基于改进PSO算法的连铸二冷过程优化仿真

连铸小方坯二冷过程优化是在实现二维传热建模和数值求解的基础完成的。冶金准则的多目标性,模型数值离散化大的计算量以及凝固相变存在引起模型求解的非线性,导致传统优化方法搜索效率低下。采用粒子群算法优化连铸二冷过程。为加强局部搜索能力,引入混沌序列对陷入局部极小点的惰性粒子重新初始化,在迭代中产生局部最优解的邻域点,帮助惰性粒子逃离束缚并且快速搜寻到最优解。仿真结果表明,改进的PSO算法有更好的搜索效率,取得了较好的效果。

Optimization and Simulation of Continuous Casting Secondary Cooling Based on Enhanced PSO Algorithm

Optimization of the secondary cooling is preformed in the continuous casting with the aid of the two dimension solidification model based on the finite element method.The cost function related to the quality of cast billets is non-linear and differentiable,which is difficult to traditional optimization algorithms,due to the large amount of calculation of the numerical solidification model and phase changes during the solidification process.An enhanced particle swarm optimization algorithm was proposed to optimize the secondary cooling of billet.To improve the ability of local searching,some particles trapped in local minimums were initialized again by chaotic series in order to introduce the neighboring regions of the local minimums in the iteration and help them break away from the local minimums to find the globe optimal solution rapidly.The results of simulation show that the proposed PSO algorithm has its high validity,robustness and efficiency.