• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.1-11
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• 2015

In this paper, the transmission of an improper-complex second-order stationary data sequence is considered over a strictly band-limited frequency-selective channel. It is assumed that the transmitter employs linear modulation and that the channel output is corrupted by additive proper-complex cyclostationary noise. Under the average transmit power constraint, the problem of minimizing the mean-squared error at the output of a widely linear receiver is formulated in the time domain to find the optimal transmit and receive waveforms. The optimization problem is converted into a frequency-domain problem by using the vectorized Fourier transform technique and put into the form of a double minimization. First, the widely linear receiver is optimized that requires, unlike the linear receiver design with only one waveform, the design of two receive waveforms. Then, the optimal transmit waveform for the linear modulator is derived by introducing the notion of the impropriety frequency function of a discrete-time random process and by performing a line search combined with an iterative algorithm. The optimal solution shows that both the periodic spectral correlation due to the cyclostationarity and the symmetric spectral correlation about the origin due to the impropriety are well exploited.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.11
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• pp.882-889
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• 2003

This paper presents the method for structure borne noise analysis of a flexible body in multibody system. The proposed method is the superposition method using the flexible multibody dynamic analysis and the finite element one. This method is executed in 3 steps. In the 1st step, time dependent quantities such as dynamic loads, modal coordinates and gross body motion of the flexible body are calculated through a flexible multibody dynamic analysis. And frequency response functions of those time dependent quantities are computed through Fourier transforms. In the 2nd step, acoustic pressure coefficients are obtained through structure-acoustic coupling analyses by the finite element method. In the final step, frequency responses of acoustic pressure at the acoustic nodes are recovered through linear superposition of frequency response functions with acoustic pressure coefficients. The accuracy of the proposed method is verified in the numerical example of a simple car model.

• Proceedings of the Acoustical Society of Korea Conference
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• 1997.06a
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• pp.27-34
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• 1997

In this study , we tried to test the classification performance of a neural netow and thereby to examine its applicability to the signals distorted by a shallow water einvironment . We conducted an acoustic experiment iin a shallow sea near Pohang, Korea in which water depth is about 60m. The signals, on which the network has been tested, is ilinear frequency modulated ones centered on one of the frequencies, 200, 400, 600 and 800 Hz, each being swept up or down with bandwidth 100Hz. we considered two transforms, STFT(short-time Fourier transform) and PWVD (pseudo Wigner-Ville distribution), form which power spectra were derived. The training signals were simulated using an acoutic model based on the Fourier synthesis scheme. When the network has been trained on the measured signals of center frequency 600Hz,it gave a little better results than that trained onthe simulated . With the center frequencies varied, the overall performance reached over 90% except one case of center frequency 800Hz. With the feature extraction techniques(STFT and PWVD) varied,the network showed performance comparable to each other . In conclusion , the signals which have been simulated with water depth were successully applied to training a neural network, and the trained network performed well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.86-91
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• 2000

In this paper, we will discuss the characteristics of the magnitude and the phase of the piano sound in frequency domain by using the FFT(Fast Fourier Transform). The method deciding the parameters representing those sounds through the mathematical model is described. We used the curve fitting method for the modeling of the harmonic part of the sound including the fundamental frequency in order to minimize the errors between original sounds and modeled sounds. furthermore, we used the line segment approximation method for the modeling of the noise part around fundamental frequency. We also applied the same method for the phase model and could get the modeled sound to be similar to the original sound using the parameters. Therefore the high compression ratio comparing the modeled sound to the original sound is achieved.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.319-327
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• 2011

Skeletal muscle fatigue is defined as a 'any reduction in the maximal capacity to generate force or power output', and is the reduction of oxygen consumption and by-product of metabolism. For the muscle fatigue therapy, low level laser has been introduced that leads the mitochondrial respiratory and attributes the muscle fatigue recovery. This study analyzed the muscle fatigue signals from electromyography(EMG) during low-level laser therapy (LLLT). Healthy subjects performed voluntary elbow flexion-extension excercise and received placebo LLLT and active LLLT using a 830 nm laser diode. Then, EMG were measured for the evaluation of muscle fatigue. The acquired EMG data were analyzed with median frequency and short time fourier transform methods. The results showed that the LLLT had a significant symptomatic relief of muscle fatigue based on the EMG frequency analysis. Therefore, the muscle fatigue analysis with EMG signals can be applied to quantitative evaluation for the monitoring of LLLT effects.

• Journal of Sensor Science and Technology
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• v.24 no.3
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• pp.169-174
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• 2015

In this study, we developed a system to detect the various defects in the metallic objects using the phenomenon that the defects cause the changes of the natural resonant frequencies. Our system consists of a FFT Amp, an Auto Impact Hammer, a Hammer controller and a PC. Auto Impact Hammer creates vibrations in the metallic objects when tapped on the surface. These vibrational signals are converted to the voltage signals by an acceleration sensor attached to the metallic part surface. These analog voltage signals were fed into an ADC (analog-digital converter) and an FFT (fast fourier transform) conversion in the FFT Amp to obtain the digital data in the frequency domain. Labview graphical program was used to process the digital data from th FFT amp to display the spectrum. We compared those spectra with the standard spectrum to find the shifts in the resonant frequencies of the metal parts, and thus detecting the defects. We used PCB's acceleration sensor and TI's TMS320F28335 DSP (digital signal processor) to obtain the resolution of 2.93 Hz and to analyze the frequencies up to 44 kHz.

• Journal of Ship and Ocean Technology
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• v.9 no.2
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• pp.21-28
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• 2005

Recently moored offshore vessels like as FPSO(Floating Production Storage Offloading) are frequently deployed in seas for a long time. For successful operation, the motion behavior of such a vessel in waves must be clarified in advance either theoretically or experimentally. It is of particular interest to examine the behavior, when swells are superposed to seas with different incident angle. Such a situation is actually reported in some offshore oilfield. In this paper, the motion of a FPSO in irregular waves including swells is studied in time domain. Hydrodynamic coefficients and wave forces are calculated in frequency domain using three-dimensional singularity distribution method. Time memory function and added mass at infinite frequency are derived by Fourier transform utilizing hydrodynamic damping coefficients. In the process, the numerical accuracy of added mass at infinite frequency is carefully examined in association with free decay simulations. It is found from numerical simulations that swells significantly affect the vertical motion of FPSO mainly because of their longer period compared to the ordinary sea waves. In particular, the roll motion is largely amplified because the dominant period of swell is closer to the roll natural period than that of seas.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.167-172
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• 2010

In this paper, we analyze and simulate the performance of a pilot signal detection algorithm based on fast Fourier transform (FFT) for several system parameters in order to detect advanced television system committee digital television (ATSC DTV) signals. Requirements for detecting DTV signals are analyzed. And the detection performance is compared according to sensing frequency and time. Form the simulation results, it is confirmed that the signal detection performance increases as the sensing frequency rises. The results of this paper can be applied for implementing cognitive radio (CR) systems in the frequency band of DTV signals.

• Journal of Power Electronics
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• v.13 no.1
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• pp.170-176
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• 2013

Power converters produce a vast range of harmonics, subharmonics and interharmonics. Harmonics analyzing tools based on the Fast Fourier Transform (FFT) assume that only harmonics are present and the periodicity intervals are fixed, while these periodicity intervals are variable and long in the presence of interharmonics. Using FFT may lead to invalid and undesired results due to the above mentioned issues. They can also lead to problems such as frequency blending, spectral leakage and the picket-fence effect. In this paper, the group-harmonic weighting (GHW) approach has been presented to identify the interharmonics in a power system. Afterwards, a modified GHW has been introduced to calculate the proper bandwidth for analyzing the various values of interharmonics. Modifying this method leads to more precise results in the FFT of a waveform containing inter harmonics especially in power systems with a fundamental frequency drift or frequency interference. Numerical simulations have been performed to prove the efficiency of the presented algorithm in interharmonics detection and to increase the accuracy of the FFT and the GWH methods.