Quantitative nondestructive evaluation with ultrasonic method using neural networks and computational mechanics

Author:

Oishi A.,Yamada K.,Yoshimura S.,Yagawa G.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Mathematics,Computational Theory and Mathematics,Mechanical Engineering,Ocean Engineering,Computational Mechanics

Reference36 articles.

1. Baker, A. R.; Windsor, C. G. 1989: The classification of defects from ultrasonic data using neural networks: The Hopfield method. NDT International 22: 97?105

2. Berry, D.; Upda, L.; Upda, S. S. 1991: Classification of ultrasonic signal via neural networks. In: Thompson, D. O.: Chimenti, D. E. (eds.); Review of Progress in Quantitative Nondestructive Evaluation 10A: 659?666. New York: Plenum Press

3. Blake, R. J.; Bond, L. J. 1990: Rayleigh wave scattering from surface features: wedges and down-steps. Ultrasonics 28: 214?228

4. Bond, L. J.; Taylor, J. 1991: Interaction of Rayleigh waves with a rib attached to a plate. Ultrasonics 29: 451?458

5. Brown, L. M.; DeNale, R. 1991: Classification of ultrasonic defect signatures using an artificial neural network. In: Thompson, D. O.; Chimenti, D. E. (eds.); Review of Progress in Quantitative Nondestructive Evaluation 10A: 705?712. New York: Plenum Press

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