摘要
热轧钢材的淬火冷却是改善钢材质量和性能的重要措施,淬火过程的核心就是控制钢板的冷却速度.针对传统的淬火控冷模型的固有缺陷,为了满足扩展钢种、规格及淬火温度高精度的要求,利用神经网络技术建立了神经网络淬火控冷温度预报模型,该模型与回归数学模型相结合,完成淬火控冷现场控制.应用结果证明,该综合模型极大地提高了钢板淬火冷却的控制精度,提高了产品的成材率.
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 showed that the comprehensive model improved greatly the controlling accuracy of quenching and cooling.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2003年第4期370-373,共4页
Journal of University of Science and Technology Beijing
