DocumentCode :
3083181
Title :
Classification of laser welds by acoustic signature
Author :
Farson, D.F. ; Fang, K.S. ; Kern, K.T.
Author_Institution :
Appl. Res. Lab., Pennsylvania State Univ., State College, PA, USA
fYear :
1990
fDate :
5-7 Dec 1990
Firstpage :
1620
Abstract :
The application of a backpropagation neural network to the classification of acoustical signals emanating from the laser welding process is discussed. The investigations which are discussed demonstrate that, at least in a relatively simple setting, the backpropagation network is capable of determining whether or not a laser weld has achieved full or partial penetration from its acoustical signature. This result is seen as having important implications for future developments in monitoring and control of these processes
Keywords :
acoustic applications; acoustic signal processing; computerised monitoring; computerised pattern recognition; laser beam welding; manufacturing computer control; neural nets; acoustic signature; backpropagation neural network; laser welds; weld classification; Acoustic beams; Laser beams; Laser theory; Monitoring; Neural networks; Optical materials; Plasma materials processing; Plasma welding; Power lasers; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1990., Proceedings of the 29th IEEE Conference on
Conference_Location :
Honolulu, HI
Type :
conf
DOI :
10.1109/CDC.1990.203888
Filename :
203888
Link To Document :
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