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Multivariate data-driven modelling and pattern recognition for damage detection and identification for acoustic emission and acousto-ultrasonics

Autor
Torres-Arredondo, M.A.; Tibaduiza, D.A.; Mcgugan, M.; Toftegaard, H.L.; Borum, K-K; Mujica, L.E.; Rodellar, J.; Fritzen, C.P
Tipus d'activitat
Article en revista
Revista
Smart materials and structures
Data de publicació
2013-10
Volum
22
Número
10
Pàgina inicial
105023-1
Pàgina final
105023-21
DOI
https://doi.org/10.1088/0964-1726/22/10/105023 Obrir en finestra nova
URL
http://iopscience.iop.org/article/10.1088/0964-1726/22/10/105023/meta Obrir en finestra nova
Resum
Different methods are commonly used for non-destructive testing in structures; among others, acoustic emission and ultrasonic inspections are widely used to assess structures. The research presented in this paper is motivated by the need to improve the inspection capabilities and reliability of structural health monitoring (SHM) systems based on ultrasonic guided waves with focus on the acoustic emission and acousto-ultrasonics techniques. The use of a guided wave based approach is driven by the...
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CoDAlab - Control, Modelització, Identificació i Aplicacions

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