A structural damage detection indicator based on principal component analysis and multivariate hypothesis testing over scores

Francesc Pozo 1 Ignacio Arruga 1 Luis Eduardo Mujica 1
1 UPC - Universitat Politècnica de Catalunya [Barcelona]
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 precisely, 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.
Keywords : Statistical methods Pattern recognition Damage detection and localization
Type de document :
Communication dans un congrès
Le Cam, Vincent and Mevel, Laurent and Schoefs, Franck. EWSHM - 7th European Workshop on Structural Health Monitoring, Jul 2014, Nantes, France. 2014
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Francesc Pozo, Ignacio Arruga, Luis Eduardo Mujica. A structural damage detection indicator based on principal component analysis and multivariate hypothesis testing over scores. Le Cam, Vincent and Mevel, Laurent and Schoefs, Franck. EWSHM - 7th European Workshop on Structural Health Monitoring, Jul 2014, Nantes, France. 2014. 〈hal-01021055〉

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