Journal ArticleDOI
Parametric time-domain methods for non-stationary random vibration modelling and analysis — A critical survey and comparison
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TLDR
A critical survey and comparison ofparametric time-domain methods for non-stationary random vibration modelling and analysis based upon a single vibration signal realization confirms the advantages and high performance characteristics of parametric methods.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2006-05-01. It has received 246 citations till now. The article focuses on the topics: Parametric statistics & Random vibration.read more
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Book ChapterDOI
Active-Sensing Structural Health Monitoring via Statistical Learning: An Experimental Study Under Varying Damage and Loading States
TL;DR: This paper postulation and experimental assessment of two statistical learning approaches, based on GPRMs and time-varying time series models, for active sensing SHM under varying structural and loading states under uncertainty are presented.
Journal ArticleDOI
Extracting a Non-parametric Instantaneous FRF of a Linear, Slowly Time-Varying system using a Multisine Excitation
John Lataire,Rik Pintelon +1 more
TL;DR: In this article, a non-parametric method for extracting information about the instantaneous dynamics of a slowly time-varying system is proposed. But the method assumes that the system is described by a linear ordinary differential equation whose coefficients are varying piecewise linearly with time, and these variations are slow w.r.t.
Proceedings ArticleDOI
An adaptive time series framework for aircraft 4D trajectory conformance monitoring
TL;DR: In present conformance monitoring, an alarm is shown to be issued instantaneously, following the emergence of an abnormal event, and the comparison with a scheme based on nominal probabilistic trajectory prediction demonstrates the benefits of the adaptive statistical time series framework.
Journal ArticleDOI
Performance assessment of modal parameters identification methods for timber structures evaluation: numerical modeling and case study
TL;DR: In this paper, four of the most common identification methods were presented in a benchmark study with respect to the modal parameters identification efficiency of timber elements under different numerical and experimental configurations, and the robustness of the selected algorithms for investigating the influences of input waveforms complexity and external noise to the performance of the algorithms was investigated.
Proceedings ArticleDOI
A New Method of Noncausal Identification of Time-varying Systems
TL;DR: The paper shows that the problem of noncausal identification of a time-varying FIR (finite impulse response) system can be reformulated, and solved, as a problem of smoothing of the preestimated parameter trajectories.
References
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Journal ArticleDOI
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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.