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Extraction of Weld Pool Width Feature Based on Visual Sensing during High-power Fiber Laser Welding
CHEN Ziqin 1,GAO Xiangdong 2 *
1.Faculty of Electromechanical Engineering, Guangdong University of Technology, GuangZhou 510006
2.Faculty of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006
*Correspondence author
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Funding: Specialized Research Fund for the Doctoral Program of Higher Education of China （No.No. 20104420110001）, National Natural Science Foundation of China（No.No. 51175095）, the Natural Science Foundation of Guangdong Province of China（No.No.10251009001000001,No. 9151009001000020）
Opened online:28 March 2012
Accepted by: none
Citation: CHEN Ziqin,GAO Xiangdong.Extraction of Weld Pool Width Feature Based on Visual Sensing during High-power Fiber Laser Welding[OL]. [28 March 2012] http://en.paper.edu.cn/en_releasepaper/content/4472333
 
 
In a high-power fiber laser welding process, the thermal radiation of a weld pool contains plenty of information for welding quality, in which the pool width can reflect the welding stability. Thus, extracting the welding pool width of high-power fiber laser welding based on infrared thermal imaging is an important method for monitoring the weld quality. This paper has analyzed the automatic seam tracking system related to image processing, we studied the 304 stainless steel welded by a 10kW high-power fiber laser continuously. A near-infrared high-speed sensing camera was used to capture the weld pool images. Image algorithms such as median filtering, gray scale stretching, cutting, dynamic threshold mathematical morphology were applied to extract the weld pool image edge and analyze and detect the weld pool width. Welding experimental results showed that the proposed methods could extract the weld pool width, which could reflect the stability status of high-power fiber laser welding process accurately and help seam tracking.
Keywords:Mechanical manufacturing and automation; Weld pool width; Seam tracking; High-power fiber laser welding; Visual sensing
 
 
 

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