• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1677-1685
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• 2014

Major problem in the high voltage power transmission line is the flashover due to polluted ceramic insulators which leads to failure of equipments, catastrophic fires and power outages. This paper deals with the development of a better diagnostic tool to predict the flashover and pollution severity of power transmission line insulators based on the wavelet transform and fuzzy c-means clustering approach. In this work, laboratory experiments were carried out on power transmission line porcelain insulators under AC voltages at different pollution conditions and corresponding leakage current patterns were measured. Discrete wavelet transform technique is employed to extract important features of leakage current signals. Variation of leakage current magnitude and distortion ratio at different pollution levels were analyzed. Fuzzy c-means algorithm is used to cluster the extracted features of the leakage current data. Test results clearly show that the flashover and pollution severity of power transmission line insulators can be effectively realized through fuzzy clustering technique and it will be useful to carry out preventive maintenance work.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.33-40
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• 2014

In this paper we propose new image coding using wavelet transform. The new method constructs hierarchical bit plane and progressively transports each bit plane. The Proposed algorithm not only supports multi-resolution, dividing original image into special band and various resolution using Antonini's wavelet basis function but also reduces blocking effects that come into JPEG. In encoding time this algorithm considers each band characters and priority of transport order, and applies to fast search of image.

• Smart Structures and Systems
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• v.20 no.3
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• pp.263-272
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• 2017

This paper presents the time response of a mixed vibration system with the viscous damping and the hysteretic damping. There are two ways to derive the time response of such a vibration system. One is an analytical method, using the contour integral of complex functions to compute the inverse Fourier transforms. The other is an approximate method in which the analytic functions derived by Hilbert transform are expressed in the state space representation, and only the effective eigenvalues are used to efficiently compute the transient response. The unit impulse responses of the two methods are compared and the change in the damping properties which depend on the viscous and hysteretic damping values is investigated. The results showed that the damping properties of a mixed damping vibration system do not present themselves as a linear combination of damping properties.

• Proceedings of the KIPE Conference
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• 2003.07a
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• pp.177-181
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• 2003

Need of power stability, reliability is increased, as using of sensitive: nonlinear load are increasing. Therefore, Power Quality Problems become the center of public interest. Many kinds of algorithms have been studied for monitoring of Power Quality Problems. Monitoring algorithms of using RMS, FT and the others are easy to applicate to system. But, it is not enough to monitor all of Foyer. Quality problems. Wavelet Transform is more proper to applicate. so, This paper presents measurement system using discrete wavelet transform.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1460-1466
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• 2011

This paper proposes the algorithm for discriminating faults from the variation due to the operation of non-linear components to prevent the mal-operation of protection relay in the distribution system. An IEEE 13 node test feeder is modeled to analyze the characteristics of the fault and each variation using EMTP-RV. Simulations with various operating conditions of transformers, non-linear loads, and unbalanced loads are performed using the test feeder model. Based on simulation results, the wavelet transform is adopted to analyze the current waveforms from the faults and variations to find out the differences between them and the algorithm for discriminating faults from the variation is proposed. The proposed algorithm is verified by using the current waveforms simulated in the KEPCO's distiribution system and IEEE 13 node test feeder.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.113-123
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• 2014

Electrophysiological recordings are considered a reliable method of assessing a person's alertness. Sleep medicine is asked to offer objective methods to measure daytime alertness, tiredness and sleepiness. As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in recognition of alertness level. In this paper, EEG signals have been analyzed using wavelet transform as well as discrete wavelet transform and classification using statistical classifiers such as euclidean and mahalanobis distance classifiers and a promising method SVM (Support Vector Machine). As a result of simulation, the average values of accuracies for the Linear Discriminant Analysis (LDA)-Quadratic, k-Nearest Neighbors (k-NN)-Euclidean, and Linear SVM were 48%, 34.2%, and 86%, respectively. The experimental results show that SVM classification method offer the better performance for reliable classification of the EEG signal in comparison with the other classification methods.

• Journal of the Korean Mathematical Society
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• v.55 no.1
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• pp.147-160
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• 2018

In this article, we establish translation theorems for the analytic Fourier-Feynman transform of functionals in non-stationary Gaussian processes on Wiener space. We then proceed to show that these general translation theorems can be applied to two well-known classes of functionals; namely, the Banach algebra S introduced by Cameron and Storvick, and the space ${\mathcal{B}}^{(P)}_{\mathcal{A}}$ consisting of functionals of the form $F(x)=f({\langle}{\alpha}_1,x{\rangle},{\ldots},{\langle}{\alpha}_n,x{\rangle})$, where ${\langle}{\alpha},x{\rangle}$ denotes the Paley-Wiener-Zygmund stochastic integral ${\int_{0}^{T}}{\alpha}(t)dx(t)$.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.515-521
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• 2010

In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_n\;=\;\frac{1}{N}Y_nY_n^TT_n$ where $Y_n\;=\;[Y_{ij}]_{n\;{\times}\;N}$ is with independent, identically distributed entries and $T_n$ is an $n\;{\times}\;n$ symmetric non-negative definite random matrix independent of the $Y_{ij}$'s. In the present paper, using the inversion formula of the Stieltjes transform, we will find that the limiting distribution of $B_n$ has a continuous density function away from zero.

• Journal of the Korean Mathematical Society
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• v.50 no.1
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• pp.111-125
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• 2013

In this paper, we consider a continuous time risk model involving two types of dependent claims, namely main claims and by-claims. The by-claim is induced by the main claim and the occurrence of by-claim may be delayed depending on associated main claim amount. Using Rouch$\acute{e}$'s theorem, we first derive the closed-form solution for the Laplace transform of the survival probability in the dependent risk model from an integro-differential equations system. Then, using the Laplace transform, we derive a defective renewal equation satisfied by the survival probability. For the exponential claim sizes, we present the explicit formula for the survival probability. We also illustrate the influence of the model parameters in the dependent risk model on the survival probability by numerical examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1139-1145
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• 2002

Wavelet transformed data can filter signal with each frequency band, because it includes detail information about original signal. Therefore, in this paper, important two noises were removed by wavelet. About AWGN environment UDWT(undecimated discrete wavelet transform), applying hard-threshold, was used and about impulse noise environment, it can be possible to recognize edge of original signal as well as superior denoising effect by using two methods, denoising by threshold and slope of signal by wavelet. SNR was used as a judgemental criterion of a denoising effect and Blocks and DTMF(dual tone multi frequency) were used as a test signal.