Abstract

Weld bead measurement and weld quality inspection are important parts in industrial welding. In this paper, a structured light vision sensor is developed to achieve on-line weld bead measurement and weld quality inspection. Firstly, a structured light vision sensor with a narrow-band optical filter is developed to reduce welding noises such as arc lights and splashes. Secondly, the weld bead type identification algorithm including image pre-processing, baseline extraction, and weld bead classification is proposed to classify filling weld bead and capping weld bead. Thirdly, feature extraction algorithms of filling weld bead and capping weld bead are presented to obtain corresponding feature points. Combining the image coordinates of feature points with structured light vision model, the weld bead size could be obtained and the weld quality could be evaluated. Finally, many weld bead measurement and weld quality inspection experiments are conducted. Experimental results demonstrate that the developed structured light vision sensor and proposed methods could achieve satisfactory performance for weld quality inspection.

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