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Self-Learning and Its Application to Laminar Cooling Model of Hot Rolled Strip

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【Author】 GONG Dian-yao,XU Jian-zhong,PENG Liang-gui,WANG Guo-dong,LIU Xiang-hua(State Key Laboratory of Rolling Technology and Automation,Northeastern University,Shenyang 110004,Liaoning,China)

【摘要】 The mathematical model for online controlling hot rolled steel cooling on run-out table(ROT for abbreviation)was analyzed,and water cooling is found to be the main cooling mode for hot rolled steel.The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient.It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control(CTC)model tuning.To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance,a laminar cooling control self-learning strategy is used.Using the data acquired in the field,the results of the self-learning model used in the field were analyzed.The analyzed results show that the self-learning function is effective.

【Abstract】 The mathematical model for online controlling hot rolled steel cooling on run-out table(ROT for abbreviation)was analyzed,and water cooling is found to be the main cooling mode for hot rolled steel.The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient.It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control(CTC)model tuning.To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance,a laminar cooling control self-learning strategy is used.Using the data acquired in the field,the results of the self-learning model used in the field were analyzed.The analyzed results show that the self-learning function is effective.

【基金】 Item Sponsored by National Natural Science Foundation of China(50474016)
  • 【文献出处】 Journal of Iron and Steel Research(International) ,钢铁研究学报(英文版) , 编辑部邮箱 ,2007年04期
  • 【分类号】TG335.11
  • 【被引频次】30
  • 【下载频次】114
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