Modeling deformation resistance for hot rolling based on generalized additive model

IF 3.1 2区 材料科学 Q1 METALLURGY & METALLURGICAL ENGINEERING
Wei-gang It , Chao Liu , Yun-tao Zhao , Bin Liu , Xiang-hua Liu
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引用次数: 1

Abstract

A model of deformation resistance during hot strip rolling was established based on generalized additive model. Firstly, a data modeling method based on generalized additive model was given. It included the selection of dependent variable and independent variables of the model, the link function of dependent variable and smoothing functional form of each independent variable, estimating process of the link function and smooth functions, and the last model modification. Then, the practical modeling test was carried out based on a large amount of hot rolling process data. An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon, silicon, manganese, nickel, chromium, niobium, etc. The integrated chemical composition, strain, strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them. The modeling process of deformation resistance was realized by SAS software, and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm. Some interesting phenomena were found, for example, there is a critical value of strain rate, and the deformation resistance increases before this value and then decreases. The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel, microalloyed steel, alloyed steel and other steel grades.

基于广义加性模型的热轧变形抗力建模
基于广义加性模型,建立了热连轧变形抗力模型。首先,给出了一种基于广义加性模型的数据建模方法。包括模型的因变量和自变量的选择,因变量的链接函数和每个自变量的平滑函数形式,链接函数和平滑函数的估计过程,以及最后的模型修正。然后,基于大量的热轧工艺数据进行了实际的建模试验。提出了一个综合变量来反映碳、硅、锰、镍、铬、铌等不同化学成分的影响。选取综合化学成分、应变、应变速率和轧制温度作为自变量,以三次样条作为它们的光滑函数。利用SAS软件实现了变形抗力的建模过程,并通过局部评分算法获得了自变量对变形抗力的影响曲线。发现了一些有趣的现象,如应变率存在一个临界值,变形阻力在此值之前先增大后减小。结果表明,新模型比传统模型具有更高的预测精度,适用于碳钢、微合金钢、合金钢等钢种。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.30
自引率
0.00%
发文量
2879
审稿时长
3.0 months
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