DocumentCode
291321
Title
Neural network approach to weld quality monitoring
Author
Quero, J.M. ; Millán, R.L. ; Franquelo, L.G.
Author_Institution
Dept. de Ingegneria de Sistemas y Autom., Seville Univ., Spain
Volume
2
fYear
1994
fDate
5-9 Sep 1994
Firstpage
1287
Abstract
Supervision of welding processes is one of the most important and complicated tasks in production lines. Artificial neural networks have been applied for modeling and physical control processes. In this paper, the authors propose the use of a neural network classifier for online non-destructive testing. This system has been developed and installed in a welding station of General Motors in Cadiz (Spain). Results confirm the validity of this novel approach
Keywords
General Motors; computerised monitoring; neural nets; nondestructive testing; pattern classification; quality control; welding; General Motors; artificial neural networks; neural network classifier; online nondestructive testing; production lines; weld quality monitoring; Artificial neural networks; Automotive engineering; Monitoring; Neural networks; Nondestructive testing; Process control; Production; Productivity; Rectifiers; Welding;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, Control and Instrumentation, 1994. IECON '94., 20th International Conference on
Conference_Location
Bologna
Print_ISBN
0-7803-1328-3
Type
conf
DOI
10.1109/IECON.1994.397979
Filename
397979
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