scholarly journals Image Processing of Aluminum Alloy Weld Pool for Robotic VPPAW Based on Visual Sensing

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 21567-21573 ◽  
Author(s):  
Chun Jiang ◽  
Fubiao Zhang ◽  
Zhenmin Wang
Keyword(s):  
Image Processing ◽  
Aluminum Alloy ◽  
Weld Pool ◽  
Visual Sensing ◽  
Alloy Weld

Image processing of weld pool and keyhole in Nd:YAG laser welding of stainless steel based on visual sensing

2011 ◽  
Vol 21 (2) ◽  
pp. 423-428 ◽  
Author(s):  
Jin-qiang GAO ◽  
Guo-liang QIN ◽  
Jia-lin YANG ◽  
Jian-guo HE ◽  
Tao ZHANG ◽  
...  
Keyword(s):  
Image Processing ◽  
Stainless Steel ◽  
Laser Welding ◽  
Weld Pool ◽  
Nd:Yag Laser ◽  
Visual Sensing

scholarly journals In-situ reactions and mechanical properties of 6061 aluminum alloy weld joint with SiCp by laser melting injection

2021 ◽  
Vol 203 ◽  
pp. 109538
Author(s):  
Boan Xu ◽  
Ping Jiang ◽  
Shaoning Geng ◽  
Yilin Wang ◽  
Jintian Zhao ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Aluminum Alloy ◽  
Weld Joint ◽  
Laser Melting ◽  
6061 Aluminum Alloy ◽  
In Situ Reactions ◽  
Alloy Weld

Image processing and control of weld pool in switch-back welding without backing plate

2005 ◽  
Vol 19 (11) ◽  
pp. 856-861
Author(s):  
S Yamane ◽  
K Oshima ◽  
H Yuzawa ◽  
Y Kaneko ◽  
H Yamamoto ◽  
...  
Keyword(s):  
Image Processing ◽  
Weld Pool ◽  
Backing Plate ◽  
And Control

scholarly journals Prediction of Fusion Hole Perforation Based on Arc Characteristics of Front Image in Backing Welding

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4706
Author(s):  
Yu Cao ◽  
Xiaofei Wang ◽  
Xu Yan ◽  
Chuanbao Jia ◽  
Jinqiang Gao
Keyword(s):  
Image Processing ◽  
Molten Pool ◽  
Detection System ◽  
Morphological Characteristics ◽  
Support Vector ◽  
Characteristic Parameters ◽  
Visual Sensing ◽  
Arc Characteristics ◽  
Grid Search Method ◽  
Processing Program

In one-side welding with back-formation, the weld is penetrated after the fusion hole is perforated. Therefore, judging whether the fusion hole is perforated is very important to realize autocontrol of penetration in one-side welding with back-formation process. Previous researches mainly focused on the morphological characteristics of the molten pool and fusion hole to judge the weld penetration state. Sometimes it is difficult to obtain the morphological characteristics of the molten pool, keyhole and fusion hole and image processing is complex. In this paper, a visual detection system of fusion holes based on visual sensing is constructed to obtain the real-time fusion hole images in backing welding. It is found that the arc characteristics in the front images contain abundant information about the perforation of fusion hole. An image processing program is developed based on MATLAB software, and the arc characteristic parameters in front images are obtained. Taking the arc characteristic parameters as the input, obtaining the penalty function and the kernel function parameters through the cross validation and grid search method, a prediction model of fusion hole perforation based on the support vector machine is put forward. The accuracy for prediction samples is 88%. By analyzing the misidentified samples, it is found that some of the newly perforated images are predicted as nonperforated ones, which has little influence on the penetration control of the weld.

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