Thema: neuronales Netz, Ultraschalldaten, Rißgröße
Autor/Institution: Zgonc, K.;Achenbach, J.D.;Lee, Y.-C.
/Northwestern Univ., Evanston, USA
Title: Crack sizing using a neural network classifier trained with data obtained
from finite element models
Titel : Rißgrößenbestimmung mit einem neuronalen Netzwerk gespeist mit Daten aus
Finite-Element-Modellen
Quelle : Review of Progress in Quantitative Nondestructive Evaluation. Proceedings
of the Twenty-First Symposium, Snowmass Village, USA, 31.7.-5.8.1994
13 14A
1995
; New York: Plenum Press
; ISBN 0-306-45062-3
; S.779-786
; 8S,9B,2T,4Q
; TIB-RO141(14,1);BAM-Z-0906/95
; E
Abstract:
An ultrasonic data processing system has been developed and applied to the
detection and sizing of EDM notches emanating from rivet holes. A shift-
invariant neural network is successfully used to classify R/T curves for
different EDM notches that are used to model cracks. A set of training
data for the neural network (NN) ist obtained by 2-D FE models. The
results show that numerical results can be applied to train the NN
classifiers and that the ultrasonic data processing system gives a good
prediction of the EDM notch sizes. To obtain even better generalization
capabilities of the classifier would require a larger number of
numerically obtained data. The data processing system is general and can
be applied also to other nondestructive testing problems. In practice,
plate waves are used to perform inspection around riveted joints.
Therefore, future work will concentrate on 3-D FE modeling which will more
accurately simulate real applications. F33,B13,H13,A25
Database Keywords: :Ultraschallprüfung, Signalverarbeitung, Finite Element Methode,
:Fehlergröße, Riß, Testfehler
23 :Neuronales Netzwerk, Funkenerodierter Schlitz
24 Z:A
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