基于遗传算法的在线炉待轧温度优化策略

2020 3rd International Conference on Mechatronics, Robotics and Automation (ICMRA) Pub Date : 2020-10-16 DOI:10.1109/ICMRA51221.2020.9398337

Zheng-guang Xu, Junxi Zhao, Kuo Sun, Siqaing Niu, Yanrong Lu, Li Yuan, Tao Liu

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引用次数: 0

摘要

建立了步进加热炉钢坯加热过程的数学模型。根据数学模型，预测了待轧一段时间后的钢坯温度状态，提出了一种遗传算法，使钢坯温度满足工艺要求，降低能耗。实现了在线寻找加热炉待轧过程的加热曲线，降低了加热炉能耗，消除了待轧结束后的加热时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Strategy of Online Furnace of Pending Rolling Temperature Optimization Based on Genetic Algorithm

A mathematical model of the steel billet heating process of the step-by-step heating furnace is established. According to the mathematical model, the state of the furnace billet's temperature is predicted after a period of time when the furnace is pending rolling, a genetic algorithm is proposed to make the billet temperature meet the process requirements and reduce energy consumption. The heating curve of the process of seeking heating furnace pending rolling on-line is realized and the energy consumption of the furnace is reduced and the heating time after the end of the pending rolling is eliminated.

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来源期刊

2020 3rd International Conference on Mechatronics, Robotics and Automation (ICMRA)

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