Research on deformation resistnce of strip steel and rolling force prediction during cold roiling based on mile not roiling parameters

In view of the influence of the fluctuation of incoming material composition, finishing temperature and coiling temperature on the deformation resistance in the cold rolling process during the hot rolling process, the optimization objective function is established by combining the analytic method and big data regression. Further, the relevant characteristic coefficients are calculated through a large number of on-site actual data, and the deformation resistance model of hot-rolled finished strip and the rolling pressure prediction model of cold rolling process are obtained. Through the field test, the deviation between the predicted rolling force and the actual rolling force is less than 2%, and the accuracy of the model can meet the engineering requirements. More importantly, after using the research results described in this paper, the quality of cold rolled strip shape has been significantly improved, which can greatly improve the economic efficiency and market competitiveness of enterprises.

Automated summary

In this study, an optimization model for deformation resistance during the cold rolling process in the hot rolling process was established using analytical methods and big data regression. The accuracy of the model was validated through actual data and field tests, and the application of the research results greatly improved the quality and shape of the cold rolled strip.