• 한국음향학회지
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• 제35권3호
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• pp.216-222
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• 2016

3차원 잡음환경에서 정숙공간은 현실적으로 매우 중요한 문제이다. 본 논문은 3차원 잡음 환경에서 정숙 공간의 성능을 크기와 소음제거 면에서 향상시키는 다채널 실시간 능동소음 제어시스템의 개발과 구현을 다루고 있다. 제안된 능동소음제어 시스템은 delay-compensated Filtered-X Least Mean Square (FXLMS) 알고리즘을 적용한다. 이와 같은 시스템의 실시간 적용을 위해서 TMS320C6713 DSP 프로세서 기반으로 설계되었다. 제안된 실시간 다채널 능동소음제어기의 성능평가는 100 ~ 500 Hz 범위의 다양한 잡음 환경에서 잡음제거를 수행하고, 정숙공간에서 음압레벨(Sound Pressure Level, SPL)측정하여 평가하였다. 실험결과는 정숙공간의 크기는 만족스러우며 최대 24 dB의 소음 감쇄가 성공적으로 생성된 것을 보여준다.

• 전기학회논문지P
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• 제63권3호
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• pp.157-162
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• 2014

The active noise control(ANC) method for noise problems solution generally uses filtered-X LMS algorithms. However, Filtered-X LMS algorithms were mainly used but these had a limitation that had to measure a transfer function of secondary noise path. However, newly proposed correlation-LMS algorithms have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time. Thus Co-LMS algorithm was developed to improve the real-time implementation performance under the variable input noise such as road noise environment. In this paper, the performance of the Co-LMS is presented in comparison with that of the Filtered-X LMS algorithm. Simulation results show that active noise control using Co-LMS have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time.

• 융합신호처리학회논문지
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• 제1권1호
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• pp.7-14
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• 2000

최근 들어 초고속 정보통신기기 소자와 디지털 신호처리 기술에 힘입어 적응잡음제거 기술이 비약적인 발전을 이룩하게 되었다. 그러나 실제로 적응잡음제거, 에코제거 등의 여러 응용에서 만족할 만한 결과를 얻기 위해서는 수천이 넘는 적응필터계수가 요구된다. 계수의 수가 많은 적응 FIR 필터의 복잡한 계산 량을 줄이고 빠른 수렴을 얻기 위한 시도로 본 연구에서는 주파수영역 적응필터와 다중지연 주파수영역 적응필터 알고리즘을 실시간 처리 관점에서 서로 비교하였다. 긴 탭의 주파수영역 적응필터에서 발생하는 시간지연은 다중지연 주파수영역 적응필터를 적용하여 개선하려다. 또한 일반 적응잡음제거환경과 Cross talk 환경에 주파수영역 적응필터을 적용하여 그 알고리즘의 실시간 처리 가능성을 dSPACE 1103 보드를 통하여 확인하였다

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.321-324
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• 1997

In this paper, Active Noise Control(ANC) algorithm is proposed based on the estimated frequency estimator of the reference signal. The conventional feedforward ANC algorithms should measure the reference and use it to calculate the gradient of the squared error and filter coefficients. For ANC systems applied to aircrafts and passenger ships, engines from which reference signal is usually measured is so far from seats where main part of controller is placed that the scheme might be difficult to implement or very costly. Feedback ANC algorithm which doesn't need to measure the reference uses the error signal to update the filter and is sensitive to unexpected transient noise like a sneeze, clapping of hands and so on The proposed algorithm estimates frequencies of the desired signal in real time using adaptive notch filter. New frequency estimation algorithm is proposed with the improved convergence rate, threshold SNR and computational simplicity. Reference is not measured but created with the estimated frequencies. It has strong similarity to the conventional feedback control because reference is made from error signal. Enhanced error signal is used to update the controller for better performance under the measurement noise and impact noise. The proposed ANC algorithm is compared with the conventional feedback control.

• 한국자동차공학회논문집
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• 제13권4호
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• pp.152-159
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• 2005

The method of induction noise reduction can be classified by using passive control or active control method. However, the passive control method has a demerit to reduce the effect of noise reduction to low frequency (below) 500Hz) range and to be limited in a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used in LMS (Least-Mean-Square) algorithm because it can obtain the complex transfer function easily in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm could not match if the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to solve the problem in this study, the Moving Bandpass Filter(MBPF) was proposed and implemented. The ANC using MBPF for the reduction of the induction noise shows that more noise reduction as 4dB than without MBPF.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.249-252
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• 2000

원자력 교육원 #2(KNPEC-2) 시뮬레이터는 1980년도 중반에 웨스팅하우스에 의해 공급되어 계속 사용되어 오다가 현재 성능개선 연구가 진행 중이다. 이번 성능개선을 통해 기존의 컴퓨터 시스템(Gould MPX)와 소프트웨어의 전면 교체가 이루어지고 있으며 최적 계산 코드를 이용한 실시간 열수력 모델 (ARTS; Advanced Real-Time Thermal-Hydraulics Simulation) 개발 , 2-Group 3D 실시간 노심모델(REMARK ; REal Time Multigroup Advanced Reactor Kinetics)를 이용한 노심 주기개선 (Cycle Update) 가상현실 기술 등을 이용한 컴퓨터 교육지원 시스템(CATS: Computer Assister Training System)등 새로운 시도가 이루어지고 있으며 본 논문은 이러한 새로운 시도가 이루어지고 있으며 본 논문은 이러한 새로운 시도들 및 그 결과에 대해 기술하고 있다. 기준발전소(Reference Plant)인 영광 1호기 12주기의 노심모델로 주기개선(Cycle Update)을 위한 REMARK의 입력자료 생성을 위해 핵설계 전산체계인 APA(ALPHA-PHOENIX-ANC) 시스템의 출력으로부터 자동으로 REMARK 입력데이타를 생성하기 위한 GUI툴 개발하였다. 또 이를 이용하여 개발된 노심모델은 최적계산코드(RETRAn 3D) 의 열수력 해법을 이용하여 개발된 NSSS 열수력코드(ARTS) 와 결합(Integration) 되어 안정 및 과도 상태 시험에 사용되었으며 원자로 냉각재 펌프 정지등의 몇 가지 과도 시험 계산결과 기존 해석 결과와 잘 일치하였다 중앙제어실(MCR; Main Control Room)내의 운전원 행동만 훈련하도록 되어있는 기존시뮬레이터의 한계를 극복하기 위해 가상현실 (VR) 저작도구를 이용한 발전소 현장 내부를 표현하는 가상발전소 (Virtual Plant) 발전소 현장에 소재하여 기존 시뮬레이터의 모의한계 밖에 있던 패널을 표현한 가상판넬(Virtual Panel)등과 강의실에서 발전소 모의 훈련을 가능케 하기 위해 가상현실 기술을 이용한 컴퓨터 지원 교육훈력 시스템(CATS ; Computer Assister Training System)을 개발 중이며 일부 개발부분을 소개하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.240-241
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• 2009

The method of the reduction of the duct noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the Least-Mean-Square (LMS) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system.

• 전자공학회논문지S
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• 제34S권12호
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• pp.106-113
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• 1997

While driving, the low frequency interior noise below 200Hz causes the main component that irritates the auditory acoustic sense. But these passive control methods bring out increment in cost and weight of the vehicle and result in low efficiency. Recently, various ANC(Active Noise Control) methos to suppress the low frequency noise began to launch into application. In this study, we implemented the active noise control system for passenger vehicle to cancel the engine booming noise using DSP-based control unit, 4 micorphones, and 2 speakers. We used MEFX-LMS (Multiple Error Filtered X-Least Mean Square) algorithm since it can be easily implemented in real time. Also, MEFX-RLS algorithm was taken to enhance the suppression of the harmonic components of the engine booming noise inspite of its computational complexity. The performance of two adaptive algorithms were analyzed with experimental resutls.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.1016-1019
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• 2004

The study of the noise reduction of an automobile has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. The method of the reduction of the induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to this problem, the modified FXLMS algorithm using Moving Bandpass Filter was proposed. In this study, MBPF was implemented and use ANC for automotive intake under revived rapidly accelerated driving conditions and it was verified its performance.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.737-742
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• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.