Online monitoring of weld defects for short-circuit gas metal arc welding based on the self-organizing feature map neural networks
Authors:
- Song YonglunSYSong Yonglun
- Ye FengYFYe Feng
- 1 January 2000
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 5 (10987576) , 239-244 vol.5
Abstract
A method for automatic detection of weld defects of short-circuit gas metal arc welding is presented. It is based on the extraction of arc signal features as well as classification of the obtained features using self-organizing feature map (SOM) neural networks in order to get the weld quality information, for example, to determine if there is a defect in the product. This is important for the online monitoring of weld quality especially in robotic welding and lays the foundation for further real-time control of weld quality.Keywords
This publication has 2 references indexed in Scilit:
- AUTOMATIC DETECTION OF BURN-THROUGH IN GMA WELDING USING A PARAMETRIC MODELMechanical Systems and Signal Processing, 1996
- Self-Organizing Maps1995