Extraction of Impulse Response Data via Wavelet Transform for Structural System Identification

1995 ◽  
Author(s):  
A. N. Robertson ◽  
K. C. Park ◽  
K. F. Alvin
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Impulse Response Function ◽  
Low Frequency ◽  
Extraction Methods ◽  
Structural Dynamic ◽  
Response Characteristics ◽  
Input Signals ◽  
The Time Domain ◽  
Structural System Identification

Abstract This paper presents a wavelet transform-based method of extracting the impulse response characteristics from the measured disturbances and response histories of linear structural dynamic systems. The proposed method appears to have alleviated some of the most pronounced deleterious aspects of both the time-domain methods that suffer from the matrix ill-conditioning of the input signals and FFT-based methods that must cope with erraneous auto and cross-correlation functions, unless the input signals are rich enough in frequency content The method is found to be effective in capturing very low frequency response components and also far insensitive to output noises than existing methods. The present method has been applied to a variety of problems, which show significant improvements over existing impulse response function extraction methods, especially for limited harmonic excitations and input/output data contaminated with noises.

Extraction of Impulse Response Data via Wavelet Transform for Structural System Identification

1998 ◽  
Vol 120 (1) ◽  
pp. 252-260 ◽  
Author(s):  
A. N. Robertson ◽  
K. C. Park ◽  
K. F. Alvin
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Gibbs Phenomenon ◽  
Impulse Response Functions ◽  
Structural Dynamic ◽  
Wavelet Method ◽  
Response Characteristics ◽  
Input Signals ◽  
Response Modes ◽  
Structural System Identification

This paper presents a wavelet transform-based method of extracting the impulse response characteristics from the measured disturbances and response histories of linear structural dynamic systems. The proposed method is found to be effective in determining the impulse response functions for systems subjected to harmonic (narrow frequency-band) input signals and signals with sharp discontinuities, thus alleviating the Gibbs phenomenon encountered in FFT methods. When the system is subjected to random burst input signals for which the FFT methods are known to perform well, the proposed wavelet method performs equally well with a fewer number of ensembles than FFT-based methods. For completely random input signals, both the wavelet and FFT methods experience difficulties, although the wavelet method appears to perform somewhat better in tracing the fundamental response modes.

scholarly journals Convolution-based time-domain simulation for fluidelastic instability in tube arrays

2021 ◽  
Author(s):  
Mingjie Zhang ◽  
Ole Øiseth
Keyword(s):  
Impulse Response ◽  
Response Function ◽  
Time Domain ◽  
Impulse Response Function ◽  
Time Domain Simulation ◽  
Unit Step ◽  
Tube Arrays ◽  
Unit Impulse ◽  
The Time Domain ◽  
Unit Impulse Response

AbstractA convolution-based numerical algorithm is presented for the time-domain analysis of fluidelastic instability in tube arrays, emphasizing in detail some key numerical issues involved in the time-domain simulation. The unit-step and unit-impulse response functions, as two elementary building blocks for the time-domain analysis, are interpreted systematically. An amplitude-dependent unit-step or unit-impulse response function is introduced to capture the main features of the nonlinear fluidelastic (FE) forces. Connections of these elementary functions with conventional frequency-domain unsteady FE force coefficients are discussed to facilitate the identification of model parameters. Due to the lack of a reliable method to directly identify the unit-step or unit-impulse response function, the response function is indirectly identified based on the unsteady FE force coefficients. However, the transient feature captured by the indirectly identified response function may not be consistent with the physical fluid-memory effects. A recursive function is derived for FE force simulation to reduce the computational cost of the convolution operation. Numerical examples of two tube arrays, containing both a single flexible tube and multiple flexible tubes, are provided to validate the fidelity of the time-domain simulation. It is proven that the present time-domain simulation can achieve the same level of accuracy as the frequency-domain simulation based on the unsteady FE force coefficients. The convolution-based time-domain simulation can be used to more accurately evaluate the integrity of tube arrays by considering various nonlinear effects and non-uniform flow conditions. However, the indirectly identified unit-step or unit-impulse response function may fail to capture the underlying discontinuity in the stability curve due to the prespecified expression for fluid-memory effects.

scholarly journals Transient Response of an Impacted Beam and Indirect Impact Force Identification Using Strain Measurements

1994 ◽  
Vol 1 (3) ◽  
pp. 267-278 ◽  
Author(s):  
Hyungsoon Park ◽  
Youn-sik Park
Keyword(s):  
Impulse Response ◽  
Impact Force ◽  
Impulse Response Function ◽  
Time History ◽  
Impulse Response Functions ◽  
Transverse Impact ◽  
History Of ◽  
Convolution Approach ◽  
The Time Domain ◽  
The Impact

The impulse response functions (force-strain relations) for Euler–Bernoulli and Timoshenko beams are considered. The response of a beam to a transverse impact force, including reflection at the boundary, is obtained with the convolution approach using the impulse response function obtained by a Laplace transform and a numerical scheme. Using this relation, the impact force history is determined in the time domain and results are compared with those of Hertz's contact law. In the case of an arbitrary impact, the location of the impact force and the time history of the impact force can be found. In order to verify the proposed algorithm, measurements were taken using an impact hammer and a drop test of a steel ball. These results are compared with simulated ones.

Transient axisymmetric motion of a floating cylinder

1985 ◽  
Vol 157 ◽  
pp. 17-33 ◽  
Author(s):  
J. N. Newman
Keyword(s):  
Free Surface ◽  
Frequency Domain ◽  
Impulse Response ◽  
Response Function ◽  
Time Domain ◽  
Impulse Response Function ◽  
Surface Effects ◽  
Added Mass ◽  
The Body ◽  
The Time Domain

A linear theory is developed in the time domain for vertical motions of an axisymmetric cylinder floating in the free surface. The velocity potential is obtained numerically from a discretized boundary-integral-equation on the body surface, using a Galerkin method. The solution proceeds in time steps, but the coefficient matrix is identical at each step and can be inverted at the outset.Free-surface effects are absent in the limits of zero and infinite time. The added mass is determined in both cases for a broad range of cylinder depths. For a semi-infinite cylinder the added mass is obtained by extrapolation.An impulse-response function is used to describe the free-surface effects in the time domain. An oscillatory error observed for small cylinder depths is related to the irregular frequencies of the solution in the frequency domain. Fourier transforms of the impulse-response function are compared with direct computations of the damping and added-mass coefficients in the frequency domain. The impulse-response function is also used to compute the free motion of an unrestrained cylinder, following an initial displacement or acceleration.

Fractional Vector-Order h-Realisation of the Impulse Response Function

2020 ◽  
Vol 14 (2) ◽  
pp. 108-113
Author(s):  
Ewa Pawłuszewicz
Keyword(s):  
Control Systems ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Linear Control ◽  
Linear Control Systems

AbstractThe problem of realisation of linear control systems with the h–difference of Caputo-, Riemann–Liouville- and Grünwald–Letnikov-type fractional vector-order operators is studied. The problem of existing minimal realisation is discussed.

A waveform inversion technique for measuring elastic wave attenuation in cylindrical bars

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 854-859 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Elastic Wave ◽  
Wave Attenuation ◽  
Waveform Inversion ◽  
Finite Size ◽  
Low Frequency ◽  
Frequency Range ◽  
Multiple Reflections ◽  
Low Frequencies ◽  
The Time Domain ◽  
Attenuation Values

A new technique for measuring elastic wave attenuation in the frequency range of 10–150 kHz consists of measuring low‐frequency waveforms using two cylindrical bars of the same material but of different lengths. The attenuation is obtained through two steps. In the first, the waveform measured within the shorter bar is propagated to the length of the longer bar, and the distortion of the waveform due to the dispersion effect of the cylindrical waveguide is compensated. The second step is the inversion for the attenuation or Q of the bar material by minimizing the difference between the waveform propagated from the shorter bar and the waveform measured within the longer bar. The waveform inversion is performed in the time domain, and the waveforms can be appropriately truncated to avoid multiple reflections due to the finite size of the (shorter) sample, allowing attenuation to be measured at long wavelengths or low frequencies. The frequency range in which this technique operates fills the gap between the resonant bar measurement (∼10 kHz) and ultrasonic measurement (∼100–1000 kHz). By using the technique, attenuation values in a PVC (a highly attenuative) material and in Sierra White granite were measured in the frequency range of 40–140 kHz. The obtained attenuation values for the two materials are found to be reliable and consistent.

FINITE IMPULSE RESPONSE DOUBLE DENSITY FILTER BANKS AND FRAMELETS

2013 ◽  
Vol 11 (01) ◽  
pp. 1350010
Author(s):  
ASHOKA JAYAWARDENA ◽  
PAUL KWAN
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Filter Bank ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Wavelet Filters ◽  
Density Filter ◽  
Shift Invariance ◽  
Factorization Methods ◽  
Invariant Properties

In this paper, we focus on the design of oversampled filter banks and the resulting framelets. The framelets obtained exhibit improved shift invariant properties over decimated wavelet transform. Shift invariance has applications in many areas, particularly denoising, coding and compression. Our contribution here is on filter bank completion. In addition, we propose novel factorization methods to design wavelet filters from given scaling filters.

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