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| Prediction technology for mechanical properties of hot-dip aluminum zinc plating unit products |
| WEI Baomin1, WANG Xiaojian1,2, BAI Zhenhua2,3 |
1. Meisteel Technology Center, Academia Sinica, Baosteel, Nanjing 210039, Jiangsu, China;
2. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Yanshan University, Qinhuangdao 066004, Hebei, China;
3. State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066004, Hebei, China |
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Abstract Aiming at the issue of poor mechanical properties of hot-dip aluminum zinc plating unit products, based on the importance analysis and data sample clustering analysis of influencing parameters for product mechanical properties, a BP neural network prediction model for mechanical properties of the hot-dip aluminum zinc plating unit product was established. The calculation of mechanical properties parameters such as yield strength, tensile strength, and elongation after fracture of the strip steel was achieved in statistical sense. Based on the flat rolling mechanism model and using deformation resistance as a bridge, the fluctuation of deformation resistance at the exit of the strip steel was calculated based on the real-time rolling force data model during the flat rolling process. Thus the yield strength, tensile strength, and elongation after fracture predicted by the BP neural network model were modified, and a set of mechanical properties prediction technology of hot-dip products combining neural network model and physical metallurgy model was further formed. The application of this technology to the on-site production of hot-dip aluminum zinc plating unit in a steel plant provides theoretical basis for the formulation of the production process of the unit.
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Received: 07 September 2023
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2024, Vol. 34 
