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唐钢2号高炉(2000m~3)采用炉墙结厚预测模型实时监控,实现了炉墙结厚在线诊断,可对炉墙黏结状态的进行量化分析,并对炉墙结厚进行分级预警。实践表明,高炉炉墙结厚预测模型,可以直观准确地反映高炉炉墙的工作状态,将传统的仪表监测数据,通过数理分析转化为高炉炉墙黏结状况的可量化参数。2016年4月16日预警高炉炉墙结厚,计算结果表明,8、9段冷却壁4个分区黏结物的平均厚度分别为69.5mm、35.75mm。
The No.2 blast furnace (2000m ~ 3) of Tangshan Iron and Steel Co., Ltd. real-time monitoring the furnace wall knot thickness prediction model to achieve on-line diagnosis of furnace wall knot thickness, quantitative analysis of furnace wall bond status and grading warning of furnace wall knot thickness. Practice shows that blast furnace wall junction thickness prediction model can reflect the working state of blast furnace wall visually and accurately, and convert the traditional instrument monitoring data into quantifiable parameters of the bonding state of blast furnace wall through mathematical analysis. April 16, 2016 Early warning blast furnace wall knot thickness, the calculated results show that the 8,9 section of the average thickness of four partitions stave were 69.5mm, 35.75mm.