• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2417-2419
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• 1998

In this paper, a new active noise control technique which combines a hybrid active noise control technique and a subband active noise control technique is presented. To reduce the computational burden the active noise control system, a weighted hybrid control technique is applied. This algorithm shows higher stability and good noise attenuation property in either broad band or narrow band active noise control systems in HVAC ducts. Computer simulations were performed to show the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.547-554
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• 2007

This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.670-672
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• 2014

In this study, we investigate active control of noise transmitted through a window of enclosures minimizing the acoustic power. To reduce noise of the enclosures, passive methods with absorbing material are generally used. The passive methods, however, are limited use due to the vantilation windows. In this case, these windows are path of noise leakage. Feedforward active noise control technology is applied to minimize the sound power from the enclosure. The feedforward controller is implemented with FIR filter based on the transfer functions calculated numerically. The controller reflects the delay due to FIR filter. The noise transmitted through the window is actively controlled, and the reduction of the power is obtained by 15dB.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.29-37
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• 1994

Active noise control of random noise which propatate in the vehicle cabin as a form of spherical wave is the target of this study. In the previous study, the adaptive algorithm for adaptive controller is presented for the application in active noise control system. And for the preliminary study of adaptive active noise control in vehicle cabin as a real system, a computer simulation is performed on the effectiveness of the adaptive algorithm in the amplitude of the pressure fluctuation. This work studies the implementation of multi-channel feedforward adaptive algorithm for the reduction of the noise inside a vehicle cabin using a number of secondary sources derived by adaptive filtering of reference noise source. Multi-channel adaptive feedforward algorithm are verified in numerical simulation and semi-experimental justification of developed system is made on a domestic passenger car. In the results of semi-experimental study, the noise of specific region in the interior of automobile are reduced for the appreciabe sound pressure level in the operating engine rpm and finally this study suggests the capabilities of the real time active noise control in 3 dimensional acoustic fields.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.889-898
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• 2008

In this study, analyze the status and problem of a noise and vibration control laws of it through the questionnaire. The method of survey was made by questionnaires which were the civil worker 138 persons and civil servant 132 persons. Based on this survey, we suggest a improvement of the noise and vibration control laws.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.710-711
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• 2014

In many cases, periodic noise occurs because most applications include motors, compressors and so on which have reciprocating motion. The noise usually contains tones at the fundamental frequency and at several higher harmonic frequencies in practice. For this type of noise, we developed a frequency-domain active noise control algorithm and determined that it's effective. However, the performance deteriorated for quasi-periodic noise. In this paper, we develop compensated frequency-domain active noise control algorithm for quasi-periodicity. And then, we implement computer simulation and compare the performance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.1
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• pp.62-68
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• 2014

Recently, MRI(magnetic resonance imager) scanner is continually used for medical diagnosis and many biomedical researches. When it operates, however, intense noise is generated. The SPL(sound pressure level) of the noise approaches 130 dB especially in 3 T(Tesla) MRI. Meanwhile, more than 3 T MRI scanners have been developed to get higher-resolution images, so louder noise is expected in the future. The intense noise makes patients feel nervous and uncomfortable. Moreover, it could possibly cause hearing loss to patient in extreme cases. For this reason, some active noise control systems have been researched. One of them used feedback Filtered-X LMS(FXLMS) algorithm which is able to control only narrowband noises and possible to diverge in severe case. In this paper, we determine the property of MRI noise. Using the property, we applied a method of open-loop and adaptive control for reducing MRI noise at target point inside bore. We verified performance of the method with computer simulation and preliminary experiment. The results demonstrate that the method can effectively reduce MRI noise at target point.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.911-917
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• 2005

There were many attempts to reduce noise behind the noise barrier using active control techniques. Omoto(1993) Shao(1997) and Yang(2001) tried to actively control the diffracted noise behind the barrier and main concerns were about the arrangement methods for the control sources. Baek (2004) tried to get better results using the simulated annealing method and the sequential searching technique. The main goal of this study is to develop and compare the performance of several optimization techniques including those mentioned above, hybrid version of simulated annealing and genetic algorithm for the optimal control source positions of active noise barrier system. The simulation results show fairly similar performance lot the small size of searching problem. However, as the number of control sources are increased, the performance of simulated annealing algorithm and genetic algorithm are better than the others. Simulations are also made to show the performance of the selected optimal control source positions not only at the receiver position but at the surrounding volume of the receiver position and plotted the noise reduction level in 3-D.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.