Industrial IoT–enabled real-time prediction of strip cross-section shape for hot-rolling steel
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00170-023-12745-8.pdf
Reference41 articles.
1. He HN, Shao J, Wang XC, Yang Q, Liu Y, Xu D, Sun YZ (2021) Research and application of approximate rectangular section control technology in hot strip mills. J Iron Steel Res Int 28:279–290. https://doi.org/10.1007/s42243-021-00558-6
2. Zhao JW, Li JD, Yang Q, Wang XC, Ding XX, Peng GZ, Shao J, Gu ZW (2023) A novel paradigm of flatness prediction and optimization for strip tandem cold rolling by cloud-edge collaboration. J Mater Process Tech 316:117947. https://doi.org/10.1016/j.jmatprotec.2023.117947
3. Wu ZD, Yang Q, Wang XC, Xu D, Zhao JW, Li JD (2023) Preset model of bending force in 6-high universal crown tandem cold rolling mill based on symbolic regression. Ironmak Steelmak. https://doi.org/10.1080/03019233.2023.2218777
4. He HN, Wang XC, Yang Q, Sun XJ, Xiao JL, Liu Y, Song GY (2018) Smart-shifting strategy of work rolls for downstream stands in hot rolling. Ironmak Steelmak 47(5):512–519. https://doi.org/10.1080/03019233.2018.1541656
5. Kim W, Won D, Tomizuka M (2015) Flatness-based nonlinear control for position tracking of electrohydraulic systems. Ieee-Asme T Mech 20(1):197–206. https://doi.org/10.1109/TMECH.2014.2310498
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