基于粒子群优化算法的带钢热连轧参数研究  

Optimal steel rolling parameter adjustment based on improved particle swarm optimization

作　　者：石嘉川[1,2] 尹东 杨贵玲[4] 

机构地区：[1]山东建筑大学信息与电气工程学院,山东济南250101 [2]山东省智能建筑技术重点技术实验室,山东济南250101 [3]国家电网山东电力公司,山东济南250001 [4]济钢集团有限公司,山东济南250132

出　　处：《山东建筑大学学报》2015年第4期323-329,共7页Journal of Shandong Jianzhu University

基　　金：国家863项目(2009AA05Z213)

摘　　要：对带钢热连轧的生产工艺参数进行优化调整,可以充分发挥设备生产能力,改善产品质量,实现节能降耗。文章利用带钢轧制模型,根据各机架压下率,分析了其出口厚度、轧制力、轧制力矩和轧制速度等相关参数以及功率消耗和板型质量等指标,以六连轧生产Q235B带钢为算例,采用惯性系数动态调整的改进粒子群优化算法(PSO)建立了热连轧参数优化模型。结果表明:优化后的轧制参数可以满足各约束条件,能够在各机架间均匀分配轧钢负荷,降低生产功耗,计算速度能够满足生产要求;经典PSO算法与改进算法的对比表明,改进算法可以提高计算效率,获得优化解。Optimizing and readjusting the parameters of hot strip rolling can make full use of the equipment capacity, improve the product quality, and realize the energy-saving and consumption- reducing. An optimization model for hot strip rolling is established in this article. The relevant parameters, including the outlet thickness, rolling force, rolling torque and rolling speed etc. , are calculated according to the adjusted reduction rates, and then, the power consumption, shape quality and other indexes are obtained. The optimization model aims to reduce power consumption by adjusting reduction rate of each frame. Simultaneously, several constraints are taken into consideration, including the equipment, production process and experience. The improved particle swarm optimization （PSO） readjusts inertial coefficient dynamically, which is employed to get optimal solutions. The production of Q235B striped steel with six continuous rolling processes is taken as an example. The optimized roiling parameters can satisfy each constrains, enable the rolling load to be evenly distributed among frames, reduce the power consumption. The computing speed meets the requirements of production. The comparison between classical PSO and the improved algorithm reveals that the latter can obtain the optimal solution with a higher probability, and its computational efficiency is significantly improved.

关 键 词：粒子群优化 轧钢 负荷分配 节能 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术] TG3[金属学及工艺—金属压力加工]