基于SPA-Markov的飞行安全态势评估与预测研究

为提高航空公司飞行安全风险控制和预测水平,利用QAR数据作为支撑,结合集 对分析和马尔科夫理论建立飞行安全态势评估模型。该模型以QAR超限事件为评估指标 ,采用集对分析中的联系度来描述安全风险等级;运用马尔科夫理论确定安全状态的转 移概率矩阵,以预测飞行安全动态变化趋势。最后以某公司A320机队6个月发生频率最 高的7类超限事件对模型进行验证。结果表明:该公司2月、6月和预测月份的安全状态 为一般风险,其他月份为低风险;总体安全状态也为一般风险,并有增加趋势。     

基于风险度量理论的煤矿安全的系统评价

对风险理论最新进展的评述认为 ,安全就是零风险 ,凡事总有风险 ,安全只是相对的 ;安全问题是系统风险问题 ,风险和安全是同一个系统不确定性状态的两种对称的描述 ;安全程度或风险大小不仅取决于客观自然因素也决定于主观因素。笔者根据姜青舫提出的满足风险度量公理的险度函数 ,对矿井风险体系的结构分析 ,提出了矿井风险集、矿井险度和安全度新型综合评价指标。使矿山的安全评价建立在合理风险理论的基础之上 ,其中相对险度指标可直接作为风险预警指标使用。     

基于FAT的使用ADS-B提供监视服务安全性评估

先对ADS-B提供监视服务进行事故树的分析,层层分析碰撞事故发生时的中间事件和基本事件,对基本事件进行赋值,同时进行定量和定性分析,得出最小割集、最小径集、结构重要度、概率重要度和临界重要度,通过临界重要度选择防范措施和工作重点,通过计算公式对顶事件进行概率计算,通过计算出的碰撞风险值与安全目标对比,得出ADS-B提供监视服务的情况下,碰撞的风险值远远小于国际民航组织规定的最小安全目标,最后得出结论证明ADS-B是安全的。     

基于集对分析和马尔科夫链的航空维修安全动态评估

为有效解决航空维修安全评估过程中诸多不确定性问题,将集对分析(SPA)理论和马尔科夫链(MC)结合,建立航空维修安全动态评估模型。基于人-机-环系统理论,在构建评估指标体系的基础上,采用SPA理论中联系度的概念,以及同势、均势和反势的定义描述航空维修安全水平及其变化特征;运用MC模型确定的状态转移概率矩阵,预测航空维修安全动态变化趋势。以某航空兵机务大队为例,评估该单位维修安全动态变化趋势。计算结果表明,模型能有效刻画该机务大队维修安全动态变化特征,得出其安全状态等级为基本安全,总体安全水平具有减弱趋势。     

石化装置BN拓扑结构节点同异反概率重要度分析

为解决石化装置贝叶斯网络(BN)拓扑结构节点状态不确定系统难以分析节点重要度的问题,借助广义集对分析(GSPA)理论探讨节点重要度。针对节点的不同逻辑关系,讨论基于GSPA理论与BN方法集成的节点状态概率表达方式。从同一性、差异性、对立性3方面,提出节点同异反概率重要度分析方法,并将其应用到某反应器火灾爆炸事件的BN拓扑结构中。结果表明:各根节点故障状态概率会影响该反应器火灾爆炸事件发生概率,各根节点联系度同一性、差异性、对立性不同,会产生不同的同异反概率重要度分布情形。     

改进广义灰色关联故障树的危化品LSSC可靠性诊断

为了探究影响危化品物流整体运作的关键事故因素,提出一种改进广义关联故障树的危化品LSSC可靠性诊断方法。结合实例构建危化品LSSC系统失效故障树,运用灰色关联技术对以最小割集构造的标准故障模式向量和底事件概率重要度组成的待检模式向量进行相关性分析,得到系统失效概率等级与失效故障模式可能性排序,确定系统关键薄弱环节。研究结果表明:该方法能够快速识别危化品物流运作系统关键事故因素,为危化品LSSC风险等级控制和分级防范措施制定提供参考和借鉴。     

基于AHP的原始风险概率定量方法研究

安全生产领域中安全评估定量分析方法有很多种,如事故树分析、事件树分析方法等,事故树分析方法虽然应用广泛,但在企业安全生产的实际使用过程中经常会受制于原始数据的取值问题导致难以量化的问题发生。为了更深入地分析概率重要度和精确定量,本文对层次分析法AHP进行研究,构建出企业原始风险概率定量的近似算法,该方法可用于原始风险概率值计算、风险等级排序、资源和治理优先级排序等多个领域,还可应用于事故树分析中近似计算概率重要度和临界重要度,对企业安全生产管理有一定的指导意义。     

基于模糊综合评价法的继电保护人员安全状态评估及应用

结合继电保护工作的实际,建立继电保护作业人员安全风险状态的层次型指标体系。根据模糊综合评估理论,针对指标体系建立状态因素集、模糊权重集和评语集,从而建立了模糊评估模型。运用改进的层次法,在采集了专家打分的基础上确定了各指标的模糊权重;根据电力安全生产实际确定了评语集的内容;引入隶属度概念给出了评判集算法。具体评价过程是：首先在咨询专家的基础上对最底层因素进行评价,然后进行模糊运算,计入隶属度,得到底层评判集。底层评判集作为上一层因素的评价集,逐层进行计算,最后得到员工安全风险状态的评估结果,该结果是一个评价集,根据最大隶属度原则,得到最后的评估结论。以实际算例证明了算法的可行性,同时简单介绍了应用情况。     

基于最小径集的系统故障概率分配方法研究

为准确、快捷地解决在复杂系统中的可靠性分配问题,在基于最小割集的可靠性分配方法的基础上建立了基于最小径集的系统故障概率分配模型.该模型的分配思想不是对系统所有的单元都进行分配,而是选择最有可能导致系统发生故障的单元进行分配.最小径集分配法只需对最小径集中的基本事件直接进行分配计算,从而大幅度减少了中间计算工作量.它的另一个突出优点是‘能提供多个可选择的分配方案,因为每一个最小径集都代表1种分配方案.根据安全系统工程的优化思想,提出了不可靠度分配方案的选择原则:在基本事件数相同的最小径集中选择概率较大的最小径集;在概率接近的最小径集中选基本事件数较少的最小径集.对于最小径集中基本事件的分配,根据概率重要度来分配是合理的,因为重要度越大的基本事件对系统的影响就越大,分配的概率就应该越小.通过矿井火灾事故树的举例,进一步描述了基于最小径集的系统故障概率分配方法的定量计算过程.研究表明,基于最小径集的系统故障概率分配法是工作量最小的分配方法,还可以进行分配方案的比较选择.     

基于Markov的列控中心多态动态可靠性分析

针对列控中心系统由冗余带来的动态时序特点和通信接口单元在实际工作环境中具有多种故障状态的问题,假设部件寿命和维修时间服从指数分布,且各单元相互独立,故障单元修复后的寿命仍服从指数分布。构建了基于马尔科夫的多状态热贮备可修系统可靠性模型,通过计算得到部件的稳态可用度、平均故障间隔时间、首次故障前平均时间、稳态故障频度、维修人员忙期稳态概率及可靠度函数等主要可靠性参数的解析表达式。最后,以CTCS-2级列控系统的列控中心为例,对该多状态热贮备可修系统可靠性解析模型进行了验证和分析。结果表明：随维修速率提高,部件的稳态可用度提高,部件的故障概率、稳态故障频度和维修人员忙期稳态概率降低;可为掌握列控中心在实际维修条件下的可靠性规律及合理开展列控中心维修工作提供技术支撑。     

Embedding the human factor in road tunnel risk analysis

The paper is focusing on road tunnel safety and builds upon the Directive 2004/54/EC launched by the European Commission; the latter sets basic requirements and suggests the implementation of risk assessment in several tunnel cases apart from technical measures imposed on the basis of tunnel structural and operational characteristics. Since the EU Directive does not indicate the method for performing risk assessment, a wide range of methods have been proposed, most of them based on quantitative risk assessment (QRA). Although the majority of current road tunnel QRAs assess physical aspects of the tunnel system and consider several hazards concerning the transportation of dangerous goods through a tunnel, they do not take into account, sufficiently, several organizational and human-related factors that can greatly affect the overall safety level of these critical infrastructures. To cope with this limitation this paper proposes a fuzzy logic system based on CREAM method for human reliability analysis (Hollnagel, 1998) in order to provide more sophisticated estimations of the tunnel operator's performance in safety critical situations. It is deduced that a human reliability analysis component to analyze operator performance, like the fuzzy system proposed here, is important for risk analysts. Consideration of organizational and human factors will enhance risk analysts’ studies and highlight the uncertainty related to human performance variability.     

Component failure recognition and maintenance optimization for offshore heave compensation systems based on importance measures

Heave compensation systems work to reduce the influence of unpredictable marine environments on offshore operations and are powered by hydraulic systems. As an important approach in the reliability field, importance measure assesses the impact of components on a system. This paper considers the importance of hydraulic system components for system performance. By analyzing the working state of each component in the passive compensation and active compensation phases, the working principle of the hydraulic system of a semi-active heave compensation experimental system is explained. According to the actual design of the experimental system and its working principle, eight types of 27 components, whose failures affect the performance, are extracted. The servo valve and the accumulator are determined to be redundant while the other components are nonredundant. Two performance-related importance measures, Griffith importance measure (GIM) and integrated importance measure (IIM), are then applied to sort the components of the hydraulic system and determine the maintenance sequence. Finally, based on the IIM value and the maintenance cost of each component, optimization strategies are proposed under different conditions using total cost and time as independent variables.     

An integrated off-on line approach for increasing stability and effectiveness of automated controlled systems based on pump dependability—case study: Offshore industry

Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standard methodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshore industry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries are considered according to OREDA classification. The approach identifies the critical pump and their fault through which the major hazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is then performed for the worst pump which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection which ultimately enhance overall operational effectiveness.     

基于人机工程的物流运输三参数风险评估模型

为了有效分析物流运输的风险状况,针对传统风险评估技术的不足,构建了一种以风险发生概率、风险后果和风险重要度为技术参数的物流运输风险三参数评估模型。首先,依据安全人机工程原理系统分析物流运输过程风险的影响因素,并建立物流运输风险评价指标体系。然后考虑风险因素的随机性和模糊性,提出了一种基于三角模糊数和模糊层次分析耦合的参数确定方法。最后,通过一个算例分析说明构建模型的有效性。结果表明,所提出方法用于物流运输风险定量分析优于传统风险评估技术。     

Optimization of test interval for ageing equipment: A multi-objective genetic algorithm approach

Reducing the unavailability of safety systems at nuclear power plants, by utilizing the probabilistic safety assessment (PSA) methodology, is one of the prime goals in the nuclear industry. In that sense, optimization of test and maintenance activities, which are defined within the technical specifications, represents quite popular and interesting domain. Obtaining optimal test and maintenance schedule is of great significance for improving system availability and performance as well as plant availability in general.On the other side, equipment aging has gradually become a major concern in the nuclear industry since the number of safety systems components, that are approaching their wear-out stage, is rising fast. Nuclear power plants life management programs, considering safety components aging, are being developed and employed. The immense uncertainty associated to the available component aging rates databases poses significant difficulties in the process of incorporation and quantification of the aging effect within the PSA and, subsequently, in the decision-making process.In this paper, an approach for optimization of surveillance test interval of standby equipment with highly uncertain aging parameters, based on genetic algorithm technique and PSA, is presented. A standard standby safety system in nuclear power plant is selected as a case study. A Monte Carlo simulation-based approach is used to assess uncertainty propagation on system level. Optimal test interval is derived on the basis of minimal system unavailability and minimal impact of components aging parameters uncertainty. The results obtained in this application indicate the fact that risk-informed surveillance requirements differ from existing ones in technical specifications as well as show the importance of considering aging data uncertainties in component aging modeling.     

基于模糊熵和非对称贴近度的安全预警评估方法

针对系统安全风险评估和预警过程中,系统安全特性和各预警因素所存在的模糊不确定性问题,将熵理论和模糊数学相结合,提出一种基于模糊熵和非对称贴近度的系统安全预警评估方法。在建立系统安全预警评估指标体系的基础上,首先,分析基于模糊熵理论确定预警指标权重的可行性,给出系统预警指标赋权算法;其次,建立基于模糊非对称贴近度确定系统安全等级的过程,第三,给出系统安全预警评估的具体计算步骤;最后,以人为因素系统的安全预警评估为例进行方法的实例验证。实例分析结果表明采用该方法所确定的系统预警指标权重更加符合客观实际,能有效解决系统安全预警评估中存在的模糊不确定性问题,系统预警决策结果合理有效。     

多因素耦合的加工车间关键风险因素定量分析

为了准确分析加工车间关键风险因素,考虑多风险因子交互影响的情境,提出了一种基于模糊决策实验室分析法的加工车间关键风险因素定量分析方法。首先,从人员、设备、环境、物料和管理因素等5个维度辨识加工车间风险因素并建立风险因素集;基于此,采用三角模糊数对专家判断语义进行表征,然后运用DEMATEL法计算多因素耦合下的风险重要度,从而确定加工车间的关键风险因素。最后,以安徽省某机械加工车间为例,说明所提出方法的应用过程。结果表明,加强对安全制度和安全文化建设等关键风险因素的控制,有助于加工车间的风险控制,改善车间生产安全。     

基于城市地铁实证分析的突发事件风险发展趋势评价模型研究

为了更好地完善突发事件风险评价过程,运用风险发展趋势评价模型对风险评价过程进行补充。采用Daniel趋势函数、灰色理论和模糊理论建立突发事件的风险发展趋势评价模型,并对广州市地铁运营风险发展趋势进行实证分析。结果表明,从执行过程看,该模型改善了突发事件风险评价的范围和评价结果的准确度,评价过程具有一定的可行性和客观性,可以推广应用到各类突发事件的风险发展趋势评价中。通过实证分析,该城市的地铁运营风险当前处于临界状态以下,可以保持当前的运营状态,与该城市的地铁运营状况相符合,对于单个子系统,乘客和员工素质系统目前处于临界状态,对整个地铁系统的安全性有较大影响,城市居民和员工素质需要进一步提高。     

重要基础设施脆弱性评价模型及其应用

将重要基础设施脆弱性定义为威胁情景、保护作用和重要性的函数,并提出一种可定量化的重要基础设施脆弱性评价模型。模型结合系统理论知识分解系统,选取威慑、延迟、检测、响应4个评价因子评估系统各环节。模型由相关领域专家确定系统各环节权重以及为评价因子赋值,应用线性加权聚集模拟技术,综合评价因子信息;依据系统状况,建立系统各环节价值函数,运行模型得到脆弱性概率密度函数,以数学期望值表示系统脆弱性总值。并将模型应用于天津市部分供水系统,不仅得到系统各环节的实际评价值,而且可得整个供水系统脆弱性评价值,为更好地改进天津市供水系统各环节的安全运行提供了科学依据。     

中小学校安全风险管理系统的提出与应用

为了提升校园的安全程度完善其管理系统,本文在阅读相关文献的基础上,结合校园应急管理以及风险辨识和评估在校园安全中的重要性,将工业安全管理技术应用于校园安全管理中,提出中小学安全风险管理系统,该系统的实施和应用,可以在一定程度上减少校园安全事故的发生,对校园的安全管理,具有实际应用价值和重要的现实意义。