CRH3型动车组牵引传动系统可靠性分析

为分析CRH3型动车组(EMU)牵引传动系统可靠性,基于其结构及运行特点,结合图论,从建立系统网络图可靠性模型入手,将系统可用度计算转化为系统网络图模型的连通概率计算。在系统各部件可维修的前提下,考虑部件停工相关性,结合京津城际高速铁路某CRH3型动车组历史运行数据,用蒙特卡罗模拟-元胞自动机(MCS-CA)算法,通过Matlab编程,计算分析系统在正常工作状态和降级(降容)运行状态下的可靠性,并绘制相应的可靠度、可用度随时间变化曲线。结果表明,动车组牵引传动系统受电弓高压进线单元故障率最高,其次是变流单元。     

基于马尔可夫的地面控制井下安全阀可靠性评估

为保障地面控制井下安全阀系统的安全运行，防止系统发生故障，建立了井下安全阀可修复系统的马尔可夫模型；针对系统设备构成复杂及共因故障等问题，基于β因子模型描述共因失效，同时将模型划分为3个独立模块，通过克罗内克积方法合并，评估系统可靠性；参照OREDA可靠性数据，定量求解井下安全阀系统可用度、可靠度以及稳态指标，研究模型中状态转移概率对系统稳态可用度的影响。研究结果表明:井下安全阀系统的可用度随时间增长而迅速到达稳态值；系统检修周期应小于2.5 a；根据可靠性分析结果，运营方应考虑系统经济与可靠性间的博弈关系，合理优化系统冗余结构与维修周期管理，防止井下安全阀系统失效。     

化工系统设备运行可靠性的综合评价模型研究

为提高化工过程系统设备运行的可靠度,讨论可靠性评价在化工过程系统管理中的适用性和发展方向,建立可靠性评价模型体系。将设备故障模式与可靠性评价相结合,分析存在的故障模式类型。用安全、环境以及经济分析方法,得到评价指标。运用无因次函数模型,建立化工过程系统设备运行可靠性的综合评价模型。利用某大型磷化工集团硫酸生产系统的实际运行数据,验证该模型的有效性。结果表明,当磷酸装置运行可靠性的综合评价值大于3.17时,需要对相应设备进行维修维护。     

基于多态故障树的多值决策图制动系统可靠性分析

针对动车组制动系统实际运行环境中故障多态性问题,提出了一种基于模块分解的多态故障树与多态多值决策图相结合的重要度分析方法。通过对系统进行故障树模型建造和模块化分解,将不同事件转化为相应变量状态、多态故障树转化为多态多值决策图,最后计算得出多状态系统Birnbaum重要度。分析结果与兰新客专动车组制动系统实际运营情况相符,验证了算法的可行性和有效性,解决了多态系统可靠性分析问题,为该路线动车制动系统故障检修和维护策略的修订提供了理论依据。     

基于云模型的电梯运行可靠性模糊综合评估

针对目前电梯可靠性评估中存在随机性和模糊性等不确定性的问题,提出了一种基于熵权法、云模型和模糊综合评价法的电梯运行可靠性评估模型。通过分析电梯各个子系统的主要特征量,建立了电梯运行可靠性评估指标体系,并运用熵权法确定各指标的权重。根据云模型实现定量指标与定性概念之间的转换,得到定量评估指标的等级隶属度。最后基于模糊综合评价法,对各指标信息进行自上而下地综合,得到整体的可靠性评估结果。实例表明了该模型的正确性与有效性,能够对电梯的状态检修提供参考。     

性能水平划分下的多状态系统可靠性分析

为准确评价多状态系统及其组件的工作性能和可靠性,并确定系统在临界状态时其组件的性能水平,用不同的性能水平划分原始系统;将组件的多态性看成是离散随机过程,建立其马尔科夫过程方程,求解得到各水平下组件在任务时间内的状态概率和性能期望值,从而确定组件对系统可用性的贡献。建立不同性能水平下的组件的Birnbaum重要度、Fussell-Vesely重要度(FV)、可靠性成果价值(RAW)和可靠性下降价值(RRW)重要度的数学模型,由此可求得各组件以及给定水平下多状态系统性能重要性度量的结果。通过柴油机燃油供给系统的可靠性分析实例进行验证,结果表明:用提出的方法既能方便地得出给定性能水平下组件与系统处于各个状态的概率和性能期望,又能得到系统各组件对系统可靠性的影响程度,有助于系统的可靠性评估和结构优化。     

用马尔可夫模型分析基于通信的列车控制系统(CBTC)的安全性

基于通信的列车控制系统 (CBTC)极有可能成为未来铁路的发展方向 ,只是目前人们对它的安全性还抱有疑虑。笔者给出一种利用马尔可夫模型分析 CBTC安全性的方法。利用系统分解和模型压缩的方法解决状态空间的激增问题。将 CBTC设备分为故障—降级型和故障—安全型两类 ,分别建立子模型 ,分析人员因素及设备故障覆盖率对系统安全性的影响。根据子模型间的独立性 ,将各子模型的事故率相加获得系统的事故率     

粉料无尘装车技术及其在电除尘器、大布袋除尘器输灰系统中的应用

传统电除尘器、大布袋除尘器输灰系统存在工艺繁杂、能耗大、输送速度慢、系统难于维护及二次扬尘问题,电除尘器、大布袋除尘器输灰系统采用粉料无尘装车技术可有效简化工艺、提高生产速度和系统运行、维护可靠性,很大程度减少能耗并彻底根除二次扬尘。     

粉料无尘装车技术及其在电除尘器,大布袋除尘器输灰系统中的应用

传统电除尘器、大布袋除尘器输灰系统存在工艺繁杂、能耗大、输送速度慢、系统难于维护及二次扬尘问题,电除尘器、大布袋除尘器输灰系统采用粉料无尘装车技术可有效简化工艺、提高生产速度和系统运行、维护可靠性,很大程度减少能耗并彻底根除二次扬尘。     

多因素影响下高速公路突发事件安全预警模型

为有效预防和及时处理高速公路突发事件,采用定性与定量相结合的方法,建立高速公路突发事件安全预警模型。首先,分析道路交通、道路条件和异常天气等多因素对高速公路安全性的影响,建立基于交通运行状态、道路结构状态和天气状态的预警指标体系,构建高速公路突发事件安全预警状态识别基本模型和3个安全预警子模型;然后,采用演算方法分析不同情况下的安全预警值浮动范围,划分安全态、准安全态、准危机态和危机态4大预警级别及3条预警线,最后通过实例验证所建模型的有效性。研究表明:用所建立的安全预警模型可识别高速公路突发事件,及时发现高速公路的安全隐患,提升高速公路安全管理水平。     

Reliability and availability modeling of Subsea Xmas tree system using Dynamic Bayesian network with different maintenance methods

Subsea Xmas tree is a vital equipment for offshore oil and gas development. Aiming at the fault mode of subsea Christmas tree system under production conditions, the fault tree of subsea tree system was established, which was transformed into Dynamic Bayesian network, and the reliability and availability of subsea tree system with different repair states are quantitatively analyzed. In this paper, the DBNs are partially verified by the method based on three axes. The results show that the reliability of subsea vertical tree system is slightly higher than that of subsea horizontal tree system. After repair and maintenance, the performance of subsea tree system has been significantly improved, and the improvement of the system performance by preventive maintenance is more obvious. Compared with the perfect repair, the performance of the system with imperfect repair is not significantly reduced. Compared with perfect repair & preventive maintenance, the performance of the system with imperfect repair & preventive maintenance is slightly reduced. In addition, the influence of failure rates and degradation probability on reliability and availability is analyzed. By comparing the influence of failure rates on the system performance of non-maintenance and maintenance, it is found that the change of failure rates has the greatest influence on the reliability and the least influence on the availability of perfect repair & preventive maintenance. By comparing the performance of each component in the subsea tree system, it is found that the failure rates has the most obvious influence on the chock module, and gate valve and tree cap have the most significant influence on the reliability of the system. In order to improve the reliability of subsea tree system, it is necessary to improve the reliability of chock module, gate valve and tree cap.     

Coping with advanced manufacturing technology

Computer aided manufacturing equipment is supposed to revolutionize batch production by increasing control over this highly uncertain mode of manufacturing. However, as computerized equipment becomes more complex it becomes less compatible with the socio-technical systems of most firms. The ensuing problems, with which management, staff specialists and workers have great difficulty in coping, lead to the new technology being only partially under control. It is difficult to evaluate whether to purchase a computerized manufacturing system and there are problems in evaluating their efficiency once they are implemented. Evidence is presented from case studies of five firms in three nations that have purchased computerized production systems. Policy recommendations and research suggestions are provided for dealing with the situation.     

A framework to estimate the risk-based shutdown interval for a processing plant

Petrochemical plants and refineries consist of hundreds of pieces of complex equipment and machinery that run under rigorous operating conditions and are subjected to deterioration over time due to aging, wear, corrosion, erosion, fatigue and other reasons. These devices operate under extreme operating pressures and temperatures, and any failure may result in huge financial consequences for the operating company. To minimize the risk and to maintain operational reliability and availability, companies adopt various maintenance strategies. Shutdown or turnaround maintenance is one such strategy. In general, shutdown for inspection and maintenance is based on the original equipment manufacturer's (OEM) suggested recommended periods. However, this may not be the most optimum strategy given that operating conditions may vary significantly from company to company.The framework proposed in this work estimates the risk-based shutdown interval for inspection and maintenance. It provides a tool for maintenance planning and decision making by considering the probability of the equipment or system for failure and the likely consequences that may follow. The novel risk-based approach is compared with the conventional fixed interval approach. This former approach, characterized as it is by optimized inspection, maintenance and risk management, leads to extended intervals between shutdowns. The result is the increase in production and the consequent income of millions of dollars.The proposed framework is a cost effective way to minimize the overall financial risk for asset inspection and maintenance while fulfilling safety and availability requirements.     

Development and application of equipment maintenance and safety integrity management system

Equipment management in process industry in China essentially belongs to the traditional breakdown maintenance pattern, and the basic inspection/maintenance decision-making is weak. Equipment inspection/maintenance tasks are mainly based on the empirical or qualitative method, and it lacks identification and classification of critical equipment, so that maintenance resources can’t be reasonably allocated. Reliability, availability and safety of equipment are difficult to control and guarantee due to the existing maintenance deficiencies, maintenance surplus, potential danger and possible accidents. In order to ensure stable production and reduce operation cost, equipment maintenance and safety integrity management system (MSI) is established in this paper, which integrates ERP, MES, RBI, RCM, SIL and PMIS together. MSI can provide dynamic risk rank data, predictive maintenance data and RAM decision-making data, through which the personnel at all levels can grasp the risk state of equipment timely and accurately and optimize maintenance schedules to support the decision-making. The result of an engineering case shows that the system can improve reliability, availability, and safety, lower failure frequency, decrease failure consequences and make full use of maintenance resources, thus achieving the reasonable and positive result.     

成套装置动态风险管理专家系统

传统的设备管理模式造成设备非计划停机次数较多、故障频繁、可靠性和可用性不高等问题。为了解决上述问题,开发了成套装置动态风险管理专家系统,该系统包括动态风险监控、数据存储、失效模式及损伤机理判别、动态风险评估、风险辅助分析5个流程。该系统通过GIS平台进行展示,使用户可以直观、方便地查找、定位管线和容器位置,实现了高风险设备的风险展示、管道剩余寿命不足报警功能和管道冲蚀图例展示。将该专家系统进行了工程应用,得到容器和管道的潜在损伤机及其风险等级,针对不同风险等级的设备,生成了不同的检维修策略,为工程应用带来了很大的方便。     

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.     

A new approach to quantitative assessment of reliability of passive systems

The objective of this paper is to show how probabilistic reliability can be assessed for complex systems in the absence of statistical data on their operating experience, based on performance evaluation of the dominant underlying physical processes. The approach is to distinguish between functional and performance probabilities when dealing with the quantification of the overall probability of a system to perform a given function in a given period of time (reliability). In the case of systems where sufficient statistical operating experience data are available, one can focus the quantitative evaluation entirely on the assessment of the functional probability for a given active item (e.g. a pump) by assuming that the specification, layout, construction and installation is such that the item is providing the assigned performance, e.g. in the form of generating the required flow rate. This is how traditional probabilistic safety assessments (PSAs) focus the reliability analysis for the various safety features on the calculation of values for the availability per demand. In contrast, for various systems relevant in advanced technical applications, such as passive safety features in innovative reactor designs, it is essential to evaluate both functional and performance probabilities explicitly and combine the two probabilities later on. This is of course due to the strong reliance of passive safety systems on inherent physical principles. In practice, this means that, for example, in case of a passive cooling system based on natural circulation of a given medium, one has to evaluate and to assess the probability to have a medium condition and a flow rate such that a cladding temperature, represented by a probability distribution, can be hold at a required level. A practical example of this method is given for the case of the reliability assessment of a residual passive heat removal system. General conclusions are drawn regarding reliability estimation of complex, interconnected systems in the absence of statistical performance data, such as for infrastructures.     

Resilience-based approach to safety barrier performance assessment in process facilities

The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly uncertain, making it challenging for the static indicators to assess the performance of safety barriers. This paper proposes a resilience−based performance assessment method for safety barriers to overcome this problem. Safety barriers are classified according to their functions first. The dynamic Bayesian network (DBN) is then introduced to calculate the availability function under normal and disruption conditions. The ratio of the system's availability, when affected by the disruption, to the initial availability, is used to determine the absorption capacity of the system. The ratio of the quantity of availability recovery to the total quantity of system represents the adaptation and restoration capacity of the system. The system's resilience is represented by the sum of absorption, adaptation, and restoration capacities. The wax oil hydrogenation process is used to demonstrate the applicability of the proposed methodology.     

Reliability analysis of subsea blowout preventers with condition-based maintenance using stochastic Petri nets

Blowout Preventer (BOP) has maintained its function as a safety barrier and the last line of defence against oil and gas spills since its development in the early 1900s. However, as drilling and exploration activities move further offshore, challenges pertaining to reliable operation of the subsea BOP systems continue to be a source of concern for stakeholders in the industry. In spite of recent advancements in reliability analysis of safety instrumented systems (SISs), the research on reliability assessment of BOP is still lacking in some regards. There are gaps in the literature with respect to the incorporation of preventive maintenance (PM) strategies as well as dynamic operating conditions into BOP reliability analysis. To address these gaps, this paper develops an advanced analysis method using stochastic Petri nets (SPN) to estimate the reliability of subsea BOP systems subject to condition-based maintenance (CBM) with different failure modes. The BOP system is divided into five subsystems which are connected in series with each other and categorised into degrading and binary units. The performance of the BOP system in terms of availability, reliability and mean-time-between failures (MTBF) is obtained and analysed. A sensitivity analysis is also performed to evaluate the effect of fault coverage factor and redundancy design on system performance. The results show that both the fault coverage factor and redundancy have significant impact on the BOP's reliability, availability and MTBF.