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Data-driven multivariate algorithms for damage detection and identification: evaluation and comparison

Autor
Torres-Arredondo, M.A.; Tibaduiza, D.A.; Mujica, L.E.; Rodellar, J.; Fritzen, C.P
Tipus d'activitat
Article en revista
Revista
Structural health monitoring: an international journal
Data de publicació
2014-01
Volum
13
Número
1
Pàgina inicial
19
Pàgina final
32
DOI
https://doi.org/10.1177/1475921713498530 Obrir en finestra nova
URL
http://shm.sagepub.com/content/13/1/19 Obrir en finestra nova
Resum
This article is concerned with the experimental validation of a structural health monitoring methodology for damage detection and identification. Three different data-driven multivariate algorithms are considered here to obtain the baseline pattern. These are based on principal component analysis, independent component analysis and hierarchical non-linear principal component analysis. The contribution of this article is to examine and compare the three proposed algorithms that have been reported...
Paraules clau
Damage detection, discrete wavelet transform, hierarchical non-linear principal component analysis, independent component analysis, principal component analysis, ultrasonic guided waves
Grup de recerca
CoDAlab - Control, Modelització, Identificació i Aplicacions

Participants