• Journal of Power Electronics
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• v.18 no.5
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• pp.1567-1576
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• 2018

The reliability of grid-connected inverters can be improved by algorithms capable of diagnosing faults in LCL filters. A fault diagnostic method during inverter startup is proposed. The proposed method can accurately generate and monitor information on the peak value and the location of the peak frequency component of the step response of a damped LCL filter. To identify faults, the proposed method compares the evaluated response with the response of a healthy higher-order damped LCL filter. The frequency components in the filter voltage response are first analytically obtained in closed form, which yields the expected trends for the filter faults. In the converter controller, the frequency components in the filter voltage response are computed using an appropriately designed fast Fourier transform and compared with healthy LCL response parameters using a finite state machine, which is used to sequence the proposed startup diagnostics. The performance of the proposed method is validated by comparing analytical results with the simulation and experimental results for a three-phase grid-connected inverter with a damped LCL filter.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.3
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• pp.184-191
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• 2018

Orthogonal frequency division multiplexing(OFDM) is a multicarrier modulation(MCM) system that enables high-speed communications using multiple carriers and has advantages of power and spectral efficiency. Therefore, this study aims to complement the existing shortcomings and to design an efficient MCM system. The proposed system uses the inverse discrete wavelet transform(IDWT) operation instead of the inverse fast Fourier transform(IFFT) operation. The bit error rate(BER), spectral efficiency, and peak-to-average power ratio(PAPR) performance were compared with the conventional OFDM system through the OFDM system design based on wavelet transform. Our results showed that the conventional OFDM and Wavelet-OFDM exhibited the same BER performance, and that the Wavelet-OFDM using the discrete Meyer wavelet had the same spectral efficiency as the conventional OFDM. In addition, all systems of Wavelet-OFDM based on various wavelets confirm a PAPR performance lower than that of conventional OFDM.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.265-272
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• 2006

This paper describes a method of parameter estimation of time series data using discrete Fourier transform(DFT). DFT have been mainly used to precisely and rapidly obtain the frequency of a signal. In a dynamic system, a real part of a mode used to learn damping characteristics is a more important factor than the frequency of the mode. The parameter estimation method of this paper can directly estimate modes and parameters, indicating the characteristics of a dynamic system, on the basis of the Fourier transform of the time series data. Real part of a mode estimates by subtracting a frequency of the Fourier spectrum corresponding to 0.707 of a magnitude of the peak spectrum from a peak frequency, or subtracting a frequency of the power spectrum corresponding to 0.5 of the peak power spectrum from a peak frequency, or comparing the Fourier(power) spectrum ratio. Also, the residue and phase of time signal calculate by simple equation with the real part of the mode and the power spectrum that have been calculated. Accordingly, the proposed algorithm is advantageous in that it can estimate parameters of the system through a single DFT without repeatedly calculating a DFT, thus shortening the time required to estimate the parameters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.361-364
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• 1995

Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.13-20
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• 2012

SLM (Selected Mapping) is an efficient PAPR (Peak-to-Average Power Ratio) reduction scheme without transmitted signal distortion in OFDM (Orthogonal Frequency Division Multiplexing) systems. However, enormous IFFTs (Inverse Fast Fourier Transforms) are needed to generate sufficient candidate OFDM signals, which cause the SLM to become quite complex. In this paper, we propose a new SLM scheme that replaces the IFFT operations with a conversion of the first candidate OFDM signal. The proposed scheme significantly reduces computational complexity, while it shows almost the same PAPR performance as the conventional SLM scheme.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.38-44
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• 2014

This paper presents design of a FMCW (Frequency Modulated Continuous Wave) level meter as well as simulation result of the designed system. The system is designed to measure maximum range of 20m since FMCW radar can be used for measuring short range distance. The distance is measured by analyzing the beat signal which is generated as result of mixing transmitting signal with the reflected received signal. The Fast Fourier Transform is applied to analyze the beat signal for calculating the displacement and Zoom FFT technique is used to minimize measurement error as well as increase the resolution of the measurement. The resolution of the measurement of the designed system in this paper is 2.2mm and bandwidth of 1.024GHz is used for simulation. Thus the simulation results are analyzed and compared in various conditions in order to get a comprehensive idea of frequency resolution and displacement resolution.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1552-1559
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• 2021

Convolution neural networks (CNNs) show notable performance in image processing and are used as representative core models. CNNs extract and learn features from large amounts of train dataset. In general, it has a structure in which a convolution layer and a fully connected layer are stacked. The core of CNN is the convolution layer. The size of the kernel used for feature extraction and the number that affect the depth of the feature map determine the amount of weight parameters of the CNN that can be learned. These parameters are the main causes of increasing the computational complexity and memory usage of the entire neural network. The most computationally expensive components in CNNs are fully connected and spatial convolution computations. In this paper, we propose a Fourier Convolution Neural Network that performs the operation of the convolution layer in the Fourier domain. We work on modifying and improving the amount of computation by applying the fast fourier transform method. Using the MNIST dataset, the performance was similar to that of the general CNN in terms of accuracy. In terms of operation speed, 7.2% faster operation speed was achieved. An average of 19% faster speed was achieved in experiments using 1024x1024 images and various sizes of kernels.

• Geomechanics and Engineering
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• v.13 no.1
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• pp.161-171
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• 2017

The underlying ground state of a railway plays a significant role in maintaining the integrity of the overlying concrete slab and ultimately supporting the train load. While effective nondestructive tests have been used to evaluate the rail track system, they can only be performed during non-operating time due to the stress wave generated by active sources. In this study, finite element numerical simulations are conducted to investigate the feasibility of detecting unfavorable substructure conditions by using a moving train load. First, a train load module is developed by converting the train load into time-variant equivalent forces. The moving forces based on the shape functions are applied at the nodes. A parametric study that takes into account the bonding state and the train class is then performed. All the synthetic signals obtained from numerical simulations are analyzed at the frequency domain using a Fast Fourier transform (FFT) and at the time-frequency domain using a Short-Time Fourier transform (STFT). The presence of a void condition amplifies the acceleration amplitude and the vibration response. This study confirms the feasibility of using a moving train load to systematically evaluate a rail track system.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.123-128
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• 2012

In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.109-112
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• 2001

Recently, the subject of \"wavelet analysis\" has drawn much attention from both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Statistics and ets. Analogous to Fourier analysis, wavelets is a versatile tool with very rich mathematical content and great potential for applications. Specially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. In this paper, discrimination analyses of acquired electrical current signals for each and mixed loads were tried by using Morlet wavelet transform. Their representative loads were classified as TV, DRY(Dryer), REF(Refrigerate), and FL(Fluorescent Lamp).