The hot strip heat-flow density in interstand water cooling zones of finishing mill was predicted by mathematical model combined with BP neural network for optimization of the model of interstand cooling.
采用BP神经网络与数学模型相结合的方法对热带精轧机组机架间水冷区带钢热流密度进行预测,进而优化了机架间冷却的数学模型。
In order to improve the control accuracy of strip finishing temperature, the heat exchange process that causes hot strip temperature variation during finish rolling was analyzed, which provides the theoretical basis of heat transfer and selfstudy model for interstand cooling control.
为了提高带钢终轧温度的控制精度,对精轧过程中导致带钢温度变化的热交换过程进行了分析,并以此作为建立机架间冷却控制的传热模型和自学习模型的理论依据。
