摘要
利用测试函数对基本粒子群算法(BPSO)、小生境粒子群算法、改进的粒子群算法(IPSO)的性能进行对比,结果表明,与基本粒子群算法相比,改进粒子群算法具有计算精度更高、收敛速度更快、搜索能力更强等优点,是一种适合铝热连轧负荷分配优化的新方法,对铝材的生产有一定的指导意义。结合项目的热连轧机实际工况,建立了轧制过程的数学模型。以各机架的出口厚度为自变量,以能耗及板形良好为目标,利用BPSO和IPSO算法对铝合金的4机架热连轧轧制规程进行优化,得到最佳的轧制负荷分配。
The performances of basic particle swarm algorithm (BPSO), small habitat par- ticle swarm algorithm and improved particle swarm algorithm (IPSO) have been compared u- sing testing functions. The simulating and comparing results show that the IPSO is a suitable way to optimizing hot rolling load distribution on tandem hot rolling mill, because the im- proved particle swarm algorithm possesses higher calculation accuracy, faster convergence speed and stronger exploration ability than those of BPS0. The IPS0 can be taken as a guide for aluminum rolling on tandem rolling mill. In combination with the actual situation of work- ing site, the mathematical model of the rolling process has been established. Taking thickness self-variations at exit of each rolling stand, using BPSO and IPSO, to produce strip with excel- lent flatness and low energy consumption, aluminum alloy hot rolling schedule of the 4-stand tandem rolling mill has been optimized. The optimized schedule made the rolling load distri- bution optimized as well.
出处
《轻合金加工技术》
CAS
北大核心
2013年第2期31-35,49,共6页
Light Alloy Fabrication Technology
关键词
热连轧
负荷分配优化
数学模型
改进粒子群算法
hot strip tandem rolling mill
load distribution optimization
mathematicalmodel
improved particle swarm algorithm