现代电子技术2026，Vol.49Issue(13)：1-8,13,9.DOI:10.16652/j.issn.1004-373X.2026.13.001
基于注意力机制和多尺度特征融合的氩花图像分割
Argon bubble image segmentation based on attention mechanism and multi-scale feature fusion
摘要
Abstract
In the bottom-blowing argon process of ladle metallurgy,the exposed area of the molten steel surface(referred to as the argon bubble region)serves as an indirect indicator of the argon gas flow rate.Accurate segmentation of the argon bubble region is crucial for optimizing the argon-blowing process.In view of this,the paper proposes a multi-branch argon bubble image segmentation algorithm based on attention mechanisms and multi-scale feature fusion,so as to enhance segmentation accuracy.The method is built upon the HRNet architecture and several improvements is introduced.Firstly,a combined Dice Focal Loss function is used to replace the conventional cross-entropy loss to eliminate the sample imbalance between the argon bubble and background regions.Secondly,depthwise separable convolutions are employed to reconstruct the residual modules of the backbone network,so as to significantly reduce both model parameters and computational cost.And then,a coordinate attention mechanism is integrated with minimal computational overhead to better get complex edge structures of the argon bubble regions.Finally,a parallel aggregation pyramid pooling module is designed to facilitate multi-scale information fusion and further improve segmentation accuracy.The experimental results show that the mIoU(mean intersection over union)of the proposed algorithm reaches 94.55%on a private dataset of a steel plant.It can be seen that the mIoU of the proposed algorithm increases by 1.62%and its accuracy reaches 99.31%compared with HRNet,so it can meet the requirements of argon bubble image segmentation in industrial production.关键词
钢包底吹氩/图像分割/HRNet/损失函数/轻量化/坐标注意力机制/金字塔池化Key words
bottom-blowing argon/image segmentation/HRNet/loss function/lightweight/coordinate attention mechanism/pyramid pooling分类
信息技术与安全科学引用本文复制引用
褚佳兴,王静宇,任国印,李豆,栗丽莎..基于注意力机制和多尺度特征融合的氩花图像分割[J].现代电子技术,2026,49(13):1-8,13,9.基金项目
国家自然科学基金项目(62466045) （62466045）
洁净钢精炼智能吹氩技术开发与应用(2024RCTD003) （2024RCTD003）
内蒙古自治区自然科学基金项目(2024LHMS06014) （2024LHMS06014）
内蒙古自治区重点研发和成果转化计划项目(2022YFSH0044) （2022YFSH0044）
内蒙古自治区高等学校科学研究项目(NJZY23076) （NJZY23076）
内蒙古自治区直属高校基本科研业务费项目(2024XKJX028,2024RCTD003) （2024XKJX028,2024RCTD003）
内蒙古自治区教育厅冶金工程一流学科科研专项项目(YLXKZX-NKD-014) （YLXKZX-NKD-014）
