Online monitoring of weld defects for short-circuit gas metal arc welding based on the self-organizing feature map neural networks

Author(s):  
Li Di ◽  
Song Yonglun ◽  
Ye Feng
2008 ◽  
Vol 580-582 ◽  
pp. 451-454 ◽  
Author(s):  
P. Praveen ◽  
K.D.V. Yarlagadda Prasad ◽  
M.J. Kang ◽  
Se Hun Rhee

Wide use of robotic machines for welding has necessitated the development of optimization techniques to achieve complete automation. The objective of the present study is to develop multiple regression model for quantitatively estimating the severity of the short circuit in pulse gas metal arc welding (GMAW-P) of aluminum, based on experimental results. The model results were found to be in good agreement with the experimental data and yielded satisfactory results.


2011 ◽  
Vol 339 ◽  
pp. 440-443 ◽  
Author(s):  
Shu Jun Chen ◽  
Chang Hui Liu ◽  
Yang Yu ◽  
Shao Jun Bai

This study proposed preset pulsed magnetic field acting on process of the short circuiting transfer. It is a controlled horizontal magnetic field which attached at the very beginning of contact between the wire and the weld pool during welding. It was found that there exists optimum conditions of magnetic field with which preset pulsed magnetic field could accelerate the rupture of the liquid bridge and reduce the peak value of welding current in the period of short circuiting transfer. This lead to energy accumulation lowered at the last phase of the short circuiting transfer and spatter loss reduced resulting from explosive short circuit rupture, in the meantime, it could improve the regularity and stability of the short circuiting transfer as well as the weld shaping quality.


2006 ◽  
Vol 47 (7) ◽  
pp. 1859-1863 ◽  
Author(s):  
Hyunbyung Chae ◽  
Cheolhee Kim ◽  
Jeonghan Kim ◽  
Sehun Rhee

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