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
Reducing uncertainty in seismic assessment of multiple masonry buildings based on monitored demolitions
TL;DR: In this article , a Bayesian model-updating framework is proposed to reduce uncertainty in seismic analysis by fusing dynamic measurements with best-practice structural models, and a vast reduction in prediction uncertainty is achieved through data-driven model updating, additionally exposing intra and inter-typological differences in terms of seismic capacity and ductility.
Journal ArticleDOI
Soil damping calculation of the offshore wind turbine supported by wide-shallow bucket foundation
TL;DR: In this article, a new theoretical calculation method of soil damping for the OWT supported by Wide-Shallow Bucket Foundation (WSBF) was proposed considering soil hysteresis characteristics.
Journal ArticleDOI
Full-scale tests of wind effects on a long span roof structure
TL;DR: In this article, the first four natural frequencies and their vibration mode shapes of the Guangzhou International Sports Arena (GISA) roof are evaluated by the stochastic subspace identification (SSI) method and comparisons with those from finite element analysis are made.
Journal ArticleDOI
Crack detection in Mindlin-Reissner plates under dynamic loads based on fusion of data and models
TL;DR: It is demonstrated, through a series of numerical experiments, that the fusion of data-driven and model-based approaches can be beneficial both in Terms of accuracy and localization, as well as in terms of computational requirements.
Book ChapterDOI
S2HM in Some European Countries
Maria Pina Limongelli,Mauro Dolce,Daniele Spina,Philippe Guéguen,Mickael Langlais,David Wolinieck,Emeline Maufroy,Christos Karakostas,Vassilios Lekidis,Konstantinos Morfidis,Thomas N. Salonikios,Emmanouil Rovithis,Konstantia Makra,Maria Giovanna Masciotta,Paulo B. Lourenço +14 more
TL;DR: In this paper, the authors describe the national initiatives and projects on seismic Structural Health Monitoring (S2HM) active in a number of European countries, including Italy, France, Greece and Portugal.
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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