基于模糊综合评价的燃气管道第三方破坏失效研究

针对燃气管道第三方破坏事故复杂的特点,基于层次分析和模糊数学的理论,计 算燃气管道第三方破坏风险失效的可能性。全面识别城镇燃气管道第三方破坏事故的危 害因素,构建包含56个基本事件的燃气管道第三方破坏故障树。利用模糊集合隶属函数 ,计算燃气管道发生第三方破坏事故基本事件的模糊概率。利用改进的层次分析法,得 出各专家权重并修正各专家的评估意见,计算管道第三方破坏失效的可能性。以某大型 省会城市燃气管道为例进行验证分析,证明该方法的风险评价结果与实际情况相符,可 为燃气公司安全风险防控提供依据。     

饮食业油烟道火灾事故概率的模糊事故树分析

根据常规事故树定量计算中基本事件概率的不确定性问题,通过引入模糊集的概念,将常规事故树中基本事件的发生概率模糊化,用三角形模糊数代替确定性发生概率,应用模糊数截集方法,推导了模糊事故树的相关算法.采用模糊事故树方法得到饮食业油烟道火灾事故发生概率,并进行了敏感性分析,找出对顶事件发生概率影响较大的基本事件,确认减小油烟道火灾事故发生的相关措施.研究表明,饮食业油烟道火灾事故概率的模糊事故树分析是切实可行的,有助于对饮食业油烟道火灾的认识、预防和扑救工作.     

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.     

基于T-S模糊故障树的输气站场设备失效可能性研究

针对目前国内缺乏输气站场设备失效数据库的特点,同时考虑到设备具有不同的故障程度,提出将指标评价引入至T-S模糊故障树分析中,对设备进行失效可能性分析。首先构建设备的T-S模糊故障树;其次对故障树底事件进行指标评价,转化成当前工况下的故障程度;再次对设备的故障可能性值进行计算;最后,利用模糊数学的方法将故障可能性值转化为失效概率,并参考API 581中的失效概率等级对设备进行失效可能性等级划分。实例分析表明,该方法不仅比传统故障树分析更切合实际,又能够避免指标评价法淡化关键指标的不足,且兼具定量评价与半定量评价的优点。     

Fuzzy fault tree analysis for fire and explosion of crude oil tanks

Crude oil tank fire and explosion (COTFE) is the most frequent type of accident in petroleum refineries, oil terminals or storage which often results in human fatality, environment pollution and economic loss. In this paper, with fault tree qualitative analysis technique, various potential causes of the COTFE are identified and a COTFE fault tree is constructed. Conventional fault tree quantitative analysis calculates the occurrence probability of the COTFE using exact probability data of the basic events. However, it is often very difficult to obtain corresponding precise data and information in advance due to insufficient data, changing environment or new components. Fuzzy set theory has been proven to be effective on such uncertain problems. Hence, this article investigates a hybrid approach of fuzzy set theory and fault tree analysis to quantify the COTFE fault tree in fuzzy environment and evaluate the COTFE occurrence probability. Further, importance analysis for the COTFE fault tree, including the Fussell–Vesely importance measure of basic events and the cut sets importance measure, is performed to help identifying the weak links of the crude oil tank system that will provide the most cost-effective mitigation. Also, a case study and analysis is provided to testify the proposed method.     

Methodology for computer aided fuzzy fault tree analysis

Probabilistic risk assessment (PRA) is a comprehensive, structured and logical analysis method aimed at identifying and assessing risks of complex process systems. PRA uses fault tree analysis (FTA) as a tool to identify basic causes leading to an undesired event, to represent logical dependency of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event.To conduct a quantitative fault tree analysis, one needs a fault tree along with failure data of the basic events (components). Sometimes it is difficult to have an exact estimation of the failure rate of individual components or the probability of occurrence of undesired events due to a lack of sufficient data. Further, due to imprecision in basic failure data, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising out of subjectivity of the data.This paper presents a methodology for a fuzzy based computer-aided fault tree analysis tool. The methodology is developed using a systematic approach of fault tree development, minimal cut sets determination and probability analysis. Further, it uses static and dynamic structuring and modeling, fuzzy based probability analysis and sensitivity analysis.This paper also illustrates with a case study the use of a fuzzy weighted index and cutsets importance measure in sensitivity analysis (for system probabilistic risk analysis) and design modification.     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为(Unsafe Human Behaviors,UHBs)对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析.构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,...     

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RBF神经网络的火灾报警系统失效概率预测

报警系统失效主要包括漏报、误报,对系统进行失效概率预测,可以帮助判断设备质量优劣,评估系统效能。利用Matlab软件编程,通过神经网络预测失效概率。根据不同场所正在使用的火灾报警器的失效数据作为原始数据,归纳总结失效原因,建立事故树,结合专家打分法与模糊理论得到网络的输入值与输出值。通过网络训练,得到可以对系统失效概率进行预测的RBF神经网络,测算效率大幅提高。以70组不同品牌、用途的火灾报警系统作为算例,通过训练数据,最终达到输入底事件发生概率可直接输出顶事件发生概率的目的。结果表明,RBF神经网络相较于BP网络与事故树算得的失效概率具有更高的拟合度,RBF神经网络模型在进行系统失效概率预测时具有可靠性。     

基于T-S模糊故障树的受电弓系统可靠性分析

针对动车组受电弓故障统计中历史故障数据的多源异构和数据缺失等问题,同时考虑到受电弓故障的多态性,提出了以信心指数修正的专家调查法结合T-S模糊故障树,对受电弓可靠性进行分析。首先构建动车组受电弓系统的T-S模糊故障树;再对故障树基本事件进行基于信心指数修正的专家调查,得出基本事件模糊故障率;然后根据基本事件模糊故障率计算顶事件模糊可能性和基本事件模糊重要度;最后根据模糊重要度分析系统不同故障状态时影响其可靠性的薄弱环节。该分析结果与动车组的实际情况相符,可为受电弓系统的检修提供参考。     

基于贝叶斯网络的页岩气集输管道失效概率计算方法研究

页岩气集输管道运行压力和出砂量在生产过程中衰减显著，这导致管道失效概率不断变化，针对这一问题，采用贝叶斯网络方法，建立了页岩气集输管道失效概率动态计算模型。首先，分析页岩气气质特征、管道运行工况及失效原因，利用逻辑门的连接关系，建立了页岩气集输管道失效故障树；其次，基于贝叶斯网络与失效故障树的结构映射关系，将失效故障树转化成贝叶斯网络结构；然后，通过贝叶斯网络的参数学习，实现模型求解；最后，进行了实例应用。研究结果表明:该模型不仅可有效计算页岩气集输管道的失效概率，还能确定影响管道失效的关键风险因素，并且可通过调整节点的状态及概率分布，实现页岩气集输管道失效概率的更新。     

基于三角模糊数的矿井火灾事故树分析

利用事故树分析法对矿井火灾进行分析,结合平煤六矿建立了矿井火灾事故树.应用模糊重要度法对事故树基本事件进行排序,把导致火灾的两大因素进行模糊分级.从模糊概率排序以及分级可以看出,引燃火源和可燃物是比较危险的因素,发生的概率比较大.要想从根本上杜绝火灾,就要严格管理这两个重要的因素.这对于煤矿决策管理有着较重要的意义.     

Methodology for Computer-Aided Fault Tree Analysis

Fault tree analysis is a systematic, deductive and probabilistic risk assessment tool which elucidates the causal relations leading to a given undesired event. Quantitative fault tree (failure) analysis requires a fault tree and failure data of basic events. Development of a fault tree and subsequent analysis require a great deal of expertise, which may not be available all the time. Computer-aided fault tree analysis is an easy-to-use approach, which not only provides reliable results but also facilitates the validation and repeatability of the analysis. This enhances the overall results of the fault tree analysis and quantitative risk analysis.This paper presents a revised methodology for computer-aided fault tree analysis. The methodology includes fault tree development, minimal cutsets determination, cutsets optimization and probability analysis. The methodology uses advanced concepts of fault tree development and static and dynamic modularizing for complex and large fault trees. Furthermore, it enables sensitivity analysis of the system for design modification and risk-based decision making. Application of the proposed methodology to a process system is also discussed in the paper.     

System failure probability evaluation using fault tree analysis and expert opinions in intuitionistic fuzzy environment

In quantitative fault tree analysis of a system, exact failure probability values of components are utilized to calculate the failure probability of the system. However, in many real world problems, it is problematic to get precise and sufficient failure data of system components due to insufficient or imprecise information about components, changing environment or new components. A methodology has already been developed by employing fuzzy set theory for the system reliability evaluation by utilizing qualitative failure data of system components when quantitative failure data of components are inaccessible or insufficient. This paper extends the concept of fuzzy set to intuitionistic fuzzy set and proposes a novel approach to evaluate system failure probability using intuitionistic fuzzy fault tree analysis with qualitative failure data of system components. The qualitative failure data such as expert opinions are collected as linguistic terms. These linguistic terms are then quantified by triangular intuitionistic fuzzy numbers in form of membership function and non-membership function. Additionally, a method is developed for combining the different opinions of experts. To illustrate the applicability of proposed approach, a case study of the crude oil tank fire and explosion accident is performed. The obtained results are very close to the results from pre-existing approaches which confirm that the proposed approach is a more realistic alternative for the study of system reliability in intuitionistic fuzzy environment when quantitative failure data of system components are not known. To help decision makers for improving the security execution of the crude oil tank system, importance measures including Fussell-Vesely importance and cut sets importance are also executed.     

模糊事故树在分析氯乙烯单体槽爆炸风险中的应用

在对氯乙烯单体槽爆炸事故构建事故树的基础上,根据现场设备实际运行状况的统计及依据专家经验所提供的模糊信息,运用模糊事故树理论,引入L-R型模糊数,应用其尖态型隶属函数,对氯乙烯单体槽进行了模糊可靠性分析,求出了氯乙烯单体槽爆炸事故的模糊概率可能性分布;并利用结构重要度系数近似值法对其进行结构重要度分析,运用对事故树底部事件进行排序分级的加权结构重要度分析法,确立了影响系统的最主要因素,为系统安全分析提供了新的方法和途径。     

基于FFTA-LOPA的化工装置安全仪表系统SIL确定方法

为了优化确定化工装置安全仪表系统（SIS）安全完整性等级（SIL）,分析了现有确定SIL的不足,针对化工装置的失效数据缺失和不确定性特点,提出模糊事故树-保护层（FFTA-LOPA）模型计算安全仪表系统SIL。以某低密度聚乙烯反应釜为例,建立了该反应釜爆炸事故树,运用模糊理论定量分析顶上事件发生的概率,最终确定其安全仪表系统安全完整性等级为SIL 1。结果表明:该方法结合两种风险分析理论,分析结果与实际和理论统计结果符合性较好,具有一定地准确性和实用性,可以为定量确定系统SIL提供理论指导。     

城镇煤气管道漏损分析与风险评价

在管道漏损的各种因素分析与分类的基础上,建立管道漏损综合评价模型,结合事故树法和专家评分法,实现对管道运行状况的评价。事故树模型采用最小割集的方法描述事故树相应的结构函数,从而评价事故树各底层事件的结构重要度。根据专家评分法,对危害因素指标和后果进行评分,实现管道工作状态的风险评价。该分析和评价方法,为实现基于风险评价的风险控制与管理提供理论依据。     

Incident tree model and incident tree analysis method for quantified risk assessment: An in-depth accident study in traffic operation

Fault tree analysis (FTA) is a logically structured process that can help identify potential causes of system failure before the failures actually occur. However, FTA often suffers from a lack of enough probabilistic basic events to check the consistency of the logic relationship among all events through linkage with gates. Sometimes, even logic relationship among all events is difficult to determine, and failures in system operation may have been experienced rarely or not at all. In order to address the limitations, this paper proposes a novel incident tree methodology that characterizes the information flow in a system instead of logical relationship, and the amount of information of a fuzzy incident instead of probability of an event. From probability statistics to fuzzy information quantities of basic incidents and accident, we propose an incident tree model and incident tree analysis (ITA) method for identification of uncertain, random, complex, possible and variable characteristic of accident occurrence in quantified risk assessment. In our research, a much detailed example for demonstrating how to create an incident tree model has been conducted by an in-depth analysis of traffic accident causation. The case study of vehicle-leaving-roadway accident with ITA illustrates that the proposed methodology may not only capture the essential information transformations of accident that occur in system operation, but also determine the various combinations of hardware faults, software failures and human errors that could result in the occurrence of specified undesired incident at the system level even accident.     

Risk assessment of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree

The oxygen-enhanced combustor has the advantages of high burning efficiency and low emissions. However, it should not be promoted for industrial use until its reliability and safety have been fully recognized. A new methodology is proposed to assess the risk of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree. In addition, it is applied to a selected pilot semi-industrial combustor. To identify the hazard source comprehensively, the pilot is divided into four subsystems: the combustor subsystem, feed subsystem, ignition subsystem and exhaust subsystem. According to the operational parameters of flow (flow rate, temperature and pressure) and the component functions in different subsystems, the cause and effect matrix can be built using the structural model, and the relationship between the operational parameters and the effects of the change for the operational parameters on the system can be presented. Based on the results of cause and effect matrix, the FMEA can be built to describe the failed models and accident scenarios of the pilot. The main accident forms include leakage, injury, fire and explosion. Accordingly, with the severity and probability analysis of different accident forms, the fire and explosion accidents should be further accessed quantitatively using the fuzzy fault tree analysis. The fault trees can be obtained in accordance with the FMEA, and the qualitative assessments of the basic events can be collected by using expert scoring. A hybrid approach for the fuzzy set theory and weight analysis is investigated to quantify the occurrence probability of basic events. Then, the importance analysis of the fault trees, including the hazard importance of basic events and the cut set importance, is performed to help determine the weak links of the fire and explosion trees. Finally, some of the most effective measures are presented to improve the reliability and safety of the combustion system.     

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.