• Proceedings of the KSR Conference
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• 2008.06a
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• pp.841-848
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• 2008

This paper examined dynamic characteristics of high speed trains using a time varying frequency transform. Fourier transform based methods are frequently used for the calculation of the dynamic characteristics of trains in the frequency domain, but they cannot represent the time-varying characteristics. Therefore it is necessary to examine their characteristics using a time-varying frequency transform. For the examination, the non-stationary vibration of wheelset, bogie, and carbody are measured using accelerometers and stored in a data aquisition system. They are processed with localization of the data by modulating with a window function, and Fourier transform is taken to each localized data, called the short-time Fourier transform. From the processed results, time varying auto-spectral density, cross-spectral density, frequency response, and coherence functions have been calculated. From the analysis, it is confirmed that the time varying frequency transform is a useful method for analyzing the dynamic characteristics of high speed trains.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.187-192
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• 2006

The regularity of railway track alignment is a crucial component fur maintaining travel safety and the smoothness of passenger ride. The conventional spectral analysis has been considered to estimate the severity of the track irregularity from measured data. The time domain data used to be changed into the frequency domain by Fourier transform. Because the measuring points can be regarded as the time points, the spatial-frequency can be introduced instead of the time-frequency. Although FFT(Fast Fourier Transform) and/or PSD(Power Spectral Density) function could provide fairly localized information within frequency domain, but chronical configurations of data could be missed. In this study, we attempt to apply the Morlet wavelet transform for the purpose of a frequency-time-domain analysis rather than a frequency-domain analysis. The applicability of wavelet transform is examined for the estimation of the track irregularity with real measured track data on the section of Kyoung-bu line by EM-120 measuring vehicle. It is shown that the wavelet transform can be an effective tool to manage the track irregularity.

• Current Optics and Photonics
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• v.7 no.5
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• pp.529-536
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• 2023

The Morlet wavelet transform method is proposed to analyze a single interferogram with spatial carrier frequency that is captured by an optical interferometer. The method can retain low frequency components that contain the phase information of a measured optical surface, and remove high frequency disturbances by wavelet decomposition and reconstruction. The key to retrieving the phases from the low-frequency wavelet components is to extract wavelet ridges by calculating the maximum value of the wavelet transform amplitude. Afterwards, the wrapped phases can be accurately solved by multiple iterative calculations on wavelet ridges. Finally, we can reconstruct the wave-front of the measured optical element by applying two-dimensional discrete cosine transform to those wrapped phases. Morlet wavelet transform does not need to remove the spatial carrier frequency components manually in the processing of interferogram analysis, but the step is necessary in the Fourier transform algorithm. So, the Morlet wavelet simplifies the process of the analysis of interference fringe patterns compared to Fourier transform. Consequently, wavelet transform is more suitable for automated programming analysis of interference fringes and avoiding the introduction of additional errors compared with Fourier transform.

• Speech Sciences
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• v.12 no.4
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• pp.17-29
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• 2005

Time-frequency representation reveals some useful information about instantaneous frequency, instantaneous bandwidth and boundary of each AM-FM component of a speech signal. In many cases, the instantaneous frequency of each component is not constant. The variability of instantaneous frequency causes degradation of resolution in time-frequency representation. This paper presents a method of adaptively adjusting the transform kernel for preventing degradation of resolution due to time-varying instantaneous frequency. The transform kernel is the form of frequency modulated function. The modulation function in the transform kernel is determined by the estimate of instantaneous frequency which is approximated by first order polynomial at each time instance. Also, the window function is modulated by the estimated instantaneous. frequency for mitigation of fringing. effect. In the proposed method, not only the transform kernel but also the shape and the length of. the window function are adaptively adjusted by the instantaneous frequency of a speech signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.115-120
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• 2002

The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line may be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.9
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• pp.725-730
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• 2002

The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line nay be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.20 no.5
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• pp.21-27
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• 2001

Impulsive sound and vibration signals in gear system are often associated with their faults. Thus these impulsive sound and vibration signals can be used as indicators in condition monitoring of gear system. The traditional continuous wavelet transform has been used for detection of impulsive signals. However, it is often difficult for the continuous wavelet transform to identify spikes at high frequency and meshing frequencies at low frequency simultaneously since the continuous wavelet transform is to apply the linear scaling (a-dilation) to the mother wavelet. In this paper, the spike wavelet transform is developed to extract these impulsive sound and vibration signals. Since the spike wavelet transform is to apply the non-linear scaling, it has better time resolution at high frequency and frequency resolution at low frequency than that of the continuous wavelet transform respectively. The spike wavelet transform can be, therefore, used to detect fault position clearly without the loss of information for the damage of a gear system. The spike wavelet transform is successfully is applied to detection of the gear fault with tip breakage.