Detection of structural changes through principal component analysis (PCA) and multivariate statistical inference
Tipus de documentComunicació de congrés
Condicions d'accésAccés obert
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.
CitacióPozo, F., Arruga, I., Mujica, L.E., Podivilova, E. Detection of structural changes through principal component analysis (PCA) and multivariate statistical inference. A: ECCOMAS Thematic Conference Smart Structures and Materials. "SMART 2015 - 7th ECCOMAS Thematic Conference on Smart Structures and Materials: proceedings book". Ponta Delgada, San Miguel, Azores: 2015.