Abstract HTML Views: 344 PDF Downloads: 177 Total Views/Downloads: 539
Abstract HTML Views: 260 PDF Downloads: 119 Total Views/Downloads: 394
As is well known that sensing and measuring the weld pool surface is very important to design intelligent welding
machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in
this paper, we focused on 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 images are collected. Afterward, 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 algorithm,
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 controller.
Experimental results demonstrate that the proposed 3D reconstruction algorithm of weld pool surface can achieve
high quality under both current disturbance and speed disturbance.