• Journal of KSNVE
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• v.11 no.3
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• pp.401-409
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• 2001

Passive type mufflers installed on every car haute inherent problem of lowering engine power and fuel efficiency caused by backpressure which is byproduct of complex internal structure. Recent improvements like installing a calve to change exhaust gas path depending on power requirement and rpm have only marginally improved performance. Tremendous amount of recent research works on active exhaust noise control have failed to commercialize because of numerous physical and economical reasons. In this paper, a unique seal-active muffler using difference of transmission paths is presented. In this system exhaust pipe is divided into two and joined again downstream. Exhaust noise is reduced by destructive interference when two-divided noise join again with transmission paths'difference which is half of the wavelength of a main noise frequency. One divided path has a sliding mechanism to change length thereby transmission path length difference is adjusted to entwine rpm change. The proposed system has minimal backpressure and does not need a secondary sound source like a speaker so it can overcome many problems of failed active noise control methods. We have verified proposed system's superior performance by simulation and comparison experiment with passive mufflers.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1725-1731
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• 2012

In this paper, experiments were conducted to validate the importance and necessity of modeling. The modeling was performed using 120Hz and 280Hz noise of KTX main interior noise frequency. After the modeling, In order to solve the system instability by the additional path that exists between the control speaker and the error microphone, the secondary path was estimated. Next, simulations were performed to verify the modeling's necessity and importance. Thought the simulation results, we confirmed that the system with the modeling is more effective for noise reduction than without the modeling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.39-40
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• 2007

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.251-260
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• 2009

In this paper, we studied on an attenuation effect of automobile exhaust noise according to the direction of canceling speaker in ANC system. Automobile exhaust noise was recorded at 800 rpm, 3500 rpm and 5000 rpm of a diesel engine. Directions of canceling speaker can be set to $30^{\circ}$, $90^{\circ}$ and $150^{\circ}$ against the primary noise flow by acrylic ducts to be made for the experimentation. DSP board with TMS320C6416 chip of Texas Instrument Co. used to control the ANC system. The algorithm of this ANC system applied the Filtered-x-LMS algorithm that is modified to compensate for a property of DSP input signal and the secondary-path effect. As an experiment result, the direction of canceling speaker was proved to influence the reduction effect of noise. The $150^{\circ}$ duct in the attenuation effect of noise showed a better result than the $90^{\circ}$ or $30^{\circ}$ duct.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1E
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• pp.56-63
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• 1992

The poblem of active oise control has been analysed using a adaptive signal processing technique. In this methods, the adaptive signal processor or model predicts the primary sound wave travelling along the acoustic plant and generates the secondary source 180° out of phase which attempts to attempts to attenuate the undesired noise by destructive interference. In the solutions presented here, acoustic propagation delay is considered as a part of the model which used the FIR filter. The effects of error path and auxiliary path transfer functioin are anayzed and a new on=-line technique for error path modeling, adaptive delayed inverse modeling is presented. In this study, using these new concepts, our system can more reduce the noise level in duct to 5dB-15dB than only using LMS algorithm system.

• Journal of Power Electronics
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• v.19 no.2
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• pp.403-412
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• 2019

Aiming at the problems of large dv/dt and di/dt in traditional single-ended converters and high electromagnetic interference (EMI) noise levels, a single-ended isolated converter using the secondary resonance technique is proposed in this paper. In the proposed converter, the voltage stress of the main power switch can be reduced and the voltage across the output diode is clamped to the output voltage when compared to the conventional flyback converter. In addition, the peak current stress through the main power switch can be decreased and zero current switching (ZCS) of the output diode can be achieved through the resonance technique. Moreover, the EMI noise coupling path and an equivalent model of the proposed converter topology are presented through the operational principle of the proposed converter. Analysis results indicate that the common mode (CM) EMI noise and the differential mode (DM) EMI noise of such a converter are deduced since the frequency spectra of the equivalent controlled voltage sources and controlled current source are decreased when compared with the traditional flyback converter. Furthermore, appropriate parameter selection of the resonant circuit network can increase the equivalent impedance in the EMI coupling path in the low frequency range, which further reduces the common mode interference. Finally, a simulation model and a 60W experimental prototype of the proposed converter are built and tested. Experimental results verify the theoretical analysis.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.299-301
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• 1992

The adaptive active noise control algorithm for duct noise attenuation is considered. A new algorithm to estimate the secondary path transfer function using multiple models is presented. The computational burden of the proposed algorithm is much smaller than the existing methods, so it could be applied to the multi-channel cases. Computer simulations were done to show the effectiveness of the proposed algorithm in a duct case.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1964-1966
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• 2001

Active Noise control(ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. This research presents ANFIS (Adaptive Network Fuzzy Inference System) controller for adaptively noise cancelling in a duct. ANC system generates secondary control sound pressure with same amplitude and with opposite phase as noise to be eliminated. ANFIS controller is trained to optimize its parameters for adaptively cancelling noise. That is ANFIS train its parameters by gradient descent and LSE method so called hybrid method. This paper present ANFIS in active noise control which provides an improvement convergence speed and limitation of linearity condition. It can model nonlinear functions of arbitrary complexity and ANFIS can construct an input-ouput mapping based on both human knowledge in the form of Takagi and Sugeno's fuzzy if-then rules and stipulated input-output data pairs. This paper also shows that the proposed ANFIS active noise control system successfully cancelled noise.

• Journal of KSNVE
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• v.10 no.6
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• pp.941-948
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• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.