加热炉自适应钢坯温度预报模型的开发

Adaptive Temperature Prediction Model of Slab in Reheating Furnace

针对目前加热炉钢坯温度预报模型的边界条件缺乏自适应性的问题，提出了一种基于神经元网络辨识的在线自适应钢坯温度预报模型，并引入粗轧机组后面的钢坯温度实时检测信号作为反馈修正钢坯温度预报。工业试验和仿真研究皆表明，该自适应钢坯温度预报模型精度高、自适应性好、鲁棒性强。

On the problem that the boundary conditions of the temperature prediction model for slab in reheating furnace are short of adaptation, an adaptive slab temperature prediction model based on neural identification is proposed. The real time temperature signal detected behind roughing rolling unit as a feedback is used for modifying the prediction. Industrial experiments and simulation results show that the model has high accuracy, good adaptation and robustness.