Use of the neural networks in the recognition of the austenitic steel types

NDT and E International

Volumn 33, Issue 2, 2000, Pages 85-89

  Ciocan, R ^a   Petulescu, P ^b   Ciobanu, D ^c   Roth, D J ^d  

^a Case Western Reserve University   (United States)

^b OVIDIUS UNIVERSITY   (Romania)

^c INSTITUTE FOR NUCLEAR RESEARCH   (Romania)

^d NASA GLENN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATTENUATION; AUSTENITE; FOURIER TRANSFORMS; LEARNING SYSTEMS; NEURAL NETWORKS; SPECTRUM ANALYSIS; ULTRASONIC PROPAGATION; VECTORS;

ULTRASONIC ATTENUATION;

STEEL;

EID: 0033881681     PISSN: 09638695     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0963-8695(99)00032-8     Document Type: Article

References (7)

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2. Stepinsky T, Ericsson L, Vagnhamar B, Gustafsson M. Neural network based classifier for ultrasonic resonance spectra. NDT.net-December 1998, Vol. 3, No. 1.
3. Petculescu P, Ciocan R, Bokas V. Investigation of the austenitic structures by ultrasonic spectral analysis. NDT.net-November 1998, Vol. 3, No. 1.
4. Krautkramer J., Krautkramer H. Ultrasonic testing of materials. 1990;Springer, Berlin.
5. Freeman J.A., Skapura D.M. Neural networks algorithms: applications and programming techniques. 1991;Addison-Wesley, Reading, MA.
6. Roth D.J. Using a single transducer ultrasonic imaging method to eliminate the effect of thickness variation in the images of ceramic composites plates. J Nondestructive Evaluation. 16:(2):1999.
7. Roth DJ. Nondestructive evaluation for nondestructive evaluation for material characterization. Notes of Course, CWRU, 1999.