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- W2026409262 abstract "Abstract This paper examines the application of artificial neural networks to the estimation of geometrical parameters of an adhered aluminium T-joint using ultrasonic Lamb waves (s0 + a1). Modulus FFTs of received signals were applied as inputs to conventional feed-forward networks, which were trained using the delta rule with momentum. The success rate of various network structures in recognising bond categories was studied as a function of the density of information applied to the network inputs and the number of hidden nodes in the network. An optimum network structure appears to exist that will solve a number of problems of this type." @default.
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- W2026409262 date "1996-06-01" @default.
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- W2026409262 title "Ultrasonic NDE of adhered T-joints using Lamb waves and intelligent signal processing" @default.
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- W2026409262 doi "https://doi.org/10.1016/0041-624x(95)00115-j" @default.
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