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Digitale Medien

Ultrasonic flaw classification in weldments using probabilistic neural networks (1992)

Song, S. J. ; Schmerr, L. W.

Springer

Journal of nondestructive evaluation 11 (1992), S. 69-77

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Details

ISSN: 1573-4862

Schlagwort(e): Welds ; flaw classification ; ultrasonics ; neural networks

Quelle: Springer Online Journal Archives 1860-2000

Thema: Elektrotechnik, Elektronik, Nachrichtentechnik , Mathematik

Notizen: Abstract A probabilistic neural network is used here to classify flaws in weldments from their ultrasonic scattering signatures. It is shown that such a network is both simple to construct and fast to train. Probabilistic nets are also shown to be able to exhibit the high performance of other neural networks, such as feed forward nets trained via back-propagation, while possessing important advantages of speed, explicitness of their architecture, and physical meaning of their outputs. Probabilistic nets are also demonstrated to have performance equal to common statistical approaches, such as theK-nearest neighbor method, while retaining their unique advantages.

Materialart: Digitale Medien

URL: http://dx.doi.org/10.1007/BF00568290

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