• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.107-111
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• 2005

It has been reviewed whether it would be suitable that the application of the time-frequency signal analysis techniques to estimate the location of the impact source in plate structure. The STFT(Short Time Fourier Transform), WVD(Wigner-Ville distribution) and CWT(Continuous Wavelet Transform) methods are introduced and the advantages and disadvantages of those methods are described by using a simulated signal component. The essential of the above proposed techniques is to separate the traveling waves in both time and frequency domains using the dispersion characteristics of the structural waves. These time-frequency methods are expected to be more useful than the conventional time domain analyses fer the impact localization problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the location estimation in a noisy environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.266-271
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• 2005

Although time-frequency analysis is useful for dispersive wave analysis, conventional methods such as the short-time Fourier transform do not take the dispersion phenomenon into consideration in the tiling of the time-frequency domain. The objective of this paper is to develop an adaptive time-frequency analysis method whose time-frequency tiling is determined with the consideration of signal dispersion characteristics. To achieve the adaptive time-frequency tiling, each of time-frequency atoms is rotated in the time-frequency plane depending on the local wave dispersion. To carry out this adaptive time-frequency transform, dispersion characteristics hidden in a signal are first estimated by an iterative scheme. To examine the effectiveness of the present method, the flexural wave signals measured in a plate were analyzed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.606-610
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• 2004

Although time-frequency analysis is useful for dispersive wave analysis, conventional methods such as the short-time Fourier transform do not take the dispersion phenomenon into consideration in the tiling of the time-frequency domain. The objective of this paper is to develop an adaptive time-frequency analysis method whose time-frequency tiling is determined with the consideration of signal dispersion characteristics. To achieve the adaptive time-frequency tiling, each of time-frequency atoms is rotated in the time-frequency plane depending on the local wave dispersion. To carry out this adaptive time-frequency transform, dispersion characteristics hidden in a signal are first estimated by an iterative scheme. To examine the effectiveness of the proposed method, the flexural wave signals measured in a plate were analyzed.

• Interaction and multiscale mechanics
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• v.2 no.1
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• pp.91-107
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• 2009

In order to accurately estimate the seismic behavior of buildings, it is important to consider both nonlinear characteristics of the buildings and the frequency dependency of the soil impedance. Therefore, transform methods of the soil impedance in the frequency domain to the impulse response in the time domain are needed because the nonlinear analysis can not be carried out in the frequency domain. The author has proposed practical transform methods. In this paper, seismic response analyses considering frequency dependent soil impedance in the time domain are shown. First, the formulation of the proposed transform methods is described. Then, the linear and nonlinear earthquake response analyses of a building on 2-layered soil were carried out using the transformed impulse responses. Through these analyses, the validity and efficiency of the methods were confirmed.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.270-276
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• 1999

Fourier transform has been one of the most commonly used tools in study of frequency characteristics of signal. However, based on the Fourier transform. it is hard to tell whether a signal's frequency contents evolve in time or not. Recently, to overcome Fourier transform fault. not to represent non-stationary signal, time-frequency analysis methods are developed and those can represent informations of signal's time and frequency at the same time. In this study we analysed ultrasonic signal for degraded SUS 316 with time-frequency analysis method. In particular the methods such as short time Fourier(STFT) and Wigner-Ville distribution(WVD) were used to extract frequency contents and characteristics from ultrasonic signals.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.173-178
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• 2002

Fourier transform has been one of the most common tools to study the frequency characteristics of signals. With the Fourier transform alone, it is difficult to tell whether signal's frequency contents evolve in time or not. Except for a few special cases, the frequency contents of most signals encountered in the real world change with time. Time-frequency methods are developed recently to overcome the drawbacks of Fourier transform, which can represent the information of signals in time and frequency at the same time. In this study, heat damage process of a carbon fiber reinforced plastic(CFRP) and glass fiber reinforced plastic(GFRP) under monotonic tensile loading was characterized by acoustic emission. Different kinds of specimens were used to determine the characteristics of Strength and AE signals. Time-frequency analysis methods were employed for the analysis of fracture mechanism in CFRP such as matrix cracking, debonding and fiber fracture.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.39-45
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• 2001

Fourier transform has been one of the most common tools to study the frequency characteristics of signals. With the Fourier transform alone, however, it is difficult to tell whether signal's frequency contents evolve in time or not. Except for a few special cases, the frequency contents of most signals encountered in the real world change with time. Time-frequency analysis methods are developed recently to overcome the drawbacks of Fourier transform, which can represent the information of signals in time and frequency at the same time. In this study, damage process of a cross-ply carbon fiber reinforced plastic (CFRP) under monotonic tensile loading was characterized by acoustic emission. Different kinds of CFRP specimens were used to determine the characteristics of AE signals. Time-frequency analysis methods were employed for the analysis of fracture mechanisms in CFRP such as mix cracking, debonding, fiber fracture and delamination.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.509-516
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• 2001

This paper introduced some advantages of the time-frequency analysis of vibration and investigated, using the time-frequency transform, the characteristics of the transient motion of a tractor seat, which occurred during the tractor traversed over a rectangular obstacle on the flat surface. The characteristics of the short-time courier and wavelet transforms as time-frequency analysis methods were introduced and discussed to figure out which is more suitable to the analysis of the transient motions of agricultural tractors. Using each transform, transient vibration of a tractor seat was analyzed. Results of the analysis showed that the transient vibration of the seat was influenced by the natural frequencies of vertical mode of chassis, pitching mode of engine and pitching mode of cab of the tractor. The time sequence of the natural mode of tractor vibration was also revealed by the time-frequency analysis. The vibration path analysis by the time-frequency transform showed that the vibration energies transmitted from the front mounts to the seat were less than those from the rear mounts. The energy reduction ratios between the cab mounts and seat were also estimated to be about 72∼78%. The front mounts showed larger reduction than the rear mounts. However, the reduction difference between the right and left sides mounts was negligibly small. The short time Fourier transform was found to be a proper method for investigating the transient motions of farm machines and their effects on the ride vibration.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• Journal of KSNVE
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• v.3 no.4
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• pp.341-352
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• 1993

Although a frequency analysis by FFT algorithm has been widely used in the vibration community, this approach has somewhat limited features when an analysist want to see the details of frequency trends because FFT shows only energy contents along frequencies. So the concept of instantaneous frequency that represents the dominant frequency component at each time needs to be introduced. In this paper, to get the instantaneous frequency, two methods are used. Methods using Hilbert transform and evolutionary spectrum are those. One of the problems of estimating instantaneous frequency using Hilbert transform is that it is normally very sensitive to signal to noise ratio(SNR) because of the differentiation. Moving window is applied on the estimation of instantaneous frequency, and instantaneous frequency histogram are used to handle this problem and proved to be very effective. Computer simulations for various signals have been done to understand the characteristics of instantaneous frequency. The usefulness of signal analysis using instantaneous frequency was tested by three simple experiments, which were engine experiment, beam experiment, and car door experiment. The instantaneous frequency analysis is found to be a useful technique to analyze the signals that have time varying frequencies.