Proceedings of the 2015 International Conference on Advanced Engineering Materials and Technology

Image processing of weld seam for Al alloy pulsed GTAW based on vision sensing

Authors
Yunxia Chen, Su Zhao, Xiaojing Wang
Corresponding Author
Yunxia Chen
Available Online August 2015.
DOI
10.2991/icaemt-15.2015.28How to use a DOI?
Keywords
arc welding robot, vision sensing,image processing,seam tracking
Abstract

In recent years, machine vision sensors have been widely used to track weld seam. A suitable way is designed to process image of aluminum alloy pulsed gas tungsten arc welding process experiments in this work. With the passive vision sensor to capture some ideal images, we adopt and compare different image processing methods to extract useful information, including target location, double filter, edge detection and seam centerline extraction. It is shown that the method has good effect on seam centerline extraction and seam tracking.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Advanced Engineering Materials and Technology
Series
Advances in Engineering Research
Publication Date
August 2015
ISBN
10.2991/icaemt-15.2015.28
ISSN
2352-5401
DOI
10.2991/icaemt-15.2015.28How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yunxia Chen
AU  - Su Zhao
AU  - Xiaojing Wang
PY  - 2015/08
DA  - 2015/08
TI  - Image processing of weld seam for Al alloy pulsed GTAW based on vision sensing
BT  - Proceedings of the 2015 International Conference on Advanced Engineering Materials and Technology
PB  - Atlantis Press
SP  - 138
EP  - 143
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaemt-15.2015.28
DO  - 10.2991/icaemt-15.2015.28
ID  - Chen2015/08
ER  -