粒子群算法在优化板坯二冷制度中的应用

Application of Particle Swarm Algorithm to Optimizing Secondary Cooling System in the Continuous Cast Slab

提出了一种基于带有变异算子的改进粒子群算法对二冷区水量进行优化的新方法。首先应用凝固原理和时空有限体积法建立连铸板坯凝固传热的数学模型,数值模拟结果与现场实测结果相符。再利用改进粒子群优化算法对二冷区各段的水量进行优化,优化之后的二冷制度使铸坯各段表面温度冷却速率和温度回升速率趋于平缓,与冶金准则对改善铸坯冷却过程和提高产品质量的要求相吻合。

A novel method based on modified particle swarm optimization (IPSO) with mutation algorithm was proposed to optimize water quantity in secondary cooling process in the continuous slab casting. An mathematical model of heat transfer in solidification process of the continuous slab has been developed based on solidification principle with a time-space finite volume method, and the simulated results based on the model are well in agreement with the experimental ones. Then, water-quantity in secondary cooling process was optimized by IPSO. Surface temperature-reduction rate and surface temperature-increment rate on the continuous slab casting at every stage tends to flat using optimized secondary cooling system, which is accordant with the requirements of metallurgical principle improving cooling process of the slab and product quality.