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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Book ChapterDOI
Damage Detection on the Z24 Bridge by a Spectral-Based Dynamic Identification Technique
TL;DR: In this article, a spectral-based method is applied to the Z24 bridge, a three-span pre-stressed concrete bridge located in Switzerland, to identify both the modal parameters and the damage of the bridge.
Book ChapterDOI
In situ testing and modeling of cultural heritage buildings in Peru
TL;DR: The results of in situ testing and modelling of four case studies in Peru and is part of the ongoing Seismic Retrofitting Project, under the auspices of the Getty Conservation Institute (GCI): Casa Arones (Cusco), Hotel Comércio (Lima), Ica Cathedral (Ica) and Kuño Tambo (Acomayo) as discussed by the authors.
Journal Article
SHM of a masonry chimney after a lightning accident
TL;DR: In this paper, the authors acknowledge the Fundacao para a Ciencia e Tecnologia, which supported this research work as a part of the Project "Improved and innovative techniques for the diagnosis and monitoring of historical masonry", PTDC/ECM/104045/2008
Journal ArticleDOI
Modal parameter identification of cable stayed bridge based on exploratory data analysis
TL;DR: In this paper, Exploratory Data Analysis (EDA) and Data Driven Stochastic Subspace Identification (DATA-SSI) were employed to identify the modal parameters of civil structures.
Journal ArticleDOI
Vibration-based structural health monitoring using large sensor networks
Arnaud Deraemaeker,André Preumont,Edwin Reynders,G. De Roeck,Jyrki Kullaa,V. Lamsa,Keith Worden,Graeme Manson,Robert J. Barthorpe,Evangelos Papatheou,Pawel Kudela,Pawel Malinowski,Wieslaw Ostachowicz,Tomasz Wandowski +13 more
TL;DR: The design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage are discussed.
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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