Literature DB >> 33924925

A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam.

Gong Zhang1,2, Yuhang Zhang1,3, Shuaihua Tuo1,3, Zhicheng Hou1, Wenlin Yang1, Zheng Xu1, Yueyu Wu1, Hai Yuan1, Kyoosik Shin4.   

Abstract

The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot's welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the X direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both X and Z direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.

Entities:  

Keywords:  complex welding seam; feature point extracting; laser sensor; seam tracking; welding robot

Year:  2021        PMID: 33924925     DOI: 10.3390/s21093067

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Robotic Non-Destructive Testing.

Authors:  Carmelo Mineo; Yashar Javadi
Journal:  Sensors (Basel)       Date:  2022-10-09       Impact factor: 3.847

2.  Internal Parameters Calibration of Vision Sensor and Application of High Precision Integrated Detection in Intelligent Welding Based on Plane Fitting.

Authors:  Chuanhui Zhu; Zhiming Zhu; Zhijie Ke; Tianyi Zhang
Journal:  Sensors (Basel)       Date:  2022-03-09       Impact factor: 3.576

  2 in total

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