Energy and mass transfer dynamic prediction model of the conditioning cylinder: modeling and applications research

Zijuan Li; Jiaojiao Chen; Zixian Feng; Shuo Sun; Yang Gao; Liyuan Zhao

doi:10.1117/12.2627630

11 March 2022 Energy and mass transfer dynamic prediction model of the conditioning cylinder: modeling and applications research

Zijuan Li, Jiaojiao Chen, Zixian Feng, Shuo Sun, Yang Gao, Liyuan Zhao

Author Affiliations +

Proceedings Volume 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021); 121600O (2022) https://doi.org/10.1117/12.2627630
Event: International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 2021, Sanya, China

Abstract

The WF315A drum hot air conditioning cylinder is the main equipment for the process of tobacco silk production. The main problem at present is not stable enough of the outlet moisture content. The large lag and uncertainty of the leaf moisturizing process made it impossible to achieve closed-loop automatic controls of the conditioning cylinder. The methods of energy and material balance were used to analyze heat and water exchange between steam and leaves. And the dynamic prediction models of the opening of the film valve and the water/heat transfer were established. Through actual production verification, the relative error of the dynamic prediction model is within ∓0.17%, which meets the production requirements of ±0.50%. At the same time, two potential industrial applications were proposed, including the prediction of equipment operating status and the establishment of automatic control systems. This work can also provide a theoretical basis of system optimization to achieve energy and material savings.

Citation Download Citation

Zijuan Li, Jiaojiao Chen, Zixian Feng, Shuo Sun, Yang Gao, and Liyuan Zhao "Energy and mass transfer dynamic prediction model of the conditioning cylinder: modeling and applications research", Proc. SPIE 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 121600O (11 March 2022); https://doi.org/10.1117/12.2627630

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KEYWORDS

Data modeling

Error analysis

Instrument modeling

Mathematical modeling

Statistical modeling

Automatic control

Control systems

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