DocumentCode :
285065
Title :
Application of neural networks in the acousto-ultrasonic evaluation of metal-matrix composite specimens
Author :
Cios, Krzysztof J. ; Tjia, Robert E. ; Vary, Alex ; Kautz, Harold E.
Author_Institution :
Toledo Univ., OH, USA
Volume :
2
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
993
Abstract :
Acousto-ultrasonics (AU) is a nondestructive evaluation (NDE) technique that was devised for the testing of various types of composite materials. A study has been done to determine how effectively the AU technique may be applied to metal-matrix composites (MMCs). The authors use the results and data obtained from that study and apply neural networks to them, particularly in the assessment of mechanical property variations of a specimen from AU measurements. It is assumed that there is no information concerning the important features of the AU signal which relate to the mechanical properties of the specimen. Minimally processed AU measurements are used while relying on the network´s ability to extract the significant features of the signal
Keywords :
automatic test equipment; composite materials; feature extraction; neural nets; signal processing; ultrasonic materials testing; NDT; acousto-ultrasonic evaluation; feature extraction; mechanical property; metal-matrix composite specimens; neural networks; signal processing; Acoustic testing; Composite materials; Data mining; Gold; Materials testing; Mechanical factors; Mechanical variables measurement; Neural networks; Nondestructive testing; Particle measurements;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.226858
Filename :
226858
Link To Document :
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