二元决策图BDD在话务故障分析中的应用①

针对移动网络通话问题日益严重,需要建立一个故障树分析（FTA）模型。利用BDD技术分析各个基本事件的结构重要度、概率重要度和临界值重要度。基本事件的排序对故障树生成的BDD节点个数有直接影响,以及节点的结构重要度和概率重要度都有影响。采用相邻底事件优先排序法,能够尽量减少BDD节点个数和对重要度的影响。利用BDD法比传统FTA法计算的重要度数值更接近,计算效率更高。     

基于BDD的关联故障树定量分析法研究

利用二元决策图(BDD)中的B—割集和节点概率,提出了基于BDD的关联故障树定量分析新算法。推导了故障树顶事件发生概率和绝对失效强度算法公式,将故障树顶事件发生概率和绝对失效强度计算结合起来,避免了复杂的最小割集和不交化求解过程,显著地减少了布尔代数运算量,给出了算法递归步骤。大量的实例分析验证了此算法的工程实用性。     

基于BDD算法的某系统事故发生概率分析

随着现代武器系统趋于大型化和复杂化,利用事故树进行系统安全性分析日益困难。本文重点研究了基于BDD的FTA优化求解算法,并利用贝叶斯方法研究小样本的独特优势,提出蒙特卡洛仿真方法求解底事件发生概率,进而利用BDD求解系统顶事件发生概率的方法。     

基于失效树分析的网络安全风险评估方法研究

本文提出了一种基于失效树分析法的网络安全风险状态评估方法,该方法通过对硬件、软件、环境及人为因素等的可靠性评估技术,计算出失效概率、顶事件和最小割集的重要度等,最后针对整个网络活动的体系结构、指导策略、人员状况等,对风险做出抉择。     

传感器可靠性技术－传感器的故障树分析

介绍了传感器故障树的建立规则，顶事件发生概率及底事件概率重要度的计算方法。     

传感器可靠性技术－传感器的故障树分析

介绍了传感器故障树的建立规则，顶事件发生概率及底事件概率重要度的计算方法。     

地下矿山巷道运输事故的致因分析

针对地下矿山巷道运输事故的案例,分析了导致事故的基本事件;通过对22个基本事件构成事故破坏模式的调查分析,得出了巷道运输事故的事故树;采用最小割集、最小径集以及结构重要度的意义对发生事故的基本事件进行定性分析,找出了导致运输事故基本事件的影响程度。该文有助于在防范事故发生时抓住主次因素,对矿山企业运输安全管理具有参考意义。     

基于DFTA的电牵引采煤机调高液压系统可靠性分析

MG950/1915型电牵引采煤机调高液压系统具有动态失效行为,用传统静态故障树法无法分析其可靠性.该文提出基于动态故障树的采煤机调高液压系统分析法,建立了油缸运动阻力大的动态故障树模型.首先求解动态故障树中不同子树的顶事件在不同时刻的发生概率,能得到整体动态故障树顶事件在不同时刻的发生概率.其次通过寻找顶事件发生概率最大的子树及子树中概率重要度最大的底事件,得到精过滤器和粗过滤器是采煤机调高液压系统的薄弱环节,为采煤机的优化设计提供了理论依据.     

基于模糊理论动车制动系统故障树可靠性分析

动车组制动系统在可靠性分析过程中存在故障数据的不确定性问题,主要表现为数据的来源不同和事件语义表述不同等,导致很难获取系统事件发生概率的精确数值。因此传统的故障树分析方法对于这类问题的处理不能得到符合现实条件的准确数据结果,故提出运用模糊数学理论将事件的发生概率进行模糊化处理,并结合专家信心指数法通过故障树分析模型计算得出制动系统底事件的模糊概率重要度,并根据各底事件在不同故障状态情况下的模糊概率重要度的大小,找出影响系统可靠性的薄弱环节。通过对兰新客专上运行的动车组制动系统进行分析,结果与动车组制动系统实际运行情况相符合,验证了算法的可行性和有效性。为根据该线路故障的特点制定相应的检修和维护策略给出了理论依据。     

海水淡化系统反渗透膜故障诊断研究

故障树分析是一种图形演绎的故障诊断方法,在能源工程和航天器可靠性等领域已得到成功应用。基于反渗透系统,对系统中关键元件反渗透膜的结构和系统工作机理进行研究,给出了"脱盐率下降"作为顶事件的故障树,并求出了最小割集和最小径集,完成了对故障基本事件的结构重要度分析。针对传统故障树分析中不确定事件得不到有效解决以及知识获取困难的这一问题,提出将粗糙集与故障树分析相结合的混合的方法。     

Evaluation method based on fuzzy relations between Dempster–Shafer belief structure

Many relations in the real world can be described by mathematical language. Fuzzy set theory can transform human language into mathematical language and use membership degree function to describe relations between events. Dempster–Shafer evidence theory provides basic probability assignment (BPA), which can describe the occurrence rate of attributes in basic events. Based on the known membership degree function and BPA distribution, a new evaluation method is proposed in this paper to analyze decision making. Given the relations among relevant events, which are expressed by BPA distribution and membership degree function, the relations among basic events and top event can be obtained. The Dempster's combination rule and pignistic probability transformation are used to transform BPA distribution into probability distribution. The belief measure is applied to deal with these fuzzy relations. Some numerical examples are given in this paper to illustrate the proposed evaluation methodology.     

Moment-independent importance measure of basic random variable and its probability density evolution solution

To analyze the effect of basic variable on failure probability in reliability analysis,a moment-independent importance measure of the basic random variable is proposed,and its properties are analyzed and verified.Based on this work,the importance measure of the basic variable on the failure probability is compared with that on the distribution density of the response.By use of the probability density evolution method,a solution is established to solve two importance measures,which can efficiently avoid the ...     

Dynamic probabilistic analysis of accidents in construction projects by combining precursor data and expert judgments

Construction accident occurrences are essentially rare, stochastic, and dynamic. This study proposes a method for accident prediction that fully captures these natures based on historical data and prior knowledge. The method utilizes the relatively high occurrence frequency of precursor events and the dependency between precursors and accidents. The modeling approach consists of three steps: (1) characterize the stochastic occurrences of precursor events over time based on precursor data; (2) estimate the failure rate of the Poisson model which is assumed to be a prior distribution of accident occurrences; and (3) elicit the expert knowledge about the stochastic dependency between near miss occurrences and accident occurrences. A copula-based Markov model is used to develop the time series model of precursors while a copula-based protocol is proposed to aid expert judgment elicitation and quantification. The probability of accident occurrence is then dynamically updated according to the observed historical near miss numbers. The proposed method is applied to a metro construction project. A five-year long near miss data were collected and used as accident precursor data, while three experts were invited to provide relevant information. The developed accident model is used to predict the accident-prone periods, which are consistent with the months that the observed near miss occurrence frequency deviates significantly from normality. Thus, the model can be used to support the planning of necessary safety improvement programs before the accident risk increased.     

基于T-S模糊故障树方法的惯性导航系统可靠性评估

针对传统故障树模型在复杂系统可靠性评估中的局限性,引入T-S模糊故障树建模方法对惯性导航系统进行可靠性评估分析.在建立T-S模糊故障树的基础上,以模糊门算法表征事件之间的逻辑关系,确定了基于基本事件模糊概率和故障程度的复杂系统可靠性评估方法,并对事件进行了概率重要度和关键重要度分析.案例分析表明,T-S模糊故障树分析方...     

基于模糊结构元的SFT概念重构及其意义

为解决SFT,特别是DSFT所结果无法表示原始离散故障数据分布特征的缺点,引入模糊结构元理论将SFT中概念及计算方式结构元化来解决该问题。首先模糊结构元特征函数可通过模糊结构元E表示原始数据的离散分布特征,并在计算过程中将E传递至最终结果。通过处理结果中E来得到分析结果的置信度。另一方面,模糊结构元特征函数可将DSFT问题转化为较成熟的CSFT进行处理,而不用为实现相同功能针对DSFT研究新的方法。论文完成了原有SFT中特征函数、基本事件发生概率分布、系统故障概率分布、概率重要度分布、关键重要度分布、系统故障概率分布趋势、因素重要度分布和因素联合重要度分布的模糊结构元化改造,并给出了结构元化后的计算方式。