Parametric time-domain methods for non-stationary random vibration modelling and analysis — A critical survey and comparison
TL;DR: 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.
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TL;DR: A systematic review of over 20 major time-frequency analysis methods reported in more than 100 representative articles published since 1990 can be found in this article, where their fundamental principles, advantages and disadvantages, and applications to fault diagnosis of machinery have been examined.
719 citations
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TL;DR: A general control design approach is proposed when global stabilization is feasible via state feedback, and instead of designing the logical form of a stabilizing feedback law directly, it is suggested that its algebraic representation should be constructed and then converted to logical form.
Abstract: State feedback stabilization for Boolean control networks is investigated in this technical note. Based on the algebraic representation of logical dynamics in terms of the semi-tensor product of matrices, a necessary and sufficient condition is derived for the existence of a globally stabilizing state feedback controller, and a general control design approach is proposed when global stabilization is feasible via state feedback. Instead of designing the logical form of a stabilizing feedback law directly, we first construct its algebraic representation and then convert the algebraic representation back to the logical form. An example is worked out to illustrate the proposed design procedure.
264 citations
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TL;DR: An overview of the principles and techniques of time-series methods for fault detection, identification and estimation in vibrating structures is presented, and certain new methods are introduced.
Abstract: An overview of the principles and techniques of time-series methods for fault detection, identification and estimation in vibrating structures is presented, and certain new methods are introduced. The methods are classified, and their features and operation are discussed. Their practicality and effectiveness are demonstrated through brief presentations of three case studies pertaining to fault detection, identification and estimation in an aircraft panel, a scale aircraft skeleton structure and a simple nonlinear simulated structure.
213 citations
Cites methods from "Parametric time-domain methods for ..."
...…versions of the above (characterized by time-dependent parameters) may be used in the non-stationary case (Petsounis & Fassois 2000; Poulimenos & Fassois 2006), while various nonlinear models, like nonlinear ARMA (NARMA) models, may be used in the nonlinear case (Leontaritis &…...
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TL;DR: In this article, a review of the state-of-the-art strategies and techniques based on vibro-acoustic signals that can monitor and diagnose malfunctions in Internal Combustion Engines (ICEs) under both test bench and vehicle operating conditions is presented.
111 citations
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TL;DR: In this article, a functional series vector time-dependent autoregressive moving average (FS-VTARMA) method is introduced and employed for the identification of a "bridge-like" laboratory structure consisting of a beam and a moving mass.
94 citations
References
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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.
Abstract: 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. These terms are a valid large-sample criterion beyond the Bayesian context, since they do not depend on the a priori distribution.
38,681 citations
01 Jan 2005
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.
Abstract: 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. These terms are a valid large-sample criterion beyond the Bayesian context, since they do not depend on the a priori distribution.
36,760 citations
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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.
Abstract: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis und praktische Anwendung der verschiedenen Verfahren zur Identifizierung hat. Da ...
20,436 citations