The Experts below are selected from a list of 71460 Experts worldwide ranked by ideXlab platform
R Pintelon - One of the best experts on this subject based on the ideXlab platform.
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Frequency Response Function estimation in the presence of missing output data
IEEE Transactions on Instrumentation and Measurement, 2015Co-Authors: Diana Ugryumova, R Pintelon, Gerd VandersteenAbstract:Frequency Response Function (FRF) estimation is part of nonparametric system identification in the Frequency domain. The FRF measurements give a quick but deep insight into the dynamics of complex systems. Data samples can get lost in some applications due to sensor failure and/or data transmission errors. We want to overcome this problem without having to repeat the measurement and/or the experiment because this can be either impossible or too expensive. In this paper, we propose a nonparametric method for estimating the FRF and its variance of a single-input single-output system from known input and noisy output measurements with missing output samples. No particular pattern of the missing data is assumed. Moreover, the proposed method provides an estimate of the missing data and its uncertainty.
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nonparametric time variant Frequency Response Function estimates using arbitrary excitations
Automatica, 2015Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:The time-variant Frequency Response Function (TV-FRF) uniquely characterises the dynamic behaviour of a linear time-variant (LTV) system. This paper proposes a method for estimating nonparametrically the dynamic part of the TV-FRF from known input, noisy output observations. The arbitrary time-variation of the TV-FRF is modelled by Legendre polynomials. In opposition to existing solutions, the proposed method is applicable to arbitrary inputs.
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detection and quantification of the influence of time variation in closed loop Frequency Response Function measurements
IEEE Transactions on Instrumentation and Measurement, 2013Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:Recently, a method has been developed for detecting and quantifying the time variation in Frequency Response Function (FRF) measurements using arbitrary excitations. The following basic assumptions have been made: 1) The input is known exactly (generalized output error stochastic framework), and 2) the time-variant system operates in an open loop. The latter excludes any interaction between the time-variant system and the generator/actuator. In this paper, we extend the results of the work by Pintelon to noisy input-output observations (errors-in-variables stochastic framework) of time-variant systems operating in a closed loop.
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detection and quantification of the influence of time variation in Frequency Response Function measurements using arbitrary excitations
IEEE Transactions on Instrumentation and Measurement, 2012Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:This paper presents a nonparametric method for detecting and quantifying the influence of time variation in Frequency Response Function measurements. The method is based on the estimation of the best linear time-invariant (BLTI) approximation of a linear time-variant (LTV) system from known input, noisy output data. The key idea consists in reformulating the single-input, single-output time-variant problem as a multiple-input, single-output time-invariant problem. In addition to the BLTI approximation of the LTV system, the contribution of the disturbing noise, the leakage error, and the time-varying effects at the output is also quantified. As such, the approximation error of the time-invariant framework is known.
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detecting a time varying behavior in Frequency Response Function measurements
IEEE Transactions on Instrumentation and Measurement, 2012Co-Authors: John Lataire, Ebrahim Louarroudi, R PintelonAbstract:This paper provides data-driven tools to detect and quantify approximately the influence of the time variation of a system under test in classical Frequency Response Function (FRF) measurements. To achieve this, the best linear time-invariant approximation of a linear time-varying system is defined and is estimated using existing FRF estimators. An analysis of the residuals of the latter estimation reveals the Frequency band in which the contributions from the time variation dominates the disturbing measurement noise and, thus, is significant. All concepts are illustrated on a simulation and real measurement examples.
Johan Schoukens - One of the best experts on this subject based on the ideXlab platform.
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smoothing the lpm estimate of the Frequency Response Function via an impulse Response truncation technique
IEEE Transactions on Instrumentation and Measurement, 2014Co-Authors: Mikaya L D Lumori, Johan Schoukens, Egon Geerardyn, John LataireAbstract:A statistical impulse Response truncation technique is applied to the local polynomial method (LPM)-estimate of the Frequency Response Function (FRF), resulting in an improved, smooth FRF. Formulated as a nonparametric linear-least-squares-estimate, the LPM is first applied to estimate the FRF from a full data record of a single-input-single-output system, systematically expressed in an output-error framework. The smooth characteristics of both the exact FRF and the leakage from transients allow for an optimal application of the local polynomial method, leading to the elimination of both the leakage and interpolation errors. The truncation method introduced in this paper makes it possible for the user to fine-tune the tradeoff between the uncertainty (variance) and the bias on the estimated instantaneous FRF.
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a nonlinear block structure identification procedure using Frequency Response Function measurements
IEEE Transactions on Instrumentation and Measurement, 2008Co-Authors: Lieve Lauwers, Johan Schoukens, R Pintelon, Martin EnqvistAbstract:Based on simple Frequency Response Function (FRF) measurements, we give the user some guidance in the selection of an appropriate nonlinear block structure for the system to be modeled. The method consists in measuring the FRF using a Gaussian-like input signal and varying in a first experiment the root-mean-square (rms) value of this signal while maintaining the coloring of the power spectrum. Next, in a second experiment, the coloring of the power spectrum is varied while keeping the rms value constant. Based on the resulting behavior of the FRF, an appropriate nonlinear block structure can be selected to approximate the real system. The identification of the selected block-oriented model itself is not addressed in this paper. A theoretical analysis and two practical applications of this structure identification method are presented for some nonlinear block structures.
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a comprehensive study of the bias and variance of Frequency Response Function measurements optimal window selection and overlapping strategies
Automatica, 2007Co-Authors: Jerome Antoni, Johan SchoukensAbstract:This paper investigates the measurement errors involved in measuring Frequency Response Functions from weighted-overlapped segment averaging, a technique that has become a standard in modern spectral analysers due to its computational advantages. A particular attention is paid to leakage errors, for which this procedure has been frequently criticised. Exact and asymptotic expressions for the bias and variance are provided, whose minimisation enables the derivation of the optimal settings to be used with this procedure. Our main finding is that a Half-sine or Diff window with 23 overlap achieves the best compromise to reduce leakage errors, and this is independently of the system Frequency Response Function. This conclusion is to be contrasted with the customary habit of using a Hanning window with 12 overlap.
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Optimized Excitation Signals for MIMO Frequency Response Function Measurements
IEEE Transactions on Instrumentation and Measurement, 2006Co-Authors: Tadeusz P. Dobrowiecki, Johan Schoukens, Patrick GuillaumeAbstract:Many different excitation signals can be chosen for the nonparametric Frequency Response Function measurements of a linear multiple-input-multiple-output (MIMO) system. In the presence of output noise they will result in different signal-to-noise ratios (SNRs) of the Frequency Response Function measurements. In this paper, these effects are analyzed and compared for three classes of multisine excitations: random multisines, approximately orthogonal random multisines, and orthogonal random multisines, taking also into account the crest-factor minimization. It is shown that the orthogonalization of the inputs yields an essential increase in the measured SNR
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variance analysis of Frequency Response Function measurements using periodic excitations
IEEE Transactions on Instrumentation and Measurement, 2005Co-Authors: T Dhaene, Johan Schoukens, R Pintelon, E Van GheemAbstract:The influence of disturbing noise and nonlinear distortions on Frequency Response Function measurements using periodic excitations has been studied in detail in the literature. A variance analysis method has been developed that allows one to detect and quantify the nonlinear distortions and the disturbing noise. In this paper, the variance analysis is generalized to detect and quantify the following nonstationary disturbances: 1) nonsynchronous periodic signals, for example, the 50 Hz mains and its harmonics, and 2) nonstationary behavior of the device under test, for example, phase or Frequency modulation.
Mark D Wallace - One of the best experts on this subject based on the ideXlab platform.
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wavelet based Frequency Response Function for time variant systems an exploratory study
Mechanical Systems and Signal Processing, 2014Co-Authors: Wieslaw J Staszewski, Mark D WallaceAbstract:Abstract A wavelet-based Frequency Response Function (FRF) is proposed for vibration analysis of systems with time-varying parameters. The classical FRF is extended to a representation in the combined time–Frequency domain using wavelet analysis. Time averaging is performed on the initial FRF to improve signal-to-noise ratio. It is shown that use of the wavelet ridge algorithm is effective in extracting and representing visually data from wavelet-based FRFs. The wavelet-based FRF is demonstrated on selected time-variant simulated lumped parameter systems and one experimental vibrating system.
John Lataire - One of the best experts on this subject based on the ideXlab platform.
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nonparametric time variant Frequency Response Function estimates using arbitrary excitations
Automatica, 2015Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:The time-variant Frequency Response Function (TV-FRF) uniquely characterises the dynamic behaviour of a linear time-variant (LTV) system. This paper proposes a method for estimating nonparametrically the dynamic part of the TV-FRF from known input, noisy output observations. The arbitrary time-variation of the TV-FRF is modelled by Legendre polynomials. In opposition to existing solutions, the proposed method is applicable to arbitrary inputs.
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smoothing the lpm estimate of the Frequency Response Function via an impulse Response truncation technique
IEEE Transactions on Instrumentation and Measurement, 2014Co-Authors: Mikaya L D Lumori, Johan Schoukens, Egon Geerardyn, John LataireAbstract:A statistical impulse Response truncation technique is applied to the local polynomial method (LPM)-estimate of the Frequency Response Function (FRF), resulting in an improved, smooth FRF. Formulated as a nonparametric linear-least-squares-estimate, the LPM is first applied to estimate the FRF from a full data record of a single-input-single-output system, systematically expressed in an output-error framework. The smooth characteristics of both the exact FRF and the leakage from transients allow for an optimal application of the local polynomial method, leading to the elimination of both the leakage and interpolation errors. The truncation method introduced in this paper makes it possible for the user to fine-tune the tradeoff between the uncertainty (variance) and the bias on the estimated instantaneous FRF.
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detection and quantification of the influence of time variation in closed loop Frequency Response Function measurements
IEEE Transactions on Instrumentation and Measurement, 2013Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:Recently, a method has been developed for detecting and quantifying the time variation in Frequency Response Function (FRF) measurements using arbitrary excitations. The following basic assumptions have been made: 1) The input is known exactly (generalized output error stochastic framework), and 2) the time-variant system operates in an open loop. The latter excludes any interaction between the time-variant system and the generator/actuator. In this paper, we extend the results of the work by Pintelon to noisy input-output observations (errors-in-variables stochastic framework) of time-variant systems operating in a closed loop.
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detection and quantification of the influence of time variation in Frequency Response Function measurements using arbitrary excitations
IEEE Transactions on Instrumentation and Measurement, 2012Co-Authors: R Pintelon, Ebrahim Louarroudi, John LataireAbstract:This paper presents a nonparametric method for detecting and quantifying the influence of time variation in Frequency Response Function measurements. The method is based on the estimation of the best linear time-invariant (BLTI) approximation of a linear time-variant (LTV) system from known input, noisy output data. The key idea consists in reformulating the single-input, single-output time-variant problem as a multiple-input, single-output time-invariant problem. In addition to the BLTI approximation of the LTV system, the contribution of the disturbing noise, the leakage error, and the time-varying effects at the output is also quantified. As such, the approximation error of the time-invariant framework is known.
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detecting a time varying behavior in Frequency Response Function measurements
IEEE Transactions on Instrumentation and Measurement, 2012Co-Authors: John Lataire, Ebrahim Louarroudi, R PintelonAbstract:This paper provides data-driven tools to detect and quantify approximately the influence of the time variation of a system under test in classical Frequency Response Function (FRF) measurements. To achieve this, the best linear time-invariant approximation of a linear time-varying system is defined and is estimated using existing FRF estimators. An analysis of the residuals of the latter estimation reveals the Frequency band in which the contributions from the time variation dominates the disturbing measurement noise and, thus, is significant. All concepts are illustrated on a simulation and real measurement examples.
Wieslaw J Staszewski - One of the best experts on this subject based on the ideXlab platform.
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wavelet based Frequency Response Function for time variant systems an exploratory study
Mechanical Systems and Signal Processing, 2014Co-Authors: Wieslaw J Staszewski, Mark D WallaceAbstract:Abstract A wavelet-based Frequency Response Function (FRF) is proposed for vibration analysis of systems with time-varying parameters. The classical FRF is extended to a representation in the combined time–Frequency domain using wavelet analysis. Time averaging is performed on the initial FRF to improve signal-to-noise ratio. It is shown that use of the wavelet ridge algorithm is effective in extracting and representing visually data from wavelet-based FRFs. The wavelet-based FRF is demonstrated on selected time-variant simulated lumped parameter systems and one experimental vibrating system.
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wavelet based Frequency Response Function comparative study of input excitation
Shock and Vibration, 2014Co-Authors: Kajetan Dziedziech, Wieslaw J Staszewski, Tadeusz UhlAbstract:Time-variant systems can be found in many areas of engineering. It is widely accepted that the classical Fourier-based methods are not suitable for the analysis and identification of such systems. The time-variant Frequency Response Function—based on the continuous wavelet transform—is used in this paper for the analysis of time-variant systems. The focus is on the comparative study of various broadband input excitations. The performance of the method is tested using simulated data from a simple MDOF system and experimental data from a frame-like structure.
