基于改进蛙跳算法的连铸二冷配水制度优化

Optimization of Continuous Casting Secondary Cooling Water Distribution System Based on Improved SFLA

在连铸二冷配水制度的优化问题的研究中,为了有效调节水量和温度,提出一种新型混合算法对水量实施动态调节。基于蛙跳算法局部搜索能力较弱的考虑,引入量子粒子群算法,以提高算法的聚类准确度及收敛性;同时,辅以混沌机制增强个体的自组织性,提高算法全局搜索能力。经实验证明,融合了量子粒子群的蛙跳算法聚类效果好,收敛速度快,且在低倍检验中,铸坯的中心疏松和角部裂纹的改善尤为明显,中间裂纹和中心缩孔也有一定程度改善,算法性能得到大幅度提升,为铸坯质量优化提供了参考。

A new hybrid algorithm was proposed for dynamically adjusting water volume to solve the optimization problem of secondary cooling water distribution. In this paper, considering the problem that the local search ability of SFLA is weak, we introduced the quantum particle swarm algorithm to improve the clustering accuracy and convergence. At the same time, supplemented with chaos mechanism, we enhanced the self organization of individuals to improve the algorithm global search capability. Experimental results show that the clustering effect of the SFLA with quantum particle swarm is good, has rapid constringency speed. And in the low times test, it is effective to improve the center porosity and corner crack of slab, intermediate crack and shrinkage were improved, the performance of the algorithm was substantially promoted.