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Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers

Autor
Gharibnezhad, F.; Mujica, L.E.; Rodellar, J.
Tipus d'activitat
Article en revista
Revista
Mechanical systems and signal processing
Data de publicació
2014-06-17
Volum
50-51
Pàgina inicial
467
Pàgina final
479
DOI
https://doi.org/10.1016/j.ymssp.2014.05.032 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0888327014002088 Obrir en finestra nova
Resum
Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Theref...
Paraules clau
Damage detection, Outliers, Robust PCA
Grup de recerca
CoDAlab - Control, Modelització, Identificació i Aplicacions

Participants