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Robust identification of weld seam based on region of interest operation

Robust identification of weld seam based on region of interest operation For welding path determination, the use of vision sensors is more effective compared with complex offline programming and teaching in small to medium volume production. However, interference factors such as scratches and stains on the surface of the workpiece may affect the extraction of weld information. In the obtained weld image, the weld seams have two distinct features related to the workpiece, which are continuous in a single process and separated from the workpiece’s gray value. In this paper, a novel method is proposed to identify the welding path based on the region of interest (ROI) operation, which is concentrated around the weld seam to reduce the interference of external noise. To complete the identification of the entire welding path, a novel algorithm is used to adaptively generate a dynamic ROI (DROI) and perform iterative operations. The identification accuracy of this algorithm is improved by setting the boundary conditions within the ROI. Moreover, the experimental results confirm that the coefficient factor used for determining the ROI size is a pivotal influencing factor for the robustness of the algorithm and for obtaining an optimal solution. With this algorithm, the welding path identification accuracy is within 2 pixels for three common butt weld types. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advances in Manufacturing Springer Journals

Robust identification of weld seam based on region of interest operation

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References (30)

Publisher
Springer Journals
Copyright
Copyright © Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature 2020
ISSN
2095-3127
eISSN
2195-3597
DOI
10.1007/s40436-020-00325-y
Publisher site
See Article on Publisher Site

Abstract

For welding path determination, the use of vision sensors is more effective compared with complex offline programming and teaching in small to medium volume production. However, interference factors such as scratches and stains on the surface of the workpiece may affect the extraction of weld information. In the obtained weld image, the weld seams have two distinct features related to the workpiece, which are continuous in a single process and separated from the workpiece’s gray value. In this paper, a novel method is proposed to identify the welding path based on the region of interest (ROI) operation, which is concentrated around the weld seam to reduce the interference of external noise. To complete the identification of the entire welding path, a novel algorithm is used to adaptively generate a dynamic ROI (DROI) and perform iterative operations. The identification accuracy of this algorithm is improved by setting the boundary conditions within the ROI. Moreover, the experimental results confirm that the coefficient factor used for determining the ROI size is a pivotal influencing factor for the robustness of the algorithm and for obtaining an optimal solution. With this algorithm, the welding path identification accuracy is within 2 pixels for three common butt weld types.

Journal

Advances in Manufacturing – Springer Journals

Published: Nov 10, 2020

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