• Transactions of the Korean hydrogen and new energy society
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• v.29 no.2
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• pp.163-169
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• 2018

The present article discusses about the measurement techniques of acoustic impedance that becomes one of the important acoustic characteristics of various boundaries found inside of propulsion systems. Acoustic characteristics including acoustic impedance and reflection coefficient can be often assessed and estimated by use of the two-microphone method. Theoretical expressions of acoustic impedance and reflection coefficient measured in an impedance tube are presented for both cases with mean flow and without flow, and the practical application of the method through calibration is also provided. The acoustic impedance and the reflection coefficient are related with axial locations of microphones, thermodynamic characteristics of gas inside, and the transfer function between the pressure wave measurements at multiple locations.

• 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㏈.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.123-129
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• 2017

This paper proposes a new nonnegative matrix factorization (NMF) based direction-of-arrival (DOA) estimation method for multiple sound sources using a dual microphone array. First of all, sound signals coming from the dual microphone array are segmented into consecutive analysis frames, and a steered-response power phase transform (SRP-PHAT) beamformer is applied to each frame so that stereo signals of each frame are represented in a time-direction domain. The time-direction outputs of SRP-PHAT are stored for a pre-defined number of frames, which is referred to as a time-direction block. Next, In order to estimate DOAs robust to noise, each time-direction block is normalized along the time by using a block subtraction technique. After that, an unsupervised NMF method is applied to the normalized time-direction block in order to cluster the directions of each sound source in a multiple sound source environments. In particular, the activation and basis matrices are used to estimate the number of sound sources and their DOAs, respectively. The DOA estimation performance of the proposed method is evaluated by measuring a mean absolute error (MAE) and the standard deviation of errors between the oracle and estimated DOAs under a three source condition, where the sources are located in [$-35{\circ}$, 5m], [$12{\circ}$, 4m], and [$38{\circ}$, 4.m] from the dual microphone array. It is shown from the experiment that the proposed method could relatively reduce MAE by 56.83%, compared to a conventional SRP-PHAT based DOA estimation method.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.6
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• pp.103-109
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• 2017

An increase in acoustic energy in a combustion chamber coupled with heat fluctuations from flame results in the occurrence of combustion instability. The assessment of combustion stability requires the prediction of acoustic energy variation by understanding the acoustical characteristics of flow boundaries in a combustion chamber. The present paper discusses about the characteristics of acoustic impedances at boundaries in terms of Strouhal number and summarizes theoretical analyses on the acoustic characteristics of injector-head-like configurations. Also, the details of the two-microphone measurement technique have been presented.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.28-36
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• 1995

In this paper, a double loop control model using leaky delay LMS algorithm are proposed for active noise control. The proposed double loop control model estimates the loudspeaker characteristic and the error path transfer function with on-line using only gain and acoustic time delay to reduce computation burden. The control of error signal through double loop control scheme makes the more robust cntrol system. The input signal of filter to estimate acoustic time delay is used difference between input signal of input microphone and adaptive filter output. And also, in nonstationary environments, the leaky delay LMS algorithm is employed to counteract parameter drift of delay LMS algorithm. For practical noise signal, the proposed double loop control model reduces noise level about 12.9 dB.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.238-243
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• 2008

Several experimental techniques for identifying the noise sources distributed over a moving vehicle have been developed recently and are used to design a low noise vehicle. The beamforming method, which uses phase information between several microphones to localize the source position, is proved to be one of the promising techniques applicable even under complicated test environments. In this study a beamforming algorithm is developed and applied to measure the dominant noise sources on a passenger car passing by. Unlike the acoustic signals from a stationary noise source, the sound generated from a moving source is distorted due to the Doppler effects. The information about the speed and relative position of the vehicle are used to eliminate the Doppler effects from the measured acoustic signal by using a de-Dopplerization algorithm. The noise generated from a moving vehicle can be grouped in many ways, however, tire noise and the noise generated from the engine are distinguishable at the speeds being tested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1528-1535
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• 1994

In this paper, a filtered-X LMS algorithm by new error path identification method is proposed for active noise control system. The proposed algorithm identifies accurately the error path transfer function using three microphones and the control of error signal through double loop scheme with on-line. In the computer simulation using the sinusoidal and the practical duct noise, the proposed algorithm reduces noise level about 29.1dB and 10.4dB, respectively. We can observe the improvement of about 0.5dB and 2.5dB in noise level compared with that obtained using the filtered-X LMS algorithm of Eriksson model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.102-110
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• 1999

The attenuation property of active noise control system is much dependent on the locations of transducers. It is very difficult to retermine the orfunal locations of transducers analytically, because the acoustic behaviors in active noise control systems are very complex and the acoustic parameters, fluid density, corqJlex propagation, coefficients, etc., are usually unknown. In this paper, effects of positions of transducers and of distances between transducers on attenuation properties of active noise control systems is investigated via computer simulations. Tbe transfer functions between the transducers are derived using the superposition principle for computer simulations. Computer simulations show that the acoustic monopole and dipole systems for duct noise attenuation are sensitive to variations of the transducer location.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.