Strip Thickness and Profile–Flatness Prediction in Tandem Hot Rolling Process Using Mechanism Model‐Guided Machine Learning-Reference-Cited by-同舟云学术

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Strip Thickness and Profile–Flatness Prediction in Tandem Hot Rolling Process Using Mechanism Model‐Guided Machine Learning

Published:2022-10-21 Issue:1 Volume:94 Page:2200447
ISSN:1611-3683
Container-title:steel research international
language:en
Short-container-title:steel research int.

Author:

Liu Yu¹,Wang Xiaojun¹,Sun Jie²,Liu Guangming³,Li Huaying³,Ji Yafeng¹^ORCID

Affiliation:

1. School of Mechanical Engineering Taiyuan University of Science and Technology Taiyuan 030024 China

2. State Key Laboratory of Rolling and Automation Northeastern University Shenyang Liaoning 110819 China

3. School of Materials Science and Engineering Taiyuan University of Science and Technology Taiyuan 030024 China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province

Program for the Scientific Activities of Selected Returned Overseas Professionals in Shaanxi Province

Publisher

Wiley

Subject

Materials Chemistry,Metals and Alloys,Physical and Theoretical Chemistry,Condensed Matter Physics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/srin.202200447

Reference25 articles.

1. A double-layer optimization model for flatness control of cold rolled strip

2. Research on cast-rolling force in twin-roll continuous strip casting based on uncertainty analysis

3. Study on mathematical model of work roll wear in skin-pass rolling of hot steel strip

4. Prediction and analysis of cold rolling mill vibration based on a data-driven method

5. Research on High‐Precision Transverse Thickness Difference Control Strategy Based on Data Mining in 6‐High Tandem Cold Rolling Mills

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1. An interpretable framework for high-precision flatness prediction in strip cold rolling;Journal of Materials Processing Technology;2024-08

2. Subsection cooling system of hot rolling silicon steel and its industrial application;Journal of Iron and Steel Research International;2024-05-17

3. Joint prediction method for strip thickness and flatness in hot strip rolling process: A combined multi-indicator Transformer with embedded sliding window;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2024-05-11

4. Online segmented thickness prediction of hot rolling strip based on IBA-XGBoost;International Journal of Data Science and Analytics;2024-04-25

5. Industrial Big Data‐Driven Modeling and Prediction for Hot‐Rolled Strip Crown with Multigrade and Multispecification Data;steel research international;2024-04-25

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