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On-Line Monitoring and Defects Detection of Robotic Arc Welding: A Review and Future Challenges

  • Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

19 Scopus citations

Abstract

Robotic arc Welding is the main manufacturing technology for key structure components in the industries of aerospace, automobile, nuclear, ship and military equipment. Real-time monitoring, controlling and detecting of the welding process and seam quality can improve the stability and reliability of weld quality while increasing the efficiency and accuracy of defect detection. In this paper, we briefly reviewed the state-of-art on-line welding process monitoring based on different sensing techniques, including image vision, laser vision and distance, arc optical emission, arc audible sound and new immerging X-ray computed tomography. Then, a concise review of feature dimension reduction and selection is provided before the multisensory information fusion. The anticipated challenges are carefully discussed from the aspect of data correlation, evaluation and deep learning. We believe that more attention should be paid on topics such as real-time inner defects detection combining with defects micro characterization; problems related to complex-thin-big structure component welding; and applications of the latest deep learning technologies.

Original languageEnglish
Title of host publicationTransactions on Intelligent Welding Manufacturing
PublisherSpringer
Pages3-28
Number of pages26
DOIs
StatePublished - 2019

Publication series

NameTransactions on Intelligent Welding Manufacturing
ISSN (Print)2520-8519
ISSN (Electronic)2520-8527

Keywords

  • Deep learning
  • Defect detection
  • Information fusion
  • Monitoring
  • Multiple sensing
  • Robotic welding

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