摘要
为解决烘丝控制中数据源单一、变量间耦合性强、烘丝机出口烟丝含水率不稳定等问题,加装了环境温湿度和蒸汽干度的智能感知传感器,结合烘丝多参数协同关联分析,建立了基于随机森林增量学习的动态预测模型,构建了烘丝机出口烟丝含水率多级调控策略,实现了滚筒管板烘丝机出口烟丝含水率的多参数特征协同优化控制。以A线“芙蓉王(硬)”牌号卷烟配方原料为对象进行测试,结果表明:①环境温湿度和蒸汽干度对烘丝控制过程具有显著影响。②应用多参数特征协同优化控制策略后,与B线传统PID控制模式相比,A线烘丝机出口烟丝含水率过程控制能力指数平均值提升45%,标准偏差平均值降低52%,非稳态时间平均值降低15%,且A线的多批次控制数据具有一致有效性。该方法可有效提高滚筒管板烘丝机出口烟丝含水率的过程控制能力,保障烟丝质量的稳定性。
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.
作者
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
WEN Guangqiu;WU Wenqiang;LIU Bin;MAO Weijun;GAO Tiegong;YANG Xingquan;JIANG Ting;ZHOU Chenglin;DENG Hongwei(Lingling Cigarette Factory,China Tobacco Hunan Industrial Co.,Ltd.,Yongzhou 425006,Hunan,China;Technology Center,China Tobacco Hunan Industrial Co.,Ltd.,Changsha 410007,China;First State Technology(Hangzhou)Co.,Ltd.,Hangzhou 311202,China)
出处
《烟草科技》
北大核心
2025年第6期82-91,共10页
Tobacco Science & Technology
基金
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)。
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
Cylinder dryer
Corrugated heating plate
Multi-parameter collaboration
Random forest
Incremental learning
Intelligent perception
Predictive control
作者简介
第一作者:文广球(1970-),男,本科,从事电气自动化、工业大数据应用研究。E-mail:326133283@qq.com;通信作者:吴文强(1980-),男,硕士,高级工程师,从事卷烟工艺、智能制造研究。E-mail:4457987@qq.com。
