基于大数据技术的炉缸状态可视化  

Visualization of hearth status based on big data technology

作　　者：张伟阳 刘小杰 李宏扬 卜象平 程相文 吕庆 ZHANG Wei-yang;LIU Xiao-jie;LI Hong-yang;BU Xiang-ping;CHENG Xiang-wen;LÜQing(College of Mechanical Engineering,North China University of Science and Technology,Tangshan 063210,Hebei,China;College of Metallurgy and Energy,North China University of Science and Technology,Tangshan 063210,Hebei,China;Tangshan Sunyu Technology Co.,Ltd.,Tangshan 063210,Hebei,China)

机构地区：[1]华北理工大学机械工程学院,河北唐山063210 [2]华北理工大学冶金与能源学院,河北唐山063210 [3]唐山数禹科技有限公司,河北唐山063210

出　　处：《钢铁》2021年第7期38-46,62,共10页Iron and Steel

基　　金：河北省高端钢铁冶金联合研究基金资助项目(E2019209314);河北省高等学校技术研究资助项目(QN2019200)。

摘　　要：为了更好地监测炉缸工作状态的变化,建立了高炉炉缸状态可视化系统,以展示炉缸热电偶温度、热流强度和炉缸活性的历史趋势和实时监控。收集了某高炉相关参数的数据,使用拉依达准则进行粗大异常值的处理并采用线性插值法进行了空缺值的填补,对热电偶温度和热流强度进行了分区域监测和计算并据此分析了炉缸炉底的侵蚀情况,最后将焦炭质量、渣铁成分和操作参数作为输入变量,提出了融合大数据技术的炉缸活性定量模型。大数据技术为钢铁行业的发展提供了新思路,进一步推动了高炉智能化炼铁。In order to better monitor the change of the working state of the hearth,a visualization system of the hearth state of the blast furnace was established to simulate the historical trend and real-time monitoring of the hearth thermocouple temperature,heat flux intensity,and hearth activity.The data of the related parameters of a blast furnace were collected,and the rough outliers were treated by the Pauta criterion and the blank values were filled by the linear interpolation method.The thermocouple temperature and heat flux intensity were monitored and calculated in different regions,and the erosion of the hearth bottom was analyzed.The coke quality,slag iron composition,and operating parameters were taken as input variables,and a quantitative model of hearth activity incorporating big data technology was proposed.Big data technology provides new ideas for the development of the iron and steel industry and further promotes the intelligent ironmaking of blast furnaces.

关 键 词：炉缸 可视化系统 热电偶温度 热流强度 炉缸活性 

分 类 号：TF573.1[冶金工程—钢铁冶金]