Digital design of reliability and maintenance optimization experiments for submerged combustion vaporizer
[Objective]The reliability assessment and maintenance optimization of complex production devices are crucial for accident prevention.Because of limited experimental sites,modes,and resources,relevant experimental teaching has many limitations in terms of content and organization.To combine the high incidence of accidents in the domestic petrochemical field and the demand for practical safety engineering talents,a data-driven project-based experimental content design exploration was carried out considering a digital liquefied natural gas(LNG)receiving station teaching experimental platform.Consequently,good feedback has been obtained.As an important hub in the oil and gas industry,natural gas supply interruption during a system failure can cause serious social impacts and production losses.Therefore,the reliability,availability,and maintainability of an LNG-receiving station system are analyzed by random access memory(RAM)to improve the stable operation and safety of the LNG receiving station.[Methods]Taking the LNG receiving station as the basic experimental platform,the failure of the core unit submerged combustion vaporizer(SCV),leading to the interruption of external transmission or accidents,was selected as the experimental object.To understand the process and structure of SCV equipment,students construct a reliability block diagram model of SCV equipment based on the RAM analysis method and process the failure data per the reliability block diagram model and the failure database of the plant cloud platform for historical data.The Monte Carlo stochastic simulation software AvSim is applied to analyze parameters,such as system unavailability and downtime,for identifying the key influencing factors of SCV accidents,and the group independently discusses how to optimize the maintenance strategy and presents the differentiated experimental comparison results.[Results]SCV was analyzed by constructing a reliability block diagram of SCV divided into a gas unit,combustion air unit,combustion chamber,water injection unit,circulating coolant water unit,heat transfer unit,and alkali addition unit.Failure data parameters of each SCV component were fitted according to the reliability data distribution characteristics using MATLAB toolbox distribution fitter.The Monte Carlo method-based RAM simulation was performed based on AvSim to obtain the results of data simulation calculations,such as system model availability and downtime.The results show that the key devices causing system unavailability are the circulation pump,electric motor,and injection pump.Thus,a preventive maintenance system and maintenance strategies,such as contingency maintenance,were established for the laboratory SCV system.[Conclusions]Under the requirements of the construction of new engineering disciplines,the new digital content design and transformation of the traditional LNG receiving station laboratory can penetrate the digital technology and basic safety engineering theoretical knowledge;solve the typical difficulties,such as biased qualitative and macromanagement of safety experiments of the complex production system;improve the student's ability to solve engineering problems;and satisfy the needs of industrial safety for compound talents.
safety experimental design for new engineeringsubmerged combustion vaporizerhybrid experimental modelMonte Carlo simulation
万方数据
维普
