蚁群多目标优化在连铸二冷配水中的应用  

Application of Ant Colony Algorithm for Multi-Objective Optimization in Secondary Cooling of Continuous Casting Slab

作　　者：裴红星[1,2] 张玉宝[1,3] 王长松[1] 曹军民[1] 金学伟[1] 

机构地区：[1]北京科技大学机械工程学院,北京100083 [2]郑州大学物理工程学院,河南郑州450052 [3]内蒙古科技大学机械学院,内蒙古包头014010

出　　处：《中北大学学报（自然科学版）》2011年第5期556-560,共5页Journal of North University of China(Natural Science Edition)

基　　金：内蒙古自治区自然科学基金资助项目（200607010705）

摘　　要：通过连铸板坯凝固传热模型,求解铸坯表面温度分布,根据冶金准则及设备约束条件设计连铸二冷优化多目标函数,按照分目标的重要程度确定其所占的权重.通过对二冷段的水量分别离散化生成蚁群算法的节点及路径,以目标函数最小化为准则,对二冷各段水量进行优化.优化后的二冷区铸坯表面最大的冷却速率由152℃/m降至72℃/m,表面最大温度回升速率由34℃/m降至12℃/m.表面温度分布趋于平缓,减少了诱发铸坯产生内裂和表面裂纹的应力因素.Temperatures of casting slab was calculated by using the heat-transfer model of continuous casting slab solidification.Multi-objective optimization function of continuous casting secondary cooling was established according to the metallurgical criteria and equipment constraints.The weight for each object was defined according to its importance.The node and path of ant colony algorithm（ACA） were generated by dispersing the water flow of every secondary cooling zone.The multi-objective conceptual design optimization was implemented for secondary cooling process.The maximum rising（dropping） rate of slab surface temperature was 12 ℃/m（72 ℃/m） after optimization,whereas it was originally 34 ℃/m（152 ℃/m）.A small fluctuation scope of surface temperature was preferable for it decreases the stress which leads to internal and surface cracks in casting slabs.

关 键 词：连铸 二冷配水 蚁群算法 多目标优化 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置] TG249.7[自动化与计算机技术—控制科学与工程]