• The Journal of the Acoustical Society of Korea
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• v.12 no.3
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• pp.76-82
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• 1993

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.91-96
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• 2016

We have surrounded undesired living noises in our life. One of biggest noises coming out of range hood during cooking in the kitchen. A range hood is one of the most important appliances in the kitchen because it ventilates polluted air out during cooking, and maintains air quality in the kitchen. But current kitchen range hoods bring up some issues; First, the range hoods consume massive amount of standby power not in use condition. Second, current models have designed manual fan operating system with sudden onset of noise with starting. In this paper, we propose an auto control system entire processes from air ventilation to noise reduction. Our system is consist of three parts (Eco-sensors pack, Main Controller and Active Noise Controller); Eco-sensors pack detects air pollution of kitchen areas and sends the detection values to Main Controller. Main Controller determines operation of range hood by detected values. Active Noise Controller is located inside of the range hood. It received starting signals from Main Controller which elicits degrees of polluted air condition and fan operating speed from 1 to 3. Once Active Noise Controller detected the signals, it runs a ventilating fan until new value from Main Controller becomes 0. while the range hood works, A noise cancellation algorithm inside of Active Noise Controller become activated to reduce levels of noise. As a result, the proposed system clearly shows reduction in power consumption include standby power and decreases in levels of noise.

• Journal of KSNVE
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• v.11 no.3
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• pp.422-427
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• 2001

In this paper is presented passive-active noise control in a duct using a ring-type smart foam. The ring-type smart foam is comprised of a PVDF film embedded in elastic noise control foam of lining shape. The embeddedPVDF element acts as an actuator to reduce noise at lower frequencies and the foam absorbs noise at higher frequencies. By implementing an adaptive filtered-x LMS algorithm, experiments are performed to reduce both tonal and broadband noise in a duct with one end closed and the other end open.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.11-18
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• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.678-683
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• 1998

Combustion instability by thermoacoustic feedback incite strong low frequency noise and vibration which damage the system and provoke the environmental problems. Therefore, it is necessary to control the thermoacoustic oscillation. In the way of controlling the instability, active control method using adaptive algorithm is applied. In this study, active noise control method using anti-sound technique is selected, whose principle is cancelling the noise with the addition of opposite phase sound. At first, simulation is performed to confirm the stability of controller, and after that control of combustion instability is carried out to get cancellation of 20-30dB SPL.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.224-229
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• 2004

In this paper, we propose a new Active Noise Control (ANC) system using a teacher forced Blind Source Separation (BSS) algorithm. The Blind Source Separation based on the Independent Component Analysis (ICA) separates the desired sound signal from the unwanted noise signal. In the proposed system, the BSS algorithm is used as a preprocessor of ANC system. Also, we develop a teacher forced BSS learning algorithm to enhance the performance of BSS. The teacher signal is obtained from the output signal of the ANC system. Computer experimental results show that the proposed ANC system in conjunction with the BSS algorithm effectively cancels only the ship engine noise signal from the linear and convolved mixtures with human voice.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1236-1243
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• 2016

This paper presents the analysis and design of an active electromagnetic interference (EMI) filter (AEF) for the common-mode (CM) noise reduction of switching power converters. The features of the several types of AEFs are discussed and compared in terms of implementation. The feed-forward AEF with a voltage-sensing and voltage-cancellation (VSVC) structure is implemented for an LLC resonant converter to replace a multiple-stage passive EMI filter and thereby reduce CM noise. The characteristics and performance of the VSVC-type AEF are investigated through theoretical and experimental works.

• Journal of KSNVE
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• v.2 no.2
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• pp.107-116
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• 1992

An adaptive signal processing technique is implemented for the active noise cancellation of the plane acoustic wave propagating in a duct. To avoid the instability caused by the acoustic feedback from the control speaker to the detect microphone, an off-line modeling of the acoustic feedback plant is done using the FIR filter. Auxiliary path required for the filtered-x LMS algorithm is modeled as well. Before going into the experiments, a simulation is carried out under the same conditions with experiments. The simulation shows that the longer the length of the adaptive filter is, the better the results are achieved. Experiments have been carried out at lower audio frequency range (50 - 400Hz), and the results are in good agreements with those of simulation study. As a results of this adaptive noise control, around 50dB is reduced for a pure tone noise, and for a bandlimited noise with the bandwidth of 316Hz, a maximum of 30dB noise reduction is attained.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.2
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• pp.35-40
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• 1997

The hysteresis control method has been frequently used for current control of power conversion equipments or motor drive systems. This method makes the measured signal follow the reference signal by changing the control signal whenever the error signal exceeds the preset band width. In this paper, hysteresis control method with fast response characteristics is applied for active noise control to suppress acoustic noise. Both Pentium processor and sound blaster 16 are used for experimental implementation, which executes A/D, D/A conversion and also is used as operating source of loudspeaker for audible noise cancellation.

• Journal of KSNVE
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• v.7 no.3
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• pp.427-437
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• 1997

Mean active intensity based active control for the cancellation of radiated noise out of the duct exit is studied. The active intensity control strategy is drerived based on the relation of the exterior sound field out of the duct termination and interior sound field of the duct. One of the characteristics of this control strategy is that the control performance can be maintained regardless of the sensor loction, compared with the conventional local pressure control methods at either interior downstream or exterior field positions. It is also suggested that the digital filtering for the active intensity control can be achieved by time-domain filtered-x LMP (Lest-Mean-Product) adaptive algorithm. Experiments for an open-ended duct are performed to compare the active intensity control performance with conventional pressure control one. Active control experiment of local sound pressure is conducted by widely used filtered-x LMS adaptive Algorithm and active intensity control implementaion uses the derived filter d-x LMP algorithm. It is shown that the exterior sound fileds was much better observable by sensing of the active intensity than by just sound pressure. It is also demonstrated that the global control performance of external field by acoustic intensity is superior to the conventional sound pressure control performance.