加热炉炉温优化算法研究  被引量:8

Study of optimization algorithm on reheating furnace temperature

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作  者:李国军[1] 雷薇[1] 陈海耿[1] 

机构地区:[1]东北大学材料与冶金学院,沈阳110819

出  处:《材料与冶金学报》2011年第4期325-328,共4页Journal of Materials and Metallurgy

基  金:国家自然科学基金资助(50974146)

摘  要:炉温制度的优化是炉子优化控制的基础,它包括炉温优化目标函数的确定和目标函数极值的求解两方面.本文建立了连续加热炉板坯加热的稳态数学模型和炉温优化模型.应用所建立的稳态数学模型定量分析了各段炉温变化对钢坯加热过程的影响,形成了启发式算法规则集.建立了考虑出炉钢坯平均温度及断面温差的目标函数,采用启发式搜索算法对钢坯加热过程的炉温制度进行了优化,对优化前后的钢坯平均温度及断面温差的进行了对比分析.计算结果表明,本文所归纳的启发式搜索规则可以满足该模型启发式算法的要求,也表明启发式搜索算法可作为加热炉炉温优化的基本算法.The optimization of the furnace temperature system is on the basis of optimized control , which includes the determination of furnace temperature optimizing object function and the solving of the extreme. In this paper, the stable model and furnace temperature optimization model were established. According to the mathematical model steady quantitatively analyze the heating process influence that change of each billet temperature, the heuristic algorithm rule sets was formed, and the furnace temperature of thin slab heating process was optimal analyzed by the minimizing fuel consumption as the object function. The comparison of the average temperature and temperature difference of cross - section before and after optimization was made. The results show that the heuristic search rules established through the dynamic mathematical model can meet the requirements of the heuristic algorithm, and show that the heuristic search algorithm can be used as the basic algorithm of the heating furnace temperature optimization.

关 键 词:加热炉模型 启发式算法 元体平衡法 炉温优化 

分 类 号:TK124[动力工程及工程热物理—工程热物理]

 

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