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

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.
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https://hal.inria.fr/hal-01021055
Contributor : Anne Jaigu <>
Submitted on : Wednesday, July 9, 2014 - 8:45:56 AM
Last modification on : Monday, November 16, 2020 - 3:56:03 PM
Long-term archiving on: : Thursday, October 9, 2014 - 10:52:02 AM

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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. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01021055⟩

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