Modelling and classification of acoustic pulse signals by wavelet networks
S. Nadaud, J.-F. Trouilhet · 2002
This article presents two modelling methods using wavelet networks. Both methods are intended to be used for an acoustic pulse signal classifier. We present a few results obtained with signals coming from a recording of the percussive response of metal parts. The object of this application is the non-destructive testing of these parts, as defects perturb the acoustic signature. The first modelling method uses wavelet networks to perform a non-linear regression on the signal to be classified. The second consists of non-linear auto-recursive modelling of the signal by means of the networks. The use of wavelet networks enables us to combine the generalizing capacities of neural networks with the efficiency of wavelet analysis of pulse signals.