• 수산해양기술연구
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• 제50권4호
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• pp.435-446
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• 2014

Tidal turbulence was examined using three-dimensional tidal velocity data observed at a trench offshore of Tongyoung, Korea. The kinetic energy and intensity, including the variation period of the flow velocity and direction, were used to investigate the relationships between tidal turbulence and fishing gear dynamics, including the effects of swimming fish during fishing operations. As the resultant velocity increased from 0.2 to 0.9 m/s, the kinetic energy also significantly increased, while the turbulence intensity decreased from 50 to 10%. Tidal flow in strong flow fields displayed shorter periods of between 4 and 10 s, as determined by fast Fourier transform, the global wavelet method, and peak event analysis, and the periods were compared with the period of response to swimming fish and to oscillation of fishing gear. As mean velocity increased, velocity amplitude also increased from 0.1 to 0.6 m/s, and its directional amplitude changed markedly from 20 and $90^{\circ}$. Our study suggests that tidal turbulence can influence fish behavior or fishing gear geometry during fishing operations, although our analysis considered only a limited area. In future work, observations should be carried out over a more extensive depth and area.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.398-401
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• 1997

The EMG signal of spinal cord injured patient is very feeble because that the information from central nervous system is not sufficiently transmitted to molter neuron or muscle fiber. Therefore the observer can not observe contraction and relaxation movement of muscle from the raw EMG signal. In this paper, we propose the muscle contraction and relaxation pattern analysis method of spinal cord injured patient whose EMG signal is composed of the sum of motor unit action potential train with additive white Gaussian noise and impulsive noise. From the EMG model, we denoise impulsive noise using median filter which is a kind of nonlinear filter and the output of median filter is transformed to wavelet transform domain for denoising additive white Gaussian noise using threshold level removal technique. As a result, we can obtain the clear contraction and relaxation pattern.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2001년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2001
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• pp.36-43
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• 2001

In Korea, we are absolutely short of earthquake data in good quality from moderate and large earthquakes, which are needed fur the study of strong ground motion characteristics. This means that the best use of the available data is needed far the time being. In this respect, several methods are suggested in this paper, which can be applied in the process of data selection and analysis. First, it is shown that the calibration status of seismic stations can be easily checked by comparing the spectra from accelerometer and velocity sensor both of which are located at the same location. Secondly, it is recommended that S/N ratio in the frequency domain should be checked before discarding the data by only look of the data in time domain. Thirdly, the saturated earthquake data caused by ground motion level exceeding the detection limit of a seismograph are considered to see if such data can be used for spectrum analysis by performing numerical simulation. The result reveals that the saturated data can still be used within the dominant frequency range according to the levels of saturation. Finally, a technique to minimize the window effect that distorts the low frequency spectrum is suggested. This technique involves detrending in displacement domain once the displacement data are obtained by integration of low frequency components of the original data in time domain. Especially, the low frequency component can be separated by using discrete wavelet transform among many alternatives. All of these methods mentioned above may increase the available earthquake data and frequency range.

• Steel and Composite Structures
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• 제36권5호
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• pp.521-531
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• 2020

The behavior variation of concrete dam is investigated, based on a new method for analyzing the data model of concrete dam in service process for the limitation of wavelet transform for solving concrete dam service process model. The study takes into account the time and position of behavior change during the process of concrete dam service. There is no dependence on the effect quantity for overcoming the shortcomings of the traditional identification method. The panel data model is firstly proposed for analyzing the behavior change of composite concrete dam. The change-point theory is used to identify whether the behavior of concrete dams changes during service. The phase space reconstruction technique is used to reconstruct the phase plane of the trend effect component. The time dimension method is used to solve the construction of multi-transformation model of composite panel data. An existing 76.3-m-high dam is used to investigate some key issues on the behavior change. Emphasis is placed on conversion time and location for three time periods consistent with the practical analysis report for evaluating the validity of the analysis method of the behavior variation of concrete dams presented in this paper.

• Journal of Astronomy and Space Sciences
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• 제35권3호
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• pp.151-161
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• 2018

Understanding solar influences on extreme weather is important. Insight into the causes of extreme weather events, including the solar-terrestrial connection, would allow better preparation for these events and help minimize the damage caused by disasters that threaten the human population. In this study, we examined category three, four, and five tropical cyclones that occurred in the western North Pacific Ocean from 1977 to 2016. We compared long-term trends in the positions of tropical cyclone occurrence and development with variations of the observed sunspot area, the solar North-South asymmetry, and the southern oscillation index (SOI). We found that tropical cyclones formed, had their maximum intensity, and terminated more northward in latitude and more westward in longitude over the period analyzed; they also became stronger during that period. It was found that tropical cyclones cannot be correlated or anti-correlated with the solar cycle. No evidence showing that properties (including positions of occurrence/development and other characteristics) of tropical cyclones are modulated by solar activity was found, at least not in terms of a spectral analysis using the wavelet transform method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.

• 한국음향학회지
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• 제38권3호
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• pp.363-369
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• 2019

복잡한 회전 기계의 소음 상태 진단을 위한 다양한 연구가 수행되고 있다. 본 연구에서는 진동신호를 이용하여 블로워 모터의 효율적이고 객관적인 소음 상태진단을 위한 지수를 개발하였다. 블로워 모터의 이상 시 가장 흔히 나타나는 소음으로 틱/클릭 소음과 톤 소음이 있다. 발생 원인과 소음 특성에 따라 틱/클릭 소음의 상태 진단에는 시간-주파수 분석법을 그리고 톤 소음 상태 진단에는 주파수 영역에서의 평활화 기법을 이용하였다. 개발한 지수를 이용하여 블로워 모터의 소음 상태 진단을 수행하고 이를 전문가에 의한 진단 결과와 비교하였다. 그 결과 약 95 %의 일치율을 보였다.

• 제어로봇시스템학회논문지
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• 제8권8호
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• pp.691-697
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• 2002

Myocardial ischemia is a disorder of cardiac function caused by insuficient blood flow to the muscle tissue of the heart. We can diagnose myocardial ischemia by observing the change of ST-segment, but this change is temporary. Our primary purpose is to detect the temporary change of the 57-segment automatically In the signal processing, the wavelet transform decomposes the ECG(electrocardiogram) signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex more easily. Amplitude comparison method is adopted to detect QRS complex. Reducing the effect of noise to the minimum, we grouped ECG by 5 data and compared the amplitude of maximum value. To recognize the ECG .signal pattern, we adopted the polynomial approximation partially and statistical method. The polynomial approximation makes possible to compare some ECG signal with different frequency and sampling period. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. After removing the distorted ECG by calculating the difference between the orignal ECG and the approximated ECG for polynomial, we compared the approximated ECG pattern with the database, and we detected and classified abnormality of ECG.

• 비파괴검사학회지
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• 제23권3호
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• pp.205-211
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• 2003

구조물의 안전성평가와 관련하여 비파괴평가 방법 중에서 음향방출 (acoustic emission, AE)기법에 의한 비파괴적 결함 발생 검출 기법은 다른 기법에 비해 비교적 새로운 평가기술로서 구조물의 이상 유무를 조기에 진단하고 주기적으로 감시할 수 있는 온-라인 모니터링에 적합하다. 그러나 한편, 국내에서는 아직까지 이에 대한 체계적인 연구가 미비한 실정이며, 대부분 값비싼 외국 시스템을 도입하여 사용하고 있는 실정이다 뿐 만 아니라 기존의 음향방출 시스템은 장치의 특성상 시스템이 매우 복잡하고 가격이 고가인 관계로 다양한 산업분야에서 실제 현장에 적용하기가 쉽지 않다. 따라서 본 연구에서는 기존의 음향방출 시스템이 가지고 있던 불필요한 낭비적인 요소들을 제거하고 실제 산업현장에 부합하는 위치표정 시스템을 개발하고자 하였다. 한편, 기존의 AE 시스템들은 위치표정을 위한 신호분석이 난해할 뿐만 아니라 박판 구조물의 경우는 위치표정이 매우 어렵다. 본 연구에서는 시간-주파수 해석에 널리 사용되고 있는 웨이블릿 기법을 이용하여 보다 정확한 위치표정을 진단하는 기법을 수행하였다.

• 한국수자원학회논문집
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• 제54권spc1호
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• pp.1083-1093
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• 2021

물 사용량 예측은 최적의 용수 공급 운영 방안을 수립하고 전력 소비량 절감을 위하여 꼭 필요한 과정이라고 할 수 있다. 그러나 수용가 단위의 물 사용량은 용도, 사용자의 패턴, 날씨 등의 다양한 요인으로 인해 변화하는 비선형적 특성을 지니고 있다. 따라서 본 연구에서는 비선형적인 수용가 단위의 물 사용량을 예측하기 위하여 다양한 기법들을 연계한 KWD 프레임워크를 제안하고자 하였다. 즉, 먼저 개별 수용가 마다 용도에 따른 유사한 패턴을 파악하기 위해 K-means (K) 군집분석을 수행하였고, 잡음성분을 제거함으로써 핵심적인 주기패턴을 파악하기 위해 Wavelet (W) 방법을 적용하였다. 또한 비선형적 특성을 학습시키기 위해 Deep learning (D) 알고리즘을 적용하였다. 그리고 기존의 선형 시계열 모형인 ARMA 모형과 비교하여 KWD 프레임워크의 성능을 분석하였다. 그 결과 제안된 모형의 상관성은 92%, ARMA 모형은 약 39%로 KWD 프레임워크가 2배 이상의 성능을 가지는 것으로 분석되었다. 따라서 본 연구에서 제안한 방법을 활용할 경우 정확한 물 사용량 예측이 가능해질 것이며, 상황에 따른 최적의 공급 방안을 수립할 수 있을 것이다.