• Title/Summary/Keyword: Signal Analysis

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A Novel Phase Extraction for the Detection of Time Parameters in Signal

  • Lee Eun-bang
    • Journal of Navigation and Port Research
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    • v.29 no.4
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    • pp.341-347
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    • 2005
  • A unique technique to extract the phase in time domain is proposed in order to measure the time parameters such as speed and depth by transmitting sound and electric waves. In the signal analysis processing, the phase of pulse signal can be transformed and digitalized with local data in real time without the effect of direct current bias and Nyquist limits. This method is sensitive to base frequency of pulse signal with high spacial resolution and is effective to compare two signals which have different forms. It is expected that the phase analysis technique will be applied to the measurement of the speed and depth accurately by ultrasonic pulse signal in water.

Comparison of On-Line Diagnotic Methods on Multi-Channel Signals in Nuclear Plant (원자력발전소 다채널 신호의 온라인 진단방법 비교)

  • Lee, Kwang-Dae;Yang, Seung-Ok
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.705-708
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    • 2003
  • In this paper, we have evaluated the methods to generate the reference signal for the diagnosis of multi-channel signals. The channel signal integrity can be known by the difference between the reference signal and each channel value. The generation method of reference signal is important in the diagnosis of multi-channel measurement system. The continuous weighting average method rejects the abnormal signal using weighting method and makes the reference signal using sumation of all channel values. This gives the simple and reasonable reference signal. The principle component analysis, one of the multivariate analysis methods, and the neural network method give the reliable reference signal by using signal models, and learning algorithm. Two methods can make the reliable reference if all signals are normal, but any signal having the drift have an effect on the reference.

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Fault Detection and Damage Pattern Analysis of a Gearbox Using the Power Spectra Density and Artificial Neural Network (파워스펙트럼 및 신경망회로를 이용한 기어박스의 결함진단 및 결함형태 분류에 관한 연구)

  • Lee, Sang-Kwon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.4
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    • pp.537-543
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    • 2003
  • Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

Develop physical layer analysis algorithm for OFDMA signal based IEEE 802.16e (IEEE 802.16e 기반 OFDMA 물리층 분석 알고리즘 연구)

  • Jang, Min-Ki
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.6
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    • pp.342-349
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    • 2019
  • We describe and anlayzes the methodology and implementation results of H / W configuration and signal characteristics analysis algorithm for analyzing equipment for analyzing OFDMA physical layer based on 802.16e. Recently, demand for signal analysis of instruments that analyze these signals with the development of digital communication signals is rapidly increasing. Accordingly, it is necessary to develop signal analysis equipment capable of analyzing characteristics of a broadband communication signal using a wideband digital signal processing module. In this paper, we have studied the basic theory of OFDMA in order to devise a device capable of analyzing characterisitcs of broadband communication signals. Second, the structure of OFDMA transmitter/receiver was examined. Third, a wideband digitizer was implemented. we design Wimax signal analysis algorithm based on OFDMA among broadband communication methods and propose Wimax physical layer analysis S/W implementation through I, Q signals. The IF downconverter used the receiver module and the LO generation module of the spectrum analyzer. Quantitative analysis result is obtained through the algorithm of Wimax signal analysis by I, Q data.

Time-Frequency Analysis Using Linear Combination Wavelet Transform and Its Application to Diagnostic Monitoring System (선형조합 웨이브릿 변환을 사용한 시간-주파수 분석 및 진단 모니터링 시스템의 적용)

  • 김민수;권기룡;김석태
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.1
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    • pp.83-95
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    • 1999
  • Wavelet transform has localization for time or frequency. It is useful to analyze a nonstationary signal. Basic function on wavelet transform is generated dilating and translating the original wavelet(mother wavelet). In this paper, time-frequency analysis method using linear combination wavelet transform is proposed. And it is applied to diagnostic monitoring system using the proposed linear combination wavelet transform. The stationary and nonstationary signal is used linear chirp signal, fan noise signal, a sinusoid signal from revolution body, electronic signal. Transform applied to signal analysis use fast Fourier transform (FFT), Daubechies, Haar and proposed linear combination method. The result of time-frequency analysis using linear combination wavelet transform is suited for portraying nonstationary time signal as well as stationary signal. Also the diagnostic monitoring system carry out the effective the signal analysis.

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Development of MATLAB-based Signal Performance Analysis Software for New RNSS Signal Design

  • Han, Kahee;Won, Jong-Hoon
    • Journal of Positioning, Navigation, and Timing
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    • v.8 no.4
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    • pp.139-152
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    • 2019
  • The design of new navigation signals is a key factor in building new satellite navigation systems and/or modernizing existing legacy systems. Navigation signal design involves selecting candidate groups and evaluating and analyzing their signal performances. This process can be easily performed through software simulation especially at the beginning of the development phase. The analytical signal performance analysis software introduced in this study is implemented based on equations between the signal design parameters of Radio Navigation Satellite Service (RNSS) and the navigation signal figures-of-merit (FoMs). Therefore, this study briefly summarizes the RNSS signal design parameters and FoMs before introducing the developed software. After that, we explain the operating sequence of the implemented software including the Graphical User Interface (GUI), and calculate the FoMs of an example scenario to verify the feasibility of the software operations.

Introduction to Chaos Analysis Method of Time Series Signal: With Priority Given to Oceanic Underwater Ambient Noise Signal (시계열 신호의 흔돈분석 기법 소개: 해양 수중소음 신호를 중심으로)

  • Choi, Bok-Kyoung;Kim, Bong-Chae;Shin, Chang-Woong
    • Ocean and Polar Research
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    • v.28 no.4
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    • pp.459-465
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    • 2006
  • Ambient noise as a background noise in the ocean has been well known for its the various and irregular signal characteristics. Generally, these signals we treated as noise and they are analyzed through stochastical level if they don't include definite sinusoidal signals. This study is to see how ocean ambient noise can be analyzed by the chaotic analysis technique. The chaotic analysis is carried out with underwater ambient noise obtained in areas near the Korean Peninsula. The calculated physical parameters of time series signal are as follows: histogram, self-correlation coefficient, delay time, frequency spectrum, sonogram, return map, embedding dimension, correlation dimension, Lyapunov exponent, etc. We investigate the chaotic pattern of noises from these parameters. From the embedding dimensions of underwater noises, the assesment of underwater noise by chaotic analysis shows similar results if they don't include a definite sinusoidal signal. However, the values of Lyapunov exponent (divergence exponent) are smaller than that of random noise signal. As a result we confirm the possibility of classification of underwater noise using Lyapunov analysis.

RF Power Detector for Location Sensing

  • Kim, Myung-Sik;Kubo, Takashi;Chong, Nak-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1771-1774
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    • 2005
  • Recently, RFID has become popular in the field of remote sensing applications. Location awareness is one of the most important keys to deploying RFID for advanced object tracking. Generally, multiple reference RF stations or additional sensors are used for the location sensing with RFID, but, particularly in indoor environments, spatial layout and cost problems limit the applicability of those approaches. In this paper, we propose a novel method for location sensing with active RFID systems not requiring the need for reference stations or additional sensors. The system triangulates the position of RF signal source using the signal pattern of the loop antenna connected to the power detector. The power detector consists of a signal strength detector and a signal analysis unit. The signal analysis unit indicates the signal strength and serial number using the signal from the strength detector, and provides the direction of the signal to the application target. We designed three different signal analysis units depending on the threshold type. The developed system can sense the direction to the transponder located over 10 m away within the maximum error of $5^{\circ}$. It falls within a reasonable range in our normal office environment.

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Efficient Signal Analysis of TDX-families PCM Signal Acquisition System with the Modified DFT

  • Lee, Jae-Kyung;Yoon, Dal-Hwan
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1913-1916
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    • 2002
  • In this paper, we have developed a PCM signal analysis system which can analyze status of signals sent from/received to the TDX-families PCM signaling service equipment. We propose the modified DFT to analyze the status of an acquired CM signal, discuss the algorithm and the discrimination of the analyzed signal.

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Characteristic wave detection in ECG using complex-valued Continuous Wavelet Transforms

  • Berdakh, Abibullaev;Seo, Hee-Don
    • Journal of Biomedical Engineering Research
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    • v.29 no.4
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    • pp.278-285
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    • 2008
  • In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.