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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.
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https://hal.inria.fr/hal-01022020
Contributor : Anne Jaigu <>
Submitted on : Thursday, July 10, 2014 - 9:56:06 AM
Last modification on : Thursday, October 24, 2019 - 11:26:02 AM
Long-term archiving on: : Friday, October 10, 2014 - 10:50:51 AM

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  • HAL Id : hal-01022020, version 1

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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⟩

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