• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.140-146
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• 2008

The damage evaluation method for framed structures using continuous wavelet transform (CWT) is proposed. CWT is applied to the response acceleration of a structure subjected to earthquake load to decompose the response acceleration corresponding to each scale, then the normalized energy value for each scale is calculated. The difference between the normalized energy curvature (NEC) in each node before and after damage indicates a damaged element, which makes it possible to assess the soundness of structural elements. As damage becomes more severe the difference in normalized energy curvature becomes larger. The NEC calculated from the signal corresponding to high scale in CWT analysis is found to be a good index that shows the location and severity of damage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1182-1188
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• 2001

The objective of this paper is to show the effectiveness of the wavelet transform by means of its capability to estimate the Lipschitz exponent. In particular, we show that the magnitude of the Lipschitz exponent can be used as a useful tool estimating the damage extent. An effective method based on the Lipschitz exponent is proposed and we present the results investigated both numerically and experimentally. The continuous wavelet transform by a Mexican hat wavelet having two vanishing moments is utilized for the estimation of the Lipschitz exponent.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2147-2158
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• 2006

The continuous wavelet transform (CWT) has a frequency-adaptive time-frequency tiling property, which makes it popular for the analysis of dispersive elastic wave signals. However, because the time-frequency tiling of CWT is not signal-dependent, it still has some limitations in the analysis of elastic waves with spectral components that are dispersed rapidly in time. The objective of this paper is to introduce an advanced time-frequency analysis method, called the dispersion-based continuous wavelet transform (D-CWT) whose time-frequency tiling is adaptively varied according to the dispersion relation of the waves to be analyzed. In the D-CWT method, time-frequency tiling can have frequency-adaptive characteristics like CWT and adaptively rotate in the time-frequency plane depending on the local wave dispersion. Therefore, D-CWT provides higher time-frequency localization than the conventional CWT. In this work, D-CWT method is applied to the analysis of dispersive elastic waves measured in waveguide experiments and an efficient procedure to extract information on the dispersion relation hidden in a wave signal is presented. In addition, the ridge property of the present transform is investigated theoretically to show its effectiveness in analyzing highly time-varying signals. Numerical simulations and experimental results are presented to show the effectiveness of the present method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.342-348
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• 2005

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.535-543
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• 2001

This paper presents the ride comfort analysis of a vehicle based on wavelet transform. Traditionally, the objective evaluation of impact harshness is based on the vibration dose value (VDV) and frequency weighting method. These methods do not consider the damping effect of the suspension system of a vehicle. In this paper, the damping is estimated using wavelet transform based on Morlet mother wavelet and its effect is considered for the subjective evaluation of impact harshness of a car.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.89-97
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• 2005

Application of proper orthogonal decomposition (POD) and continuous wavelet transform (CWT) is introduced to study wind speed and building roof pressures of flow separation region. In this study, a detailed analysis of the approach wind flow, wind-induced building pressure and the relation between the two fields was carried out using the POD technique and CWT analysis. The results show potential of the application of POD and CWT in characterization of spatio-temporal and spectral properties of the approach wind and its induced dynamic pressure events. Some of findings resulting from the application of this analysis can be summarized as follows: (1) The POD first principal coordinate of the roof pressure in the separated shear layer is closely correlated with the longitudinal component of oncoming flow. (2) The CWT analysis suggests that the extreme peak pressure in the separated shear layer is due to condensed large-scale eddy motions.

• Earthquakes and Structures
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• v.6 no.4
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• pp.393-408
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• 2014

In this paper, a direct identification of modal parameters using the continuous wavelet transform is proposed. The purpose of this method is to transform the differential equations of motion into a system of algebraic linear equations whose unknown coefficients are modal parameters. The efficiency of the present method is confirmed by numerical data, without and with noise contamination, simulated from a discrete forced system with four degrees-of-freedom (4DOF) proportionally damped.

• Geomechanics and Engineering
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• v.36 no.1
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• pp.1-8
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• 2024

We propose a new method for detecting voids behind tunnel concrete linings using the impact-echo method that is based on continuous wavelet transform (CWT) and a convolutional neural network (CNN). We first collect experimental data using the impact-echo method and then convert them into time-frequency images via CWT. We provide a CNN model trained using the converted images and experimentally confirm that our proposed model is robust. Moreover, it exhibits outstanding performance in detecting backfill voids and their status.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.81-87
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• 2001

The human auditory system is appropriate for the "constant Q"system. The STFT (Short Time Fourier Transform) is not suitable for the auditory perception model since it has constant bandwidth. In this paper, the CWT (continuous wavelet transform) is employed for the auditory filter model. In the CWT, the frequency resolution can be adjusted for auditory sensation models. The proposed CWT is applied to the modeling of the JNVF. In addition, other signal processing methods such as STFT, VER-FFT and VFR-STFT are discussed. Among these methods, the model of JNVF (Just Noticeable Variation in Frequency) by using the CWT fits in with the JNVF of auditory model although it requires quite a long time.