Original scientific paper

Prediction of alloy addition in ladle furnace (LF) based on LWOA-SCN

C. Y. Shi orcid.org/0000-0002-4846-4707 ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
B. S. Wang ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
S. Y. Guo ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
X. X. Yin ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
Y. K Wang ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
L. Zhang ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
R. Chen ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China
Z. C. Ma ; School of Global 100-100, Liaoning Institute of Science and Technology, Benxi, China

Abstract

The amount of alloy added during the LF refining process affects the hit rate of steel composition control. Therefore, improving the accuracy of the alloy addition amount can help improve efficiency and reduce production costs. To address the existing problem of inaccurate alloy addition in the refining process, the group established an alloy addition prediction model based on an improved whale swarm optimization algorithm and stochastic configuration network (LWOA-SCN) with the historical smelting data of a steel mill. The model can effectively improve the prediction accuracy and convergence speed of the model. The research results show that the model is more advantageous in improving the hit rate of alloy addition, which provides theoretical guidance for practical production.

Keywords

LF refining; alloy addition; stochastic configuration network; improved whale swarm algorithm

Hrčak ID:

300991

URI

https://hrcak.srce.hr/300991

Publication date:

3.7.2023.

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