• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.969-974
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• 2007

In this paper, a beamforming technique is introduced to measure the acoustic impedance at both normal and oblique incidence in a free field. The acoustic impedance is obtained by separating incident and reflected signals using the adaptive nulling method which is one of the various beamforming algorithms. To obtain better results, pressure vector commonly used in array signal processing is replaced with the transfer function vector between each microphone and the white Gaussian noise is suppressed by a wavelet shrinkage technique. The experiments conducted in a semi-anechoic room show that the proposed method is efficient and accurate in measuring the acoustic impedance of sound absorbing materials under a free field condition.

• New & Renewable Energy
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• v.5 no.2
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• pp.25-30
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• 2009

The wind tunnel test to identify the acoustic noise source position of the wind turbine blade was conducted in KARI low speed wind tunnel. Microphone array and time-domain beamforming methodology was applied to this study. To reduce the data processing time, a modified beamforming method with a criteria between calculation time step and grid size for rotating angle in the cylinderical coordinate system was proposed. The test results shows that the data processing time to identify the noise source position was reduced to 20% compared with conventional method. And the dominant noise source of the blade moves from inboard to blade tip as the frequency increases.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.3-10
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• 2000

This paper proposes acoustic holographic measuring system to estimate an absolute position of sound source. Using the measured signals, the estimation of the position is calculated by the Cross-spectrum algorithm of the beamformed signal and a linear arrayed microphone's signals. As the results of comparing the reference microphone method with beamforming method through the measurement of sound field, the beamforming acoustic holographic method is progressed above 20 percent than that of a reference microphone method in the resolution, and the utility of the proposed system could be confirmed.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.645-651
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• 2003

This paper presents a revised beamforming inversion method for ocean acoustic tomography. In the proposed inversion method, the relation between group velocity and phase velocity that are the characteristics of the waveguide is used for the inversion of perturbed sound speed profile. The group velocity and phase velocity can be expressed as a function of the travel time and arrival angle of the received signals that are analyzed by the beamforming signal processing. This paper illustrates the simulated results of inversion for the fluctuated sound speed profile of the East Korea Sea and we found the applicability of revised beamforming inversion method to range independent ocean.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.395-402
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• 2016

In this paper, a wideband adaptive beamforming approach for an acoustic vector sensor linear array is presented. It is a very important issue to estimate the stable covariance matrix for adaptive beamforming. In the conventional wideband adaptive beamforming based on coherent signal-subspace (CSS) processing, the error of bearing estimates is resulted from the focusing matrix estimation and the large number of data snapshot is necessary. To alleviate the estimation error and snapshot deficiency in estimating covariance matrix, the steered covariance matrix method in the pressure sensor is extended to the vector sensor array, and the subarray technique is incorporated. By this technique, more accurate azimuth estimates and a stable covariance matrix can be obtained with a small number of data snapshot. Through simulation, the azimuth estimation performance of the proposed beamforming method and a wideband adaptive beamforming based on CSS processing are assessed.

• Smart Structures and Systems
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• v.29 no.6
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• pp.777-783
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• 2022

Even though several deep learning-based methods have been applied in the field of acoustic source localization, the previous works have only been conducted using the two-dimensional representation of the beamforming maps, particularly with the planar array system. While the acoustic sources are more required to be localized in a spherical microphone array system considering that we live and hear in the 3D world, the conventional 2D equirectangular map of the spherical beamforming map is highly vulnerable to the distortion that occurs when the 3D map is projected to the 2D space. In this study, a 3D deep learning approach is proposed to fulfill accurate source localization via distortion-free 3D representation. A target function is first proposed to obtain 3D source distribution maps that can represent multiple sources' positional and strength information. While the proposed target map expands the source localization task into a point-wise prediction task, a PointNet-based deep neural network is developed to precisely estimate the multiple sources' positions and strength information. While the proposed model's localization performance is evaluated, it is shown that the proposed method can achieve improved localization results from both quantitative and qualitative perspectives.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.200-204
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• 2005

The use of beamforming method and de-Dopplerization technique was applied in studying the rotating sound sources. Acoustic analysis of a moving sound source required that the measured sound signals be do-Dopplerized and restored as of the original emission signals. Two main issues of the signal reconstruction in time domain are addressed herein: First, to remove Doppler effect from the measured data and to restore the original emission data of the moving source. The difference of the time domain beamforming from the frequency domain beamforming was mentioned. Also, the time domain beamforming method is deployed in the test and the comparisons were made to the frequency domain results. The time domain signal reconstruction was numerically simulated prior to the application. To validate the de-Dopplerization Performance, the rotating Point sources were examined and localized by the use of a phased array of microphone. The application of prop-rotor was conducted in a hovering condition. The results of reconstructing time signals of rotating sources and its locations were shown in the power distribution maps. In the prop-rotor measurements, the acoustic source locations were successfully verified in varying positions for different frequencies of interest.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.949-958
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• 2018

A voice recognition control system is a system for controlling a peripheral device by recognizing a voice. Recently, a voice recognition control system have been applied not only to smart devices but also to various environments ranging from IoT(: Internet of Things), robots, and vehicles. In such a voice recognition control system, the recognition rate is lowered due to the ambient noise in addition to the voice of the user. In this paper, we propose a dual channel acoustic beamforming hardware architecture for MEMS(: Microelectromechanical Systems) microphones to eliminate ambient noise in addition to user's voice. And the proposed hardware architecture is designed as ASIC(: Application-Specific Integrated Circuit) using TowerJazz $0.18{\mu}m$ CMOS(: Complementary Metal-Oxide Semiconductor) technology. The designed dual channel acoustic beamforming ASIC has a die size of $48mm^2$, and the directivity index of the user's voice were measured to be 4.233㏈.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.403-409
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• 2016

Traditional towed line arrays using omni-directional sensor suffer from the well known port-starboard ambiguity, because the direction of arrival is determined by conic angle. The operational method and structure of the sensor arrays method have been proposed to solve this problem. Recently, a lot of research relating to the acoustic vector sensor are studied. In this paper, we study port-starboard discrimination for roll of acoustic vector sensor array. With one omni-directional sensor and three orthogonally-placed directional sensors, an acoustic vector sensor is able to measure both the acoustic pressure and the three directional velocities at the point of the sensor. The wrong axis due to the roll at directional sensors can degrade performance of beamforming. We investigate port-starboard discrimination for roll of sensor array and confirm the validity of performance of beamforming with compensated the roll.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.838-839
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• 2013

In this paper, optimum beamforming method using spherical microphone array is presented. Beamforming method has been recognized as an important study in localizing sound sources or visualizing acoustic fields in three-dimensional space. Its geometrical arrangement of sensors in space enables to process array signal to analyze the fields of interest by steering array response in three-dimensional.