• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 학술대회 논문집 전문대학교육위원
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• pp.154-158
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• 2006

The switching-mode power converter has been widely used because of its features of high efficiency and small weight and size. These features are brought by the ON-OFF operation of semiconductor switching devices. However, this switching operation causes the surge and EMI(Electromagnetic Interference) which deteriorate the reliability of the converter themselves and entire electronic systems. This problem on the surge and noise is one of the most serious difficulties in AC-to-DC converter. Random Pulse Width Modulation (RPWM) is peformed by adding a random perturbation to switching instant while output-voltage regulation of converter is performed. RPWM method for reducing conducted EMI in single switch three phase discontinuous conduction mode boost converter is presented. The more white noise is injected, the more conducted EMI is reduced. But output-voltage is not sufficiently regulated. This is the reason why carrier frequency selection topology is proposed. In the case of carrier frequency selection, output-voltage of steady state and transient state is fully regulated. A RPWM control method was proposed in order to smooth the switching noise spectrum and reduce it's level. Experimental results are verified by converter operating at 300v/1kW with $5%{\sim}30%$ white noise input. Spectrum analysis is performed on the Phase current and the CM noise voltage. The former is measured with Current Probe and the latter is achieved with LISN, which are connected to the spectrum analyzer respectively.

• 한국인터넷방송통신학회논문지
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• 제18권4호
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• pp.55-60
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• 2018

본 논문은 전력선 통신에서 딥 러닝 기술 적용시킨 연구의 초기 결과를 보여준다. 본 논문에서는 전력선 통신의 성능을 감소시키는 원인인 잡음을 제거하기 위해 딥 러닝 기술을 적용시켜 효과적인 잡음 제거를 목표로 하고 수신 단에서 딥 러닝 모델을 추가하여 잡음을 효과적으로 제거하는 시스템을 제안한다. 딥 러닝 모델을 학습시키기 위해서는 데이터가 필요하므로 기존의 데이터들을 저장하고 있다고 가정하고 제안하는 시스템에 대해 시뮬레이션을 진행하여 부가 백색 가우시안 잡음 채널의 이론적 결과와 비트 에러률을 비교하여 제안하는 시스템 모델이 잡음을 제거하여 통신 성능을 향상시킨 것을 확인한다.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.118-120
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• 2021

현대 사회는 IoT 기술의 발달에 따라 CCTV, 탐사로봇 등 폭넓은 분야에서 다양한 디지털 장비들이 보급되고 있다. 이에 데이터처리의 중요성이 커지고 있으며, 영상 분야에서도 데이터를 수신하는 과정에서 발생하는 잡음을 제거하기 위한 다양한 연구들이 진행되고 있다. 대표적인 잡음으로 AWGN(additive white Gaussian noise)이 있으며, 잡음을 제거하기 위한 기존의 필터로는 평균필터(AF : average filter), 알파 트림드 평균필터(A-TAF : alpha trimmed average filter), 메디안필터(MF : median filter) 등이 있다. 하지만 기존의 필터들은 고주파영역에서의 잡음 제거 특성이 다소 미흡한 성능을 보이는 단점이 있다. 따라서 본 논문에서는 고주파영역에 존재하는 AWGN을 효과적으로 제거하기 위해 표준편차를 기반한 거리에 따른 가중치필터를 제안한다.

• 한국정보통신학회논문지
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• 제15권10호
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• pp.2239-2246
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• 2011

영상신호를 처리하는 과정에서 잡음에 의해 영상의 열화가 발생하고 있으며, 가우시안 잡음과 임펄스 잡음이 중첩되어 생성된 복합잡음에 의해 훼손되는 경우가 많다. 따라서 본 논문에서는 에지정보를 고려하며 임펄스 잡음과 AWGN(additive white gaussian noise) 잡음이 중첩된 복합잡음을 제거하는 알고리즘을 제안하였다. 제안한 알고리즘은 먼저 잡음의 종류를 판단과정을 거친 후, 그 결과가 AWGN이라고 하면 self-adaptive weighted mean 필터를 사용하여 구하여진 값과 마스크 내의 중간값 사이의 평균을 출력으로 한다. 만약 임펄스 잡음이라고 판단 될 경우, 변형된 비선형 필터를 이용하여 처리한다. 그리고 시뮬레이션을 통해 기존의 방법들과 그 성능을 비교하였고 판단 기준으로 PSNR(peak signal to noise ratio)을 사용하였다. 테스트 영상들에 대한 시뮬레이션 결과로부터 제안한 방법은 기존의 방법들보다 잡음제거나 에지보존 등 방면에서 우수한 성능을 나타내었다.

• 한국정밀공학회지
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• 제14권3호
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• pp.107-113
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• 1997

This paper presents the active control of a flexible cantilever beam vibration. The cantilever beam was excitied by a steady-state harmonic and white noise point force and the control was performed by one piezo ceramic actuator bonded to the surface of the beam. An adaptive controller based on filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, gap sensor was used as an error sensor while the sinusoidal or white noise was applied as a disturbance. In the case of sinusoidal input, more than 20 dB of vibration reduction was achieved over all range of the natural frequencies and it takes 5 seconds to control the vibration at first natural frequency and 1 second at other natural frequencies. In the case of white noise input, 7 dB of vibration reduction was achieved at the first natural frequency and good control performance was achieved in the considered whole frequency range. Results indicate that the vibration of a flexible cantilever beam could be controlled effectively when the piezo ceramic actuator was used with filtered-x LMS algorithm.

• 전자공학회논문지SC
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• 제41권3호
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• pp.25-32
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• 2004

본 논문에서는 두 개의 사인파 신호의 위상 차이를 계산해 내기위한 개선된 위상 측정 알고리즘을 제안하였다. 이 알고리즘은 두 개의 입력신호의 양자화된 샘플링 데이터를 사용하여 위상과 크기를 구해낸다. 측정 알고리즘의 중요 파라메타들은 몇개의 해석식으로 표현되기 때문에 위상을 계산하기 위해 필요한 연산량이 상당히 줄어들고 따라서 더 빠른 속도로 위상을 계산해 낼 수 있게 되었다. 또한 본 논문에서 제시한 알고리즘을 사용하여 입력신호의 한주기 전체를 샘플링할 경우에는 입력신호에 harmonic distortion이 발생하더라도 위상 측정 오차가 전혀 발생하지 않음을 수식으로 증명하였으며 컴퓨터 시뮬레이션을 통하여 이를 확인하였다. 그리고 입력신호에 가우시안 백색 잡음(white gaussian noise)이 발생할 경우에 위상 측정 오차가 얼마나 발생하는 지에 대하여 여러 가지 관점에서 컴퓨터 시뮬레이션을 수행하고 그 결과를 분석하였다.

• Wind and Structures
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• 제16권2호
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• pp.157-178
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• 2013

Output-only modal parameter identification is based on the assumption that external forces on a linear structure are white noise. However, harmonic excitations are also often present in real structural vibrations. In particular, it has been realized that the use of forced acceleration responses without knowledge of external forces can pose a problem in the modal parameter identification, because an external force is imparted to its impulse acceleration response function. This paper provides a three-stage identification procedure as a solution to the problem of harmonic and white noise excitations in the acceleration responses of a linear dynamic system. This procedure combines the uses of the mode indicator function, the complex mode indication function, the enhanced frequency response function, an iterative rational fraction polynomial method and mode shape inspection for the correlation-related functions of the force-embedded acceleration responses. The procedure is verified via numerical simulation of a five-floor shear building and a two-dimensional frame and also applied to ambient vibration data of a large-span roof structure. Results show that the modal parameters of these dynamic systems can be satisfactorily identified under the requirement of wide separation between vibration modes and harmonic excitations.

• 전기전자학회논문지
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• 제25권3호
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• pp.544-547
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• 2021

Recently, various display products are being applied to automobiles. In the process of acquiring an image from a display product, a large amount of additive white Gaussian noise(AWGN) is generated. Generally known denoising techniques focus on removing noise, so detailed components including image information are proportionally lost in the process of removing noise. The algorithm proposed in this paper proposes a method to effectively remove noise while preserving the detail of image information.

• Journal of Preventive Medicine and Public Health
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• 제26권4호
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• pp.565-573
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• 1993

Noise is not only affecting the ear and the auditory cortex locally, but its influence is widely spread throughout the brain structures, e. g., the reticular formation, the brain stem nuclei or the subcortical forebrain area. Hence, any of the organism's activities can be hindered or stimulated by noise. High noise is a stressor and the catecholamine level can be used both as a stress marker and as an indicator of modified sympathetic nervous system activity. Several recent studies have found that the urinary excretion of catecholamines is increased due to high noise intensity, especially unexpectedly high and long lasting noise. The present study was conducted in order to examine the effects of noise stress on urinary excretion of ctecholamines in rats and humans. Rats were exposed to 90 dB noise for 10, 30, and 60 minutes, 3 and 12 hours. 24 hour . urinary samples were collected and the catecholamones were extracted by alumina and analyzed by HPLC-ECD. Catecholamine levels increased with time of exposure up to 60 minutes : norepinephrine concentration at 60 min of noise=1.038 ng/ml, epinephrine=0.636 ng/ml. Urine catecholamines of blue collar workers exposed to 90 dB of noise at the work place were collected between 2 and 4 p.m. and compared to that of white collar workers exposed to 70 dB. Mean norepinephrine level of the blue collar workers was 0.89 ng/ml (${\pm}0.25$), epinephrine 0.24ng/m1 (${\pm}0.09$), and that of the white collar workers 0.48 ng/ml (${\pm}0.12$), epinephrine 0.19 ng/ml(${\pm}0.05$). It was concluded that noise acts as a stressor and increases the catecholamine levels in both rats and humans.