A neural network architecture for ultrasonic nondestructive testing

Y. Guez, K. D. Donohue, N. M. Bilgutay

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


This paper considers the application of neural networks for detecting defects in materials consisting of dense micro-structures using ultrasonic pulse-echo systems. The motivation for this work is the desire to detect defects modeled by small complex scattering centers. To preserve signal features useful for defect detection, minimal preprocessing is performed on the data presented to the neural network. This paper describes modifications to the typical feed-forward multi-layer perceptron architecture for direct application to sampled RF ultrasonic A-scans.

Original languageEnglish
Article number234085
Pages (from-to)777-780
Number of pages4
JournalProceedings - IEEE Ultrasonics Symposium
StatePublished - 1991
Event1991 IEEE Ultrasonics Symposium. ULTSYM 1991 - Orlando, United States
Duration: Dec 8 1991Dec 11 1991

Bibliographical note

Funding Information:
This work was partially supported by SDIO/IST managed by the Office of Naval Research under Contract No. N00014-86-K-0520 and by the National Science Foundation under Grant No. MIP-8920602.

Publisher Copyright:
© 1991 IEEE.

ASJC Scopus subject areas

  • Acoustics and Ultrasonics


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