• Title/Summary/Keyword: Time-Frequency Signal Analysis

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

  • Lee, Seung-Kyu;Yoo, Hong-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.12
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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.

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

  • Lee, Hyun-Dong;Ju, Jae-Hyun;Kim, Ki-Chai;Park, Won-Zoo;Lee, Kwang-Sik;Lee, Dong-In
    • Proceedings of the KIEE Conference
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    • 2001.07c
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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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Waveform Analysis Using Wavelet Transform (웨이블렛 변환에 의한 파형 해석)

  • Kim, Hee Joon
    • Economic and Environmental Geology
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    • v.28 no.5
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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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A Parameter Estimation of Time Signal and Analysis of Low Frequency Oscillation in Power Systems (시간영역에서 파라미터 추정과 전력계통의 저주파진동 해석)

  • Shim Kwan-Shik;Nam Hae-Kon;Kim Yong-Gu
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.3
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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.

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

  • 이기영;박두환;정종원;김기현;이준탁
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2002.05a
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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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A Study on the Measurement of Back Muscle Fatigue During Dynamic Contraction Using Multiple Parameters (다중 파라메터를 이용한 동적 수축시 허리 근육 피로 측정에 관한 연구)

  • Yoon, Jung-Gun;Jung, Chul-Ki;Yeo, Song-Phil;Kim, Sung-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.7
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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.

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

  • 이현동;이광식
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.15 no.4
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    • pp.62-68
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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 electrical 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, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

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

  • Kim, Tae-Hyung;Yoon, Dong-Han
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.1
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    • pp.8-15
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    • 2005
  • The analysis of Rader signal that have non-linearity variable phase is signal that contact easily in several fields such as radar, telecommunication, seismic, sonar and biomedical applications. In generally, Non-stationary signal means that spectral characteristics are varying with time and instantaneous frequency is only one frequency or narrow range of frequencies varying as a function of time. Therefore, Instantaneous frequency is vary important variable that understanding physical characteristic of signal. This paper was describes continuous wavelet transform to determine instantaneous frequency at non-staionary signal and compare to existing method. When white noise or various frequency is overlapped each other in sign, existing method was can not decide corrected instantaneous frequency, but when used continuous wavelet transform, very well decide correctly frequency regardless of component of signal.

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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    • v.2C no.5
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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.

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

  • 박재오;이정재
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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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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