• 제목/요약/키워드: Time-Frequency Signal Analysis

검색결과 717건 처리시간 0.026초

힐버트 황 변환을 이용한 충격을 받는 시스템의 과도특성 분석 (Transient Characteristics Analysis of Structural Systems Undergoing Impact Employing Hilbert-Huang Transformation)

  • 이승규;유홍희
    • 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.

웨이브렛 변환을 이용한 부분방전신호의 잡음제거 특성 (Noise elimination of PD signal using Wavelet Transform)

  • 이현동;주재현;김기채;박원주;이광식;이동인
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 C
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    • pp.1679-1681
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    • 2001
  • In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electromagnetic wave detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, inclued noise signal in detected PD signal is well elimiated. we can propose the true shape of PD signal.

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웨이블렛 변환에 의한 파형 해석 (Waveform Analysis Using Wavelet Transform)

  • 김희준
    • 자원환경지질
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    • 제28권5호
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    • pp.527-533
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    • 1995
  • A disadvantage of Fourier analysis is that frequency information can only be extracted for the complete duration of a signal f(t). Since the Fourier transform integral extends over all time, from $-{\infty}$ to $+{\infty}$), the information it provides arises from an average over the whole length of the signal. If there is a local oscillation representing a particular feature, this will contribute to the calculated Fourier transform $F({\omega})$, but its location on the time axis will be lost There is no way of knowing whether the value of $F({\omega})$ at a particular ${\omega}$ derives from frequencies present throughout the life of f(t) or during just one or a few selected periods. This disadvantage is overcome in wavelet analysis which provides an alternative way of breaking a signal down into its constituent parts. The main advantage of the wavelet transform over the conventional Fourier transform is that it can not only provide the combined temporal and spectral features of the signal, but can also localize the target information in the time-frequency domain simultaneously. The wavelet transform distinguishes itself from Short Time Fourier Transform for time-frequency analysis in that it has a zoom-in and zoom-out capability.

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시간영역에서 파라미터 추정과 전력계통의 저주파진동 해석 (A Parameter Estimation of Time Signal and Analysis of Low Frequency Oscillation in Power Systems)

  • 심관식;남해곤;김용구
    • 대한전기학회논문지:전력기술부문A
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    • 제54권3호
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    • pp.122-132
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    • 2005
  • This paper presents a novel approach based on Prony method to analysis of small signal stability in power system. Prony method is a valuable tool in identifying transfer function and estimating the modal parameter of power system oscillation from measured or computed discrete time signal. This paper define the relative residue of time signal and propose the condition to select low frequency oscillation in each generator. This paper describes the application results of proposed algorithm with respect to KEPCO systems. Simulation results show that the proposed algorithm can be used as another tools of power systems analysis.

Wavelet 변환을 이용한 과도신호의 시간-주파수 해석에 관한 연구 (A Study on the Time-Frequency Analysis of Transient Signal using Wavelet Transformation)

  • 이기영;박두환;정종원;김기현;이준탁
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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    • pp.219-223
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    • 2002
  • Voltage and current signals during impulse tests on transformer are treated as non-stationary signals. A new method incorporating signal-processing method such as Wavelets and courier transform is proposed for failure identification. It is now possible to distinguish failure during impulse tests. The method is experimentally validated on a transformer winding. The wavelet transforms enables the detection of the time of occurrence of switching or failure events. After establishing the time of occurrence, the original waveform is split into two or more sections. The wavelet transform has ability to analysis the failure signal on time domain as well as frequency domain. Therefore, the wavelet transform is superior than courier transform to analysis the failure signal. In this paper, the fact was proved by real data which was achieved.

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다중 파라메터를 이용한 동적 수축시 허리 근육 피로 측정에 관한 연구 (A Study on the Measurement of Back Muscle Fatigue During Dynamic Contraction Using Multiple Parameters)

  • 윤중근;정철기;여송필;김성환
    • 대한전기학회논문지:시스템및제어부문D
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    • 제55권7호
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    • pp.344-351
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    • 2006
  • The fatigue of back muscle in the repetitive lifting motion was studied using multiple parameters(FFT_MDF, RMS, 2C, NT) in this study. Recent developments in the time-frequency analysis procedures to compute the IMDF(instantaneous median frequency) were utilized to overcome the nonstationarity of EMG signal using Cohen-Posch distribution. But the above method has a lot of computation time because of its complexity. So, in this study, FFT_MDF(median frequency estimation based on FFT) algorithm was used for median frequency estimation of back muscle EMG signal during muscle work in uniform velocity portion of lumbar movement. The analysis period of EMG signal was determined by using the run test and lumbar movement angle in dynamic task, such as lifting. Results showed that FFT_MDF algorithm is well suited for the estimation of back muscle fatigue from the view point of computation time. The negative slope of a regression line fitted to the median frequency values of back muscle EMG signal was taken as an indication of muscle fatigue. The slope of muscle fatigueness with FFT_MDF method shows the similarity of 77.8% comparing with CP_MDF(median frequency estimation based on Cohen Posch distribution) method.

웨이브렛 변환의 노이즈 제거기법에 의한 부분방전신호 특성 (Characteristics of Partial Discharges Signals Utilizing Method of Wavelet Transform Denoising Process)

  • 이현동;이광식
    • 조명전기설비학회논문지
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    • 제15권4호
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    • pp.62-68
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    • 2001
  • 본 논문은 전기적 검출법에 의해 측정된 부분방전 신호에 대하여 웨이브렛 변환을 적용하여 각기 다른 주파수 성분을 동시에 추출하고 이들의 시간정보를 얻음으로써 시간과 주파수 영역에서 동시에 해석할 수 있도록 하였다. 그리고, 웨이브렛 변환의 노이즈 제거기법을 적용하여 부분방전 측정시에 포함되어 있는 노이즈를 제거하여 잡음제거 효과를 나타내었다.

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연속 웨이브렛 Ridge를 이용한 순간주파수 결정 (Determination of Instantaneous Frequency By Continuous Wavelets Ridge)

  • 김태형;윤동한
    • 한국정보통신학회논문지
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    • 제9권1호
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    • pp.8-15
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    • 2005
  • 비선형적인 위상 변화를 지닌 비정상(non-stationary)신호는 레이더, 통신, 지질탐사, 음향, 생체공학 응용등 여러 분야에서 쉽게 접하는 신호이다. 비정상 신호는 일반적으로 시간의 변환에 따라 신호의 스페트럼 특성이 변화하는 신호를 의미하며, 순간 주파수는 신호의 특정시간에 해당하는 신호성분의 주파수를 의미한다. 따라서 열거한 레이더, 음향, 생ㅊ신호등에 있어서 순간 주파수는 신호의 물리적 특성을 파악하기 위한 중요한 변수이다. 이 논문에서는 연속 웨이브렛 변환을 이용한 비정상 신호의 순간 주파수를 결정에 대하여 연구하였고, 기존의 방법과 비교하였다. 신호에 잡음이나 여러 가지의 주파수가 중첩되어 있는 경우, 기존에 방법들로서는 정확한 순간 주파수를 결정할 수 없는 반면, 웨이브렛 변환을 이용한 경우, 신호의 성분에 관계없이 상당히 정확한 순간주파수를 결정할 수 있음에 대하여 설명하였다.

Super-High-Speed Lightwave Demodulation using the Nonlinearities of an Avalanche Photodiode

  • Park, Young-Kyu
    • KIEE International Transactions on Electrophysics and Applications
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    • 제2C권5호
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    • pp.273-278
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    • 2002
  • Even though the modulating signal frequency of the light is too high to detect directly, the signal can be extracted by frequency conversion at the same time as the detection by means of the non-linearity of the APD. An analysis is presented for super-high-speed optical demodulation by an APD with electronic mixing. A normalized gain is defined to evaluate the performance of the frequency conversion demodulation. The nonlinear effect of the internal capacitance was included in the small signal circuit analysis. We showed theoretically and experimentally that the normalized gain is dependent on the down converted difference frequency component. In the experiment, the down converted different frequency outputs became larger than the directly detected original signal for the applied local signal of 20㏈m.

Wavelet 변환기저 Scalogram을 이용한 주파수 도약신호 분석 (Analysis of Frequency Hopping Signals using Wavelet Transform-Based Scalogram)

  • 박재오;이정재
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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    • pp.45-48
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    • 2000
  • In this paper algorithms of frequency hopping sequences generation such as Lempel-Greenberger, optimum Lempel-Greenberger and Kumar sequences for spread spectrum communications are described. Using the scalogram based on wavelet transform, time-frequency characteristics of frequency hopped signals corresponding to the considered hopping sequences are analyzed.

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