Feature information extraction method for narrow gap U-type groove based on laser vision

The precise measurement of weld groove position and geometric dimensions serves as the foundation for predicting and planning welding strategies and process parameters. The steep sidewalls of narrow gap U-type grooves pose challenges for sensing and detection during the welding process. This paper presents a feature information extraction method for narrow gap U-type grooves based on laser vision technology. Firstly, the image acquisition system is calibrated using the incident plane of the laser beam. Subsequently, a digital image processing technique is employed to enhance the collected images, combining a 3D spatial domain enhancement algorithm with a laser stripe image refinement method based on Euclidean distance transformation. Finally, the transverse and vertical positions of the groove, as well as its geometric features such as width, depth, assembly gap, and misalignment, are computed and measured using feature point positioning. The proposed algorithm is experimentally verified for its accuracy, robustness, and real-time performance. The results indicate that the method effectively suppresses unevenness in laser stripe brightness and mitigates random noise in the captured images. The average measurement errors for transverse position, vertical position, width, depth, assembly gap, and misalignment of the groove are 0.0857 mm, 0.0987 mm, 0.1664 mm, 0.2216 mm, 0.0935 mm, and 0.0997 mm, respectively. Furthermore, the average image processing time per frame is 58 ms, meeting the requirements of pre-weld detection in arc welding.