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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Nacional Autónoma de México
2008
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| Online Access: | https://www.redalyc.org/articulo.oa?id=47413019003 |
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Table of Contents:
- PATTERN CLASSIFICATION OF DECOMPOSED WAVELET INFORMATION USING ART2 NETWORKS FOR ECHOES ANALYSIS M. Solís H. Benítez-Pérez E. Rubio L. Medina-Gómez E. Moreno G. Gonzalez L. Leija Ingeniería NDT ART2 Networks Defect Location Pattern recognition Wavelets coefficients The Ultrasonic Pulse-Echo technique has been successfully used in a non-destructive testing of materials. To perform Ultrasonic Non-destructive Evaluation (NDE), an ultrasonic pulsed wave is transmitted into the materials using a transmitting/receiving transducer or arrays of transducers,that produces an image of ultrasonic reflectivity. The information inherent in ultrasonic signals or image are the echoes coming from flaws, grains, and boundaries of the tested material. The main goal of this evaluation is to determine the existence of defect, its size and its position; for that matter, an innovative methodology is proposed based on pattern recognition and wavelet analysis for flaws detection and localization. The pattern recognition technique used in this work is the neural network named ART2 (Adaptive Resonance Theory) trained by the information given by the time-scale information of the signals via the wavelet transform. A thorough analysis between the neural network training and the type wavelets used for the training has been developed, showing that the Symlet 6 wavelet is the optimum for our problem. 2008 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47413019003 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.1 Vol.6