穿孔效率与能耗的建模与综合优化  

Modeling and Optimization for Piercing Efficiency and Energy Consumption

作　　者：肖冬[1] 王继春[1] 毛志忠[1] 潘孝礼[1,2] 

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110004 [2]上海宝钢股份有限公司钢管分公司,上海201900

出　　处：《钢铁研究学报》2013年第1期14-22,共9页Journal of Iron and Steel Research

基　　金：国家自然科学基金资助项目(61203214);辽宁省博士启动基金(20101037);国家博士后基金(20100481203);中央高校青年教师科研启动基金(N100304010);国家863计划资助项目(2011AA060204)

摘　　要：对于无缝钢管穿孔生产,穿孔效率和穿孔能耗是衡量生产的两个重要指标。但由于其影响因素复杂,难以建立机制模型,故难以实现对其模型的综合优化。为实现穿孔效率和穿孔能耗的综合优化,根据穿孔生产工艺将穿孔过程分成3个部分,提出了基于均值子时段MICR方法的穿孔效率和穿孔能耗的预报模型。在预报模型的基础上,采用遗传算法对各段工艺参数的平均值进行寻优,得到穿孔效率和穿孔能耗综合优化结果。仿真和试验结果表明,基于穿孔效率和穿孔能耗预报模型的优化方法可有效取得最优工艺参数,为穿孔效率的提高和穿孔能耗的降低提供依据。Piercing efficiency and energy consumption were the important quality indexes in the production of seamless tubes.The complex factors that affected efficiency and consumption make it difficult to establish the mechanism models for optimization.Based on the production process,the piercing process was divided into three parts.An energy consumption prediction model was proposed based on step mean value staged MPLS method.On the basis of batch process prediction model,genetic algorithm was adopted to calculate the optimal mean value of each process parameters and the minimum piercing energy consumption.The simulated results show that the optimization method based on the energy consumption prediction model can obtain the optimal process parameters effectively and also provide reliable evidences for practical production.

关 键 词：无缝钢管 穿孔效率 穿孔能耗 多向独立成分回归 遗传算法 

分 类 号：TG335[金属学及工艺—金属压力加工]