热轧带钢力学性能预测模型及其应用  

Quality prediction model of the mechanical properties of hot-rolled steel strips and its application

作　　者：王丹民[1] 李华德[1] 周建龙[2] 梅兵[2] 

机构地区：[1]北京科技大学信息工程学院,北京100083 [2]邯郸钢铁集团公司,邯郸056015

出　　处：《北京科技大学学报》2006年第7期687-690,共4页Journal of University of Science and Technology Beijing

摘　　要：为实现对热轧带钢的屈服强度、抗拉强度、断裂延伸率等力学性能的预测及控制,利用人工神经网络技术,分别建立了根据生产工艺参数预测力学性能的质量模型,以及根据力学性能要求对生产工艺参数进行优化的逆质量控制模型.利用质量预测模型,分析得出屈服强度随卷取温度的上升而下降的变化规律,进而可以对组织性能进行在线调整,实现在线应用.To predict and control the yield strength, tensile strength, and elongation of hot-rolled steel strips, a quality model, which could predict the mechanical properties of hot-rolled steel strips with technological parameters, and a reverse quality control model, which could optimize technological parameters with the mechanical properties, were established by applying the technology of artificial neural network. With the quality prediction model it was proved that the value of yield strength decrease with the increase of coiling temperature. Based on this, the mechanical properties of hot-rolled steel strips could be controlled through the real time regulation of coiling temperature to meet production requirements.

关 键 词：热轧带钢 力学性能 质量预测 神经网络 

分 类 号：TG335.5[金属学及工艺—金属压力加工]