基于CREAM和贝叶斯网络的航空维修人为差错概率预测

航空维修差错不仅严重威胁着飞行安全,同时也会增加航空公司的维修成本。针对航空维修人员发生差错成因的复杂性以及历史事故数据缺乏的情况下,将人因可靠性与失误分析方法（CREAM）和贝叶斯网络（BN）相结合,提出一种改进的维修差错分析模型。根据维修任务构建相应的贝叶斯网络模型,为各子节点设置条件概率表（CPT）;基于维修基地的实际维修环境,对行为形成因子（PSFs）进行评估,得到共同绩效条件（CPCs）的水平;利用各CPC因子下各个行为功能失效模式的权重因子,对各认知活动进行失效概率的修正;将修正概率作为贝叶斯网络根节点的输入,利用推理机制,得到差错发生概率。通过案例分析和计算,验证了所述方法的可行性和有效性。     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Dynamic-risk-informed safety barrier management: An application to cost-effective barrier optimization based on data from multiple sources

An integrated approach for performance assessment and management of safety barriers in a systemic manner is needed concerning the prevention and mitigation of major accidents in chemical process industries. Particularly, the effects of safety barriers on system risk reduction should be assessed in a dynamic manner to support the decision-making on safety barrier establishments and improvements. A simulation approach, named Simulink-based Safety Barrier Modeling (SSBM), is proposed in this paper to conduct dynamic risk assessment of chemical facilities with the consideration of the degradation of safety barriers. The main functional features of the SSBM include i) the basic model structures of SSBM can be determined based on bow-tie diagrams, ii) multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) may be combined to update barrier failure probabilities and initiating event probabilities, iii) SSBM is able to handle uncertainty propagation in probabilistic risk assessment by using Monte Carlo simulations, and iv) cost-effectiveness analysis (CEA) and optimization algorithms are integrated to support the decision-making on safety barrier establishments and improvements. An illustrative case study is demonstrated to show the procedures of applying the SSBM on dynamic risk-informed safety barrier management and validate the feasibility of implementing the SSBM for cost-effective safety barrier optimization.     

Accident models and organisational factors in air transport: The need for multi-method models

Event analysis is needed to learn and improve safety. In air transport, ‘occurrences’ are routinely reported by pilots and air traffic controllers, and in-flight data analysis systems automatically monitor aircraft system behaviour and capture parameter threshold exceedances. The safety analyst of a large airline has to analyse dozens of occurrences each day. To understand why events happened the analyst has to go beyond the given information and make causal inferences. The analyst is able to do this for causal factors closely related in time and space to the event itself by applying individual knowledge and expertise. But typically the result of the analysis is ad hoc reaction to each individual event. Systematic analysis is needed to find areas of improvement for factors that are further removed from the event (latent factors). New tools are needed to help the analyst in this respect. There is a need for models that represent possible causal event sequence scenarios that include technical, human, and organisational factors. Building such models is a huge task, and requires the combination of detailed knowledge of all aspects of the system, processing huge amounts of data, a substantial mathematical background and the ability to capture this all in a user friendly software tool to be used by the safety analysts. Experience in Causal Modelling of Air Transportation System (CATS) in the Netherlands and similar projects in FAA and Eurocontrol in aviation shows that this is indeed a formidable task, but it has to be done to further improve safety.     

The impact of risk tolerance,risk perception and hazardous attitude on safety operation among airline pilots in China

The present study integrates personality approach and social cognition approach to investigate the relationships between risk tolerance, risk perception, hazardous attitude and safety operation behavior in order to understand the mechanisms underlying pilots’ safety operation behavior in aviation. The study sample consisted of 118 commercial airline pilots from China Southern Airlines Ltd. The results show risk tolerance displays an indirect effect on safety operation behavior through influencing hazardous attitude; risk perception has a significant moderating effect on the relationship between risk tolerance and safety operation behavior. Based on the above, it can be concluded that the low risk tolerance primarily influences safety operation behavior indirectly through affecting hazardous attitude. With risk perception increasing, the negative effects of risk tolerance on safety operation behavior are gradually reduced. Practical implications for aviation safety campaigns are also discussed.     

基于贝叶斯网络的物流无人机失效风险评估*

为降低城市物流无人机（UAV）失效坠落风险,通过考虑其运行环境和系统故障等因素的影响,以城市物流无人机运行数据为基础,从系统故障、运行环境和人为因素3方面提取失效诱因;分析物流无人机失效模式,并构建意外坠落事故的贝叶斯网络;基于所建网络和失效诱因发生概率分别计算不同工况下意外坠落事故及各中间事件概率,并基于网络拓扑结构展开反向推理,推演事故的主要失效诱因。结果表明:物流无人机正常运行时发生安全事故的概率为6.54×10-3;其中,电池电量不足、桨叶失效和电池故障是坠落事故的主要诱因,计算结果可为无人机运行安全风险防控提供依据。     

Safety assessment of natural gas storage tank using similarity aggregation method based fuzzy fault tree analysis (SAM-FFTA) approach

Fault tree analysis (FTA) is an important method to analyze the failure causes of engineering systems and evaluate their safety and reliability. In practical application, the probabilities of bottom events in FTA are usually estimated according to the opinions of experts or engineers because it is difficult to obtain sufficient probability data of bottom events in fault tree. However, in many cases, there are many experts with different opinions or different forms of opinions. How to reasonably aggregate expert opinions is a challenge for the engineering application of fault tree method. In this study, a fuzzy fault tree analysis approach based on similarity aggregation method (SAM-FFTA) has been proposed. This method combines SAM with fuzzy set theory and can handled comprehensively diverse forms of opinions of different experts to obtain the probabilities of bottom events in fault tree. Finally, for verifying the applicability and flexibility of the proposed method, a natural gas spherical storage tank with a volume of 10,000 m³ was analyzed, and the importance of each bottom event was determined. The results show that flame, lightning spark, electrostatic spark, impact spark, mechanical breakdown and deformation/breakage have the most significant influence on the explosion of the natural gas spherical storage tank.     

航空安全信息管理的问题与对策

航空安全信息是民航实施安全风险控制和事故预防的基础,对航空安全水平的提高有重要的作用。笔者总结了民航安全信息的基本构成和来源,及其在安全风险识别、管理决策方面的功用;结合中国民航安全管理状况及行业发展趋势,分析了当前中国民航安全信息管理方面存在的主要问题,指出当前民航安全信息存在着数量不足、质量不高、交流共享困难、分析利用不充分等问题,不利于基于数据驱动的安全管理机制的建立和向规章符合性基础上的绩效管理的转变。针对安全信息管理的这些问题,文章建议民航局通过改善安全信息管理政策、建立航空企业安全信息共享平台、建立国家航空安全信息分析中心、开发安全信息分析利用工具等措施来改善安全信息的收集、分析利用和共享,为提高行业安全管理水平服务。     

Dynamic accident modeling for high-sulfur natural gas gathering station

Dynamic accident modeling for a gas gathering station is implemented to prevent high-sulfur natural gas leakage and develop equipment inspection strategy. The progress of abnormal event occurring in the gas gathering station is modeled by the combination of fault tree and event sequence diagram, based on accident causal chain theory, i.e. the progress is depicted as sequential failure of safety barriers, then, the occurrence probability of the consequence of abnormal event is predicted. Consequences of abnormal events are divided into accidents and accident precursors which include incidents, near misses and so on. The Bayesian theory updates failure probability of safety barrier when a new observation (i.e. accident precursors or accidents data) arrives. Bayesian network then correspondingly updates failure probabilities of basic events of the safety barriers with the ability of abductive reasoning. Consequence occurrence probability is also updated. The results show that occurrence probability trend of different consequences and failure probability trend of safety barriers and basic events of the safety barriers can be obtained using this method. In addition, the critical basic events which play an important role in accidents occurrence are also identified. All of these provide useful information for the maintenance and inspection of the gas gathering station.     

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors

INTRODUCTION: Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. METHOD: The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. RESULTS: This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. IMPACT ON INDUSTRY: "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.     

民航机务维修系统安全风险监测

从人的因素、飞机的因素、环境因素和管理因素4方面分析了民航机务维修系统安全风险影响因素,结合专家调查意见建立了机务维修系统安全风险监测指标体系,并给出各个指标的含义及其衡量方法。根据机务维修系统安全风险指标及其数据特点,建立了行业机务维修系统安全风险模糊综合评价模型,并进行实例分析。结果表明,采用笔者建立的指标体系和风险模型可以方便地进行机务维修系统的安全风险评价和预警,从而找出主要的安全风险影响因素,为采取安全风险管理措施提供依据。     

基于知识地图的民用航空安全信息事件分析

安全信息的深入分析是数据驱动的安全管理基础。为深入挖掘民航安全信息的价值,分析不安全事件的发展和演化过程,预测事件可能引发的后果及可能性,以2011—2015年民航安全信息网收集的390起重着陆事件为样本,结合事件链因果关系分析,运用知识地图分析法,按照事件发展演化过程建立样本信息中包含知识信息及其因果关系、各事件链间的相关关系、不同后果事件演化的可能性的重着陆事件知识地图。结果表明,该知识地图能够获取重着陆事件在时间、地点、机型、运行阶段、原因、后果及可能的预防及管控重点,可以实现一起或多起重着陆事件信息的知识分析,发现可能存在的安全风险,预判引发严重后果事件的可能性,为有效实施风险管理提供依据。     

直升机电力作业非线性动态安全评价模型

为有效提高直升机电力作业安全评价能力,落实通用航空作业标准化和规范化管理,本文以直升机电力作业中人员因素、直升机设备因素、电力作业设备因素、自然环境因素、机场环境因素、组织因素、规章管理因素7个模块为一级指标建立安全评价指标体系。结合多位专家给出的概率语义值,基于模糊集与改进的证据融合理论量化各指标风险程度,同时采用三角模糊数法确定中间节点条件概率,最后利用贝叶斯网络模型灵活推理能力,提出直升机电力作业非线性动态安全评价模型。通过对某通用航空公司直升机电力作业安全状况评价分析可知,企业组织因素、电力作业设备因素以及人员因素为主要薄弱环节,需加强管理,可通过提高从业人员的安全防范意识、提高设备可靠性以及加强人员培训等措施对风险进行预防。     

Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis

Vast amounts of oil & gas (O&G) are consumed around the world everyday that are mainly transported and distributed through pipelines. Only in Canada, the total length of O&G pipelines is approximately 100,000 km, which is the third largest in the world. Integrity of these pipelines is of primary interest to O&G companies, consultants, governmental agencies, consumers and other stakeholder due to adverse consequences and heavy financial losses in case of system failure. Fault tree analysis (FTA) and event tree analysis (ETA) are two graphical techniques used to perform risk analysis, where FTA represents causes (likelihood) and ETA represents consequences of a failure event. ‘Bow-tie’ is an approach that integrates a fault tree (on the left side) and an event tree (on the right side) to represent causes, threat (hazards) and consequences in a common platform. Traditional ‘bow-tie’ approach is not able to characterize model uncertainty that arises due to assumption of independence among different risk events. In this paper, in order to deal with vagueness of the data, the fuzzy logic is employed to derive fuzzy probabilities (likelihood) of basic events in fault tree and to estimate fuzzy probabilities (likelihood) of output event consequences. The study also explores how interdependencies among various factors might influence analysis results and introduces fuzzy utility value (FUV) to perform risk assessment for natural gas pipelines using triple bottom line (TBL) sustainability criteria, namely, social, environmental and economical consequences. The present study aims to help owners of transmission and distribution pipeline companies in risk management and decision-making to consider multi-dimensional consequences that may arise from pipeline failures. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process. A simple example is used to demonstrate the proposed approach.     

基于模糊集和改进TOPSIS方法的跑道侵入风险评估

为预防民航机场跑道侵入事件的发生,减轻塔台管制员面临的跑道运行安全的压力,根据国际民航组织(ICAO)颁布的《防止跑道侵入手册》描述的空中交通管制(ATC)因素,建立影响跑道侵入的ATC指标评价体系。首先运用模糊集理论建立评价模型,并计算子指标的模糊可能性值,其值反映所论子指标风险概率。其次,采用改进的TOPSIS方法进行验证,并计算子指标的信度效度值。结果表明,得出的子指标风险值与模糊可能性值的排序一致。最后,根据子指标风险值的大小提出防止跑道侵入事件发生的建议。     

基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*

为分析海底管道运行中存在的泄漏风险,提出1种基于毕达哥拉斯模糊数与贝叶斯网络的风险评估模型。首先,通过毕达哥拉斯模糊数转换专家定性评价,拓展专家意见模糊范围;然后,结合主客观组合赋权法,利用毕达哥拉斯梯形爱因斯坦混合几何算子（PTFEHG）实现专家意见的聚合;最后,通过贝叶斯网络的推理与敏感性分析,计算海底管道泄漏风险的失效概率,并辨识关键风险因素。研究结果表明:该方法可以结合专家意见对海底管道泄漏风险进行定量分析,并识别导致泄漏事故的关键风险因素,对海底管道安全管理具有指导意义。     

A novel tool for Bayesian reliability analysis using AHP as a framework for prior elicitation

Quantitative risk assessment (QRA) is a powerful and popular technique to support risk-based decisions. Unfortunately, QRAs are often hampered by significant uncertainty in the frequency of failure estimation for physical assets. This uncertainty is largely due to lack of quality failure data in published sources. The failure data may be limited, incompatible and/or outdated. Consequently, there is a need for robust methods and tools that can incorporate all available information to facilitate reliability analysis of critical assets such as pipelines, pressure vessels, rotating equipment, etc. This paper presents a novel practical approach that can be used to help overcome data scarcity issues in reliability analysis. A Bayesian framework is implemented to cohesively integrate objective data with expert opinion with the aim toward deriving time to failure distributions for physical assets. The Analytic Hierarchy Process is utilized to aggregate time to failure estimates from multiple experts to minimize biases and address inconsistencies in their estimates. These estimates are summarized in the form of informative priors that are implemented in a Bayesian update procedure for the Weibull distribution. The flexibility of the proposed methodology allows for efficiently dealing with data limitations. Application of the proposed approach is illustrated using a case study.     

运输航空飞行安全绩效模糊动态评估模型*

为完善民航安全绩效体系建设,提高企业风险防范能力,促进其健康发展,参考“空客飞行品质监控项目”和企业QAR监控项目,结合指标重要性分析和一线人员、专家的有关建议,构建飞行安全绩效评估指标体系。基于混合型中心点三角白化权函数和TAN模型设计运输航空飞行安全绩效模糊动态评估模型。研究结果表明:该模型具有良好的实用性和可操作性,能够满足航空公司对安全绩效评估的需求。     

基于事件提取和改进MMHC的航空旅客运输事故征候贝叶斯网络建模*

为表征航空旅客运输事故征候演化机理,提出事故征候贝叶斯网络的建模方法。基于事故征候中致因事件、结果事件及分类标准的定义,以7 265起事故征候案例为样本,利用事件提取算法,识别事故征候叙述文本中的致因事件,利用改进的最大最小爬山算法实现网络建模;依据事件提取的测试集验证与结构学习的交叉验证,检验建模算法的准确性与有效性;基于证据敏感性指标,识别关键致因事件。结果表明:航空旅客运输事故征候贝叶斯网络模型包含94个节点和247条有向弧。空降冲突、严重设备故障、机组成员疾病及火灾烟雾是模型中高风险关联的致因事件,在安全监管过程中消除或减弱关键致因事件的发生能有效控制系统风险。