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Automatic Welding Seam Tracking and Identification

In the automatic welding process on mid/thick plates, the precision of the welding position has an important effect on welding quality, which mainly relies on the identification of the welding seam. However, due to some possible disturbances in complex unstructured welding environments, e.g., strong...

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Published in:IEEE transactions on industrial electronics (1982) 2017-09, Vol.64 (9), p.7261-7271
Main Authors: Xinde Li, Xianghui Li, Shuzhi Sam Ge, Khyam, Mohammad Omar, Chaomin Luo
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Language:English
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cited_by cdi_FETCH-LOGICAL-c291t-e0f24296e287356afb11bfe5a356530a29f0ea952136f932e7f98fcd398573143
cites cdi_FETCH-LOGICAL-c291t-e0f24296e287356afb11bfe5a356530a29f0ea952136f932e7f98fcd398573143
container_end_page 7271
container_issue 9
container_start_page 7261
container_title IEEE transactions on industrial electronics (1982)
container_volume 64
creator Xinde Li
Xianghui Li
Shuzhi Sam Ge
Khyam, Mohammad Omar
Chaomin Luo
description In the automatic welding process on mid/thick plates, the precision of the welding position has an important effect on welding quality, which mainly relies on the identification of the welding seam. However, due to some possible disturbances in complex unstructured welding environments, e.g., strong arc lights, welding splashes, thermal-induced deformations, etc., it is a great challenge to identify the welding seam. In this paper, we propose a robust automatic welding seam identification and tracking method by utilizing structured-light vision. First, after the preprocessing of the welding image, the gray distribution of the laser stripe is tracked and the profile of the welding seam is searched in a small area by using the Kalman filter, with the aim to avoid some disturbances. Second, in order to extract the welding seam profile, a series of centroids obtained by scanning the columns in the rectangular window are fitted using the least-squares method. Third, a character string method is proposed to qualitatively describe the welding seam profile, which might consist of different segment and junction relationship elements. And then, these character strings acquired from the object image are matched with those from the model, so that the position of the welding seam can be determined. Finally, the advantages of the new algorithm are testified and compared through several experiments.
doi_str_mv 10.1109/TIE.2017.2694399
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However, due to some possible disturbances in complex unstructured welding environments, e.g., strong arc lights, welding splashes, thermal-induced deformations, etc., it is a great challenge to identify the welding seam. In this paper, we propose a robust automatic welding seam identification and tracking method by utilizing structured-light vision. First, after the preprocessing of the welding image, the gray distribution of the laser stripe is tracked and the profile of the welding seam is searched in a small area by using the Kalman filter, with the aim to avoid some disturbances. Second, in order to extract the welding seam profile, a series of centroids obtained by scanning the columns in the rectangular window are fitted using the least-squares method. Third, a character string method is proposed to qualitatively describe the welding seam profile, which might consist of different segment and junction relationship elements. 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source IEEE Electronic Library (IEL) Journals
subjects Arc welding
Automatic welding
Centroids
Columns (structural)
Deformation
Disturbances
Image acquisition
Kalman filter
Kalman filters
Laser beam welding
Laser modes
Least squares method
qualitative description
Robots
Robustness
Seam tracking
Sensors
Strings
Thick plates
Welding
welding seam identification
welding tracking
title Automatic Welding Seam Tracking and Identification
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