A novel knowledge database construction method for operation guidance expert system based on HAZOP analysis and accident analysis

An expert system for operation guidance will contribute to identifying the operatoration problems and indicating the resolutions thereof, because the information stored in the expert system can be utilized to resolve the corresponding technical problems. However, there are several problems that should be solved in the practical application of the expert system, such as lack of corresponding knowledge or resolutions utilized to cope with the problems, inapplicable resolutions, too many resolutions for the operators to choose from to obtain the best one in the first time, etc. Obtaining and storing as much as information in the database of the expert system are important issues in the construction process of the expert system. The accident analysis results contain a limited number of accident cases and the HAZOP analysis only refers to a single deviation analysis. This paper has presented a novel knowledge database construction method for an operation guidance expert system based on the HAZOP analysis and the accident analysis, which can be used to resolve the above problems. The HAZOP analysis results are combined with the accident analysis results and the combination information can be stored in the database of the expert system, and can be employed to forecast accidents or identify accident causes. The structures of the operation guidance table and the accident investigation table have been illustrated. The residuum hydrotreating process expert system is taken as an example to illustrate the knowledge database construction method. With the aid of this expert system, the operators will well understand the operations and adopt the best resolutions to deal with the abnormal situations. Also the operators can identify potential risks existing in the plant which will result in accidents according to the accident analysis results associated with the HAZOP analysis results.     

基于三角模糊数的HAZOP分析在石油化工装置中的应用

工艺危害分析强调运用系统的方法对危害进行辨识、分析,并采取必要的措施消除和减少危害。HAZOP分析能对工艺过程非常系统、全面的进行分析,但传统的HAZOP分析在量化风险时,对于偏差原因发生的可能性评价存在较大的主观性。本文对于没有统计资料的HAZOP分析偏差原因发生可能性,采用专家打分法,利用三角模糊数来表示其模糊发生概率。对于有统计资料的偏差原因,直接表示成三角模糊数。这种方法能够很好的表示HAZOP分析偏差发生概率。介绍了基于三角模糊数的HAZOP分析步骤,并在石油化工装置中进行了应用。这对HAZOP分析技术在石油化工装置中的推广具有重要意义。     

基于数据挖掘的化工生产事故致因主题抽取

为充分挖掘化工生产事故数据中的有效信息和潜在规律,提高对化工事故认知水平,针对某化工集团2010—2016年共1 578起事故数据,利用社会网络分析等方法揭示事故要素间的关联关系;运用潜在狄利克雷分配（LDA）模型进行事故聚类,并抽取到5个事故致因主题。研究结果表明:LDA主题模型等数据挖掘技术能有效挖掘大量事故数据中的潜在信息;5个事故致因主题中,4个涉及到人因或组织层面的缺陷;员工注意力不集中和现场风险管理不足这2个致因主题间具有较强相关性;员工注意力不集中、现场风险管理不足以及设备问题是导致事故发生的主要原因。     

化工生产事故预防信息系统研究

为指导操作人员正确地处理化工生产过程中的问题,防范人为误操作导致的事故发生,开发了以化工生产的危险与可操作性分析结果和典型事故原因分析结果为知识库的事故预防信息系统.系统实时在线监测化工生产过程中的关键变量,通过判定变量间的影响关系,实现对化工生产过程潜在危险的辨识、预警并给予实时操作指导,以确保生产安全,提高装置的生产效率.最后,以丙烯聚合工艺为例,在多功能过程试验控制平台上进行了验证,探讨了事故预防信息系统的应用方法.     

A new approach of integrating industry prior knowledge for HAZOP interaction

Accidents often occur in the petrochemical industry, which have a negative impact on society and the environment. Learning Process Safety Knowledge (PSK) from accident cases is essential to prevent accidents and improve safety level. Hazard and Operability Analysis (HAZOP) is a popular hazard risk analysis method. Its report contains large-scale PSK, which can provide safety analysis and decision support for the industry. Subject to the characteristics of PSK, existing researches mine them in the form of sequence labeling. However, there are two intractable problems that cause the PSK mined by the model to be inaccurate. (1) PSK in HAZOP is domain specific, which is rare or even absent in general-domain texts. (2) The entity boundaries are ambiguous. Most domain-specific entities for HAZOP lack boundary characters. Inaccurate security knowledge is not acceptable from the perspective of process safety engineering. To solve the problems, we present a PSK mining architecture with External Lexicon Prior knowledge called EDPMA, EDPMA is prior knowledge-based multi-task HAZOP knowledge mining model. Specifically, EDPMA consists of prior knowledge constructor and sequence labeling model. The prior knowledge constructor expresses prior knowledge in the form of word embedding by three steps. For the sequence annotation model, we improve its embedding and decoding layers. The former incorporated the word vectors generated by the prior knowledge constructor, and the latter added the task of entity boundary prediction. We conduct multiple evaluation experiments on HAZOP datasets. The experimental results show that the accuracy, recall and F1-score of the EDPMA model are 92.92%, 91.85% and 92.38% respectively, which is better than the existing research. Our study represents a meaningful attempt to introduce prior knowledge in HAZOP knowledge mining and makes an important contribution to intelligence the field of process safety.     

Evaluation on consequences prediction of fire accident in emergency processes for oil-gas storage and transportation by scenario deduction

This paper takes the safety in emergency processes as the starting point, from the perspective of scenario deduction, to study the consequences of fire accidents for oil-gas storage and transportation. Through the statistical analysis of actual accident cases, 19 frequently occurring basic scenarios in emergency processes are summarized. The scenario evolution paths of fire accidents for oil-gas storage and transportation are given by analyzing the evolution law of the accident development. Fuzzy numbers are introduced to express experts' qualitative judgment on accident scenarios. The empirical probabilities of scenario nodes are obtained by defuzzification calculation, and the state probability of each scenario node is calculated by using the dynamic Bayesian network joint probability formula. Under the comprehensive consideration about the probability statistics of actual accident cases, the critical scenario nodes on the evolution path and their final scenario probabilities are jointly determined to realize the optimization of the scenario evolution path. By constructing the correlation between the optimized scenario evolution path and the accident consequences, an accident consequence prediction model is established. The occurrence probability of accident consequences is calculated by the defuzzification method and dynamic Bayesian network. The accuracy of the consequence prediction model is verified by the July 16 Dalian's Xingang Harbor oil pipeline explosion accident. The research results provide scientific basis for helping decision makers to make the effective emergency measures that are most conducive to the rapid elimination of accidents and reducing the severity of accident consequences.     

Association analysis of accident factors in petrochemical storage tank farms

In order to identify and clarify the association between the factors leading to accidents in a petrochemical tank area, this study analyzes investigation reports of 212 petrochemical tank farm accidents and combines this with the “association rule” mining and science related to complex networks. The main risk factors are determined and a risk factor data set is constructed; 75 association rules are extracted from the factor data set based on the Apriori algorithm. Then the obtained association rules are used to construct an accident factors network of the petrochemical storage tank area, and the topology characteristics of the network are further analyzed to reveal the importance of factors. Factors with large node degree, betweenness, and clustering coefficients are obtained, such as “violation of operating regulations”, “high concentration of flammable gas in the air”, “lack of experience and professional skills”, etc. These factors play an important role in the formation and development of accidents. The results also show that the accident cause network of the petrochemical storage tank area has a small average shortest path length and a large cluster coefficient, indicating a relatively close connection between the accident factors. The contributions of this study is not only extracting the hidden relationships among contributory factors to tank farm accidents using association analysis, but also revealing which factors are more important for the tank farm safety through the complex network.     

基于主成分分析法的液体管道泄漏后果综合评价模型

基于主成分分析和后果评价模型,提出了一种液体管道泄漏后果综合评价方法。将液体管道泄漏后果划分为火灾、爆炸和中毒3大类14个基本指标,建立后果评价指标体系。在VCE等后果模拟计算的基础上得到初始数据,运用SPSS软件处理相关数据,使用主成分分析法得到各指标相互独立的综合评价模型。选择天津港某码头进行实例分析,运用该方法对该港口储运的15类有代表性液体危险化学品进行综合评价,得到了各化学品的综合评价值以及按照其发生泄漏后危险性大小的排序。结果表明,该方法适用于评价港口码头等储运多种液体危险化学品的行业。     

A new intelligent assistant system for HAZOP analysis of complex process plant

There are several problems that should be solved in the practical application of HAZOP analysis, such as the inheritance instrument of experience knowledge, the classification of accident reasons, the recurrence of analysis process and the verification of analysis results. This paper presents a new HAZOP assistant program named HELPHAZOP, which can be used to cope with these problems. With the aid of this program, a number of influence relationship models, which can be utilized to present the relationship structure of the whole system, can be established, and a variety of spread paths, which can be employed to describe the occurrence of the accidents, can be identified. These models and paths can help analyzers to understand the analysis process of different chemical processes and to verify the analysis results. Experience knowledge or information of process parameters stored in this program, including deviations, abnormal reasons, consequences and disaster-causing ways, can contribute to the analysis of some new plants. The program has been applied in the HAZOP analysis process of residuum hydrotreating process. The probability of the human errors which would be happened because of the misunderstanding or the deficiency of plant experience in the HAZOP analysis has been reduced and the accuracy, practicability and analysis efficiency of the accident forecast have been greatly improved.     

基于传递熵与KELM的炼油化工过程风险传播路径分析方法

基于炼油化工过程复杂,设备众多,某一设备的监测变量发生扰动可能会传播至其相邻设备引发出一系列故障链。现有方法多是针对某一设备进行监测与诊断,以期降低事故后果,而忽视了对过程风险传播路径的预测以防止事故的发生。因此,提出一种基于传递熵与核极限学习机的炼油化工过程风险传播路径分析方法,该方法针对某一工艺扰动,分析其在风险发展过程中的扰动传播过程,基于传递熵分析法建立炼油化工过程风险传播推绎模型;并提出一种基于KELM的风险传播搜索方法,预测风险传播路径;将该方法应用于分馏塔冲塔过程。研究结果表明:该方法可辨识出未来一段时间内风险的可能传播路径,以便操作人员及时采取预防措施,保证过程安全及产品质量。     

HAZOP研究与故障树分析在合成氨装置危险辨识中的应用

合成氨装置的原料、产品危险性高,并且生产过程复杂,因此在运行过程中可能导致火灾、爆炸、中毒等事故,有些事故甚至给社会和环境造成严重破坏.对HAZOP研究与故障树分析进行组合,应用在合成氨装置的危险辨识中.通过HAZOP研究,合成氨主体装置共发现风险因素23项,其中合成氨装置的合成气压缩单元安全隐患较多,因此对其进行故障树分析,合成气压缩机单元火灾、爆炸故障树的最小割集为72个,最小径集为6个.从基本事件结构重要度结果来看,压缩机三级出口压力探测器( PIA3-2)故障,对压缩机发生火灾、爆炸的影响程度最大,应重点防范.     

基于模糊数学的石油化工装置HAZOP风险分析技术研究

对传统的HAZOP分析中偏差原因发生可能性进行量化。对于有统计数据的,根据行业数据、公司经验及企业事故建立HAZOP风险分析统计数据库;对于没有统计数据的HAZOP分析偏差原因发生概率,通过专家主观评判,用模糊数理论将专家自然语言转换为模糊数,采用左右模糊排序法将模糊数转换为模糊失效概率值。研究了偏差后果严重程度的划分标准,并根据偏差原因概率和偏差后果严重程度确定风险等级,利用风险矩阵得出偏差风险的大小。从而把HAZOP分析方法从定性改进为半定量的分析方法。据此对石油化工装置进行了HAZOP风险分析。     

基于FMEA和HAZOP的综合分析方法及应用研究

氯乙烯聚合生产过程复杂、设备众多,事故风险高,诸多危险因素极易引发火灾、爆炸、中毒等事故,导致生产停顿、设备损坏,甚至会造成大量人身伤亡和巨额财产损失。本文将故障类型和影响分析（FMEA）和危险性和可操作性研究（HAZOP）相结合,对某氯碱生产企业氯乙烯聚合生产过程的生产设备和工艺的危险性进行了系统安全分析,并科学的提出了一系列预防控制措施。这两种评价方法优势互补,不仅可以更全面合理的找出可能导致事故发生的不安全因素,而且更为系统安全分析提供了一种新的途径,使得系统的危险性分析更科学、完整和全面,这为有效预防和减少事故的发生提供了理论支撑。     

催化裂化装置火灾及爆炸事故后果分析

对石油化工企业典型生产装置--催化裂化装置发生火灾及爆炸事故后果进行分析,研究分析了催化裂化装置油浆泵泄漏引发池火灾和石油气泄漏引发无约束蒸气云爆炸两种事故的后果情况,给出这两种事故的各种伤亡半径,从而直观的为企业提供了事故后果情况,为企业的事故预防工作提供依据.     

相关关系和因果关系在事故分析中的应用——研究综述与启示

从事故中吸取教训是安全科学的主要任务,回顾拆解曾经的研究成果,从理论基础研究和应用实践研究两个方面进行了文献综述,以期达到总结前期成果和启示后续研究的目的。结果表明,在横向研究中,一方面在全学科的宏观层面,相关和因果的研究在经济与管理科学和社会科学中的开展较为成熟,而在安全科学与灾害防治领域还处于发展阶段。同时自2003年至2012年,是相关关系和因果关系研究成果的快速发展时期;另一方面在生产安全事故范围的微观层面,相关和因果的研究相对集中于事故控制阶段的相关关系的研究;在纵向研究中,对于生产安全事故分析时需要进行的描述、解释、预测和控制4个阶段中在选取相关关系和因果关系时有所侧重,在事故描述阶段偏重使用相关关系;在事故解释阶段,如果是解释事故发生的可能性主要偏重使用因果关系。如果是解释事故发生的损失程度主要偏重使用相关关系;在事故预测阶段,偏重相关关系;在事故控制阶段偏重因果关系。     

Process industry accidents in Sri Lanka: Analysis and basic lessons learnt

Accidents in the process industry could be prevented or reduced by having good safety management measures. Such preventive measures could be further improved through the experiences and lessons learnt from past accidents. Therefore, analysis results of past accidents are valuable sources of information for determining root causes and as case material to prevent and reduce the adverse consequences of accidents in the process industry.This paper looks at accidents in the process industry that have occurred in the past 10 years from 1997 to 2006 in Sri Lanka to gain an understanding of the nature and consequences of accidents. Lessons and main areas of concern to improve safety in the Sri Lanka process industry are discussed. The analysis is done for different event types based on specific operating process stage during which the accident occurred such as processing, loading and unloading, repair and maintenance and storage, the immediate effect types such as fire, explosion, chemical releases and emissions and the consequences of each accident. Fire incidents were observed in 38 accidents analyzed. The results show that the highest number of accidents has occurred during processing operations followed by accidents during maintenance and repair work. The cause analysis shows that many accidents have occurred due to technical and human failures.The accidents are then classified according to the severity of the consequences in order to compare the nature of accidents experienced in Sri Lanka with respect to accidents in other countries in the world.     

企业事故调查分析方法探讨

对企业事故调查分析方法进行了探讨,明确了企业事故调查分析程序,提出了具体的事故调查取证方法、事故原因分析方法和事故责任分析方法。     

在役柴油加氢装置HAZOP分析技术

柴油加氢装置属甲类火灾危险生产装置,为了保障其安全生产,实现事故早期预防,对其进行风险分析和安全评价势在必行.HAZOP分析方法是流程工业广泛使用的一种危险辨识和分析方法,具有较好的系统性和完备性.首先介绍了HAZOP分析方法的由来及应用情况,其次分析了在役装置HAZOP分析的难点,并提出了相应的建议,然后详述了在役装置HAZOP方法的分析流程.最后以中石油某石化公司在役柴油加氢装置为例进行了HAZOP分析,辨识出可能存在的安全隐患和潜在危险,对较高风险提出了必要的安全保护措施和合理的改进建议.结果表明,HAZOP分析是提高在役装置安全性的一种有效手段,其结果为装置安全管理提供了可靠的依据.     

数据挖掘与现场调查结合的电动汽车事故分析

为了解电池热失控引起的电动汽车自燃事故起因,降低事故发生率,统计梳理2020年新能源汽车起火事故概况,并基于动力电池失效机制和车辆运行数据,提出一种融合事故阶段安全参数关联分析、事故现场调查和全生命周期数据一致性分析的事故多维分析方法,采用该方法深入剖析一起电动汽车起火事故.研究结果表明:事故多维分析方法可通过探究事故...