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热轧带钢力学性能预测模型及其应用
引用本文:王丹民,李华德,周建龙,梅兵.热轧带钢力学性能预测模型及其应用[J].北京科技大学学报,2006,28(7):687-690.
作者姓名:王丹民  李华德  周建龙  梅兵
作者单位: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
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.

关 键 词:热轧带钢  力学性能  质量预测  神经网络  热轧带钢  力学性能  性能预测模型  在线应用  application  steel  mechanical  properties  prediction  model  在线调整  组织性能  变化规律  卷取温度  分析  质量预测模型  质量控制模型  优化  工艺参数  生产工艺  质量模型  参数预测
收稿时间:2005-04-25
修稿时间:2005-09-02

Quality prediction model of the mechanical properties of hot-rolled steel strips and its application
WANG Danmin,LI Huade,ZHOU Jianlong,MEI Bing.Quality prediction model of the mechanical properties of hot-rolled steel strips and its application[J].Journal of University of Science and Technology Beijing,2006,28(7):687-690.
Authors:WANG Danmin  LI Huade  ZHOU Jianlong  MEI Bing
Abstract: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.
Keywords:hot-rolled steel strip  mechanical properties  quality prediction  artificial neural network
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