• Journal of Welding and Joining
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• v.21 no.6
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• pp.33-39
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• 2003

Wavelet transform analysis results show a spectrum energy distribution of CWT along scale factors distinguish the partial, full and over penetration in a electron beam welding by analyzing the curve of spectrum energy at small scale, middle and large scale range, respectively. Two types of signals collected by Ion collector and x-ray sensors and analyzed. The acquired signals from sensors are very complicated since these signals are very closely related the dynamics of keyhole which interact the very high density energy with materials during welding. The results show the wavelet transform is more effective to diagnosis than Fourier Transform, further for the general welding defects which are not a periodic based, but a transient, non-stationary and time-varying phenomena.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.55.4-56
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• 2015

The Hilbert-Huang Transform (HHT) is composed of the Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis (HSA). The EMD decomposes any time series data into a small number of components called the Intrinsic Mode Functions (IMFs), compared to the Discrete Fourier Transform which decomposes a data into a large number of harmonic functions. Each IMF has varying amplitude and frequency with respect to time, which can be obtained by HSA. The time resolution of the modes in HHT is the same as that of the given time series, while in the Wavelet Transform, Constant Q Transform and Short-Time Fourier Transform, there is a tradeoff between the resolutions in frequency and time. Based on the time-dependent amplitudes of IMFs, we develop an Event Trigger Generator and demonstrate its efficiency by applying it to gravitational-wave data.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.27-33
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• 2003

In closed-die forging process, blocker has been used to fill and distribute metal well in finisher die. Generally, the blocker shape was determined by an expert with many experiences. However, the manual blocker design process takes much time and efforts, so various automatic methods for the blocker design process have been suggested for the last three decades. The method with filtering in FFT (Fast Fourier Transform) for the blocker design provides general solution than other methods. But, due to the properties of FFT in time-frequency domain, this method has some drawbacks such as long calculation time, difficulty of local control and additional boundary process after filtering. In this study, DWT (Discrete Wavelet Transform), which is more flexible and is more wildly used than FFT, is applied to the blocker design. The method with filtering in DWT is very proper to design blocker in both 2-D and 3-D shapes. To verify the efficiency of this method, blockers of some models are designed and the results show that blocker design with DWT is effective fer the blocker designs

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.113-118
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• 2024

In this paper, we propose an optimal wavelet in a system for canceling background noise of acoustic signals. This system performed Discrete Wavelet Transform(DWT) instead of the existing Short Time Fourier Transform(STFT) and then improved noise cancellation performance through a deep learning process. DWT functions as a multi-resolution band-pass filter and obtains transformation parameters by time-shifting the parent wavelet at each level and using several wavelets whose sizes are scaled. Here, the noise cancellation performance of several wavelets was tested to select the most suitable mother wavelet for analyzing the speech. In this study, to verify the performance of the noise cancellation system for various wavelets, a simulation program using Tensorflow and Keras libraries was created and simulation experiments were performed for the four most commonly used wavelets. As a result of the experiment, the case of using Haar or Daubechies wavelets showed the best noise cancellation performance, and the mean square error(MSE) was significantly improved compared to the case of using other wavelets.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.498-503
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• 2009

As for Hadamard Transform, because the calculation time of this transform is slower than Discrete Cosine Transform (DCT) and Fast Fourier Transform (FFT), the effectiveness and the practicality are insufficient. Then, the computational complexity can be decreased by using the butterfly operation as well as FFT. We composed calculation time of FFT with that of Fast Complex Hadamard Transform by constructing the algorithm of Fast Complex Hadamard Transform. They are indirect conversions using program of complex number calculation, and immediate calculations. We compared calculation time of them with that of FFT. As a result, the reducing the calculation time of the Complex Hadamard Transform is achieved. As for the computational complexity and calculation time, the result that quadrinomial Fast Complex Hadamard Transform that don't use program of complex number calculation decrease more than FFT was obtained.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.9
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• pp.425-432
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• 2000

Wavelet transform is a new method fro electric power quality analysis. Several types of mother wavelets are compared using voltage sag data. Investigations on the use of some mother wavelets, namely Daubechies, Symlets, Coiflets, Biorthogonal, are carried out. On the basis of extensive investigations, optimal mother wavelets for the detection of voltage sag are chosen. The recommended mother wavelet is 'Daubechies 4(db4)' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. This paper presents a discrete wavelet transform approach for determining the beginning time and end time of voltage sags. The technique is based on utilising the maximum value of d1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. The procedure is fully described, and the results are compared with other methods for determining voltage sag duration, such as the RMS voltage and STFT(Short-Time Fourier Transform) methods. As a result, the voltage sag detection using wavelet transform appears to be a reliable method for detecting and measuring voltage sags in power quality disturbance analysis.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.130-138
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• 2003

This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.9
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• pp.937-946
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• 2002

In this paper, we present a stable solution of the transient electromagnetic scattering from the conducting objects. This method does not utilize the conventional marching-on in time (MOT) solution. Instead we solve the time domain integral equation by expressing the transient behavior of the induced current in terms of weighted Laguerre polynomials. By using this basis functions for the temporal variation, the time derivative in the integral equation can be handled analytically. Since these temporal basis functions converge to zero as time progresses, the transient response of the induced current does not have a late time oscillation. To show the validity of the proposed method, we solve a time domain electric feld integral equation and compare the results of MOT, Mie solution, and the inverse discrete Fourier transform (IDFT) of the solution obtained in the frequency domain.

• Korea-Australia Rheology Journal
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• v.18 no.2
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• pp.91-98
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• 2006

We compare FT (Fourier Transform) and SD (Stress Decomposition), the interpretation methods for LAOS (Large Amplitude Oscillatory Shear). Although the two methods are equivalent in mathematics. they are significantly different in numerical procedures. Precision of FT greatly depends on sampling rate and length of data because FT of experimental data is the discrete version of Fourier integral theorem. FT inevitably involves unnecessary frequencies which must not appear in LAOS. On the other hand, SD is free from the problems from which FT suffers, because SD involves only odd harmonics of primary frequency. SD is based on two axioms on shear stress: [1] shear stress is a sufficiently smooth function of strain and its time derivatives; [2] shear stress satisfies macroscopic time-reversal symmetry. In this paper, we compared numerical aspects of the two interpretation methods for LAOS.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.201-208
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• 2002

In this paper, we present a new formulation using time-domain electric field integral equation (TD-EFIE) to obtain transient scattering response from arbitrarily shaped three-dimensional conducting bodies. The time derivative of the magnetic vector potential is approximated with a central finite difference and the scalar potential is time averaged by dividing it into two terms. This approach with an implicit method using central difference results in accurate and more stable transient scattering responses from conducting objects. Detailed mathematical steps are included and several numerical results are presented and compared with the inverse discrete Fourier transform (IDFT) of the frequency-domain solution.