• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.67-76
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• 2013

We present an innovative real-time laser welding monitoring technique employing the correlation analysis of the plasma plume optical emission generated during the process. The plasma optical radiation emitted during Nd:YAG laser welding of S45C steel samples has detected with a Photodiode and analyzed under different process conditions. The discrete DC voltage difference, filter methods and wavelet transform has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. Considering that wavelet analysis can decompose the optical signals, extract the characteristic information of the signals and define the defects location accurately, it can be used to implement process-control of laser welding.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1880-1884
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• 2000

The discrete wavelet transform is utilized as preprocessing of Neural Network(NN) to identify aging state of internal partial discharge in transformer. The discrete traveler transform is used to produce wavelet coefficients which are used for Classification. The statistical parameters (maximum of wavelet coefficients, average value, dispersion, skewness, kurtosis) using the wavelet coefficients are input into an back-propagation neural network. The neurons whose weights have obtained through Result of Cross-Validation. The Neural Network learning stops either when the error rate achieves an appropriate minimum or when the learning time overcomes a constant value. The networks, after training, can decide if the test signal is Early Aging State or Last Aging State or normal state.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1485-1490
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• 2008

This paper proposes a new Fourier transform-based phasor estimation method to eliminate the adverse influence of the exponentially decaying dc offsets when Discrete Fourier Transform (DFT) is used to calculate the phasor of the fundamental frequency component in a relaying signal. By subtracting the result of odd-sample-set DFT from the result of even-sample-set DFT, the information of dc offsets can be obtained. Two dc offsets in a relaying signal are treated as one dc offset which is piecewise approximated in one cycle data window. The effect of the dc offsets can be eliminated by the approximated dc offset. The performance of the proposed algorithm is evaluated by using computer-simulated signals and EMTP-generated signals. The algorithm is also tested on a hardware board with TMS320C32 microprocessor. The evaluation results indicate that the proposed algorithm has the stable and accurate eliminating performance even if the input signal contains two decaying dc components having different time constants.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.907-910
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• 2001

In this paper, we address a new time delay estimation method using third-order statistics and subband adaptive filtering to improve the accuracy of target detection for acoustic backscattered signals in a noise interference environment. Each reference and primary signals are decorrelated using the multiresolution analysis framework through a M-band discrete wavelet transform(M-DWT). Then noise effect can be reduced. Here, time delays are estimated iteratively in each subband using two different adaptation mechanisms that minimize the mean squared error (MSE) between the references and primary signal. More specifically, third-order cumulants and projection cross-correlation(PCC) criterion are utilized to achieve an effective SNR improvement for the time delay estimation.

• Journal of the Korean Society of Safety
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• v.6 no.2
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• pp.21-30
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• 1991

In this paper, we study effect of waveness at the optical surface roughness measurement. In generally, waveness components cause errors in calculation of the roughness value of metal surface. We study about surface roughness signals In the frequency domain for separate two signal component of real roughness and waveness by digital signal processing methods. Thereafter, determine low and high Component of frequency spectrum. By this separating frequency value we design liner low and high pass filter which cutoff frequency is 1 Hz. After this process, converted each filtered spectrum by inverse discrete fourier transformation to time domain waveness and real roughness signals We calculate surface roughness value from filtered roughness signals. For evaluate this method, we use five specimens roughness signal which obtained from optical surface roughness measuring system in 3mm/s moving speed with 0.1 mm laser beam spot size As a result, we obtain more linerized roughness value than that of unfiltered roughness signals.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.991-993
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• 1999

This study proposed a new algorithm to assess autonomic function activity using Time-Frequency Representation(TFR). TFR is a way of describing the time-valiant energy of a signal. A discrete Wigner representation that is capable of filtering out any cross terms occuring in the Wigner-Ville Distribution(WVD) is used for time-variant energy distribution of heart rate variability(HRV) signals. And the marginal condition are evaluated to estimate power spectrum of HRV signals. The proposed algorithm showed that estimated power spectrum of HRV signals well describe the autonomic nerve system function and also showed the dynamics of autonomic nervous system response.

• Research in Mathematical Education
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• v.11 no.2
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• pp.143-151
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• 2007

Nowadays there are practically no mathematical courses in which Computer Algebra Systems (CAS) programs, such as MATHEMATlCA, Maple, and TI-89/92, are not used to some extent. However, generally the usage of these programs is reduced to illustration of computing processes: calculation of integrals, differentiation, solution of various equations, etc. This is obtained by usage of standard command of type: Solve [...] in MATHEMATICA. At the same time the main difficulties arise at teaching nonconventional mathematical courses such as coding theory, discrete mathematics, cryptography, Scientific computing, which are gaining the increasing popularity now. Now it is impossible to imagine a modern engineer not having basic knowledge in discrete mathematics, Cryptography, coding theory. Digital processing of signals (digital sound, digital TV) has been introduced in our lives.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.54-61
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• 2001

A software package to classify acoustic emission (AE) signals using the wavelet transform and the neural network was developed Both of the continuous and the discrete wavelet transforms are considered, and the error back-propagation neural network is adopted as m artificial neural network algorithm. The signals acquired during the 3-point bending test of specimens which have artificial defects on weld zone are used for the classification of the defects. Features are extracted from the time-frequency plane which is the result of the wavelet transform of signals, and the neural network classifier is tamed using the extracted features to classify the signals. It has been shown that the developed software package is useful to classify AE signals. The difference between the classification results by the continuous and the discrete wavelet transforms is also discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.5
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• pp.258-265
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• 1985

A design method for a single-input single-output discrete time model reference adaptive system is described in this paper. By using the state-variable filters into inputs and outputs in reference model and unknown system, a simple adaptive structure which use all accessible signals can be constructed. Some papers for the adaptive shstem is which thw relative degree of unknown system have one or two have been reported, but the resulting adaptive system are intricate in structures and the design theories for the model reference adaptive system are not generalized. In this paper, for having two or more relative degrees, it has been verified that an adaptive scheme can be obtained by introducing a simple linear filter.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.166-168
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• 2002

This paper presents a new numerical algorithm suitable for defining recloser reclaims time and blocking automatic reclosing during permanent faults on overhead lines. It is based on terminal voltage input data processing. The decision if it is safe or not to reclose is determined from the voltage signal of faulted and tripped line phase using Total Harmonic Distortion factor calculated by Discrete Fourier Transform. The algorithm was successfully tested using signals recorded on the real power system. The tests demonstrate the ability of presented algorithm to determine the secondary arc extinction time and to block unsuccessful automatic reclosing of HV lines with permanent fault.