基于计算机视觉技术的熔池表面三维重建算法

Zhen-Hai Mu
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引用次数: 2

摘要

众所周知,对熔池表面的传感和测量对于设计能够模仿熟练的焊工选择合适的焊接参数的智能焊机是非常重要的。因此,本文重点研究了智能焊机开发中的关键问题——熔池表面三维重建问题。首先,描述了熔池表面三维重建系统的框架。焊缝熔池表面三维重建系统采用单摄像头立体视觉系统,从熔池中提取原始数据,然后采集左右图像。然后利用像素差分平方匹配算法和立体匹配算法对图像进行处理。其次,利用点云数据对熔池表面进行三维重建。其次,阐述了基于立体匹配的熔池表面三维重建算法。该算法首先通过马尔可夫随机场计算匹配代价函数,然后通过引导滤波器计算加权匹配代价。第三,为了测试算法的性能,我们开发了一个基于线性模型预测控制器的实验平台来测量焊接池的宽度、长度、凸度和先前的输入。实验结果表明,本文提出的熔池表面三维重建算法在电流干扰和速度干扰下均能获得较高的重建质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology
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.
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