NDLI: Welding deviation detection algorithm based on extremum of molten pool image contour

Content Provider	Springer Nature Link
Author	Zou, Yong Jiang, Lipei Li, Yunhua Xue, Long Huang, Junfen Huang, Jiqiang
Copyright Year	2016
Abstract	The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in the gas metal arc welding(GMAW) molten pool images that is very important for the control of welding seam tracking. The physical meaning for the curvature extremum of molten pool contour is revealed by researching the molten pool images, that is, the deviation information points of welding wire center and the molten tip center are the maxima and the local maxima of the contour curvature, and the horizontal welding deviation is the position difference of these two extremum points. A new method of weld deviation detection is presented, including the process of preprocessing molten pool images, extracting and segmenting the contours, obtaining the contour extremum points, and calculating the welding deviation, etc. Extracting the contours is the premise, segmenting the contour lines is the foundation, and obtaining the contour extremum points is the key. The contour images can be extracted with the method of discrete dyadic wavelet transform, which is divided into two sub contours including welding wire and molten tip separately. The curvature value of each point of the two sub contour lines is calculated based on the approximate curvature formula of multi-points for plane curve, and the two points of the curvature extremum are the characteristics needed for the welding deviation calculation. The results of the tests and analyses show that the maximum error of the obtained on-line welding deviation is 2 pixels(0.16 mm), and the algorithm is stable enough to meet the requirements of the pipeline in real-time control at a speed of less than 500 mm/min. The method can be applied to the on-line automatic welding deviation detection.
Starting Page	74
Ending Page	83
Page Count	10
File Format	PDF
ISSN	10009345
Journal	Chinese Journal of Mechanical Engineering
Volume Number	29
Issue Number	1
e-ISSN	21928258
Language	English
Publisher	Chinese Mechanical Engineering Society
Publisher Date	2015-10-23
Publisher Place	Beijing
Access Restriction	Subscribed
Subject Keyword	welding deviation welding seam tracking molten pool contour curvature extremum gas metal arc welding(GMAW) Mechanical Engineering Theoretical and Applied Mechanics Manufacturing, Machines, Tools Engineering Thermodynamics, Heat and Mass Transfer Power Electronics, Electrical Machines and Networks Electronics and Microelectronics, Instrumentation
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Mechanical Engineering

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