Modeling of HDT pneumatic drying machine for moisture control

The drying process in cigarette factories, centered around the HDT pneumatic drying machine, has historically faced significant challenges with moisture inconsistency. To address this issue, a steady-state model grounded in mass and energy conservation principles was developed, focusing on key variables such as tobacco moisture content and temperature. By integrating model-based feedforward control, the system successfully reduced moisture fluctuations across different batches, ensuring more consistent tobacco moisture levels. Validation through Monte Carlo simulation confirmed the model’s accuracy, and actual control effect demonstrated a mean reduction of 7.65% in the standard deviation of cooling moisture and a 20.27% decrease in the standard deviation of overall moisture variation, significantly improving batch consistency.

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Publication Details

Journal
Drying Technology
Published
2025-03-26
DOI
https://doi.org/10.1080/07373937.2025.2481614
Citations
2
Primary Topic
Industrial Automation and Control Systems
Type
article
Field-Weighted Citation Impact
2.43
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article

Modeling of HDT pneumatic drying machine for moisture control

Fanda Pan, Shuang‐Hua Yang, Yi Cao, Chenchen Zhou et al.
2 citations
Drying Technology
Industrial Automation and Control Systems
2.43
article

Modeling of HDT pneumatic drying machine for moisture control

Fanda Pan, Shuang‐Hua Yang, Yi Cao, Chenchen Zhou, Hongxin Su, Xincheng Zhu, Kaihua Yang
article en
2 citations

Abstract

The drying process in cigarette factories, centered around the HDT pneumatic drying machine, has historically faced significant challenges with moisture inconsistency. To address this issue, a steady-state model grounded in mass and energy conservation principles was developed, focusing on key variables such as tobacco moisture content and temperature. By integrating model-based feedforward control, the system successfully reduced moisture fluctuations across different batches, ensuring more consistent tobacco moisture levels. Validation through Monte Carlo simulation confirmed the model’s accuracy, and actual control effect demonstrated a mean reduction of 7.65% in the standard deviation of cooling moisture and a 20.27% decrease in the standard deviation of overall moisture variation, significantly improving batch consistency.

Drying TechnologyVol. 43(6)
China Tobacco (CN), Quzhou University (CN), University of Reading (GB), Zhejiang University (CN)
Openalex Percentile: Top 13%
Industrial Automation and Control Systems
2.43
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