Prediction of the quality of pulsed metal inert gas welding using statistical parameters of arc signals in artificial neural network

International Journal of Computer Integrated Manufacturing

Volumn 23, Issue 5, 2010, Pages 453-465

  Pal, Sukhomay ^a   Pal, Surjya K ^b   Samantaray, A K ^b  

^a UNIVERSITY OF PRETORIA   (South Africa)

^b INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Arc signal; Back propagation neural network; Bead geometry; Deposition efficiency; Distortion; PMIGW; Radial basis function network; Weld strength

Indexed keywords

BACKPROPAGATION; DISTORTION (WAVES); FORECASTING; FUNCTIONS; GAS METAL ARC WELDING; GAS WELDING; INERT GASES; INTELLIGENT SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; TORSIONAL STRESS; WELDS;

ARC SIGNALS; BACK PROPAGATION NEURAL NETWORKS; BEAD GEOMETRY; DEPOSITION EFFICIENCIES; PMIGW; WELD STRENGTH;

INERT GAS WELDING;

EID: 77951519810     PISSN: 0951192X     EISSN: 13623052     Source Type: Journal    
DOI: 10.1080/09511921003667698     Document Type: Article

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