Abstract
A skilled welder determines the weld joint penetration from his/her observation of the weld pool surface during the welding process. This paper addresses the characterization of the 3D weld pool surface in gas tungsten arc welding (GTAW), i.e., extracting a set of characteristic parameters from the 3D weld pool surface to determine the backside bead width that measures the degree of weld joint penetration in complete penetration welding. To this end, an innovative machine vision system is used to measure the specular weld pool surface in real time. Various experiments under different welding conditions have been performed to produce complete penetration welds with different backside bead widths and acquire corresponding images for reconstructing the weld pool surface and calculating candidate characteristic parameters. The experiments have been designed to produce acceptable distributions for the candidate characteristic parameters to ensure the validity of the resultant models. Through least squares algorithm-based statistic analyses, it was found that the width, length, and convexity of the 3D weld pool surface provides the optimal model to predict the backside bead width with acceptable accuracy. A foundation is thus established to effectively extract information from the weld pool surface to facilitate a feedback control of weld joint penetration.
Original language | English |
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Pages (from-to) | 195S-203S |
Journal | Welding Journal (Miami, Fla) |
Volume | 91 |
Issue number | 7 |
State | Published - Jul 2012 |
Keywords
- 3-D
- Characterization
- Gas tungsten arc welding (GTAW)
- Image processing
- Least squares
- Machine vision
- Surface geometry
- Weld pool
ASJC Scopus subject areas
- Mechanics of Materials
- Mechanical Engineering
- Metals and Alloys