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Proceedings Paper

Research on real-time tracking algorithm of weld seam based on Fourier transform profilometry
Author(s): Qingyu Liu; Xinghua Wang; Hongwei Sun
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Paper Abstract

With the continuous development of robotic welding automation, the weld seam tracking system plays a decisive role in guiding the welding robot to perform accurate and real-time space welding operations. At present, the seam tracking is mostly performed by a laser with a laser. The laser triangulation method is used to identify and judge the position of the inflection point of the line segment in the image. However, the identification method relies heavily on the processing algorithm of the inflection point position in the image, and the recognition result lacks welding. Sewing space pose information. Therefore, how to obtain the full spatial information of the weld by the collection and processing of the line and the surface is of great significance to the development of the weld tracking. The grating projection technique based on Fourier transform profilometry can realize the full collection of the local information of the weld seam. Through the subsequent algorithm processing of the local features, the whole feature information of the weld seam is continuously extracted to guide the space position and attitude of the weld gun. Avoid the deviation of traditional weld seam tracking due to unmatched factors such as weld joints and bumps in the weld. On this basis, the correlation feature recognition of the collected spatial point cloud is proposed. Based on the proximity probability feature extraction method, accurate and real-time identification and tracking of non-standard welds are realized. Finally, the experimental results show that the weld seam tracking based on Fourier transform profilometry is more complete and accurate for the full-feature information of the weld seam, and has better recognition effect.

Paper Details

Date Published: 21 June 2019
PDF: 8 pages
Proc. SPIE 11059, Multimodal Sensing: Technologies and Applications, 1105915 (21 June 2019); doi: 10.1117/12.2526051
Show Author Affiliations
Qingyu Liu, Nanjing Univ. of Science and Technology (China)
Jiangsu Automation Research Institute (China)
Xinghua Wang, Jiangsu Automation Research Institute (China)
Hongwei Sun, Jiangsu Automation Research Institute (China)
Nanjing Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 11059:
Multimodal Sensing: Technologies and Applications
Ettore Stella, Editor(s)

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