引用本文:
【打印本页】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 1139次   下载 0  
分享到: 微信 更多
深度学习在焊接领域的应用研究现状
胡波
作者单位
胡波  
摘要:
随着以深度神经网络为代表的深度学习模型取得突破性快速发展,同时得益于更强大的计算机、更大的数据集和能够训练更深网络的技术,深度学习在智能焊接等智能制造领域取得了大量应用。概述了深度学习技术在焊接过程控制、焊缝缺陷检测等方面的研究进展,当前的研究表明深度学习方法能够提高焊接过程实时控制精度和焊接缺陷的识别准确率。
关键词:  深度学习  焊接过程控制  焊接缺陷  神经网络
DOI:
分类号:
基金项目:
Research status of the application of deep learning in welding field
Hu Bo
Abstract:
With the rapid development of deep learning models represented by deep neural networks, and thanks to the more powerful computers, larger data sets and networks that be trained deeper, deep learning has gained a lot of applications in the field of intelligent manufacturing including intelligent welding. This paper summarizes the research progress of deep learning technology in welding process control and weld defect detection. The current research showed that deep learning methods can improve the accuracy of real-time control of welding processes and the recognition accuracy of weld defects.
Key words:  deep learning  welding process control  welding defect  neural network

分享按钮