基于BP神经网络的苯储罐泄漏事故风险评价模型研究

为了在事故发生之前对苯储罐进行风险评价，提出1种基于BP神经网络的泄漏事故风险评价方法，利用该方法构建了苯储罐的风险评价模型，并对模型进行了训练及验证。研究结果表明:BP神经网络成功完成了建模任务，且模型训练结果较好，可利用基于BP神经网络所构建的苯泄漏事故风险评价模型对苯储罐发生泄漏事故的风险进行评价。     

液化四氟乙烷小孔泄漏试验研究

采用高速摄影技术,考察了液化四氟乙烷发生小孔泄漏时,其水平泄漏和垂直泄漏的初始云团演化行为、泄漏的质量流率、喷射速度和喷射角,并与理论计算公式进行了对比。结果表明:水平喷射两相云团尾部出现涡流,涡流大幅加快了云团向空气中扩散的速率;垂直喷射的两相云团在地面形成液池,液池大幅增加了液化气体向空气中蒸发的速率。水平泄漏试验的喷射角与容器内超压变化规律相似,泄放初期喷射角逐渐增大,经历一段平坦期,到泄放末期喷射角减小。水平泄漏和垂直泄漏的初始喷射速度分别为25 m/s和20 m/s,与理论值26.6 m/s基本吻合。水平泄漏的质量流率的试验值和理论值分别为0.0598 kg/s和0.0684 kg/s,垂直泄漏的分别为0.0472 kg/s和0.059 6 kg/s,结果对比基本吻合,推荐的泄漏质量流率和小孔喷射速度公式可以用于液化四氟乙烷小孔泄漏。     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

液化石油气槽车泄漏处置专用接头套组的应用探讨

针对消防救援车辆缺乏专业堵漏和倒罐装备、应急处置受限等问题,研究采用专用注压接头套组与消防车配合,通过向事故槽车阀门注水加压或惰性气体的方式实施辅助堵漏,能够实现因地制宜、快速有效地解决现场液化石油气大量泄漏的问题,降低事故危害。     

应急修复耦合资源回收的实践-以一起化工企业突发环境事件为例

通过东莞市一起铜氨蚀刻液泄漏引致突发环境事件的应急处理过程,介绍了污染控制和应急修复技术的应用情况,通过将高浓含氨污水蒸发制取NH4Cl产品,以及将污水处理至优于《地表水环境质量标准》（GB3838-2002）之Ⅰ类水质要求,作为我国首例应急修复耦合资源回收制取化工产品的成功案例,为化工类企业突发环境事件的应急处理提供决策参考.     

锅炉过热器爆漏原因的统计分析和预防措施

以100余起公开报道的锅炉过热器爆漏事故案例进行统计分析为基础,将引起过热器爆漏的直接原因归纳为长期超温、短期超温、腐蚀、磨损和焊接缺陷,对产生事故的机理和主要原因进行了探讨和归类,认为运行管理不当是造成过热器爆漏的最重要方面。分析并提出了设计、安装、制造、检修和运行管理过程中对爆漏风险贡献最大的各单因素及其成因。针对造成爆漏的根本原因提出了预防措施,为锅炉的安全运行和合理检修提供了科学依据。     

泵设备机械密封泄漏事故防范技术探讨

分析了多起石化行业因果设备机械密封泄漏引发的重大火灾事故原因,研究表明:机械密封泄漏的诱发因素多是泵轴承严重故障后,机械密封过度磨损导致密封失效,使高温油料泄漏。为有效防范机械密封泄漏事故,提出防范措施:一是要加强泵轴承的监测,及时发现泵轴承存在的问题,避免泵轴承长期带病运行;二是要加强机泵组的联锁控制,当轴承出现严重故障后,能使机泵组及时停车,避免机械密封过度磨损导致泄漏。     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

埕岛油田海底管道漏磁检测与安全评估

提出了埕岛油田海底管道内缺陷漏磁检测需解决的主要问题,研发了325 mm管道内缺陷漏磁检测装置,确定了海底管道漏磁检测工艺流程,配套了管道检测发射装置、接受装置等相关设施,实现了海底管道的漏磁检测、缺陷分析和安全评估。     

高压直流输电换流阀冷却系统泄漏保护分析

提出了一种高压晶闸管换流阀冷却系统泄漏保护方法,当水冷却系统在一定时间内泄漏量超过换流阀要求的泄漏流量时泄漏保护能正确动作,同时避免由于冷却介质的热胀冷缩而引起误判断,对国内新建直流工程有指导意义。