Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

A bayesian network-based safety assessment method for solid propellant granule-casting molding process

The safety of the solid propellant molding process is vital for the stable production of high-quality propellants. Failure events caused by abnormal parameters in the molding process may have catastrophic consequences. In this paper, a Bayesian network (BN) model is proposed to assess the safety of the solid propellant granule-casting molding process. Fault tree analysis (FTA) is developed to construct a causal link between process variables and process failures. Subsequently, expert experience and fuzzy set theory (FST) are used to obtain failure probabilities of the basic events (BEs). Based on the mapping rules, FTA provides BN with reliable prior knowledge and a network structure with interpretability. Finally, when new evidence is obtained, the probability is updated with the diagnostic reasoning capability of BN. The results of the sensitivity analysis and diagnostic inference were combined to identify key parameters in the granule-casting molding process, including curing temperature, vacuum degree, extrusion, calendering roll distance, length setting value, holding time, and polish time. The results of this paper can provide effective supporting information for managers to conduct process safety analysis.     

游乐设施危险源、损伤、失效和故障概念辨析

针对游乐设施行业危险源、损伤、失效和故障四个概念的认知差异,通过研究相关领域这四个概念定义内涵及外延,结合游乐设施安全保障要求高、人-机-环交互频繁、运行工况复杂的特点,重新定义游乐设施这四个概念,辨析相互之间的逻辑关系,并结合游乐设施事故案例进行解析.结果表明:新定义对游乐设施危险源、失效、损伤和故障之间的关系阐述更加清晰准确,为后续的风险评价奠定良好基础.     

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down.A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator.     

基于时频分析的裂纹转子碰摩故障特征研究

为研究转子系统耦合故障特性,采用有限元方法建立了含有横向裂纹、转静碰摩的非线性转子动力学模型。首先研究了不同转速下裂纹、碰摩单一故障下转子系统的振动响应,其次研究了两种故障耦合情况下系统的振动响应特征。采用波形图、FFT谱图、瞬时频率和Hilbert-Huang时频谱(HHS)相结合的方法对故障转子振动信号进行了分析。分析结果表明:运用多种时频分析相结合的方法可以较为全面地了解转子的故障特征,裂纹转子在1/5、1/3临界转速时会发生较为明显的5X、3X谐波,且裂纹的产生会导致响应幅值增大,从而引起更为严重的碰摩。      

某热处理厂火灾事故的故障树分析研究

故障树分析法(FTA)是根据系统可能发生的事故或已经发生的事故结果,来研究与事故发生有关的原因、条件和规律,进而实施危险辨识的系统工程方法。本文通过对一起火灾事故的FTA分析,研究相应的控制措施。     

城乡接合部居民楼火灾风险评价及防控对策研究

为了准确探究城乡接合部居民楼火灾事故致因机理,预防与控制城乡接合部日常生产与生活过程中引发火灾事故的有效途径,建立信息面更全、实际性更强的火灾风险评估模型是目前行之有效的手段。基于湖南省某地发生火灾事故的实际情况,根据事故树分析法,以城乡接合部居民楼火灾事故为顶事件构建事故树,计算得到事故树的最小割集、最小径集和结构重要度,研究城乡接合部居民楼火灾事故的发生模式、致因因素及影响程度,为改善城乡接合部居民楼火灾安全提供重要的理论依据,并提出相应的防控措施及对策。     

A review on different pipeline fault detection methods

Pipeline faults like leakage and blockage always create problem for engineers. Detection of exact fault quantity and its location is necessary for smooth functioning of a plant or industry and safety of the environment. In this paper brief discussion is made on various pipeline fault detection methods viz. Vibration analysis, Pulse echo methodology, Acoustic techniques, Negative pressure wave based leak detection system, Support Vector Machine (SVM) based pipeline leakage detection, Interferometric fibre sensor based leak detection, Filter Diagonalization Method (FDM), etc. In this paper merit and demerits of all methods are discussed. It is found that these methods have been applied for specific fluids like oil, gas and water, for different layout patterns like straight and zigzag, for various lengths of pipeline like short and long and also depending on various operating conditions. Therefore, a comparison among all methods has been done based on their applicability. Among all fault detection methods, Acoustic reflectometry is found most suitable because of its proficiency to identify blockages and leakage in pipe as small as 1% of its diameter. Moreover this method is economical and applicable for straight, zigzag and long, short length pipes for low, medium and high density fluid.     

Spatial distribution of soil radon as a tool to recognize active faulting on an active volcano: the example of Mt. Etna (Italy)

This study concerns measurements of radon and thoron emissions from soil carried out in 2004 on the eastern flank of Mt. Etna, in a zone characterized by the presence of numerous seismogenic and aseismic faults. The statistical treatment of the geochemical data allowed recognizing anomaly thresholds for both parameters and producing distribution maps that highlighted a significant spatial correlation between soil gas anomalies and tectonic lineaments. The seismic activity occurring in and around the study area during 2004 was analyzed, producing maps of hypocentral depth and released seismic energy. Both radon and thoron anomalies were located in areas affected by relatively deep (5-10 km depth) seismic activity, while less evident correlation was found between soil gas anomalies and the released seismic energy. This study confirms that mapping the distribution of radon and thoron in soil gas can reveal hidden faults buried by recent soil cover or faults that are not clearly visible at the surface. The correlation between soil gas data and earthquakes depth and intensity can give some hints on the source of gas and/or on fault dynamics.     

铁路安全预警系统的研究和实现

结合哈尔滨铁路局实际运营系统 ,基于事故树分析理论 ,探讨了铁路安全预警系统的实现。首先论述了事故树的建立方法和以事故树分析法为基础的铁路安全预警系统的核心算法 ,然后讨论了具体实现的数据结构和事故树编码方法 ,最后简要提出了铁路安全预警系统的系统设计思想