Research on robot weld seam recognition technology based on deep learning

Diyu Guan; Zhiyong Xing; Yingxin Tao; Yang Zhang

doi:10.1117/12.3040179

13 September 2024 Research on robot weld seam recognition technology based on deep learning

Diyu Guan, Zhiyong Xing, Yingxin Tao, Yang Zhang

Proceedings Volume 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024); 1325404 (2024) https://doi.org/10.1117/12.3040179
Event: Fourth International Conference on Optics and Image Processing (ICOIP 2024), 2024, Chongqing, China

Abstract

When the robot performs real-time pipeline weld tracking, the weld image obtained by the camera will be interfered with by solid arc noise and spatter, which makes it challenging to ensure the stability of the weld quality of the pipeline. This paper proposes an automatic weld seam feature recognition algorithm based on an improved U-Net neural network. The method extracts the global features of the weld image through the backbone network after down-sampling and upsampling in the U-Net network, fuses the laser stripe information at multiple scales, and utilizes the feature enhancement module to obtain more explicit weld feature images. Experiments have shown that the accuracy can reach 99.17%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Diyu Guan, Zhiyong Xing, Yingxin Tao, and Yang Zhang "Research on robot weld seam recognition technology based on deep learning", Proc. SPIE 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024), 1325404 (13 September 2024); https://doi.org/10.1117/12.3040179

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