• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.123-128
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• 2002

Over the range(OTR) has been applied for cooking and ventilation functions especially in northern Amarica. Because flow rate and operating rpm of the double sided sirocco fan for ventilation are much higher and than the microwave oven system, the major noise source is the sirocco fm. Recently, the quiet fan development is one of very important issues for amenity. In this study, the noise source identification using multi-microphone array system was carefully carried out and numerical simulations for understanding the aerodynamic and aeroacoustic of the fan were peformed. The sound level of tonal noise is predicted with a good accuracy but that of the broadband shows some discrepancy. In order to reduce the broadband noise, the inlet region of sirocco fan have to be modified that the secondary flow should be suppressed. Based on these results, new low noise fan and OTR is now developing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.969-974
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• 2007

In this paper, a beamforming technique is introduced to measure the acoustic impedance at both normal and oblique incidence in a free field. The acoustic impedance is obtained by separating incident and reflected signals using the adaptive nulling method which is one of the various beamforming algorithms. To obtain better results, pressure vector commonly used in array signal processing is replaced with the transfer function vector between each microphone and the white Gaussian noise is suppressed by a wavelet shrinkage technique. The experiments conducted in a semi-anechoic room show that the proposed method is efficient and accurate in measuring the acoustic impedance of sound absorbing materials under a free field condition.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.535-538
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• 2004

마이크로폰을 이용하여 평면상에 직교형으로 배열된 음인 도래 방향 탐지 시스템을 구성하고, A/D 변환에 있어 일반저인 샘플링 기법과 spilt-beam형 어군 탐지 시스템에 적용된 4분 샘플링 기법을 이용하여 공기중에서의 음원의 토래 방향 탐지 성능에 관한 실험을 수행하였다. 일반 실내에서 단일 주파수의 음원에 대하여 직교형 마이크로폰 배열을 사용한 음인 토래 방향 탐지 시스템 및 4분 샘플링 기법의 적용이 유용함을 확인하였다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2753-2755
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• 2005

최근 들어 공장에서만 사용되는 로봇을 탈피하여, 사람과 함께 생활하면서 서비스를 제공할 수 있는 인간 친화적인 로봇이 전 세계적으로 개발되고 있다. 인간과 자연스런 상호작용을 위하여, 화자를 바라보고, 깨끗한 음성신호를 얻는 과정에서 음원의 위치 추적은 필연적이다. 본 연구는 마이크로폰에 도달되는 동일 신호의 도착시간지연(Time Delay of Arrival)정보를 이용하여, 음원 위치를 구하는 기존의 수학적인 방법론[1]을 소개하고 검토한다. 모의실험을 통하여, 방법론[1]이 허상음원을 생성하는 음원 위치 측정임을 보인다.

• Speech Sciences
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• v.15 no.3
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• pp.17-28
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• 2008

In many practical applications of robots, finding the location of an incoming sound is an important issue for the development of efficient human robot interface. Most sound source localization algorithms make use of only those microphones that are acoustically visible from the sound source or do not take into account the effect of sound diffraction, thereby degrading the sound source localization performance. This paper proposes a new sound source localization method that can utilize those microphones that are acoustically shadowed from the sound source. The experiment results show that use of the acoustically shadowed microphones, which receive higher signal-to-noise ratio signals than the others and are closer to the sound source, improves the performance of sound source localization.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.44-45
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• 2017

본 논문에서는 비균등 선형 마이크로폰 어레이를 활용한 convolutional neural network (CNN) 기반의 음원분리 방법을 제안한다. 우선, 주어진 어레이 배치에 따라 채널간의 시간차를 분석하고, 분석된 시간차에 따라 주파수별로 방사각과 넓이에 따라 입력 오디오 신호의 spectral magnitude를 예측한다. 그러고 나서, CNN 분류기로부터 최적의 방사각과 넓이를 선별하고 이를 통해 음원을 분리한다.

• New & Renewable Energy
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• v.5 no.2
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• pp.25-30
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• 2009

The wind tunnel test to identify the acoustic noise source position of the wind turbine blade was conducted in KARI low speed wind tunnel. Microphone array and time-domain beamforming methodology was applied to this study. To reduce the data processing time, a modified beamforming method with a criteria between calculation time step and grid size for rotating angle in the cylinderical coordinate system was proposed. The test results shows that the data processing time to identify the noise source position was reduced to 20% compared with conventional method. And the dominant noise source of the blade moves from inboard to blade tip as the frequency increases.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.219-225
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• 2013

This paper presents a method using Maximum-Likelihood Linear Regression (MLLR) adaptation to improve recognition performance of Limabeam algorithm for speech recognition using microphone array. From our investigation on Limabeam algorithm, we can see that the performance of filtering optimization depends strongly on the supporting optimal state sequence and this sequence is created by using Viterbi algorithm trained with HMM model. So we propose an approach using MLLR adaptation for the recognition of speech uttered in a new environment to obtain better optimal state sequence that support for the filtering parameters' optimal step. Experimental results show that the system embedded with MLLR adaptation presents the word correct recognition rate 2% higher than that of original calibrate Limabeam and also present 7% higher than that of Delay and Sum algorithm. The best recognition accuracy of 89.4% is obtained when we use 4 microphones with 5 utterances for adaptation.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1590-1597
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• 2007

This paper deals with the noise source localization of the Korean High Speed Train (KTX) at the speed of 300 km/h. Using Microfonarray system and beamforming technology typical pass-by noise sources and their frequency characteristics are investigated. It is primarily aimed at investigating the location and characteristics of the high speed train emission. The results from the microphone array tests are also analyzed in relation to the remarks from analytic studies and experimental investigations on the high speed train that have been done with the intention of understanding the interior noise mechanism. The acoustical image shows the low frequency noise sources mainly at the position of the under part of the train at high speeds and the related source mechanism are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.837-842
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• 2004

The positions of rotating sound sources have been localized by experiments with the Doppler effects removed. In order to do-Dopplerize the sound signals emitted from moving sources, two kinds of signal reconstruction methods were applied. One is the forward propagation method and the other is the backward propagation method. Forward propagation method analyze the source emission time based on the instantaneous distance between sensors and the assumed source position, then the signals are reconstructed with respect to the emission time. On the other hand, the backward method uses time delay to do-Dopplerize the acquired data for the received time of reference. In both techniques, the reconstructed signal data were processed using beamforming algorithm to produce power distributions at the frequency of interest. Experiments have been carried out for varying frequencies, rotating speeds and the object distances. Forward propagation method has shown better performance in locating source position than the backward propagation method.