• 대한의용생체공학회:의공학회지
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• 제25권5호
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• pp.377-382
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• 2004

본 연구에서는 건강한 남성 13명을 대상으로 최대자발 근수축의44%, 55%, 66%에 해당하는 40, 50, 60kg의 부하를 주었으며 초당 48$^{\circ}$의 속도로 요추신전 운동을 반복함으로써 근피로를 유발 시켰으며, 피검자의 왼쪽 척추기립근에 표면전극을 부착하여 근전도 신호를 측정하였다. 웨이브렛을 이용하여 '시-주파수'영역에서 근전도 신호를 주파수대역별로 분리하여 근피로도를 측정하고 중앙주파수를 이용하여 얻은 결과를 비교하였다. 본 연구에서는 중앙주파수가 시간에 따라 더 맞은 주파수 영역으로 천이되며 단지 대표 주파수의 경향만 나타냄을 확인할 수 없었다. 그러나 웨이브렛을 이용한 근피로도 분석 방법은 중앙주파수와는 달리 근육의 피로함에 따라 고주파수 대역의 신호(375～438Hz)는 일정하거나 감소하고 저주파영역의 신호(0∼125Ha)는 증가하는 경향이 확인되어 웨이브렛 분석을 통해서 근피로를 정량화할 수 있음을 알 수 있었다. 본 연구를 통해 동 적운동 시 웨이브렛을 이용한 분석방법이 중앙주파수 보다 근피로도를 분석하는데 있어 더욱 유용함을 확인할 수 있었다.확인할 수 있었다.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.449-452
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• 2014

We present a multi-tap microwave photonic filter with high selectivity through applying time-to-frequency mapping and optical frequency comb shaping techniques. When arranged in the time-to-frequency mapping stage, by a Fourier transform, the deviation of the optical taps to the target profile is significantly reduced while maintaining the apodization profile, resulting in high sidelobe suppression in the filters. By applying a simple time-to-frequency mapping stage to the conventional optical frequency combs, we demonstrate a substantially enhanced (>10dB) sidelobe suppression, resulting in filter lineshapes exhibiting a significantly high (>40dB) main lobe to sidelobe suppression ratio. These results highlight the potential of the technique for implementation in various passband filters with high sidelobe suppression.

• 대한기계학회논문집A
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• 제33권12호
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• pp.1442-1448
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• 2009

Transient characteristics of a signal can be effectively exhibited in time-frequency domain. Hilbert-Huang Transform (HHT) is one of the time-frequency domain analysis methods. HHT is known for its several advantages over other signal analysis methods. The capability of analyzing non-stationary or nonlinear characteristics of a signal is the primary advantage of HHT. Moreover, it is known that HHT can provide fine resolution in high frequency region and handle large size data efficiently. In this study, the effectiveness of Hilbert-Huang transform is illustrated by employing structural systems undergoing impact. A simple discrete system and an axially oscillating cantilever beam undertaking periodic impulsive force are chosen to show the effectiveness of HHT.

• Smart Structures and Systems
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• 제1권3호
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• pp.257-266
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• 2005

In Lamb wave detection of damages in smart structures, the excitation pulse is usually designed as a narrow band burst wave for the convenience of analysis and recognition. However, the wideband excitation can excite more modes in plate/shell structure and thus provides extra information for changes of the structure. This paper presents a method that can extract information in wideband Lamb wave signals. By transforming the detected signals into various sub-frequency band, the measured signal can be converted to its equivalences of narrow band excitations, therefore, the information in different frequency bands can be acquired from a single test and in the same time the complicity of wideband signal can be simplified. Some test results are provided to verify this method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.265-267
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• 2003

The wavelet transform(WT) has been extensively applied in solving many problems in applied science and engineering following its introduction in early 1980's. The WT analyzes a signal in a changeable frequency range by employing a moving window whereby along time window is used to obtain low frequency information and short time window is used to obtain high frequency information. In this paper, after various fault types in 154 KV transmission system was simulated by using EMTP, and the RMS values by changing Mother wavelet was calculated by applying wavelet transform to the simulated voltage and current signal.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.517-524
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• 1998

This paper discusses the development of a reactive power controller using digital signal processing. Digital Signal Processing is the technique of using digital devices to Process continuous signals or data, often in real-time. And DSP algorithms are associated with a discrete time interval between input samples. When one designs a digital filter, one can use a Laplace transform to determine the continuous time frequency response. The corresponding discrete time transform is called Z transform and depends upon discrete samples of the input spaced equally in time. The objectives of this paper are to minimize real power losses and improve the power factor of a given system. Also, the implementation of a direct-form non recursive filter on the TMS320C31 has been described. The application of this microprocessor-based controller using DSP on test system reveals its numerous advantages. Performance and features of the controller for the reactive power control are analyzed.

• 한국철도학회논문집
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• 제14권6호
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• pp.495-500
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• 2011

철도차량의 승차감은 승객이 느끼는 감정이므로 물리적인 진동의 크기뿐만 아니라 인간의 감응도(느낌)도 고려하여야 하며, 이러한 진동에 대한 인간의 감응도를 나타낸 것이 주파수 보정곡선이다. 주파수 보정곡선은 라플라스 변환형태의 전달함수이기 때문에 이 전달함수를 직접 사용하여 시간 영역에서의 승차감의 평가가 불가능하다. 이를 해결하기 위해서 본 논문에서는 라플라스 변환형태의 전달함수를 시간 영역에서 사용할 수 있는 전달함수로 변환하는 방법을 제시하고 다양한 예제를 통해 이 방법에 대한 타당성을 입증하였다.

• 한국전기전자재료학회논문지
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• 제19권2호
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• pp.162-168
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• 2006

Recently, diagnosis techniques have been investigated to detect a Partial Discharge associated with a dielectric material defect in a high voltage electrical apparatus, However, the properties of detection technique of Partial Discharge aren't completely understood because the physical process of Partial Discharge. Therefore, this paper analyzes the process on surface discharge of polymer insulator using wavelet transform. Wavelet transform provides a direct quantitative measure of spectral content in the time~frequency domain. As it is important to develop a non-contact method for detecting the kaolin contamination degree, this research analyzes the electromagnetic waves emitted from Partial Discharge using wavelet transform. This result experimentally shows the process of Partial Discharge as a two-dimensional distribution in the time-frequency domain. Feature extraction parameter namely, maximum and average of wavelet coefficients values, wavelet coefficients value at the point of $95\%$ in a histogram and number of maximum wavelet coefficient have used electromagnetic wave signals as input signals in the preprocessing process of neural networks in order to identify kaolin contamination rates. As result, root sum square error was produced by the test with a learning of neural networks obtained 0.00828.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 추계학술대회 논문집 Vol.17
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• pp.662-665
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• 2004

Recently, diagnosis techniques have been investigated to detect a partial discharge associated with a dielectric material defect in a high-voltage electrical apparatus However, the properties of detection technique of PD aren't completely understood because the physical process of PD. Therefore, this paper analyzes the process on Surface Discharge of Polymer Insulator using Wavelet transform. Wavelet transform provides a direct quantitative measure of spectral content in the time-frequency domain. As it is important to develop a non-contact method for detecting the Contamination Degree, this paper analyzes the electromagnetic waves emitted from PD using Wavelet transform. This paper experimentally shows the process of PD as a two-dimensional distribution in the time-frequency domain. This method is shown to be useful for detecting prediction of contamination degree.