| Revista: | Journal of applied research and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000367674 |
| ISSN: | 1665-6423 |
| Autors: | Solís, M1 Benítez Pérez, H1 Rubio, E1 Medina Gómez, L1 Moreno, E2 Gonzalez, G3 Leija, L3 |
| Institucions: | 1Universidad Nacional Autónoma de México, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, México, Distrito Federal. México 2Instituto de Matemática Cibernética y Física, Centro Ultrasónico, La Habana. Cuba 3Instituto Politécnico Nacional, Centro de Investigación y de Estudios Avanzados, México, Distrito Federal. México |
| Any: | 2008 |
| Període: | Abr |
| Volum: | 6 |
| Número: | 1 |
| Paginació: | 33-44 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | 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 |
| Disciplines | Ingeniería |
| Paraules clau: | Ingeniería de materiales, Localización de fallas, Pruebas no destructivas, Reconocimiento de patrones, Coeficientes wavelet |
| Keyword: | Engineering, Materials engineering, Fault location, Non destructive testing, Wavelet coefficients, Pattern recognition |
| Text complet: | Texto completo (Ver HTML) |
