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Multi-objective optimization of continuous casting secondary cooling water based on differential evolution algorithm

机译:基于差分进化算法的连铸二次冷却水多目标优化

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The secondary cooling water has a considerable influence on cracks and other internal defects of the billets. This research aims to develop an optimization algorithm used for solving the optimal secondary cooling water flowrate under different casting speeds. An multi-objective optimization algorithm based on differential evolution(DE) algorithm was developed for Pareto-optimal solutions for solving an optimal control of secondary cooling water distribution. The optimization method consists of the solidification heat transfer mathematical model, DE algorithm linked with three conflicting objective functions according to certain metallurgical criteria and some technological constraints. The Pareto-optimal solutions were controlled by crowding distance to improve the diversity of solutions. The application of the developed optimization algorithm for determining optimal setting of cooling parameters demonstrate that better results can be obtained in improving the product quality.
机译:二次冷却水对钢坯的裂纹和其他内部缺陷有相当大的影响。本研究旨在开发一种优化算法,用于求解不同铸造速度下的最佳二次冷却水流量。针对二次冷却水分配的最优控制问题,提出了一种基于微分进化(DE)算法的多目标优化算法,用于帕累托最优解。优化方法包括凝固传热数学模型,根据一定的冶金标准和一定的技术约束条件,将三个相互矛盾的目标函数联系起来的DE算法。通过拥挤距离控制帕累托最优解,以提高解的多样性。所开发的优化算法用于确定冷却参数的最佳设置的应用表明,在改善产品质量方面可以获得更好的结果。

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