic binary decision tree (DBDT) is first proposed. To build the DBDT model of a given DFT, we present an adapted format of the traditional Shannon's decomposition theorem. Considering that the chosen variable index has a great effect on the final scale of disjoint calculable cut sequences generated from a built DBDT, which to some extent determines the computational efficiency of the proposed method, some heuristic branching rules are presented. To validate our proposed method, a case study is analyzed. The results indicate that the proposed method is reasonable and efficient. Copyright © 2015 John Wiley & Sons, Ltd.     

某型工程车系统可靠性分析

本应用失效树分析法,以某型工程车进行了可靠性分析,建立了该系统的失效树,在此基础上用最小割集法和系统失效树的可靠性仿真法计算了该系统的可靠性参数,并对一些结果进行了比较。     

Semi-Markov failure rates processes

Usually, a reliability function is defined by a failure rate which is a real function taking the non-negative real values. In this paper the failure rate is assumed to be a stochastic process with non-negative and right continuous trajectories. The reliability function is defined as an expectation of a function of that random process. Particularly, the failure rate defined by the semi-Markov processes is considered here. The theorems dealing with the renewal equations for the conditional reliability functions with a semi-Markov process as a failure rate are presented in this paper. A system of that kind of equations for the discrete state space semi-Markov process is applied for calculating the reliability function for the 3-states semi-Markov random walk. Using the introduced system of renewal equations for the countable state space, the reliability function for the Furry-Yule failure rate process is obtained.     

模糊重要度分析方法的研究

阐述故障树分析中从精确到模糊的重要分析法,提出了模糊重要度分析的新方法－中值法,它是用模糊故障树分析技术对结构复杂的新型系统进行可靠性、贮存可靠性研究的重要组成部分。同时,本文用两种模糊重度分析方法对一故障树作了重要度分析。     

模糊技术在可靠性工程中的应用

本文主要介绍模糊集合理论和技术在可靠性工程中的应用现状及其发展趋势，尤其是在系统故障诊断，故障树分析（ＦＴＡ）系统可靠性分配，人的可靠性，软件可靠性，结构可靠性以及系统安全性工程中的应用和技术关键，并从工程应用的需要出发针对存在问题预测和提出各种解决途径。     

Computational methods for discrete hidden semi-Markov chains

We propose a computational approach for implementing discrete hidden semi-Markov chains. A discrete hidden semi-Markov chain is composed of a non-observable or hidden process which is a finite semi-Markov chain and a discrete observable process. Hidden semi-Markov chains possess both the flexibility of hidden Markov chains for approximating complex probability distributions and the flexibility of semi-Markov chains for representing temporal structures. Efficient algorithms for computing characteristic distributions organized according to the intensity, interval and counting points of view are described. The proposed computational approach in conjunction with statistical inference algorithms previously proposed makes discrete hidden semi-Markov chains a powerful model for the analysis of samples of non-stationary discrete sequences. Copyright © 1999 John Wiley & Sons, Ltd.     

Reconfigurable chaotic logic gates based on novel chaotic circuit

The logical operations are one of the key issues in today’s computer architecture. Nowadays, there is a great interest in developing alternative ways to get the logic operations by chaos computing. In this paper, a novel implementation method of reconfigurable logic gates based on one-parameter families of chaotic maps is introduced. The special behavior of these chaotic maps can be utilized to provide same threshold voltage for all logic gates. However, there is a wide interval for choosing a control parameter for all reconfigurable logic gates. Furthermore, an experimental implementation of this nonlinear system is presented to demonstrate the robustness of computing capability of chaotic circuits.