Application of Neural Networks to Quenching and Control Cooling
-
摘要: 熱軋鋼材的淬火冷卻是改善鋼材質量和性能的重要措施,淬火過程的核心就是控制鋼板的冷卻速度.針對傳統的淬火控冷模型的固有缺陷,為了滿足擴展鋼種、規格及淬火溫度高精度的要求,利用神經網絡技術建立了神經網絡淬火控冷溫度預報模型,該模型與回歸數學模型相結合,完成淬火控冷現場控制.應用結果證明,該綜合模型極大地提高了鋼板淬火冷卻的控制精度,提高了產品的成材率.Abstract: The quenching and cooling of hot-rolling steel is a important step to improve the quality and mechanical properties of steel plates. It is the key to a quenching procedure to control the speed of cooling. Against the inherent shortcoming of the traditional quenching model and for the requirement of expanding steel varieties, specifications and improving the precision of quenching temperature, a temperature forecast model in quenching and control cooling was established by the method of neural networks. Combining this forecast model with the previous regression mathematical model, the real-times control of quenching and control cooling was accomplished. The result shows that the comprehensive model improved greatly the controlling accuracy of quenching and cooling.
-
Key words:
- neural network /
- quenching /
- mathematical model
-

計量
- 文章訪問數: 133
- HTML全文瀏覽量: 16
- PDF下載量: 8
- 被引次數: 0