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There is a strong correlation between the geometry of the weld pool surface and the degree of penetration in arc welding. To measure the geometry of the weld pool surface robustly, many structured light laser line based monitoring systems have been proposed in recent years. The geometry of the specular weld pool could be computed from the reflected laser lines based on different principles. The prerequisite of accurate computation of the weld pool surface is to segment the reflected laser lines robustly and efficiently. To find the most effective segmentation solutions for the images captured with different welding parameters, different image processing algorithms are combined to form eight approaches and these approaches are compared both qualitatively and quantitatively in this paper. In particular, the gradient detection filter, the difference method and the GLCM (grey level co-occurrence matrix) are used to remove the uneven background. The spline fitting enhancement method is used to remove the fuzziness. The slope difference distribution-based threshold selection method is used to segment the laser lines from the background. Both qualitative and quantitative experiments are conducted to evaluate the accuracy and the efficiency of the proposed approaches extensively.

A measurement system with three degrees of freedom (3 DOF) that compensates for errors caused by incident beam drift is proposed. The system's measurement model (i.e. its mathematical foundation) is analyzed, and a measurement module (i.e. the designed orientation measurement unit) is developed and adopted to measure simultaneously straightness errors and the incident beam direction; thus, the errors due to incident beam drift can be compensated. The experimental results show that the proposed system has a deviation of 1 μm in the range of 200 mm for distance measurements, and a deviation of 1.3 μm in the range of 2 mm for straightness error measurements.