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
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;
Conference_Titel :
Industrial Electronics, Control and Instrumentation, 1994. IECON '94., 20th International Conference on
Conference_Location :
Bologna
Print_ISBN :
0-7803-1328-3
DOI :
10.1109/IECON.1994.397979
