{"title":"An adaptive optimization method toward batch-wise variable set point of outlet moisture content for the tobacco drying process","authors":"Yulei Gao, Tianyu Wang, X. Zhou, Mian Li, Chiyuan Zhang, Peng Qin, Yaojing Yang, Libin Zhang","doi":"10.1080/07373937.2023.2222472","DOIUrl":null,"url":null,"abstract":"Abstract The tobacco drying process in the cigarette production has an important effect on the final product quality. Therefore, the intelligent control methods have been widely investigated to ensure the stability of tobacco’s outlet moisture content. The existing work mostly uses a relatively fixed set point of the outlet moisture content for different tobacco batches, which can lead to unforeseen product quality after several processes following the drying process and inaccessible amount of dehydration for the rotary dryer. Some tobacco moisture prediction methods have been studied recently while the relationship with the intelligent control methods remain largely unexplored. To deal with these issues, a novel method is proposed in this paper to identify the optimal set point of the drying outlet moisture content for each tobacco batch. An encoder-decoder model is first developed to forecast the post-drying moisture trajectory. Then, an adaptive filter with specially designed mechanisms and a confidence interval of the dehydration level are constructed to obtain the design constraints. Based on all above, a constrained optimization problem is formulated and solved by the genetic algorithm. Extensive experiments on 895 tobacco batches from a large cigarette factory are carried out, which involves both algorithmic evaluation and field test. It turns out that the proposed method achieves the superior performance and leads to an improvement of the product quality in real production.","PeriodicalId":11374,"journal":{"name":"Drying Technology","volume":"41 1","pages":"2156 - 2170"},"PeriodicalIF":2.7000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drying Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/07373937.2023.2222472","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The tobacco drying process in the cigarette production has an important effect on the final product quality. Therefore, the intelligent control methods have been widely investigated to ensure the stability of tobacco’s outlet moisture content. The existing work mostly uses a relatively fixed set point of the outlet moisture content for different tobacco batches, which can lead to unforeseen product quality after several processes following the drying process and inaccessible amount of dehydration for the rotary dryer. Some tobacco moisture prediction methods have been studied recently while the relationship with the intelligent control methods remain largely unexplored. To deal with these issues, a novel method is proposed in this paper to identify the optimal set point of the drying outlet moisture content for each tobacco batch. An encoder-decoder model is first developed to forecast the post-drying moisture trajectory. Then, an adaptive filter with specially designed mechanisms and a confidence interval of the dehydration level are constructed to obtain the design constraints. Based on all above, a constrained optimization problem is formulated and solved by the genetic algorithm. Extensive experiments on 895 tobacco batches from a large cigarette factory are carried out, which involves both algorithmic evaluation and field test. It turns out that the proposed method achieves the superior performance and leads to an improvement of the product quality in real production.
期刊介绍:
Drying Technology explores the science and technology, and the engineering aspects of drying, dewatering, and related topics.
Articles in this multi-disciplinary journal cover the following themes:
-Fundamental and applied aspects of dryers in diverse industrial sectors-
Mathematical modeling of drying and dryers-
Computer modeling of transport processes in multi-phase systems-
Material science aspects of drying-
Transport phenomena in porous media-
Design, scale-up, control and off-design analysis of dryers-
Energy, environmental, safety and techno-economic aspects-
Quality parameters in drying operations-
Pre- and post-drying operations-
Novel drying technologies.
This peer-reviewed journal provides an archival reference for scientists, engineers, and technologists in all industrial sectors and academia concerned with any aspect of thermal or nonthermal dehydration and allied operations.