• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.667-691
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• 2016

This study focuses on the damage detection of defect types in plate structures based on wavelet transform (WT) and curvelet transform (CT). In particular, for damage detection of structures these transforms have been developed since the last few years. In recent years, the CT approach has been also introduced in an attempt to overcome inherent limitations of traditional multi-scale representations such as wavelets. In this study, the performance of CT is compared with WT in order to demonstrate the capability of WT and CT in detection of defect types in plate structures. To achieve this purpose, the damage detection of defect types through defect shape in rectangular plate is investigated. By using the first mode shape of plate structure and the distribution of the coefficients of the transforms, the damage existence, the defect location and the approximate shape of defect are detected. Moreover, the accuracy and performance generality of the transforms are verified through using experimental modal data of a plate.

• Speech Sciences
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• v.7 no.4
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• pp.3-10
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• 2000

This paper presents a time-based Pitch Determination Algorithm (PDA) for the reliable estimation of Pitch Period (PP) in speech signals. Based on the Dyadic Wavelet Transform (DyWT) , the proposed PDA detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. We also examine the problem of conventional PDAs based on DyWT; their performance is compared with the proposition of this paper. The effectiveness of the proposed method is tested with real speech signals containing a transition between the voiced and the unvoiced interval where the energy of the voiced signal is unsteady. The result shows that the proposed method provides good performance in estimating both the unsteady GCI positions as well as the steady parts.

• Composites Research
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• v.13 no.1
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• pp.61-68
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• 2000

A new approach is presented for the analysis of transient waves propagating in anisotropic composite laminates. The wavelet transform (WT) using the Gabor wavelet is applied to the time-frequency analysis of dispersive flexural waves. It is shown that the peaks of the magnitude of WT in time-frequency domain is related to the arrival times of group velocity. Experiments are performed using a lead break as the simulated fracture source on the surface of quasi-isotropic and unidirectional laminates. For predictions of the dispersion of the flexural mode, Mindlin plate theory is shown to give good agreement with the experimental results. Based on the frequency-dependent arrival times and angular dependence of group velocities of flexural waves, the problem of source location in anisotropic laminates is considered and the results are given.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.12
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• pp.45-61
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• 1996

This paper presents the ECG data compression using wavelet transform (WT) and adaptive fractal interpolation (AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data cmpression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 wihtout any entropy coding.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.221-224
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• 1996

This paper presents the ECG data compression using wavelet transform(WT) and adaptive fractal interpolation(AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data compression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arrhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 without any entroy coding.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.834-840
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• 2007

A generator plays an important role in transferring an electric power to power system networks. The generator protection systems in Korea have been imported and operated through a tum-key from overseas entirely. Therefore, a study of the generator protection field has in urgent need for a stable operation of the imported goods, and for preparation of next generation protection system. The paper describes the fault detection algorithm using WT(Wave!et Transform) of currents for a generator protection. The fault current signals after executing a terminal fault modeling collect using a MA TLAB package, and calculate the wavelet coefficients through the process of a multi -level decomposition (MLD). The proposed algorithm for a fault detection using the Daubechies WT (wavelet transform) was executed with a C language for the command line function and for the real time realization after analyzing MATLAB's graphical interface. The advanced technique had complemented the defects of a DFT by applying a Daubechies WT. and had improved faster a speed and more accurate of fault discriminant than a conventional DFR.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.265-267
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• 2003

The wavelet transform(WT) has been extensively applied in solving many problems in applied science and engineering following its introduction in early 1980's. The WT analyzes a signal in a changeable frequency range by employing a moving window whereby along time window is used to obtain low frequency information and short time window is used to obtain high frequency information. In this paper, after various fault types in 154 KV transmission system was simulated by using EMTP, and the RMS values by changing Mother wavelet was calculated by applying wavelet transform to the simulated voltage and current signal.

• Smart Structures and Systems
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• v.2 no.2
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• pp.127-140
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• 2006

In this study, a wavelet-based covariance-driven system identification technique is proposed for damage assessment of structures under ambient excitation. Assuming the ambient excitation to be a white-noise process, the covariance computation is shown to be able to separate the effect of random excitation from the response measurement. Wavelet transform (WT) is then used to convert the covariance response in the time domain to the WT magnitude plot in the time-scale plane. The wavelet coefficients along the curves where energy concentrated are extracted and used to estimate the modal properties of the structure. These modal property estimations lead to the calculation of the stiffness matrix when either the spectral density of the random loading or the mass matrix is given. The predicted stiffness matrix hence provides a direct assessment on the possible location and severity of damage which results in stiffness alteration. To demonstrate the proposed wavelet-based damage assessment technique, a numerical example on a 3 degree-of-freedom (DOF) system and an experimental study on a three-story building model, which are all under a broad-band excitation, are presented. Both numerical and experimental results illustrate that the proposed technique can provide an accurate assessment on the damage location. It is however noted that the assessment of damage severity is not as accurate, which might be due to the errors associated with the mode shape estimations as well as the assumption of proportional damping adopted in the formulation.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.501-510
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• 2000

Recently, advanced signal analysis which is called "time-frequency analysis" has been used widely in nondestructive evaluation applications. Wavelet transform(WT) and Wigner Distribution are the most advanced techniques for processing signals with time-varying spectra. Wavelet analysis method is an attractive technique for evaluation of material characterization nondestructively. Wavelet transform is applied to the time-frequency analysis of ultrasonic echo waveform obtained by an ultrasonic pulse-echo technique. In this study, the feasibility of noise suppression of ultrasonic flaw signal and frequency-dependent ultrasonic group velocity and attenuation coefficient using wavelet analysis of ultrasonic echo waveform have been verified experimentally. The Gabor function is adopted the analyzing wavelet. The wavelet analysis shows that the variations of ultrasonic group velocity and attenuation coefficient due to the change of material characterization can be evaluated at each frequency. Furthermore, to assure the enhancement of detectability and naw sizing performance, both computer simulated results and experimental measurements using wavelet signal processing are used to demonstrate the effectiveness of the noise suppression of ultrasonic flaw signal obtained from austenitic stainless steel weld including EDM notch.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.49-50
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• 2011

본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)를 함께 사용한 WSVD(Wavelet Singular Value Decomposition)를 이용하여 발전기 탈락 시의 전압 변동 특성을 분석하였다. WSVD 특성 분석을 위해 부산 지역의 345kV급 송전계통을 EMTP-RV로 모델링하였으며, 이 계통모델에서 발전기 탈락을 모의하였다. MATLAB을 통해 이 때 측정된 전압의 WSVD를 계산하여 발전기 탈락에 따른 특성을 분석하였다.