REVIEW ARTICLE
3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology
Zhen-Hai Mu*
Article Information
Identifiers and Pagination:
Year: 2015Volume: 9
First Page: 820
Last Page: 825
Publisher Id: TOMEJ-9-820
DOI: 10.2174/1874155X01509010820
Article History:
Received Date: 26/05/2015Revision Received Date: 14/07/2015
Acceptance Date: 10/08/2015
Electronic publication date: 7/10/2015
Collection year: 2015
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
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.