• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.375-377
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.30-32
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be Improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• 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 KSNVE
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• v.6 no.6
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• pp.851-856
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• 1996

The active noise cancellation system showing the effective convergence and stability has been studied by simplifying the controller structures using the weighting factors of control error path to the multi-channel filtered-x LMS algorithm which needs a lot of calculations and the performance has been verified experimentally. Besides, to implement the system performance in a vehicle cabin, experimental work for selecting the suitable numbers and positions of the microphones and speakers was accomplished. Effectively combining a TMS 320C 31 main processor conducting real number calculations and having various functions with other components, the purpose-built system board for active noise cancellation has been designed and with this board, car active noise cancellation system showing maximum stable 10dB noise reduction has been obtained at the car idling conditions above 3000rpm range.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.775-780
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• 1994

A new simple method to formulate the adaptive algorithm to control the coefficients of FIR filter is introduced. The filter is used in the active noise control system. The introduced algorithm includes the LMS algorithm as a special case. The validity of the theoretical result is confirmed by the computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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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.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.332-334
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• 1994

This paper proposes a robust active noise control (ANC) system. The system constructs filter with a standard model. An adaptive litter, connected to the system in parallel, compensates the modeling error. When the adaptive filter does not work, the proposed system is robust while the conventional system loses the noise control capability. But proposed ANC system shows that the performance is comparable with that of the conventional ANC system under normal conditions.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.9
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• pp.694-701
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• 2002

In this paper, through the study on locations of structural transducers for active control of the radiated sound from the vibrating plate, the active structural acoustic control (ASAC) system is proposed. And, for the evaluation of the proposed location, the experiment of the active structural acoustic control is implemented using the multi-channel filtered-x LMS algorithm and an additional filter (Acoustic Prediction Filter) to estimate the radiated sound using the acceleration signals of the plate. The structural transducers are piezoceramic actuator (PZT) and accelerometer. PZT is used as an actuator to reduce the vibration and the radiated sound. To maximize the control performance, each PZT actuator is located at the position that has the largest control sensitivity of the plate bending moment in the direction of x and y coordinates and the optimal PZT location is validated experimentally. Also, to find the acoustic prediction filter accurately, two accelerometers are located at the positions that have the largest radiation efficiencies of the plate, and the proposed locations are validated by simulation using the Rayleigh integral. The multi-channel filtered-x LMS algorithm is introduced to control a complex 2-D structural vibration mode. Finding the locations of structural transducers for active structural acoustic control of the radiated sound, the active structural acoustic control (ASAC) system can be presented and validated by experiments using a real time control system.

• Journal of Korean Society of Disaster and Security
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• v.16 no.3
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• pp.45-56
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• 2023

In this study, the application of ANC (Active Noise Control) technology to address inter-floor noise was explored. To achieve this, an ANC system was developed to manage the heavy impact sound within the frequency range of 40 to 500 Hz. The ANC system utilized an adaptive filter employing a feedforward approach based on the Fx-LMS algorithm. To set up the ANC system, a comprehensive analysis of various variables within the system was performed using computational simulations. This process enabled the identification of optimal filter settings and system configuration arrangements. In addition, the ANC system was implemented in the inter-floor noise test room at the Korea Conformity Laboratories (KCL). Through a certified standard testing procedure, it was confirmed that the ANC system led to a 4 dB reduction in inter-floor noise when the system was activated compared to when it was turned off. The results of this study indicate that the developed ANC system has an effect significant enough to elevate the rating criteria by one level for heavy impact sound.