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As is well known that sensing and measuring the weld pool surface is very important to design intelligent weld- ing machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in this paper, we concentrate the problem of weld pool surface 3D reconstruction, which is a key issue in intelligent welding machines development. Firstly, the framework of the weld pool surface 3D reconstruction system is described. The weld pool surface 3D reconstruction system uses a single camera stereo vision system to extract original data from weld pool, and then the left and right image are collected. Afterwards, we utilize Pixel difference square and matching algorithm and Stereo matching algorithm to process images. Next, the 3D reconstruction of weld pool surface is constructed using the point cloud data. Secondly, stereo matching based weld pool surface 3D reconstruction algorithm is illustrated. In this al- gorithm, the matching cost function is computed through the Markov random field, and then the weighted matching cost is calculated via the guided filter. Thirdly, to test the performance of our proposed algorithm, we develop an experimental platform to measure weld pool width, length, convexity and the previous inputs based on a linear model predictive con- troller. Experimental results demonstrate that the proposed 3D reconstruction algorithm of weld pool surface can achieve high quality under both current disturbance and speed disturbance.

3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology