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中南大学学报(英文版)

Journal of Central South University

Vol. 26    No. 9    September 2019

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Modeling hot strip rolling process under framework of generalized additive model
LI Wei-gang(李维刚)1, 2, YANG Wei(杨威)1, ZHAO Yun-tao(赵云涛)1, YAN Bao-kang(严保康)1, LIU Xiang-hua(刘相华)3

1. Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;
2. National-provincial Joint Engineering Center of High Temperature Materials and Lining Technology, Wuhan University of Science and Technology, Wuhan 430081, China;
3. Research Institute of Science and Technology, Northeastern University, Shenyang 110819, China

Abstract:This research develops a new mathematical modeling method by combining industrial big data and process mechanism analysis under the framework of generalized additive models (GAM) to generate a practical model with generalization and precision. Specifically, the proposed modeling method includes the following steps. Firstly, the influence factors are screened using mechanism knowledge and data-mining methods. Secondly, the unary GAM without interactions including cleaning the data, building the sub-models, and verifying the sub-models. Subsequently, the interactions between the various factors are explored, and the binary GAM with interactions is constructed. The relationships among the sub-models are analyzed, and the integrated model is built. Finally, based on the proposed modeling method, two prediction models of mechanical property and deformation resistance for hot-rolled strips are established. Industrial actual data verification demonstrates that the new models have good prediction precision, and the mean absolute percentage errors of tensile strength, yield strength and deformation resistance are 2.54%, 3.34% and 6.53%, respectively. And experimental results suggest that the proposed method offers a new approach to industrial process modeling.

 

Key words: industrial big data; generalized additive model; mechanical property prediction; deformation resistance prediction

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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