Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review

Welding is a method of realizing material connections, and the development of modern sensing technology is pushing this traditional process towards automation and intelligence. Among many sensing methods, visual sensing stands out with its advantages of non-contact, fast response and economic benefi...

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Veröffentlicht in:Robotics and computer-integrated manufacturing Jg. 89; S. 102767
Hauptverfasser: Guo, Qiang, Yang, Zi, Xu, Jinting, Jiang, Yan, Wang, Wenbo, Liu, Zonglin, Zhao, Weisen, Sun, Yuwen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.10.2024
Schlagworte:
Image processing
Real-time monitoring
Robotic welding
Vision sensing technology
Weld seam tracking
Weld seam tracking
Image processing
Robotic welding
Real-time monitoring
Vision sensing technology
ISSN:0736-5845, 1879-2537
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Zusammenfassung:Welding is a method of realizing material connections, and the development of modern sensing technology is pushing this traditional process towards automation and intelligence. Among many sensing methods, visual sensing stands out with its advantages of non-contact, fast response and economic benefits, etc. This paper provides a comprehensive review of visualization methods in the context of specific welding processes in the following five aspects. The problem of IWP location is summarized from two directions of active and passive vision. Weld seam identification and tracking methods are discussed in detail based on the morphological characteristics of the weld seam. The feasibility of different weld path planning methods is analyzed based on the point cloud information and the composite vision information. Two types of monitoring means based on infrared sensing and visible light sensing are summarized taking into account the thermal and morphological characteristics of the weld pool, and welding defect detection technology is summarized by comparing the intelligent detection algorithms and the traditional detection algorithms. Finally, by combining the existing developments in computer technology, composite sensing technology, machine learning technology, and multi-robot control technology, the article concludes with a summary and trends in the development of automated welding technologies.
ISSN:0736-5845
1879-2537
DOI:10.1016/j.rcim.2024.102767