Detection of structural changes through principal component analysis (PCA) and multivariate statistical inference

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Title:	Detection of structural changes through principal component analysis (PCA) and multivariate statistical inference
Author:	Pozo Montero, Francesc; Arruga Cantalapiedra, Ignacio; Mujica Delgado, Luis Eduardo; Podivilova, Elena
Other authors:	Universitat Politècnica de Catalunya. Institut de Ciències de l'Educació; Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III; Universitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
Abstract:	This paper is focused on the development of a damage detection indicator that combines a data driven baseline model (reference pattern obtained from the healthy structure) based on principal component analysis (PCA) and multivariate hypothesis testing. More pre- cisely, a test for the plausibility of a value for a normal population mean vector is performed. The results indicate that the test is able to accurately clasify random samples as healthy or not.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures -Structural engineering -damage detection -PCA -multivariate hypothesis testing -structural health monitoring -Enginyeria d'estructures
Rights:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Conference Object
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