摘要
智能仪表是大型工业过程和复杂装备系统传感与控制的“神经”,其健康状态直接影响系统的安全可靠运行。传统的智能仪表通常作为测量工具监测工艺过程和重点装备的运行状态,本体故障的忽视极易导致采集数据不准确、不可靠,影响工业过程管控效率,也易导致操作人员误判,从而引发安全事故。文中通过对智能仪表预测性维护的技术架构进行解析,建立了机理分析、数据采集、特征分析、故障自检、异常检测、故障诊断和寿命预测的技术路线,同时,从复杂工业过程视角将智能仪表分解为“传输”、“传感”和“传递”,总结了仪表本体级和系统级预测性维护的关键技术,分析了智能运维、安全仪表风险管控、信息安全风险管控3种典型应用场景,推演了诊断自组态和云边协同架构的技术发展趋势。研究可为智能仪表及系统运维由离线向在线、由预防性维护向预测性维护的转变奠定基础。
Intelligent instrumentation is the“nerve”of sensing and control in large industrial process and complex equipment system,and its health status directly affects the safe and reliable operation of the system.Traditional intelligent instrumentation is usually used as a measuring tool to monitor the running state of process and key equipment,and the neglect of the ontology failure can easily lead to inaccurate and unreliable data collection,affecting the efficiency of industrial process control,and is also easy to lead to misjudgment by operators,resulting in safety accidents.This paper analyzed the technical connotation of predictive maintenance for intelligent instrument,and established the technical route of mechanism analysis,data acquisition,feature analysis,fault self-test,anomaly detection,fault diagnosis and life prediction.Intelligent instrument was divided into“transmission”,“sensing”and“communication”from the perspective of complex industrial processes.The key technologies of predictive maintenance of instrument ontology level and system level were summarized.Three typical application scenarios of intelligent operation and maintenance,security instrument risk management and control,and information security risk management and control were analyzed,and the technological development trends of diagnostic self-configuration and cloud-edge collaborative architecture were deduced.The research can lay a foundation for the transformation of operation and maintenance of intelligent instrumentation and system from offline to online and from preventive maintenance to predictive maintenance.
作者
王成城
王金江
张来斌
王凯
邬长江
WANG Chengcheng;WANG Jinjiang;ZHANG Laibin;WANG Kai;WU Changjiang(College of Safety and Ocean Engineering,China University of Petroleum;Instrumentation Technology and Economy Institute;Key Laboratory of Oil and Gas Production Safety and Emergency Technology of Emergency Management Department)
出处
《仪表技术与传感器》
CSCD
北大核心
2024年第4期29-37,共9页
Instrument Technique and Sensor
基金
国家自然科学基金重点项目(52234007)。
关键词
智能仪表
预测性维护
异常检测
故障诊断
寿命预测
intelligent instrument
predictive maintenance
abnormal detection
fault diagnosis
life prediction
