电焊机2024，Vol.54Issue(12)：28-34,7.DOI:10.7512/j.issn.1001-2303.2024.12.05
ECA注意力机制增强的轻量级网络焊接熔池轮廓提取方法
Enhanced Lightweight Network for Melt Pool Contour Extraction with ECA Attention Mechanism
张昆 1范东阳 1袁飞 2黄勇 3李晓鹏3
作者信息
- 1. 海军装备部驻上海地区第一军事代表室,上海 201913
- 2. 江南造船(集团)有限责任公司,上海 201913
- 3. 南京理工大学 材料科学与工程学院,江苏 南京 210094
- 折叠
摘要
Abstract
Online detection of arc additive molten pool morphology features is an important way to achieve system intelli-gence and automation.However,current methods for extracting molten pool contours mostly use traditional processing algo-rithms based on threshold segmentation.These algorithms have low accuracy and poor robustness in the presence of arc in-terference.Reports on using deep learning for molten pool contour extraction are relatively rare,and there are certain chal-lenges in terms of real-time performance.To address this issue,this paper proposes an improved efficient semantic segmenta-tion model based on DeepLabv3+for molten pool contour extraction.Experimental results show that the proposed algorithm achieves the mean Intersection over Union(mIoU)of 96.08%and the mean pixel accuracy(mPA)of 97.85%,while reduc-ing inference time from 60.72 ms to 23.11 ms,thus meeting the requirements for accurate and real-time molten pool contour extraction.关键词
语义分割/熔池轮廓提取/轻量级网格/ECA注意力机制Key words
semantic segmentation/melt pool contour extraction method/lightweight network分类
信息技术与安全科学引用本文复制引用
张昆,范东阳,袁飞,黄勇,李晓鹏..ECA注意力机制增强的轻量级网络焊接熔池轮廓提取方法[J].电焊机,2024,54(12):28-34,7.
