• Structural Engineering and Mechanics
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• v.48 no.5
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• pp.697-709
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• 2013

A simulation method called modified differential transform is studied to solve the free vibration problems of uniform Euler-Bernoulli beam. First of all, the modified differential transform method is derived. Secondly, the modified differential transformation is applied to uniform Euler-Bernoulli beam free-free vibration. And then a set of differential equations are established. Through algebraic operations on these equations, we can get any natural frequency and normalized mode shape. Thirdly, the FEM is applied to obtain the numerical solutions. Finally, mode experimental method (MEM) is conducted to obtain experimental data for analysis by signal processing with LMS Test.lab Vibration testing and analysis system. Experimental data and simulation results are illustrated to be in comparison with the analytical solutions. The results show that the modified differential transform method can achieve good results in predicting the solution of such problems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.3
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• pp.116-122
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• 2006

The underground transmission lines is continuously expanded in power systems. Therefore the fault of underground transmission lines are increased every year because of the complication of systems. However the studies dealing with fault location in the case of the underground transmission lines are rarely reported except for few papers using traveling wave method and calculating underground cable impedance. This paper describes the algorithm using fuzzy system and travelling wave method in the underground transmission line. Fuzzy inference is used for fault discrimination. To organize fuzzy algorithm, it is important to select target data reflecting various underground transmission line transient states. These data are made of voltage and average of RMS value on zero sequence current within one cycle after fault occurrence. Travelling wave based on wavelet transform is used for fault location. In this paper, a variety of underground transmission line transient states are simulated by EMTP/ATPDraw and Matlab. The input which is used to fault location algorithm are Detail 1(D1) coefficients of differential current. D1 coefficients are obtained by wavelet transform. As a result of applying the fuzzy inference and travelling wave based on wavelet transform, fault discrimination is correctly distinguished within 1/2 cycle after fault occurrence and fault location is comparatively correct.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.3
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• pp.292-300
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• 2014

The Laplace Transform solution is used as a mathematical model to analyse the thermal performance of the building constructed using different wall materials. The solution obtained from Laplace Transform is an analytical solution of an one dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures. The main purpose of the study is showing the detail of obtaining solution process of the Laplace Transform. This study is conducted using weather data from two different locations in Korea: Seoul, Busan for both winter and summer conditions. A comparison is made for the cases of an on-off controller and a proportional controller. The weather data are processed to yield hourly average monthly values. Energy consumption load is well calculated from the solution. The result shows that there is an effect of mass on the thermal performance of heavily constructed house in mild weather conditions such as Busan. Building using proportional control experience a higher comfort level in a comparison of building using on-off control.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1685-1688
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• 2003

The modem multimedia applications which are video Processor, video conference or video phone and so forth require real time processing. Because of a large amount of image data, those require high compression performance. In this paper, the proposed image processing encoder was designed by using wavelet transform encoding. The proposed filter block can process image data on tile high speed because of composing individual function blocks by parallel and compute both highpass and lowpass coefficient in the same clock cycle. When image data is decomposed into multiresolution, the proposed scheme needs external memory and controller to save intermediate results and it can operate within 33㎒.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1357-1360
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• 2009

In this study, the 0-th order diffraction could be efficiently removed with the obtained data for one hologram using the numerical reconstruction method. This method has a reduced data acquisition and processing time compared with the existing method wherein the data for two or more phase holograms are obtained for regeneration, and efficiently eliminates the 0-th order diffraction.

• 전기의세계
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• v.17 no.1
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• pp.11-20
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• 1968

A typical type-1 positioning servomechanism is theoretically analyzed as a multirate sampled-data system which contains two or more signals sampled at different rates by the Z-transform method. And also it is analyzed as a continuous system by using the Younsei 101 Electronic Analog Computer. Comparing the solution of the multirate sampled data system with that of the continuous system to a step input, it is concluded that the response time of the output of the multirate sampled-data system is reduced by a multirate controller, the ripple between samples is lessened and all the transients are diminished within one period.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1-10
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• 2020

This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

• ETRI Journal
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• v.36 no.1
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• pp.42-50
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• 2014

Orthogonal frequency division multiplexing (OFDM) is a modulation technique that allows the transmission of high data rates over wideband radio channels subject to frequency selective fading by dividing the data into several narrowband and flat fading channels. OFDM has high spectral efficiency and channel robustness. However, a major drawback of OFDM is that the peak-to-average power ratio (PAPR) of the transmitted signals is high, which causes nonlinear distortion in the received data and reduces the efficiency of the high power amplifier in the transmitter. The most straightforward method to solve this problem is to use a nonlinear mapping algorithm to transform the signal into a new signal that has a smaller PAPR. One of the latest nonlinear methods proposed to reduce the PAPR is the $L_2$-by-3 algorithm, which is based on the discrete sliding norm transform. In this paper, a new algorithm based on the $L_2$-by-3 method is proposed. The proposed method is very simple and has a low complexity analysis. Simulation results show that the proposed method performs better, has better power spectral density, and is less sensitive to the modulation type and number of subcarriers than $L_2$-by-3.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1454-1462
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• 2008

This paper is focused on the analysis of the noise and vibration measured near the wheelset of the high-speed trains using a time-varying frequency transform as a preliminary research of running monitoring. Due to the non-stationary characteristics, it is necessary to examine noise and vibration of the train with time-varying frequency transforms. In this paper, the short-time Fourier transform method is utilized - the stored data is localized by modulating with a window function, and Fourier transform is taken to each localized data. For the examination, the non-stationary noise and vibration of the high-speed train's wheelset are measured by using some microphones and accelerometers, and those signals are stored in a on-board data acquisition system. The non-stationary random signal analyses with the short-time Fourier transform are performed, and the result are classified as follows; auto-spectral density, cross-spectral density, frequency response, and coherence functions. From those functions, it is possible to observe the frequency characteristics of sleepers, switchers, tunnels, and steel bridges. Also, some distinct peaks, which are not dependent upon the train's speed, are identified from the results.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.37-43
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• 2005

Real time monitoring of exit burr formation is critical in manufacturing automation. In this paper, acoustic emission (AE) was used to detect the burr formation during drilling. By using wavelet transform (WT), AE data were compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net (ANN). In order to validate the in process AE monitoring system, both WT-based ANN and cutting condition (cutting speed, feed, drill diameter, etc.) based ANN outputs were compared with experimental data.