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
Citations
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Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples
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.
Journal ArticleDOI
State Feedback Stabilization for Boolean Control Networks
Rui Li,Meng Yang,Tianguang Chu +2 more
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.
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Time-series methods for fault detection and identification in vibrating structures
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.
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Vibro-acoustic condition monitoring of Internal Combustion Engines: A critical review of existing techniques
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.
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Parametric identification of a time-varying structure based on vector vibration response measurements ☆
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.
References
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Book
Identification of Time-Varying Processes
TL;DR: Time-varying process identification (TVPI) techniques facilitate adaptive noise reduction, echo cancellation, and predictive coding of signals in mobile communications systems.
Journal ArticleDOI
A smoothness priors time-varying AR coefficient modeling of nonstationary covariance time series
Genshiro Kitagawa,Will Gersch +1 more
TL;DR: In this article, a smoothness priors time varying AR coefficient model approach for the modeling of nonstationary in the covariance time series is presented, where the unknown white noise variances are hyperparameters of the AR coefficient distribution.
Journal ArticleDOI
Natural frequencies and dampings identification using wavelet transform: application to real data
TL;DR: In this article, the wavelet transform is used as a time-frequency representation for system identification purposes, and wavelet analysis of the free response of a system allows the estimation of the natural frequencies and viscous damping ratios.
Book
Probabilistic Methods in Structural Engineering
TL;DR: Theories of structures and theory of probability and structural codes, mathematical models for random process analysis, and statistical analysis of random functions.
Journal ArticleDOI
Time-varying system identification and model validation using wavelets
TL;DR: The authors apply an P-test and an AIC based approach for multiresolution analysis of TV systems and advocate the use of a wavelet basis because of its flexibility in capturing the signal's characteristics at different scales, and discuss how to choose the optimal wavelets basis for a given system trajectory.