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
Vibration-based estimation of axial force for a beam member with uncertain boundary conditions
TL;DR: In this paper, the axial force of a two-dimensional Euler-Bernoulli beam member is estimated based on dynamic measurements from at least five sensors, and the proposed method is capable of estimating axial forces as well as the translational and rotational stiffness at both beam ends.
Journal ArticleDOI
Modal identification and damage detection using the data-driven stochastic subspace and armav methods
TL;DR: In this article, the authors present results of modal identification and damage detection on the Steel-Quake structure using the autoregressive moving average vector and data-driven stochastic subspace methods.
Journal ArticleDOI
Swinging-bell resonances and their cancellation identified by dynamical testing in a modern bell tower
TL;DR: In this article, a case study of a bell tower is presented, where the frequency characteristics of the bell-swinging action are determined through spectral analyses of the structure forced response signals, measured during the swinging motion of each bell separately.
Journal ArticleDOI
Finite element modelling of a silo based on experimental modal analysis
TL;DR: In this paper, a finite element model of a cylindrical shell structure is validated by means of experimental results obtained on a silo on which ovalling has been observed, including the connection between the silo and the supporting structure.
Scaling Factor Estimation Using an Optimized Mass Change Strategy, Part 1: Theory
TL;DR: In this paper, a procedure to optimize the mass change strategy is proposed, which uses the modal parameters (natural frequencies and mode shapes) of the original structure as the basic information.
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.
Related Papers (5)
Subspace Identification for Linear Systems: Theory - Implementation - Applications
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