Fault diagnosis of pipeline and pump unit systems using status coupling analysis

Earlier studies on fault diagnosis of the pipeline and pump unit systems (PPU) relied mainly on independent equipment analyses, which usually lead to false alarms because of the loss of information fusion. The aim of this study is to utilize the status coupling relationship to improve fault detection sensitivity and reduce false alarm rate. A real-time status identification of related equipment step is added between capturing abnormal signals and listing out diagnosis results. For example, when the pipeline pressure fluctuation is found abnormal, a status analysis of pump units is performed immediately, if the pump units are proven to be operational normally, then the pipeline leak alarm is acknowledged valid. The logical reasoning algorithm is used to capture abnormal conditions of pipeline pressures. The pump unit faults are captured by combining information from multiple sources. Field applications show that the proposed method significantly improves the PPU fault detection capability on fault detection sensitive and accuracy.     

Statistical fault detection using PCA-based GLR hypothesis testing

Safe process operation requires effective fault detection (FD) methods that can identify faults in various process parameters. In the absence of a process model, principal component analysis (PCA) has been successfully used as a data-based FD technique for highly correlated process variables. Some of the PCA detection indices include the T² or Q statistics, which have their advantages and disadvantages. When a process model is available, however, the generalized likelihood ratio (GLR) test, which is a statistical hypothesis testing method, has shown good fault detection abilities. In this work, a PCA-based GLR fault detection algorithm is developed to exploit the advantages of the GLR test in the absence of a process model. In fact, PCA is used to provide a modeling framework for the develop fault detection algorithm. The PCA-based GLR fault detection algorithm provides optimal properties by maximizing the detection probability of faults for a given false alarm rate. The performance of the PCA-based GLR fault detection algorithm is illustrated and compared to conventional fault detection methods through two simulated examples, one using synthetic data and the other using simulated continuously stirred tank reactor (CSTR) data. The results of these examples clearly show the effectiveness of the developed algorithm over conventional methods.     

基于Bayesian网络的常减压装置设备故障概率分析

为分析影响常减压蒸馏装置平稳运行的设备失效模式及故障部件,基于1 151条设备故障数据,采用Bayesian网络分析方法,分别对离心泵、压缩机、电动机构建基于Bayesian网络的设备故障概率分析模型,分析故障部件、失效模式、故障后果之间的定量概率关系。研究结果表明:离心泵、压缩机、电动机停运的关键致因部件分别为轴承箱密封故障、活塞环故障、轴承故障,同时得到导致设备停运的故障部件敏感度排序。研究结果有助于提高设备故障风险防范及检维修工作效率,同时可为备件优化方案提供思路。     

Building an Executive Information System for Maintenance Efficiency in Petrochemical Plants—An Evaluation

This study used the manufacturing process in the petrochemical industries as an example and developed a dedicated maintenance programme and executive information system (EIS) for this industry. The software for EIS was established on a CMMS platform, with logical and extractive analysis used to store the information in a KPI databank. The system developed can provide plant managers and engineers with a complete summary of information and keep them updated regarding the present status of their maintenance efforts. The objective of this study was to establish a management system for maintaining knowledge in the petrochemical industries, such as the management of standard operating procedures (SOPs), historical records and the analysis of data for the facility. To design the software, a review of petrochemical facility was purposed to enhance the maintenance efforts and facilitate the decision-making process. The main functions of the system include asset reliability analysis, failure analysis and maintenance benefit cost analysis. For the petrochemical industry, the impact of safety and environment caused by equipment malfunction is more substantial than that of other industries. If executives can manage essential points effectively and make decisions according to a key performance index, risks to safety and environment, which result from equipment malfunction, can be decreased and safety can be enhanced for petrochemical refineries.     

基于RBI技术的海上平台延期服役静设备定量化安全评估技术

针对海上延期服役平台静设备的安全风险评估与控制问题,应用RBI风险评估技术的评估理论和方法对海上延期服役平台静设备的定量化安全管理方法进行了实践和探索,并选择某延期服役平台进行风险分析相关结论的工程验证。其具体过程是运用定量RBI技术,首先根据工艺流程和介质特点对海上平台静设备分别进行了物流回路和损伤回路的划分,并以此为基础对延期服役平台静设备的安全风险进行定量评估,进而得出各静设备单元的失效可能性、失效后果及风险等级,最后通过得出的损伤模式、损伤机理及对应的腐蚀速率,从而制定针对性的检测策略。将利用这些检验策略所检测出的真实情况与分析结论进行对比,最终验证了RBI技术在延期服役平台静设备风险评估方面具有很强的适用性。     

基于文本故障视角的通信保障应急预案有效性评估研究

应急通信预案作为应急通信保障的行动纲领,其文本有效性将直接影响预案有效性,进而影响到整个应急救援行动的有效性。针对预案文本有效性问题,从文本故障视角出发,基于故障树分析法构建通信保障应急预案有效性评估模型;采用语句成分分析法和伪代码转换法对预案进行故障形式诊断,结合标准故障树,计算预案的有效性并给出具体评估步骤;最终,通过4个样本预案对模型进行实例分析,结果表明:该模型能够提高预案文本故障的识别效率,对预案的编制或修订具有参考意义。     

固定消防设施在扑救商场火灾中的应用及其故障对策研究

当固定消防设施在不能正常使用的情况下,研究消防队员如何协助单位值班人员将消防控制设施恢复自动状态,在第一时间内利用固定消防设施进行火情侦察,疏散救人,并启动喷淋泵、消火栓泵和防排烟风机,同时,分析如何将单位的固定消防设施和消防队的移动消防装备相结合,通过技术、战术配合,内外联动,提高灭火救援效率,有效控制火势、扑灭火灾。     

浮头式换热器故障树的建立

通过现场调研，运用故障树对浮头式换热器常见故障进行分析，得出浮头式换热器系统的主要故障为腐蚀导致的泄漏。从而，从设计、焊接制造、安装、操作维护等几个环节提出改进措施，为浮头式换热器的可靠性分析提供指导。     

Embedding the human factor in road tunnel risk analysis

The paper is focusing on road tunnel safety and builds upon the Directive 2004/54/EC launched by the European Commission; the latter sets basic requirements and suggests the implementation of risk assessment in several tunnel cases apart from technical measures imposed on the basis of tunnel structural and operational characteristics. Since the EU Directive does not indicate the method for performing risk assessment, a wide range of methods have been proposed, most of them based on quantitative risk assessment (QRA). Although the majority of current road tunnel QRAs assess physical aspects of the tunnel system and consider several hazards concerning the transportation of dangerous goods through a tunnel, they do not take into account, sufficiently, several organizational and human-related factors that can greatly affect the overall safety level of these critical infrastructures. To cope with this limitation this paper proposes a fuzzy logic system based on CREAM method for human reliability analysis (Hollnagel, 1998) in order to provide more sophisticated estimations of the tunnel operator's performance in safety critical situations. It is deduced that a human reliability analysis component to analyze operator performance, like the fuzzy system proposed here, is important for risk analysts. Consideration of organizational and human factors will enhance risk analysts’ studies and highlight the uncertainty related to human performance variability.     

基于PCA_Fuzzy_RF模型的煤层底板突水预测

针对煤层底板突水问题,提出了基于主成分分析、模糊数学和随机森林的一种新预测模型。首先通过主成分分析将6个影响因素(水压、采高、隔水层厚度、断层落差、煤层倾角、断层距工作面距离)进行降维,提取4个主成分因子,其次对主成分因子进行模糊化,作为随机森林模型的输入变量,建立基于PCA_Fuzzy_RF的煤层底板突水预测模型。利用华北矿区实测资料的50组数据作为PCA_Fuzzy_RF模型的训练数据,10组数据作为测试数据,并将预测结果与BP神经网络及Fisher模型进行对比分析,结果表明,PCA_Fuzzy_RF模型的误判率为0,适用于解决煤层底板突水问题。     

A framework for dependability engineering of critical computing systems

This paper presents a development model focused on the production of dependable systems. Three classes of processes are distinguished: (1) the system creation process which builds on the classical development steps (requirements, design, realization, integration); (2) dependability processes (i.e. fault prevention, fault tolerance, fault removal and fault forecasting); and (3) other supporting processes such as quality assurance and certification. The proposed approach relies on the identification of basic activities for the system creation process and for the dependability processes, and then on the analysis of the interactions among the activities of each process and with the other processes. Finally, to support the development of dependable systems, we define for each system creation activity, a checklist that specifies the key issues that need to be addressed with respect to each dependability process.     

Method to assess and optimise dependability of complex macro-systems: Application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately.A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems, environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation.The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.     

Modelling of heating furnace fire scenarios using fault tree analysis,a bayesian network,and a thermal transfer method for system reliability analysis

Energy production for oil companies requires high-performance equipment. However, after a certain period of use, this equipment could be damaged, causing numerous problems and defects, impeding production, and leading to incidents that may cause material and human losses. Therefore, it is necessary to master the performance parameters of each equipment, which are key indicators of its functionality and can indicate the possibility of reusing it after inspection and diagnosis. However, it is worth noting that the studied system is a vertical cylindrical furnace in Algeria's refinery. This paper describes a new hybrid approach, a methodology that evaluates system reliability by combining two studies. The first is based on the surety of the system's functioning through an analysis with a fault tree to identify the risks, followed by a quantitative analysis using a Bayesian method. The second study follows the thermal calculation of the equipment's performance parameters, namely: the thermal efficiency (η), heat transfer coefficient (h), and heat absorbed quantity (Q), using heat balance equations to quantify the heat absorbed quantity and identify the fluid flow regime inside the tube. The calculation considers three cases: The design case, the failure case, and the after renovation case. The originality of this work appears when the collected findings from the second study are fed into the first study's Bayesian Network (BN) to analyse the system's reliability using the calculated parameters. Then, BN is used to calculate the Probabilistic Importance Factors (PIFs) in order to identify the most impactful system components. Finally, a prediction analysis was conducted. The latter reveals that one of the furnace's major faults is the fumes accumulation inside the combustion chamber. Corrosion, overheating, coke formation inside the tubes, dumper deformation, and burner tip clogging all contribute to this fault.     

多因素影响下系统故障预防的多方案比选方法研究*

为研究多因素影响下系统遭遇危险事件前预防方案的选优,在集对分析和空间故障树基础上提出比选方法。首先,论述集对分析与空间故障树理论结合的可行性;其次,研究系统故障预防的多因素多方案比选方法和步骤;最后,通过实例进行分析。研究结果表明:停运方案没有因素分量系数影响,其损失是停运带来的经济损失;无措施方案的系统常分量系数最小,因素分量系数最大;采取措施方案中,当常分量系数相差不大时,因素分量系数积最小者为最优方案。使用赵森烽-克勤概率表示危险事件的发生特征是可行的;常分量系数代表方案对系统故障预防效用的可靠性,因素分量系数代表该可靠性的稳定性;结合常分量系数和因素分量系数即可确定最优方案。该方法适合于故障发生对因素变化敏感的系统。     

Improving body posture while fueling with a newly designed pump nozzle

Background. Although petrol pumps are a very common and highly used simple technology, their design consideration for comfort and safety to prevent high-pressure load and musculoskeletal injuries to the body is a neglected area in many countries including Iran. Objectives. This study attempted to design a new pump nozzle, and to assess the differences in musculoskeletal load related to body posture when a price/volume display is mounted on the pump nozzle. Methods. For postural analysis, photographs recording the posture of 100 randomly selected customers while fueling at petrol pumps and the rapid upper limb assessment (RULA) technique were used. Results. The results of this study showed that RULA scores improved significantly after the newly designed pump nozzle was used. Conclusion. The newly designed pump nozzle is useful in reducing load related to body posture while fueling.     

海洋钻井平台事故致因分析与评价指标研究

该文在广泛调研国内外已发生的海洋平台事故基础上,从人因失误、工艺设备、物料危险、管理缺陷和危险环境五个方面系统分析事故致因因素,提出海洋钻井平台事故致因评价框架,提出5个一级评价指标和24个二级评价指标,根据层次分析法,计算确定各指标的标准权重值.最后针对某在役海洋钻井平台,开展实例研究.为实际评价海洋钻井平台事故风险提供一种新方法,具有一定的实际应用价值.     

煤矿安监系统数据通信可靠性的研究

煤矿安全生产监控系统的通信网络可归纳为单分站单设备、单分站双设备、双分站单设备和双分站双设备几种组网模式,通过对其任务可靠性和基本可靠性进行比较分析,综合考虑任务完成概率和维护成本两方面的要求,提出了双分站,局部(高故障点处)双设备的组网模式,以期有效提高通信网络的系统可靠性。     

锅炉转动机械运行故障的分析与判断

结合典型实例介绍了在锅炉运行中判断给水泵、风机等转动机械故障及基本分析方法和处理方法，亦即根据运行中转动机械的故障特征，通过听、看、摸、闻，去检查寻找运行故障中的表面现象，来确定故障部位、原因并处理。     

一种改进的CSCA+PCA化工过程异常检测技术

为了解决化工过程异常检测时因参数众多且数据庞杂而导致一些异常无法被有效检出的问题,在Brownlee的克隆选择分类算法（CSCA）基础上,通过引入主成分分析（PCA）技术,进行数据降维和数据重整,探讨了人工免疫算法在化工过程异常检测中的适用效果和技术方案,以TE过程数据作为样本进行异常检测和分类实验。结果表明,过程异常数据的规模、属性的数目对CSCA异常检测效果具有明显影响,而通过主成分分析进行数据降维之后,CSCA检测效果有所提高;进一步的数据重整之后,CSCA对过程异常分类辨识的准确率可提升到85%以上;基于CSCA+PCA的数据降维及重构之后的过程异常检测技术方案,可以获得较高的异常检测准确率,从而一定程度上为化工过程安全运行提供技术保障。     

核电站重要敏感性设备分析

核电站重要敏感性设备管理是国内首次采用归纳法和演绎法对核电站重要敏感系统和设备进行识别和设备分级的一种新方法。目标是为了找到导致反应堆紧急停堆、强迫停机和非计划跳机跳堆风险的主要部件 ,并采用 80 - 2 0的原理进行有效的管理 ,建立有效的风险管理 (预防、探测、改正行动 PDC ,Prevention/Detec tion/Correction)大纲和PDC管理数据库 ,并对大部分的重要敏感设备的子部件进行的FMEA(FailureModeandEffectAnalysis)分析 ,识别其失效机理 ,从而确定重要敏感设备清单和预防跳机跳堆的改正行动 ,减少未来由于设备失效导致的跳堆次数 ,达到提高核电站的设备可靠性、安全性和经济性的目的。