• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.165-168
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• 2000

Engine noise is one of the major causes of the interior noise, and so has been studied in various ways in recent days. Recently air induction noise has been extensively studied to reduce the engine noise. Conventional method to reduce the noise is adding several resonators to the induction system. However this causes a reduction of engine output power and an increase of fuel consumption. Thus in this study, the feasibility of applying the active noise control to the induction system is studied to the overcome the above disadvantage.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2265-2271
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• 1994

With the improvement of standard of living, requirement for comfortable and quiet environment has been increased and, therefore, there has been a many researches for active noise reduction to overcome the limit of passive control method. In this study, active noise control is performed in a duct system using intelligent control technique which needs not decide the coefficients of high order filter and the mathematical modeling of a system. Back propagation algorithm is applied as an intelligent control technique and control system is organized to exclude the error microphone and high speed operational device which are indispensable for conventional active noise control techniques. Furthermore, learning is performed by organizing acoustic feedback model, and the effect of the proposed control technique is verified via computer simulation and experiment of active noise control in a duct system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.12-20
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• 2002

To control the noise of an enclosed sound field, we built a state space model using the acoustic modal parameter description. Using the state space model, we can investigate the controllability and observability, and find an appropriate position of control speaker and microphone to control sound field of the enclosed space. We implemented LQR(linear quadratic regulator) controller and reduced order observer to reduce the first acoustic mode. Experiments showed satisfactory results of 4∼10 dB reduction of magnitude of the first acoustic mode, and support the feasibility of the proposed scheme to lightly damped acoustic field.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.565-570
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• 2000

In order to make a quiet zone, one can consider methods to generate a secondary sound field that cancels a primary sound field. Active noise control (ANC) is one of the kinds. This paper mainly deals with the issues on determining the optimal positions of control sources and sensors for making a desired quiet zone. The issues address the reason why the positions are important, how the positions are optimized, and what the measure on the optimal positions is in an uncertain sound field. It is also shown that a power control is applicable to a specific uncertain sound field. In addition, this paper shows that a control material method, which passively changes a boundary condition, is essentially found to be on the same road of ANC.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.433-438
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• 1999

This paper describes Active Noise Cancellation/Control(ANC) method that removes the information of the unnecessary noise and doesn't remove the informations of the necessary noise(warning sound, operating sound etc.) for the induced noise of the mechanical system. In this paper, the noise source Is axial fan, and the Feedback Active Noise control method that can effectively control BPF generated from the axial fan is used, and the Filtered-X LMS algorithm for adaptive algorithms is used. The experiments are executed for two case(propagating noise in the duct, emission noise for exterior free field). The part to be removed is BPF noise, and the band-pass filter not to effect to the other frequencies is used. Also, to investigate the effect of the noise reduction for human, we are compared with the results that are controlled for using Loudness before and after. As a results, we are certified that the BPF is decreased only and frequencies outside of BPF are not affected, and we acquire the reduction effects of 6.7 dB Loudness Level, then the frequency to be removed is controlled. Therefore, we can be certified that sound pressure as well as loudness can be effectively decreased for human sound quality

• Journal of KSNVE
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• v.8 no.6
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• pp.1030-1036
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• 1998

When the lateral dimensions of a duct is larger than or comparable to the wavelengths of Interest, higher order modes propagate in the duct. These modes will be radiated and produce noise. A number of sensors and actuators for control of radiating noise from the duct have to be incorporated with the number of modes which one wants to control. These considerations motivated the present study that considers a control system which has less microphones and control sources than required. In this work, by theoretical analysis, the control performance of such a kind of system is investigated in terms of sound-field variables and control system variables. The possible maximum and minimum value. mean and variance of residual acoustic potential energy are derived for the set of primary sound fields.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.763-768
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• 2012

Active window system which can reduce the environmental noises, such as traffic noise and construction noise, from an open window into a room was proposed in the previous works. The key idea of the proposed active window system was that the control sources are approximately collocated with the primary noise source in terms of the acoustic power for global noise reduction throughout the interior room. Moreover, because it is important not to intrude into the living space in the building environment, no error sensors were used and an open-loop control method using control sources at the window frame and the reference sensors outside the room was used for the proposed system. The open-loop control gain was calculated by the interior room model assumed as the semi-infinite space, and the interior sound field was estimated by Rayleigh integral equation under the baffled window model assumption. However, windows with a finite thickness should were considered for the calculation of the open-loop control gain of the active window system since these are representative of most window cases. Therefore, the finite thickness window model based on the Sgard's model was derived and the open-loop control gain using the interior sound field estimated by that model was calculated for active window system. To compare the performance of these two models, a scale-model experiment was performed in an anechoic chamber according to noise source directions. Experimental results showed that the performance for the thickness window model is better than the baffled window model as the angle with respect to the perpendicular direction is larger.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.12 s.105
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• pp.1378-1388
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• 2005

Spatial control of sound is essential to deliver better sound to the listener's position in space. As it can be experienced in many listening environments. the quality of sound can not be manifested over every Position in a hall. This motivates us to control sound in a region we select. The primary focus of the developed method has to do with the brightness and contrast of acoustic image in space. In particular, the acoustic brightness control seeks a way to increase loudness of sound over a chosen area, and the contrast control aims to enhance loudness difference between two neighboring regions. This enables us to make two different kinds of zone - the zone of quiet and the zone of loud sound - at the same time. The other perspective of this study is on the direction of sound. It is shown that we can control the direction of perceived sound source by focusing acoustic energy in wavenumber domain. To begin with, the proposed approaches are formulated for pure-tone case. Then the control methods are extended to a more general case, where the excitation signal has broadband spectrum. In order to control the broadband signal in time domain, an inverse filter design problem is defined and solved in frequency domain. Numerical and experimental results obtained in various conditions certainly validate that the acoustic brightness, acoustic contrast, direction of wave front can be manipulated for some finite region in space and time.

• 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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• 2013.04a
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• pp.379-380
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• 2013