热轧带钢卷取温度智能预报系统及仿真程序的研究（英文）

Research on intelligent prediction system and simulation program of hot-strip coiling temperature

将先进的控制理论和智能优化算法应用于实际生产中,是进一步提高热轧带钢卷取温度控制精度的有效途径。在设计了“优生”和“返祖”两个新的遗传操作的基础上,提出了参数智能化设计的遗传算法,并将其应用于基于遗传神经网络的卷取温度预报系统;利用某钢厂热轧作业部的历史数据,对模型进行了有导师训练和离线测试;基于MFC(微软基类库)的仿真程序结果表明:该卷取温度预报系统预报精度高,且算法收敛速度快,不仅可以提高热轧带钢的产品质量,同时为发展高端、高附加值的带钢产品提供了有力的技术支持。

The application of advanced control theory and intelligent optimization algorithm in actual production is an effective way to further improve the coiling temperature control accuracy of hot strip.A genetic algorithm for parameter intelligent design is proposed in this paper based on the design of two new genetic operations,eugenic and atavistic.And it is applied in the coiling temperature prediction system based on Genetic Neural Network.U-sing the historical data of the hot rolling operation department of a steel mill,the model was trained and in-line tested and the simulation results of MFC(Microsoft Base Class Library)show that the coiling temperature predic-tion system has high precision and fast convergence speed.It can not only improve the quality of hot rolled strip products,but also provide strong technical support for the development of high-end and high value-added strip products.