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作 者:祁建伟[1] 陈久升 王连杰 李凯 QI Jianwei;CHEN Jiusheng;WANG Lianjie;LI Kai(The Automation Department of Taishan Iron and Steel Group Co.,Ltd.,Jinan 271100,China)
机构地区:[1]山东泰山钢铁集团有限公司自动化部,山东济南271100
出 处:《山东冶金》2023年第3期48-50,55,共4页Shandong Metallurgy
摘 要:介绍了工业互联网的设备监测与故障诊断系统在泰山钢铁集团不锈钢厂设备管理系统中的应用。本项目是将现场设备振动、温度等信号采集起来,通过对设备状态数据、运行数据和现场视频数据进行全周期监测,建立设备故障知识图谱,对发生故障的设备进行诊断和定位。通过数据挖掘技术,对工业设备运行趋势进行动态智能分析预测,建立了基于工业互联网的大数据机组健康状态监测与诊断系统及其服务平台,可使企业避免意外事故停机和安全事故,减少企业维修费用,提高设备运行效率和备件成本。This paper mainly describes the application of the equipment monitoring and fault diagnosis system of Industrial Internet in the equipment management system of the stainless steel plant of Mount Taishan Steel.This project collects signals such as vibration and temperature of on-site equipment,and monitors equipment status data,operation data,and on-site video data throughout the entire cycle to establish a knowledge graph of equipment faults.It diagnoses and locates the faulty equipment,and uses data mining techniques to dynamically and intelligently analyze and predict the operating trends of industrial equipment,The big data unit health monitoring and diagnosis system and its service platform based on Industrial Internet have been established,which can enable enterprises to avoid unexpected downtime and safety accidents,reduce enterprise maintenance costs,and improve equipment operation efficiency and spare parts costs.
分 类 号:TP277[自动化与计算机技术—检测技术与自动化装置]
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