• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.281-287
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• 1997

In the conventional inverse modeling method for on-line modeling of the secondary path transfer function, the signal to noise ratio between the arbitrary random signal and the plant noise have to keep at -10 - -20 dB. For these reasons, the modeling can't be exactly implemented by the conventional method alone and the convergence time for modeling becomes too long. In this study, by combining the conventional inverse modeling method with an adaptive line enhancer, or with an adaptive noise canceller, a rigorous transfer functions of secondary path modeling and the control of a primary noise have been implemented simultaneously.

• 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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• 2007.11a
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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.

• 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.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.267-271
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• 1996

In this study, performance improvement of the inverse modeling as the on-line control method for the estimation, control experiment is performed. As the modeling errors is occurred in duct system arbitrarily, a case using the filtered-x LMS algorithm only as the control method, a case using tile inverse modeling method only and a case using the inverse modeling with the adaptive line enhancer are compared. The estimation errors between real secondary path transfer functions and the estimated and the control performances of primary noises with these estimated transfer functions are compared.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.283-287
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• 1996

The exhaust noise reduction of automobile with the active muffler is experimentally investigated. The control algorithm is the filtered-x LMS algorithm and the inverse algorithm with the adaptive line enhancer. Also, the control efficiency is increased with synthesized second harmonic engine frequency. In the experiment, the active muffler is applied to the end of exhaust system in automobile and the control with on-line secondary path modeling method(inverse algorithm) is compared the control of off-line secondary path modeling method. As secondary path transfer functions are changed, the experimental results show that the control performance with on-line method is more efficient than that with off-line method in the exhaust noise reduction of automobile.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.11
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• pp.1837-1843
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• 1997

This study experimentally demonstrates the use of active muffler attached to the automotive exhaust system to reduce exhaust noise. For improving the signal to noise ratio in the process of estimation of secondary path transfer functions, the on-line algorithm that conventional inverse modeling is combined with adaptive line enhancer is used as the control algorithm. Active muffler is designed that the primary noise and the control sound are propagated as a plane wave in the outlet. Therefore, the error microphone could be placed out of the tail pipe center of a high temperature and the radiation noise to the outside could be reduced in the whole area around the outlet. The control experiment for reducing exhaust noise with active muffler is implemented during run-up at no load. From the experimental results presented, compared with the conventional off-line method, the proposed on-line method is capable to acquire a reduction of exhaust noise above 5 dB in overall sound power level.