Principal Component Analysis for Fault Detection and Structure Health Monitoring - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Principal Component Analysis for Fault Detection and Structure Health Monitoring

Abstract

The aim of this paper is to propose an algorithm for detecting faults such as cracks in an underground structure to ensure its health monitoring. The proposed approach is based on the PCA algorithm. Once PCA components are computed, we can see easily the impact of a crack on their norms. The impact represents a good indication to detect abrupt change.
Fichier principal
Vignette du fichier
0135.pdf (552.78 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01022020 , version 1 (10-07-2014)

Identifiers

  • HAL Id : hal-01022020 , version 1

Cite

Nicolas Stoffels, Vincent Sircoulomb, Guillaume Hermand, Ghaleb Hoblos. Principal Component Analysis for Fault Detection and Structure Health Monitoring. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01022020⟩
238 View
822 Download

Share

Gmail Facebook Twitter LinkedIn More