摘要
板坯温度跟踪模型的计算温度是加热炉调控炉温的重要依据,精确的板坯计算温度是加热炉燃烧控制模型良好工作的前提。针对现场板坯温度跟踪模型的计算温度与实际温度误差较大的问题,从模型入手,以埋偶实验测得的实际值为依据,对板坯温度跟踪模型的关键参数总括热吸收率进行优化,从而提高模型的计算精度。由于遗传算法在全局优化方面具有较大的优势,因此针对总括热吸收率的特点对遗传算法进行改进,通过全局搜索得到总括热吸收率的最优设定。通过离线模型验证,该方法明显提高了模型的计算精度。
An accurate calculated temperature of the slab can promise a good work for the reheating furnace control model ,because it is one of the key factors to regulate the furnace temperature. Based on the field data, we can raise efficiency of the model, via solving the problem of the improper set for the total heat exchange factor, the key parameter of the model. Given the advantage of the Genetic Algorithm in global optimization,we can improve the algorithm for the proper set of the total heat exchange factor. It is critically verified by the off-line model that this solution has achieved a better accuracy of the model.
出处
《系统仿真技术》
2012年第4期259-265,共7页
System Simulation Technology
基金
国家自然科学基金资助项目(61074088)
关键词
板坯温度
遗传算法
总括热吸收率
全局优化
slab＇s temperature
genetic algorithm
total heat exchange factor
global optimization
