管道焊接中焊缝缺陷检测的研究现状
Research Status of Weld Defect Detection in Pipeline Welding
张宽 1王树强 1芦伟1
作者信息
摘要
文中研究了管道焊接领域焊缝缺陷检测方法的现状及发展趋势.通过对传统非破坏性检测方法和计算机深度学习技术检测方法的综合比较,发现传统方法在准确性和效率方面存在局限性.因此,引入计算机深度学习技术,介绍了基于各种算法的焊缝缺陷检测方法.结果表明,这些方法在焊缝检测中优于传统方法.未来将引入新的模型,使管道焊缝检测技术向自动化和智能化、全数字化和信息化发展,并探索其在实际工程中的应用前景,以提高管道焊接质量和安全性.
Abstract
The current status and development trends of weld defect detection methods in the field of pipeline welding were studied in this paper.Through a comprehensive comparison between traditional non-destructive detection methods and computer deep learning technology detection methods,it is found that traditional methods have limitations in accuracy and efficiency.Therefore,the introduction of computer deep learning technology and the introduction of weld defect detection methods based on various algorithms were introduced.The results indicate that these methods are superior to traditional methods in weld seam detec-tion.In the future,new models were introduced and making the pipeline weld detection technology develop towards automation,intelligence,full digitalization,and informatization,and its application prospects in practical engineering was explored to im-prove the quality and safety of pipeline welding.
关键词
管道焊接/焊缝缺陷检测/计算机视觉/深度学习/卷积神经网络Key words
pipeline welding/weld defect detection/computer vision/deep learning/convolutional neural networks引用本文复制引用
出版年
2024
NETL
NSTL
万方数据