Real-time GMAW quality classification using an artificial neural network with airborne acoustic signals as inputs
- Naval Surface Warfare Center, Annapolis, MD (United States). Carderock Div.
The acoustic signal produced by the gas metal arc welding (GMAW) arc contains information about the behavior of the arc column, the molten pool and droplet transfer. It is possible to detect some defect producing conditions from the acoustic signal from the GMAW arc. An intelligent sensor, called the Weld Acoustic Monitor (WAM) has been developed to take advantage of this acoustic information in order to provide real-time quality assessment information for process control. The WAM makes use of an Artificial Neural Network (ANN) to classify the characteristic arc acoustic signals of acceptable and unacceptable welds. The ANN used in the Weld Acoustic Monitor developed its own set of rules for this classification problem by learning a data base of known GMAW acoustic signals.
- OSTI ID:
- 33210
- Report Number(s):
- CONF-930641-; ISBN 0-7918-0785-1; TRN: IM9518%%31
- Resource Relation:
- Conference: OMAE `93: 12th international conference on offshore mechanics and arctic engineering, Glasgow (United Kingdom), 20-24 Jun 1993; Other Information: PBD: 1993; Related Information: Is Part Of OMAE 1993: Volume 3, Part A -- Materials engineering; Salama, M.M.; Toyoda, Masao; Liu, S.; Dos Santos, J.F.; Kocak, M.; Williams, J. [eds.]; PB: 434 p.
- Country of Publication:
- United States
- Language:
- English
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