烟草科技2025，Vol.58Issue(6)：82-91,10.DOI:10.16135/j.issn1002-0861.2024.0921
基于多参数特征协同优化的滚筒管板烘丝机出口烟丝含水率的控制及应用
Moisture control in cut tobacco output from cylinder dryer with corrugated heating plate by collaborative optimization of multi-parameters
摘要
Abstract
To achieve single data source and strong coupling of variables in the control of tobacco drying and reduce unstable moisture content in cut tobacco output from a cylinder dryer,intelligent sensors were installed for smart sensing of ambient temperature,relative humidity and steam dryness.By combining with the multi-parameter collaborative correlation analysis,a dynamic prediction model based on random forest incremental learning was established.The multi-level control strategy for moisture control in cut tobacco output from cylinder drying was developed to realize the multi-parameter characteristic collaborative optimization control of moisture content.Tests were conducted with blended tobacco material for"Furongwang(Hard)"brand cigarette in production line A,and the results showed that:1)Ambient temperature,relative humidity and steam dryness significantly affected the control process of cut tobacco drying.2)Compared with production line B using the traditional PID control mode,the average process control capability index for moisture content in the cut tobacco increased by 45%,the average standard deviation decreased by 52%,and the average unsteady time decreased by 15%in production line A.In addition,the control data from several batches in line A was validated with higher consistency.This method effectively improves the moisture control capability in cut tobacco output from the cylinder dryer and ensures the consistency of the cut tobacco quality.关键词
滚筒烘丝机/管板结构/多参数协同/随机森林/增量学习/智能感知/预测控制Key words
Cylinder dryer/Corrugated heating plate/Multi-parameter collaboration/Random forest/Incremental learning/Intelligent perception/Predictive control分类
轻工业引用本文复制引用
文广球,吴文强,刘斌,毛伟俊,高铁功,杨兴权,江婷,周成林,邓红伟..基于多参数特征协同优化的滚筒管板烘丝机出口烟丝含水率的控制及应用[J].烟草科技,2025,58(6):82-91,10.基金项目
湖南中烟工业有限责任公司智能制造重大专项项目"烘丝机智能控制集成技术研究"(KY2023CG0011). （KY2023CG0011）
