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.     

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.     

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.     

Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis

Failure of oil and gas transmission pipelines was analyzed by fault tree analysis in this paper. According to failure modes of pipeline: leakage and rupture, a fault tree of the pipeline was constructed. Fifty-five minimal cut sets of the fault tree had been achieved by qualitative analysis, while the failure probability of top event and the important analyses of basic events were evaluated by quantitative analysis. In conventional fault tree analysis, probabilities of the basic events were treated as precise values, which could not reflect real situation of system because of ambiguity and imprecision of some basic events. In order to overcome this disadvantage, a new method was proposed which combined expert elicitation with fuzzy set theories to evaluate probability of the events. As an example, failure probability of pipeline installation was assessed by using the proposed method, achieving its fuzzy failure probability of 6.4603×10⁻³. The method given in this article is effective to treat fuzzy events of FTA.     

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。     

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.     

故障树在含硫油罐火灾分析中的应用

含硫油罐爆炸主要是由自燃、明火、雷击和静电引起的,应用故障树分析法(FTA)对其进行了分析,建立了含硫油罐爆炸的故障树.采用下行法求出了系统的最小割集,通过故障树的定性分析和定量分析,提出了预防含硫油罐火灾爆炸事故的对策,给出了具体的防爆炸措施.故障树的分析结果可以为油罐的安全管理提供理论指导.     

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

A method is presented for analysis of reliability of complex engineering systems using information from fault tree analysis and uncertainty/imprecision of data. Fuzzy logic is a mathematical tool to model inaccuracy and uncertainty of the real world and human thinking. The method can address subjective, qualitative, and quantitative uncertainties involving risk analysis. Risk analysis with all the inherent uncertainties is a prime candidate for Fuzzy Logic application. Fuzzy logic combined with expert elicitation is employed in order to deal with vagueness of the data, to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing.The proposed model is able to quantify the fault tree of LPG refuelling facility in the absence or existence of data. This paper also illustrates the use of importance measures in sensitivity analysis. The result demonstrates that the approach is an apposite for the probabilistic reliability approach when quantitative historical failure data are unavailable. 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.     

SFT下的云化故障概率分布变化趋势研究

为了扩展空间故障树SFT的应用性,特别是处理具有离散性、随机性和模糊性(不确定性)的实际运行中系统产生的故障数据,利用云模型重构系统故障概率分布变化趋势的计算方法。通过故障概率分布变化趋势可得到系统故障概率随某一因素变化情况。建立云化故障概率分布变化趋势方法的目的在于,对于可靠性数据普遍存在的不确定性可使用云模型进行表示;构建的故障概率分布函数是连续的,可进行函数求导以方便得到变化趋势。将云化故障概率分布变化趋势方法应用于经典实例,得到了一些定性和定量结果。论述了该方法在理论和实际应用上的价值。     

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.     

模糊概率事件的故障树分析

许多职业事故的基本致因事件多属于模糊事件,其概率很难确定。本文以煤矿典型危害——内因火灾为例,探讨了模糊概率下的故障树分析问题。煤矿内因火灾故障树虽具有确定的结构形式,其基本致因事件的概率却无法统计。经过长期的生产实践,煤矿中一大批防火专家可以用自然语言较准确地描述基本事件发生的可能性,这就为故障树分析提供了有效信息。文中以模糊数学为基础,引入Delphi方法,征集并整理了25位专家对龙凤矿内因火灾致因的意见,确定了基本事件的模糊概率及其临界重要度排序,提出了行之有效的防治内因火灾措施。     

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。     

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。     

An extension of the fuzzy improved risk graph and fuzzy analytical hierarchy process for determination of chemical complex safety integrity levels

The risk graph (RG) is widely used to evaluate the safety integrity level (SIL) of safety instrument systems (SIS). However, subjective opinion-based conventional RGs cannot provide successful results for the problems of risk parameters, such as shortages or lack of data; hence, the output of a conventional approach lacks sufficient reliability. We introduced the fuzzy improved risk graph (FIRG), an extension of fuzzy set theory, to deal with possible ambiguities during SIL study and increase the reliability of conventional RGs. In the present study, the levels of consequences defined as linguistic terms were converted into qualitative intervals; therefore, by correlating the proposed approach with experts’ opinions and attributing weight factors, a desired SIL value was obtained. The output of this new approach can be compared directly with quantitative risk assessment techniques to improve the safety performance of industrial systems.     

计算机辅助事故树分析中的图形输入法

笔者提出计算机辅助事故树分析中事故树数据的图形输入法。通过详细讨论数据采集过程中数据结构的选用和算法设计 ,不但能方便地实现计算机辅助事故树绘图 ,而且在绘图的同时得到事故树的全部数据 ,进而可对事故树进行全部定性和定量分析。这种方法是计算机辅助事故树分析中绘图和数据输入方法的重要补充 ,同时也将有益于其他类型树及图的绘制和分析。最后 ,给出了一个实例 ,应用图形输入法得到满意的结果。该方法不仅是事故树的新绘制方法 ,也是全新的事故树数据输入法 ,是事故树算法的拓展和补充     

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.     

An extended HAZOP analysis approach with dynamic fault tree

An extended hazard and operability (HAZOP) analysis approach with dynamic fault tree is proposed to identify potential hazards in chemical plants. First, the conventional HAZOP analysis is used to identify the possible fault causes and consequences of abnormal conditions, which are called deviations. Based on HAZOP analysis results, hazard scenario models are built to explicitly represent the propagation pathway of faults. With the quantitative analysis requirements of HAZOP analysis and the time-dependent behavior of real failure events considered, the dynamic fault tree (DFT) analysis approach is then introduced to extend HAZOP analysis. To simplify the quantitative calculation, the DFT model is solved with modularization approach in which a binary decision diagram (BDD) and Markov chain approach are applied to solve static and dynamic subtrees, respectively. Subsequently, the occurrence probability of the top event and the probability importance of each basic event with respect to the top event are determined. Finally, a case study is performed to verify the effectiveness of the approach. Results indicate that compared with the conventional HAZOP approach, the proposed approach does not only identify effectively possible fault root causes but also quantitatively determines occurrence probability of the top event and the most likely fault causes. The approach can provide a reliable basis to improve process safety.     

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。     

原油集输联合站故障树分析研究

采用故障树分析法对原油集输联合站生产工艺流程和危险危害因素进行分析,确定原油集输联合站的故障树因素表,以该站故障为顶上事件,以火灾爆炸、介质泄漏、其他危险作为故障树的中间事件,建立联合站故障树。通过定性定量分析,求取联合站故障树的最小割集为77组,进而确定故障树顶事件的事故发生概率为5.68×10-3和底事件结构重要度,得出影响集输联合站安全性的重要因素为通风不良、储罐密封不良、液体腐蚀、盘管穿孔和人员误操作等。因而提出加强原油集输联合站安全监察和监控措施,及时地发现和处理故障,以提高联合站运行安全可靠性和生产效率。     

长江干线船舶碰撞原因的故障树分析一以武汉海事局辖区水域为例

以2007年武汉海事局辖区船舶碰撞资料为基础,利用故障树分析方法构建该水域船舶碰撞故障树,进行定性、定链分析,得到包括航行疏于戒备、车舵控制失误、疏于了望等14个主要危险因素及各因素的相关事故数。在故障树分析的基础上,构建布尔代数和最小割集,计算各危险旧素的概率重要度,以衡精各危险因素发生概率的变化给碰撞事故发生概率带来的影响;计算临界重要度,从敏感度和概率双重角度衡量每个危险因素的重要度。通过分析发现应急操作不当、违反其他规定、航行疏于戒备、违反分道通航、疲劳驾驶等人为因素是引起该水域船舶碰撞的重要原因。建议船公司重视船员应急培训,提高船员应急处置能力,海事管理机构加大相关法规宣传力度和监管力度。