Structural health monitoring by combining machine learning and dimensionality reduction techniques
Type
Articles dans des revues avec comité de lectureAuthor

10921 Institut de Recherche en Génie Civil et Mécanique [GeM]
111023 École Centrale de Nantes [ECN]

111023 École Centrale de Nantes [ECN]
10921 Institut de Recherche en Génie Civil et Mécanique [GeM]
Date
2019Journal
Revista Internacional de Metodos Numericos para Calculo y Diseno en IngenieriaAbstract
Structural Health Monitoring is of major interest in many areas of structural mechanics. This paper presents a new approach based on the combination of dimensionality reduction and data-mining techniques able to differentiate damaged and undamaged regions in a given structure. Indeed, existence, severity (size) and location of damage can be efficiently estimated from collected data at some locations from which the fields of interest are completed before the analysis based on machine learning and dimensionality reduction techniques proceed.
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