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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Journal ArticleDOI
The directional choi–williams distribution for the analysis of rotor-vibration signals
TL;DR: In this paper, a new signal processing technique, the directional Choi-Williams distribution (dCWD), is proposed to account for complex-valued time-varying signals, which represent the planar motion of rotating machinery at each instant of time.
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A polynomial-algebraic method for non-stationary TARMA signal analysis—part II: application to modeling and prediction of power consumption in automobile active suspension systems
TL;DR: The P-A method achieves low computational complexity while eliminating the need for initial guess parameter values and avoiding local extrema problems, and its performance is demonstrated via Monte Carlo simulations.
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Estimation of stationary structural system parameters from non-stationary random vibration data: A locally stationary model method
W. Gersch,T. Brotherton +1 more
TL;DR: In this article, the structural system parameters are estimated from a long non-stationary ambient vibration time series record using a locally stationary autoregressive (AR) model and a time duration weighted average of the estimates in each stationary segment.
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Identification of time varying modal parameters
TL;DR: In this paper, the ability to track time varying frequency and damping parameters using on-line versions of seven time domain system identification algorithms; Least Squares, double least squares, Correlation Fit, Instrumental Variables, instrumental matrix with delayed observations, extended least squares and maximum likelihood, is examined.
Identification of time varying modal parameters
TL;DR: In this paper, the ability to track time varying frequency and damping parameters using on-line versions of seven time domain system identification algorithms; Least Squares, Double Least Square, Correlation Fit, Instrumental Variables and Instrumental Matrix with Delayed Observations.