Mechanical Property Prediction of Hot-rolled Strip by Intelligent Correction Network

Author

Xu, Yunbo ; Yu, Yongmei ; Zheng, Hui ; Wang, Guodong ; Zhang, Pijun

Author_Institution

State Key Lab. of Rolling Technol. & Autom., Northeastern Univ., Shenyang

Volume

1

fYear

0

fDate

0-0 0

Firstpage

1062

Lastpage

1065

Abstract

Based on physical metallurgy and neural network, intelligent prediction models of mechanical property in hot strip mill were developed. A new idea of intelligent correction about mechanical property was proposed. Physical metallurgy models calculated the base value, and the deviation of predicted value with measured value under different technology conditions was obtained by neural network. The simulation indicates that predicted and measured results are in good agreement and the relative error is very low. For 88% yield strength and 98 % tensile strength results, the error is within plusmn3 %, and for 80 % elongation results it is within plusmn6%

Keywords

hot rolling; mechanical engineering computing; metallurgy; neural nets; production engineering computing; yield strength; hot strip mill; hot-rolled strip; intelligent correction network; intelligent prediction models; mechanical property prediction; neural network; physical metallurgy models; Automation; Electronic mail; Intelligent control; Intelligent networks; Mechanical factors; Milling machines; Neural networks; Predictive models; Strips; intelligent correction; mechanical property; neural network; physical metallurgical models;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712508

Filename

1712508