3D Reconstruction of Weld Pool Surface by a Biprism Stereo System

2012 ◽  
Vol 236-237 ◽  
pp. 469-473 ◽  
Author(s):  
Ya Dong Zhang ◽  
Zhi Min Liang ◽  
Dian Long Wang ◽  
Jun Wang

3D shape of the weld pool surface can be used to infer the penetration state of the weld pool, which has an importance influence on weld quality. In this paper, a novel stereo camera system that used only one camera and a biprism placed in front of the lens was applied to capture virtual image pair of the weld pool surface. The most advantage of the system setup is that corresponding points lie on the same scan line automatically, i.e. the stereo image pair is self rectified. The calibration of the system was done using plane pattern by Zhang’s algorithm and the standard SSD stereo matching algorithm was applied to find the corresponding points in the left and right image. The reconstructed 3D shape of the weld pool surface during base current period of P-GMAW by the system has shown that the technique has potential application for control of weld process

2015 ◽  
Vol 9 (1) ◽  
pp. 820-825
Author(s):  
Zhen-Hai Mu

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.


2009 ◽  
Vol 105 (12) ◽  
pp. 123104 ◽  
Author(s):  
C. X. Zhao ◽  
I. M. Richardson ◽  
S. Kenjeres ◽  
C. R. Kleijn ◽  
Z. Saldi

2018 ◽  
Vol 256 ◽  
pp. 57-68 ◽  
Author(s):  
J.K. Huang ◽  
M.H. Yang ◽  
J.S. Chen ◽  
F.Q. Yang ◽  
Y.M. Zhang ◽  
...  

2017 ◽  
Vol 35 (2) ◽  
pp. 98s-102s ◽  
Author(s):  
Van Anh Nguyen ◽  
Shinichi Tashiro ◽  
Bui Van Hanh ◽  
Manabu Tanaka

2020 ◽  
Vol 10 (10) ◽  
pp. 3569 ◽  
Author(s):  
Manh Ngo Huu ◽  
Anh Nguyen Van ◽  
Tuan Nguyen Van ◽  
Dang Tran Hai ◽  
Thanh Nguyen Van ◽  
...  

In this study, the effect of oxygen in the shielding gas on the material flow behavior of the weld pool surface was discussed to clarify the dominant driving weld pool force in keyhole plasma arc welding (KPAW). To address this issue, the convection flow on the top surface of weld pool was observed using a high-speed video camera. The temperature distribution on the surface along keyhole wall was measured using the two-color pyrometry method to confirm the Marangoni force activity on the weld pool. The results show that the inclination angle of the keyhole wall (keyhole shape) increased especially near the top surface due to the decrease in the surface tension of weld pool through surface oxidation when a shielding gas of Ar + 0.5% O2 was used. Due to the change in the keyhole shape, the upward and backward shear force compositions created a large inclination angle at the top surface of the keyhole. From the temperature measurement results, the Marangoni force was found to alter the direction when 0.5% O2 was mixed with the shielding gas. The shear force was found to be the strongest force among the four driving forces. The buoyant force and Lorentz force were very weak. The Marangoni force was stronger than the Lorentz force but was weaker than shear force. The interaction of shear force and Marangoni force controlled the behavior and speed of material flow on the weld pool surface. A strong upward and backward flow was observed in the case of mixture shielding gas, whereas a weak upward flow was observed for pure Ar. The heat transportation due to the weld pool convection significantly changed when only a small amount of oxygen was admixed in the shielding gas. The results can be applied to control the penetration ratio in KPAW.


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