Journal ArticleDOI
Reference-based stochastic subspace identification for output-only modal analysis
Bart Peeters,Guido De Roeck +1 more
TLDR
In this paper, a novel approach of stochastic subspace identification is presented that incorporates the idea of the reference sensors already in the identification step: the row space of future outputs is projected into the rowspace of past reference outputs.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 1999-11-01. It has received 1236 citations till now. The article focuses on the topics: Operational Modal Analysis & Subspace topology.read more
Citations
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Journal ArticleDOI
Triggering expectation and residual excitation of distributed random decrement technique
Yan Zhang,L.J. Wu,H.W. Song +2 more
TL;DR: In this paper, a distributing process is proposed for Random Decrement Technique (RDT) to accurate modal identification, whose signal is overlap-averaged under Gaussian white noise excitation.
Journal ArticleDOI
Towards a more realistic modelling of the uncertainty on identified mode shapes due to measurement noise
TL;DR: In this article, the authors apply this approach to the numerical example of a simply supported beam and show that there is a strong spatial correlation in the mode shapes uncertainty and that adding independent noise directly on the mode shape is not a very realistic approach to assess the impact of noise on damage identification.
Journal ArticleDOI
Operational modal analysis application to support structure identification under rotating machinery unbalance
Leonardo B. Saint Martin,Leonardo L. Gusmão,Tiago Henrique Machado,Eduardo Paiva Okabe,Katia Lucchesi Cavalca +4 more
TL;DR: In this article, the authors apply an OMA approach to a rotating system using the ramp-up excitation aiming to extract the modal parameters of the support structure of the rotating machines.
Journal ArticleDOI
Uncertainty Quantification for Stochastic Damage Localization for Mechanical Systems
TL;DR: In this article, the derivation of the uncertainty of the state space system can be used to derive uncertainty on the damage localization residuals and help to decide about the damage location.
Journal ArticleDOI
Identification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace Identification
T. Janesupasaeree,V. Boonyapinyo +1 more
TL;DR: In this paper, the covariance-driven stochastic subspace identification technique (SSI-COV) was presented to extract the flutter derivatives of bridge decks from the buffeting test results.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Book
Modal Testing: Theory and Practice
TL;DR: A survey of the technology of modal testing, a new method for describing the vibration properties of a structure by constructing mathematical models based on test data rather than using conventional theoretical analysis.
Book
Subspace Identification for Linear Systems: Theory - Implementation - Applications
Peter Van Overschee,Bart De Moor +1 more
TL;DR: This book focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finitedimensional dynamical systems, which allow for a fast, straightforward and accurate determination of linear multivariable models from measured inputoutput data.
Book
Applied system identification
TL;DR: In this paper, the authors introduce the concept of Frequency Domain System ID (FDSI) and Frequency Response Functions (FRF) for time-domain models, as well as Frequency-Domain Models with Random Variables and Kalman Filter.
Effective construction of linear state-variable models from input/output functions.
B. L. Ho,R. E. Kalman +1 more
TL;DR: Markov parametric algorithm for effective construction of minimal realizations of linear state-variable finite-dimensional dynamical systems from input-output data is presented in this article, where a Markov-parametric algorithm is used to construct the minimal realization.
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Subspace Identification for Linear Systems: Theory - Implementation - Applications
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