• Journal of Power Electronics
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• 제18권5호
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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.

• 한국전자파학회논문지
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• 제29권3호
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• pp.184-191
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• 2018

OFDM(Orthogonal Frequency Division Multiplexing)은 다중캐리어를 사용해 고속통신을 가능하게 하는 MCM(MultiCarrier Modulation)시스템이며, 전력과 스펙트럼 효율의 단점을 갖는다. 따라서 본 논문에서는 기존의 단점을 보완하고, 효율적인 MCM시스템 설계를 목표로 한다. 제안하는 시스템은 IFFT(Inverse Fast Fourier Transform) 연산 대신에 IDWT(Inverse Discrete Wavelet Transform) 연산을 사용하게 된다. 웨이블릿 변환 기반의 OFDM 시스템 설계를 통해 기존의 OFDM 시스템과 BER(Bit Error Rate), 스펙트럼 효율, PAPR(Peak to Average Power Ratio) 성능 비교를 진행하였다. 그 결과, 기존의 OFDM과 Wavelet-OFDM은 동일한 BER 성능을 나타내었고, Discrete Meyer 웨이블릿을 사용한 Wavelet-OFDM에서는 기존의 OFDM과 동일한 스펙트럼 효율을 갖는다. 또한, 여러 가지 웨이블릿을 기반으로 구성한 Wavelet-OFDM의 모든 시스템은 기존의 OFDM보다 낮은 PAPR 성능을 갖는다.

• 대한전기학회논문지:전력기술부문A
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• 제55권7호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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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.

• 인터넷정보학회논문지
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• 제13권2호
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• pp.13-20
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• 2012

OFDM (Orthogonal Frequency Division Multiplexing) 시스템에서 SLM (Selected Mapping)은 전송신호의 왜곡 없이 PAPR (Peak-to-Average Power Ratio)을 효율적으로 줄일 수 있는 기법이다. 하지만, 충분한 후보 OFDM 신호를 생성하기 위해서는 많은 양의 IFFT (Inverse Fast Fourier Transform) 연산을 필요로 하고, 이는 SLM 기법을 매우 복잡하게 만든다. 따라서 본 논문에서는 첫 번째 후보 OFDM 신호를 변환하여 나머지 IFFT 연산들을 대체하는 새로운 SLM 기법을 제안한다. 제안된 기법은 기존의 SLM 기법과 비교하여 거의 같은 PAPR 저감 성능을 보임과 동시에 계산 복잡도는 크게 감소 시킬 수 있다.

• 한국위성정보통신학회논문지
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• 제9권2호
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• pp.38-44
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• 2014

본 논문은 FMCW(Frequency Modulated Continuous Wave) 레이더 레벨 측정기 설계와 시뮬레이션을 통한 성능분석에 대하여 기술한다. 설계된 레벨미터는 FMCW radar를 이용하여 최대 20m 거리를 측정하며, 거리 계산을 위한 비트신호 분석기법으로 FFT(Fast Fourier Transform)와 Zoom-FFT를 적용하였다. 성능 분석을 위해 시뮬레이션을 통하여 두가지 기법을 비교 분석한 결과, 측정오류를 최소화하고 측정의 분해능을 향상시키기 위해서는 Zoom-FFT 기법이 보다 적절한 기법임을 확인하였다. 시뮬레이션은 주파수 분해능과 측정거리 분해능의 최적 값을 얻기 위해 다양한 조건에서 분석하였고, 1.024GHz 주파수 조건에서 2.2mm의 측정 분해능을 확인하였다.

• 한국멀티미디어학회논문지
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• 제24권11호
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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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• 제13권1호
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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.

• 디지털융복합연구
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• 제10권7호
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• pp.123-128
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• 2012

본 논문에서는 보다 정확한 물체 인식을 위하여 물체의 특징점 검출 시스템을 제안한다. 물체의 특징점 검출 시스템은 학습 단계와 검출 단계로 구분된다. 학습 단계에서는 각 특징점의 탐색영역을 설정하기 위한 관심영역모델과 탐색영역에서 특징점을 검출하기 위한 각 특징점별 검출기를 생성한다. 검출 단계에서는 학습 단계에서 생성했던 관심영역모델을 이용하여 입력 영상에서 각각의 특징점의 탐색영역을 설정한다. 시스템에서 검출하고자 하는 특징점 검출 방법은 고속 푸리에 변환을 이용하기 때문에 검출 속도가 빠르며 물체의 추적 시 실패하는 확률이 낮아진다. 제안하는 방법을 개발하여 실험 영상에 적용한 결과 추적하고자 하는 물체가 불규칙적인 속도로 움직일 때에도 안정적으로 추적함을 알 수 있었다. 실험 결과는 기존의 방법들에서 사용되었던 다양한 데이터 집합에 적용하였을 때 우수한 성능을 보여준다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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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).