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Filtrado adaptativo no lineal para la reducción de ruido estructural en inspecciones por ultrasonidos

Authors: García Izquierdo, Miguel Ángel; González Hernández, Margarita; Martínez-Graullera, Óscar; Sánchez Martín, Teresa;

Filtrado adaptativo no lineal para la reducción de ruido estructural en inspecciones por ultrasonidos

Abstract

[ES] Este trabajo presenta un nuevo método para la reducción de ruido estructural. Para incrementar la visibilidad del defecto esta técnica usa el ruido residual obtenido con un predictor no lineal adaptativo basado en una red neuronal. Los resultados obtenidos con acero inoxidable y laminados de CFRP muestran que este nuevo método posee mejores prestaciones para la reducción de ruido estructural que las técnicas adaptativas lineales.

[EN] A new method to reduce the structural noise of dispersive materials is presented. In order to increase SNR, this technique used residual noise obtained with an adaptive non-linear predictor, which is based on a neuronal network. Experiments with stainless steel and CFRP laminates show that this new method has better results in the structural noise reduction compared with linear adaptive conventional techniques.

6 pp.-- PACS nr.: 43.35.Zc.-- Comunicación presentada en los siguientes congresos: II Congreso Iberoamericano de Acústica. XXXI Congreso Nacional de Acústica – TecniAcústica 2000. II Jornadas Iberoamericanas de Ultrasonidos. II Congreso Ibérico de Acústica. EAA Symposium on Architectural Acoustics (Madrid, 16-20 Octubre 2000).

Este trabajo ha sido realizado gracias a la financiación de los proyectos ref. 07T/0041/1998 de la Comunidad de Madrid y R-PETRI-95-0377-OP del MEC.

Publicado también en número especial de la Revista de Acústica, Vol. XXXI, año 2000.

Peer reviewed

Keywords

Structural noise reduction, Linear adaptive techniques, Adaptive non-linear predictor

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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