• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.288-293
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• 2009

This study presents the active noise control of duct noise. The duct was excited by a steady-state harmonic and white noise force and the control was performed by one control speaker attached to surface of the duct. An adaptive controller based on filtered x LMS(FXLMS) algorithm was used and controller was defined by minimizing the square of the response of the error microphone. The assemble controller, which is called a hybrid ANC(active noise control) system, was combined with feedforward and feedback controller. The feedforward ANC attenuates primary noise that is correlated with the reference signal, while the feedback ANC cancels the narrowband components of the primary noise that are not observed by the reference sensor. Furthermore, in many ANC applications, the periodic components of noise are the most intense and the feedback ANC system has the effect of reducing the spectral peaks of the primary noise, thus easing the burden of the feedforward ANC filter.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.5
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• pp.34-40
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• 2001

In this paper, a narrowband active noise control system to reduce the noise in thermal power plants is proposed. The narrowband active noise control system contains rectangular wave generator and has a multi channel feed forward adaptive algorithms which uses the adjoint LMS algorithm. Although the effectiveness have been proven in the filtered-X LMS broadband active noise control system, this algorithm has much more computational complexity than that of narrowband active noise control system. The proposed active control system that uses the adjoint LMS algorithm, compared to the previous broadband active noise control system, not only is more effective in controlling narrowband noise but also has a more stable structure. Adaptive filter contains the FIR structure and IIR structure for primary and secondary path models. The simulation proves the effectiveness of the proposed algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.284-292
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• 2008

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, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed 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 and experimental results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.598-603
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• 2007

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, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed 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 the noise in duct system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.178-183
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• 1995

본 연구에서는 플랜트 잡음이 강한 음향 환경에서 기존의 인버스 필터링 방법에 적용 선형 증진기를 부착하여 부가경로 전달함수의 온라인 모델링과 주소음원에 대한 제어 시뮬레이션을 수행하여 다음과 같은 결과를 얻었다. 첫째로, 신호대 잡음비가 낮은 음향 환경에서 적응 선형 증진기를 이용하여 플랜트 잡음을 제거함으로써 부가경로 전달함수의 온라인 모델링을 수행할 수 있었다. 둘째로, 실제의 부가경로 전달함수가 변한 상태에서 제안된 알고리즘을 이용하여 제어 시뮬레이션을 수행하여 주소음원에 대한 제어와 정확하게 새로운 부가경로 전달함수를 예측할 수 있었다. 향후 본 연구에서 제안된 알고리즘을 실시간 어셈블리화하여 능동 소음 제어 실험한 결과를 발표할 예정이다.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2479-2482
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• 2003

능동소음제어 시스템에서 많이 사용되어 온 적응 알고리듬은 filtered-X LMS (FXLMS) 알고리듬으로, 이 알고리듬에서의 수렴속도는 필터링 된 신호에 의해서 좌우되기 때문에 FXLMS 적용시 실제 수렴성능이 저하되거나 수렴이 안 되는 경우도 발생할 수 있다. 본 논문의 목적은 변환영역에서 능동소음제어 시스템의 2차 경로 모델링을 행함으로써 전체 능동소음제어 시스템 동작의 수렴성능을 향상시키려는 것이다

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.251-257
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• 1998

Active mufflers have been mainly applied in the large industrial engine due to considerable expense for implementation, but a necessity of development has been increased by the tightened regulation of exhaust noise and the request of high power. In this study, the active muffler prototype for installing in an automobile is designed and constructed. The active muffler is designed so that the primary noise and the control sound are propagated as a plane wave in the outlet. Therefore, the error microphone could be placed outside the high temperature centers of the tail pipe, and the noise radiating to the outside could be reduced in the whole areas around the outlet. For evaluating the control performance of the prototype, the control experiments of band-pass filtered random signal and the modulation of sinusoidal signal which are generated from the primary noise speaker as practical exhaust sound level are implemented. And to investigate the radiation pattern from the outlet of tail pipe and the noise reduction level of points placed adjacent to the outlet, the sound level of adjacent points of thirty is measured.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1759-1766
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• 2010

The performance of noise attenuation of the adaptive active noise control algorithm is improved using the recurrent neural network. The FXLMS that has been frequently used in the active noise control is simple and has low computational load, but this method is weak to nonlinearity of the main or secondary path since it is based on the FIR linear filter method. In this paper, the recurrent neural network filter has been developed and applied to improvement of the active noise attenuation by simulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.133-142
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• 2014

The least mean square(LMS) algorithm has been popular owing to its simplicity, stability, and availability to implement. But it inherently has a problem of slow convergence speed, and the presence of a transfer function in the secondary path following the adaptive controller and the error path has been shown to generally degrade the stability and the performance of the LMS algorithm in applications of acoustical noise control. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used and the bi-directional Filtered-x LMS(BFXLMS) algorithm is very attractive among them, which increase the convergence speed and the performance of the controller with nearly equivalent computation complexity. In this paper, a mathematical analysis for the BFXLMS algorithm is presented. In terms of view points of time domain, frequency domain, and stochastic domain, the characteristics and stabilities of algorithm is accurately analyzed.