2008
DOI: 10.1155/2008/304362
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Real Time Estimation of Modal Parameters and Their Quality Assessment

Abstract: In this paper the recursive method for modal parameters estimation is formulated and verified. Formulated algorithms are implemented in the FPGA electronic chip. As a result, the modal parameters and confidence bounds for the modal parameters are obtained in real time. The algorithms and their implementations are tested on laboratory test rig data and applied to – flight modal analysis of an airframe structure.

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Cited by 12 publications
(5 citation statements)
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References 8 publications
(8 reference statements)
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“…The progression of variable airspeeds in a hypersonic flutter test does not satisfy the assumption of a stationary stochastic process, which is the theoretical basis of these damping methodologies. Some researchers [27,28] have successfully solved modal identification for nonstationary measured signals by using time-domain modeling methods such as ARMA or TVAR, which are mathematically equivalent to the system stability criterion discussed here.…”
Section: Hypersonic Flutter Analysis Frameworkmentioning
confidence: 99%
“…The progression of variable airspeeds in a hypersonic flutter test does not satisfy the assumption of a stationary stochastic process, which is the theoretical basis of these damping methodologies. Some researchers [27,28] have successfully solved modal identification for nonstationary measured signals by using time-domain modeling methods such as ARMA or TVAR, which are mathematically equivalent to the system stability criterion discussed here.…”
Section: Hypersonic Flutter Analysis Frameworkmentioning
confidence: 99%
“…Figure 4 shows the stationary behaviour of the Gaussian white noise excitation in the time domain. However, if one considers only a small part of this signal, the stationary and broadband behaviour is not so Time (s) ×10 9 Excitation in frequency domain obvious. This is particularly visible in the combined timefrequency domain where the energy distribution of the white noise signal varies with time and frequency from high to near zero amplitudes.…”
Section: Input Excitation For Analysis Of Time-variant Systemsmentioning
confidence: 99%
“…The method presented in [8] is an evolutionary approach and is also used for modal identification. Timescale approaches have been used also for online identification procedures based on adaptive wavelets [9][10][11][12][13]. An overview of different wavelet-based approaches can be found in [13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…The time-frequency analysis includes methods based on the short-time Fourier transform, Wigner-Ville distribution and many other approaches based on the so-called Cohen's class distributions [3,4]. The time-scale approaches are based on the application of the wavelet analysis and include methods for damping estimation [5][6][7], identification of nonlinear systems [8], estimation of instantaneous frequency [9], methods based on adaptive wavelets [10,11] and methods based on the transfer function [12]. Good overviews of wavelet-based methods for time-variant systems are given in [13][14][15].…”
Section: Introductionmentioning
confidence: 99%