• 전기학회논문지
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• 제63권8호
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• pp.1092-1097
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• 2014

In this paper, we propose the grid-based output control method for wind farm. To do this, we propose the output control method using the PSO(Particle Swarm Optimization) algorithm. Secondly, we propose the method for detecting the harmonics using STFT(Short-Time Fourier Transform) algorithm. And last, we propose the method for compensating the harmonics using neural network. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.555-576
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• 2016

In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

• 진공이야기
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• 제2권3호
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• pp.4-10
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• 2015

We developed a real-time three-polarizer spectroscopic ellipsometer based on a new data acquisition algorithm and a general data reduction (the process of extracting the ellipsometric sample parameters from the Fourier coefficients). The data acquisition algorithm measures Fourier coefficients of radiant flux waveform accurately and precisely. The general data reduction is introduced to represent the analytic functions of the standard uncertainties of the ellipsometric sample parameters, and the extracted theoretical values closely agree with the corresponding experimental data. Our approach can be used for optimization of measurement conditions, instrumentation, simulation, standardization, laboratory accreditation, and metrology.

• 품질경영학회지
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• 제51권1호
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• pp.119-129
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• 2023

Purpose: This study proposes a classification model for implementing condition-based maintenance (CBM) by monitoring the real-time status of a machine using acceleration sensor data collected from a vehicle. Methods: The classification model's performance was improved by applying Fourier transform to convert the acceleration sensor data from the time domain to the frequency domain. Additionally, the Generative Adversarial Network (GAN) algorithm was used to augment images and further enhance the classification model's performance. Results: Experimental results demonstrate that the GAN algorithm can effectively serve as an image augmentation technique to enhance the performance of the classification model. Consequently, the proposed approach yielded a significant improvement in the classification model's accuracy. Conclusion: While this study focused on the effectiveness of the GAN algorithm as an image augmentation method, further research is necessary to compare its performance with other image augmentation techniques. Additionally, it is essential to consider the potential for performance degradation due to class imbalance and conduct follow-up studies to address this issue.

• ETRI Journal
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• 제41권3호
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• pp.316-325
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• 2019

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.

• 동력기계공학회지
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• 제12권2호
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• pp.55-61
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• 2008

This paper discusses the advantages of using Fourier-based periodic excitation and of combining internal and external models in dynamic robot parameter identification. Internal models relate the joint torques or forces with the motion of the robot; external models relate the reaction forces and torques on the bedplate with the motion data. This combined model allows to combine joint torque/force and reaction torque/force measurements in one parameter estimation scheme. This combined model estimation will yield more accurate parameter estimates, and consequently better predictions of actuator torque, which is shown by means of a simulated experiment on a CRS A465 industrial robot.

• Geomechanics and Engineering
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• 제7권2호
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• pp.149-164
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• 2014

One of the most advanced classes of techniques for ground response analysis is based on the use of Transfer Functions. They represent the ratio of Fourier spectrum of amplitude motion at the free surface to the corresponding spectrum of the bedrock motion and they are applied in frequency domain usually by FFT method. However, Fourier spectrum only shows the dominant frequency in each time step and is unable to represent all frequency contents in every time step and this drawback leads to inaccurate results. In this research, this process is optimized by decomposing the input motion into different frequency sub-bands using Wavelet Multi-level Decomposition. Each component is then processed with transfer Function relating to the corresponding component frequency. Taking inverse FFT from all components, the ground motion can be recovered by summing up the results. The nonlinear behavior is approximated using an iterative procedure with nonlinear soil properties. The results of this procedure show better accuracy with respect to field observations than does the Conventional method. The proposed method can also be applied to other engineering disciplines with similar procedure.

• 전자공학회논문지A
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• 제32A권8호
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• pp.56-63
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• 1995

A new method is presented for the synthesis of lossy tapered transmission line having presecribed frequency characteristic in the passband. The theory of lossy case extends lossless cases suggested by Klopfenstein and others, and a special optimization process based on the Fourier transfrom pair and generalized Taylor's procedure is proposed for exact designs of frequency-dependent and distance-dependent lossy tapered line. The process is achieved by control of zero points of lobe-like input reflection coefficient. The validity of the suggested method is confirmed by synthesizing a lossy microstrip transformer and analyzing the simulation results.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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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.

• 한국정밀공학회지
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• 제19권5호
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• pp.110-117
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• 2002

This paper proposes a optimization of the design variables of linear motor for the improvement of thrust. Especially, this paper treats the shoe, which can be good to flow of a magnetic flux in linear motor. Firstly, this paper uses a space harmonic analysis method(SHAM) based on Fourier series, for analyzing the characteristics of core type linear motor, including slot structure and shoe. And compare the magnetic flux densities of linear motor at air gap with the results of the SHAM and the Finite Element Method(FEM). Secondly, this paper uses a genetic algorithm, which is good to find the global solutions. The design variables are the pole pitch of magnet, the pitch of slot, the height of slot, the width of shoe and the width of magnet. The maximum thrust with optimum design variables is about 247 N which is improved about 16%.