Analysis of Intelligent Welding Strategies Based on Machine Vision

DOI

10.2991/978-94-6239-648-7_47How to use a DOI?

Keywords

Machine vision; intelligent welding; weld inspection; image processing; quality control

Abstract

With the fast development of industrial automation, welding process is one of the core production processes that affects product quality and production efficiency of enterprises with its welding quality and efficiency. Non-contact inspection, real-time information acquisition, and high-precision recognition make machine vision technology the main core driver to upgrade intelligent welding technology in the future. The application of machine vision technology in intelligent welding is discussed for weld seam detection and identification as well as monitoring weld quality. First, the author studies the basic theory of machine vision and intelligent welding technology and lays a theoretical foundation, clarifying coordination mechanisms between vision system and welding equipment. Second, according to weld identification needs, an image acquisition scheme is designed based on the actual engineering environment. Image pre-processing is conducted and features and recognition are extracted by employing various algorithms, such as the template matching algorithm and the Hough transform algorithm, then results locate accurately welded seams experimentally. Third, we construct a real-time monitoring system for welding in this work based on machine vision platform, where by introducing machine learning method and relying on visual characteristic information of pores, cracks, and lack of fusion in the welding process, visual characteristics are further extracted and identified to complete the online weld quality detection. Finally, we construct an experimental platform to test weld positioning precision and weld defect recognition accuracy under various conditions. A highly automatized welding system using machine vision greatly accelerates welding automation intelligence; therefore, machine vision has become an essential supportive force for promoting high-end manufacturing to achieve higher quality.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Junying Tong
PY  - 2026
DA  - 2026/04/24
TI  - Analysis of Intelligent Welding Strategies Based on Machine Vision
BT  - Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
PB  - Atlantis Press
SP  - 426
EP  - 438
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-648-7_47
DO  - 10.2991/978-94-6239-648-7_47
ID  - Tong2026
ER  -