浸没燃烧式气化器可靠性与维修优化实验的数字化设计  

Digital design of reliability and maintenance optimization experiments for submerged combustion vaporizer

作　　者：王海清[1] 黄志宇 汪肆杰 王振宇 WANG Haiqing;HUANG Zhiyu;WANG Sijie;WANG Zhenyu(College of Mechanical and Electronic Engineering,China University of Petroleum(East China),Qingdao 266580,China)

机构地区：[1]中国石油大学(华东)机电工程学院,山东青岛266580

出　　处：《实验技术与管理》2024年第12期199-204,共6页Experimental Technology and Management

基　　金：国家重点研发计划课题(2019YFB2006305)。

摘　　要：复杂生产装置的可靠性评估与维修优化,是防止安全事故的重要途径。由于实验场地、模式和资源等限制,相关实验教学在内容和组织形式上均存在诸多局限,难以满足新工科建设对安全专业人才培养的要求。该文以液化天然气(LNG)接收站的核心单元浸没燃烧式气化器(SCV)为实验对象,要求学生在理解LNG接收站工艺流程和SCV设备构造的基础上,首先建立SCV的可靠性框图,并结合可靠性数据库进行失效数据预处理;然后应用AvSim软件对具体故障模式进行模拟,分析系统不可用度、停机时间等参数以识别造成SCV事故的关键影响因素;最后分组独立研讨维修策略的优化,并给出差异化的实验比较结果。该文验证了融合数据驱动和可靠性、可用性与维修性RAM仿真的混合实验模式,通过采用量化分析与软件工具,解决了复杂生产系统的安全实验偏定性、偏宏观管理等问题,同时数字化设计的实验模式,增加了实验教学的工程吸引度和结果的区分度。[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 un

关 键 词：新工科安全实验设计 浸没燃烧式气化器 混合实验模式 蒙特卡洛仿真 

分 类 号：X937[环境科学与工程—安全科学]