Plastic Deformation Resistance of Steel Grades EP450-Sh and EP823-Sh in Hot and Cold State

Kosmatski, Ya. I.; Fokin, N. V.; Barichko, B. V.; Yakovleva, K. Yu.; Nikolenko, V. D.

doi:10.1007/s11015-021-01209-7

Cited by 1 publication

(1 citation statement)

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“…This method can use a large number of data for classification and fitting, and further establish a calculation model, which is more suitable for field production [16]. Because the analytic method uses the Gleeble thermal simulator data in the research process, these models are mainly aimed at specific steel grades and cannot be widely used [17,18]. The big data regression method avoids this situation.…”

Section: State Of the Artmentioning

confidence: 99%

Research on deformation resistance of strip steel and rolling force prediction during cold rolling based on the hot rolling parameters

Xiying¹,

Baomin²,

Wang³

et al. 2022

Ironmaking & Steelmaking

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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.

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Section: State Of the Artmentioning

confidence: 99%