摘要
热轧带钢卷取温度是反映热轧带钢性能指标的重要参数之一,介绍了某700 mm热连轧机层流冷却的组成及其工作原理,针对其具体情况,基于实时数据,应用数据挖掘工具,从理论和工艺的角度分析了控冷过程中热轧带钢更换规格温差大问题产生的原因,得出了热轧带钢更换规格的规律,并应用回归统计建立了温度补偿模型,进行了实验研究,实验结果表明,应用数据挖掘技术从立体的现场数据中得出热轧层流冷却控制模型的做法,对提高控冷精度,优化生产工艺具有一定意义。
Coiling temperature of hot rolled strip is one of important parameters in reflecting its material performance index.It presents a laminar cooling system for 700 mm hot strip mill and its working principle.Based on real-time data,by applying data mining tools,the reason of bigger coiling temperature deviation during changing the strip is analyzed in rolling theory and techniques,and then,the coiling temperature laws for changing hot rolled strip specifications is got for the laminar cooling system of a certain plant.After that a compensation model is built by utilizing regression statistics,and experiments are done.The experimental results show the application of data mining in obtaining hot rolling laminar cooling control model from site data is significant for improving the precision of controlled cooling and optimizing the production process.
出处
《机械设计与制造》
北大核心
2012年第5期139-140,共2页
Machinery Design & Manufacture
基金
国家自然科学基金资助项目(50675189)
河北省科技支撑计划项目(10212150)
河北省自然科学基金资助项目(E2012407010
E2009000405)
河北省教育厅资助项目(2011136)
关键词
热轧
层流冷却
卷取温度
数据挖掘
数学模型
Hot rolled
Laminar cooling
Coiling temperature
Data mining
Mathematics model
