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Fast Multi-Order Stochastic Subspace Identification

Michael Döhler 1 Laurent Mevel 1
1 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : Stochastic subspace identification methods are an efficient tool for system identification of mechanical systems in Operational Modal Analysis (OMA), where modal parameters are estimated from measured vibrational data of a structure. System identification is usually done for many successive model orders, as the true system order is unknown and identification results at different model orders need to be compared to distinguish true structural modes from spurious modes in so-called stabilization diagrams. In this paper, this multi-order system identification with the subspace-based identification algorithms is studied and an efficient algorithm to estimate the system matrices at multiple model orders is derived.
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https://hal.inria.fr/inria-00527484
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Submitted on : Tuesday, October 19, 2010 - 1:56:49 PM
Last modification on : Wednesday, May 19, 2021 - 4:18:06 PM
Long-term archiving on: : Thursday, January 20, 2011 - 2:41:33 AM

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Michael Döhler, Laurent Mevel. Fast Multi-Order Stochastic Subspace Identification. [Research Report] RR-7429, INRIA. 2010. ⟨inria-00527484⟩

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