Slag foaming estimation in the electric arc furnace using machine learning based long short-term memory networks

Slag foaming estimation in the electric arc furnace using machine learning based long short-term memory networks

Slag foaming is a key factor in terms of quality and productivity in the electric arc furnace (EAF) steelmaking process. Optimal control of slag foaming is required, but is difficult due to the absence of practical on-line measuring methods and the broad process variability. In this study, a soft se...

Full description

Bibliographic Details
Main Authors: Kyungchan Son, Jaegak Lee, Haejin Hwang, Wonseok Jeon, Hyunseok Yang, Il Sohn, Younghwan Kim, Hyungsic Um
Format: Article
Language:English
Published: Elsevier 2021-05-01
Series:Journal of Materials Research and Technology
Subjects:
Electric arc furnace (EAF)
Slag foaming height
Long short-term memory (LSTM) network
Soft sensor model
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785421002118

Internet

http://www.sciencedirect.com/science/article/pii/S2238785421002118

Similar Items