适用于数字化主控室的核电厂HRA基础数据架构研究

目前国内开展核电厂人员可靠性分析(HRA)采用的人员失误概率基础数据库年限较为久远,且缺乏对于数字化主控室环境下人员失误模式的考虑。本文基于多个HRA方法及国外典型人员可靠性数据库的设计,结合国内电厂的实际情况,搭建了核电厂HRA基础数据库的框架,对于其中的绩效影响因子(PSF)架构采用数据库概念设计阶段的自顶向下设计方法,结合数字化环境下新增的人员失误模式,给出可供采集的PSF数据项,完成可适用于数字化环境的核电厂HRA基础数据库中PSF架构的搭建,并针对核电厂HRA基础数据架构着手开发相应的数据库软件,为核电厂人员可靠性数据的采集、防人因失误工作的开展提供有效支持。

Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

Quantitative Human Reliability Analysis for Crew During Shipping Operation

A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.

Human Factors Analysis in Software Engineering

The general human factors analysis analyzes human functions, effects and influence in a system. But in a narrow sense, it analyzes human influence upon the reliability of a system, it includes traditional human reliability analysis, human error analysis, man-machine interface analysis, human character analysis, and others. A software development project in software engineering is successful or not to be completely determined by human factors. In this paper, we discuss the human factors intensions, declare the importance of human factors analysis for software engineering by listed some instances. At last, we probe preliminarily into the mentality that a practitioner in software engineering should possess. Key words human factors analysis - software engineering - software reliability CLC number TP 311.5 Foundation item: Supported by the National Natural Science Foundation of China (60173013)Biography: Xu Ren-zuo (1946-), male, Professor, research direction: software engineering, software reliability engineering, software safety and software testing.

Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.

改进贝叶斯网络模型在起重作业人机交互差错风险分析中的应用

为量化分析起重作业人机交互差错风险,根据安全工效学原理及安全技术规范将起重作业人、机、环相关影响因素作为根节点,按照事故致因层次关联关系确定子节点,构建起重作业人机交互差错的3层级贝叶斯网络模型(Bayesian Network, BN);基于模糊集理论,采用认知可靠性与失误分析方法(Cognitive Reliability and Error Analysis Method, CREAM),厘定贝叶斯网络父节点失效概率以及中间节点条件概率;利用逆向推理仿真技术分析起重作业人机交互差错发生的因果链,探究起重伤害事故发生的人机交互差错风险。结果表明:起重作业人机交互差错最可能致因链为起重设备安全检查不到位→管理人员失误→人员操作失误→起重伤害事故发生;单因素失效条件下,起重作业人机交互差错风险概率呈线性增长趋势;在多因素失效条件下,一级节点因素失效概率愈大则人机交互差错效应愈显著,且呈现非线性增长态势。

基于CREAM方法的海上风机安装人因可靠性评估

采用认知可靠性和差错分析法(Cognitive Reliability and Error Analysis Method,CREAM)对固定式海上风机安装作业的人因可靠性进行评估,并引入结构熵权法和马尔可夫方法对传统CREAM进行改进,实现人因差错概率、平均人为差错时间等人因可靠性指标的定量计算。在充分结合现实条件的情况下,考虑海上风机安装的天气、海浪和操作水平等环境和人为因素的影响,针对固定式海上风机安装作业的要求和特点,结合作业人员可靠性评估结果,从操作素质、组织管理、环境改善等方面提出发展建议。

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

一种人因可靠性分析(HRA)方法

从控制论角度说明人因可靠性分析方法 ,在分析现有两代人因可靠性分析方法不足的基础上 ,结合控制论 。

基于层次灰色关联分析的舱室内环境HRA评价

舱室是操作者操纵和执行任务的工作空间,其内环境直接影响到操作者的工作状态和工作效率。为了在安全性要求较高的舱室设计中进行HRA(Human Reliability Analysis)分析,以人机工程学和认知心理学为基础,分析了影响人机交互效率的主要因素和认知失误原因,建立了人机交互综合认知模型,在此基础上改进了CPC(Common Performance Condition)评价因子,并采用层次分析法确定其权重。运用灰色关联分析改进CREAM(Cognitive Reliability and Error Analysis Method)方法计算出认知失误概率,实现了舱室内环境人因可靠性的定量评价。最后设计并编制了评价系统,使得评价决策过程数字化,并以石油钻机司钻控制室设计方案评价为例作为验证。

航天器人机交互安全性分析综述

航天器自身软硬件可靠性水平提高后,人机交互(HMI)失误逐渐成为影响航天器安全性的薄弱环节。文章阐述了开展HMI安全性分析的必要性和重要性;在分析地面操作、遥操作、在轨操作等航天任务安全性特点的基础上,从人因可靠性分析(HRA)方法、引入HRA的系统安全性分析方法、人为失误基础数据采集3个方面对航天器HMI安全性分析情况进行分析;指出了现有HMI方法不完全适用于多人、长时、舱外任务场景及人为失误基础数据匮乏等不足,并对国内相关研究发展提出了建议,例如研究适用于我国航天器的HMI安全性分析方法、加强人为失误基础数据的采集和处理、开发适配的软件工具等。

一种基于HRA的数字化人-机界面评价方法研究

为识别数字化人-机界面中可能诱发人因失误或弱化操纵员绩效的设计缺陷,建立了一种基于HRA的人-机界面评价方法:HCR+CREAM+HEC。首先,采用HCR方法从事件整体中识别出失误概率高的风险场景;然后,针对高风险场景采用CREAM方法确定各种失误模式及其失误概率,并对失误概率进行排序;最后,依据数字化人-机界面特征建立人因工程检查表,对失误概率高的人-机界面进行审查,以识别人-机界面设计中存在的缺陷,并提出改进建议。结果表明,该方法能快速有效地识别出数字化人-机界面设计中存在的容易诱发人因失误的缺陷,通过设计优化提高核电站数字控制系统运行的安全性。

基于贝叶斯网络的HRA研究在舰船PSA中的应用

通过分析概率安全评价对人因可靠性分析的本质需求,运用人为失误率预计技术与人的认知可靠性模型相结合的方法对概率安全评价中的人因事故进行分析计算,并针对传统事件树、故障树分析方法的局限性,采用了贝叶斯网络结构评估的方法将计算结果合理融入到整体中.通过舰船弹药库的起火实例分析说明了该方法的运用过程和有效性.

An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

APPLICATION OF HUMAN COGNITIVE MODEL FOR TIME DEPENDENT OPERATOR BEHAVIOR IN CHINESE NPP

This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.

基于工程数据的行为形成因子权重确定方法

针对行为形成因子影响人员行为的问题,提出一种行为形成因子权重的确定方法。评述现有的行为形成因子权重确定方法,指出存在的缺陷和不足,构建一种基于工程数据的行为形成因子权重确定方法。结果表明:该方法能得到不同人为差错类型所对应行为形成因子的权重,更具客观性,可为人为差错的管理提供有效指导,为人为差错概率量化提供支持。

基于操作规程和人机界面的人为差错辨识方法

为提高武器装备的操作安全性,提出一种人为差错辨识方法。介绍人为差错辨识的基本概念和现有方法,指出现有方法存在的不足,提出基于操作规程和人机界面的人为差错辨识方法;通过分析操作规程建立人为差错模式的包络,通过分析人机界面基本特征筛选出有效的人为差错模式。结果表明:该方法可提高人为差错辨识结果的有效性,为人为差错管理提供指导。

基于模糊逻辑的人为差错概率量化方法

为满足人机系统概率风险评估的需要,提出一种人为差错概率量化方法。分析技能、规则和知识为基础(skill,rule and knowledge-based,SRK)框架和行为模式的确定方法Hanaman决策树法,指出在确定行为模式的过程中考虑行为模式影响因素的不确定性是必要的;使用模糊逻辑方法处理行为模式各个影响因素的不确定性,根据Hanaman决策树构建模糊推理规则,利用系统人为行为可靠性程序(systematic human action reliability procedure,SHARP)方法所提供的人为差错概率区间确定人为差错概率的隶属度函数。结果表明:该方法考虑了任务场景的不确定性,可以得到人为差错概率的精确值,满足人机系统概率风险评估的需要。

一种层次化的人为差错分类方法

针对人为差错在差错描述的全面性、一致性以及方法本身的有效性等方面的不足,提出一种层次化的人为差错分类新方法。将当前的各种人为差错分类方法分为3类,分析各种方法的特点和缺陷。提出从宏观到微观分层次的分类思想,将人为差错分为4个层次,针对每个层次构建详细的分类框架;运用该方法对航空维修中的人为差错进行示例分析,演示方法的使用流程。分析结果表明:该方法是一种有效的人为差错分类方法,可用于指导各种任务场景的人为差错辨识。

STPA和CREAM方法在飞行冲突调配人因差错研究中的应用

为了研究管制员飞行冲突调配的人因差错问题,进而有效评估管制员解决飞行冲突的可靠性,以保障空中交通的安全运行,提出系统理论过程分析(System Theoretic Process Analysis, STPA)与认知可靠性与失误分析方法(Cognitive Reliability and Error Analysis Method, CREAM)相结合的人因可靠性分析方法。首先,通过STPA方法构建系统控制模型,识别不安全控制行为(Unsafe Control Action, UCA)以及致因因素,找到管制员在调配飞行冲突过程中可能存在的差错行为;其次,基于CREAM扩展法对管制员的差错行为进行定量分析,得到管制员调配飞行冲突的人因失误概率。研究显示:使用该方法能够系统、全面地识别出管制员在调配飞行冲突过程中出现的差错行为,进而计算管制员飞行冲突调配的人因失误概率。实例分析表明该方法可以预测管制员在飞行冲突调配过程中的人因失误概率及可靠性,为管制员人因可靠性分析提供了新思路。