烟草科技2026，Vol.59Issue(8)：82-90,9.DOI:10.16135/j.issn1002-0861.2025.0865
基于改进BiSeNet的片烟加料机雾化效果实时监测系统
Real-time monitoring system for the atomization effect in a tobacco strip casing cylinder based on an improved BiSeNet
摘要
Abstract
To realize the real-time monitoring of the casing atomization effect of nozzles during the tobacco strip casing process,a real-time visual monitoring system based on deep learning was designed.The system integrates image acquisition module,image processing module and online alarm module to acquire real-time images of nozzle atomization.The image processing module extracts atomization features by morphological processing and an improved lightweight semantic segmentation model(LightBiSeUNet).Based on an asymmetric dual-path parallel architecture comprising a detail branch and a semantic branch,the model effectively suppresses complex interferences,such as the bright background of the cylinder by introducing lightweight depthwise separable convolution(LightConv),Squeeze-and-Excitation(SE)channel attention mechanism,and global average pooling-based global context enhancement(GAP-based GCE)module,achieving adaptive focusing on irregular atomization edges.Experimental results showed that:1)The LightBiSeUNet model achieved a mean intersection over union(MIoU)of 99.57%with a parameter count of about 0.110 M,enabling precise segmentation of atomization images captured by a high-speed camera frame by frame.2)Comparisons with U-Net,MobileUNet and BiSeNet further verified its advantages in segmentation accuracy and resistance to overfitting.3)The application in the industrial production line of Liuzhou Cigarette Factory indicated that the closed-loop control based on high-frequency feedback from this vision system enabled the casing cylinder to intervene in transient anomalies in seconds,reducing the coefficient of variation of casing uniformity from 4.80%to 2.24%.This method enables real-time and accurate monitoring of atomization effect and provides a new approach for real-time and lightweight deployment of industrial image segmentation.关键词
片烟加料机/雾化效果/实时监测/机器视觉/轻量化模型/闭环控制Key words
Tobacco strip casing cylinder/Atomization effect/Real-time monitoring/Machine vision/Lightweight model/Closed-loop control分类
轻工纺织引用本文复制引用
赵晓雷,李玉珩,黄晓飞,韦斌,胡德征,吴明慧,李志远,华庆钊,李朝栋,郝明磊..基于改进BiSeNet的片烟加料机雾化效果实时监测系统[J].烟草科技,2026,59(8):82-90,9.基金项目
秦皇岛烟草机械有限责任公司科研项目"加料机智能管理系统研究"(Y202412). （Y202412）
