• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.05a
• /
• pp.1080-1084
• /
• 2007

Many different methods for sound source localization have been developed. Most of them mainly depend on time delay of arrival (TDOA) or on empirical or analytic head related transfer functions (HRTFs). In real implementation, since the direct path between a source and a sensor is interrupted by obstacles as like a head or body of robot, it has to be considered the number of sensors as well as their positions. Therefore, in this paper, we present the methods, which are included sensor position problem, to localize the sound source with 4 microphones to cover the 3D space. Those are modified two-step TDOA methods. Our conclusion is that the different method has to be applied in case to be different microphone position on real robot platform.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.12
• /
• pp.950-955
• /
• 2002

The coupled finite/boundary element method is used in numerical analysis for acoustic radiation from the vibration of rectangular composite plate which is simply supported. This analysis is validated using the Wallace equation for an isotropic plate. Active control of sound fields has been tarried out using 3 pairs of piezoelectric sensor/actuator and a pair of viscoelastic material by Passive constrained layer damping treatment. The results show that the optimal placement of piezoelectric sensor/actuator and VE patch is required to control the sound fields from a vibrating composite plate.

• International journal of advanced smart convergence
• /
• v.9 no.4
• /
• pp.132-138
• /
• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.8
• /
• pp.104-109
• /
• 2019

Damage caused by wild animals such as pheasants and magpies is a problem in rural areas. A bird repellent system based on sensing and repelling farm pest animals and birds is proposed herein. This system is equipped with a bird model part on a supporting platform and comprises a sound source generator, a system control user interface, and a sensor in the center. The sensor is composed of an illuminance sensor and a PIR sensor. The illuminance sensor distinguishes between day and night, whereas the PIR sensor detects birds or wild animals and outputs them from the sound generator. The entire system can be managed easily by the user interface and system control.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.108-112
• /
• 2001

Heart sound contains rich information regarding the dynamics of the heart and the auscultation has been a first choice of routine procedures for diagnosis of the heart. However, heart sounds captured using a conventional stethoscope are not often loud or clear enough for doctors to precisely classify their characteristics, especially, under the noisy environments of the hospital. A simple auscultation device that removed shortcomings of the conventional stethoscope was constructed in the study. The device employed a polymer based adherent differential output sensor which was on contact with skin through a coupling medium and appropriated electronic circuits for signal amplification and conditioning An ordinary headphone is taken to hear the captured heart sounds and the volume can be adjusted to hear well. It is also possible that the device sends the captured heart sound signals to a PC where the signals are further processed and viualized.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.227-236
• /
• 2019

In this study, we develop a Korotkoff sound based automatic blood pressure measurement device including sensor, hardware, and analysis algorithm. PVDF-based sensor pattern was developed to function as a vibration sensor to detect of Korotkoff sounds, and the film's output was connected to an impedance-matching circuit. An algorithm for determining starting and ending points of the Korotkoff sounds was established, and clinical data from subjects were acquired and analyzed to find the relationship between the values obtained by the auscultatory method and from the developed device. The results from 86 out of 90 systolic measurements and 84 out of 90 diastolic measurements indicate that the developed device pass the validation criteria of the international protocol. Correlation coefficients for the values obtained by the auscultatory method and from the developed device were 0.982 and 0.980 for systolic and diastolic blood pressure, respectively. Blood pressure measurements based on Korotkoff sound signals obtained by using the developed PVDF film-based sensor module are accurate and highly correlated with measurements obtained by the traditional auscultatory method.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.707-708
• /
• 2012

• The Journal of the Acoustical Society of Korea
• /
• v.32 no.1
• /
• pp.32-42
• /
• 2013

Typical underwater piezoelectric spherical sensors are omni-directional, thus can measure the scalar quantity sound-pressure-magnitude only with the limitation not being able to measure the direction of the incoming wave. This paper proposes a method to simultaneously measure both the magnitude and direction of the sound wave with the spherical sensor. The method divides the piezoceramic sphere of the sensor into eight elements, and distinguishes the magnitude and direction of the sound pressure by combining the output voltage of the elements in a particular manner. Further, through the analysis of the sensitivity variation in relation to the structural parameters like radius and thickness of the piezoceramic sphere, we have suggested the way to improve the sensitivity of the vector sensor.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.6
• /
• pp.600-605
• /
• 2020

In this paper, we propose a sound event detection method using a multi-channel multi-scale neural networks for sound sensing home monitoring for the hearing impaired. In the proposed system, two channels with high signal quality are selected from several wireless microphone sensors in home. The three features (time difference of arrival, pitch range, and outputs obtained by applying multi-scale convolutional neural network to log mel spectrogram) extracted from the sensor signals are applied to a classifier based on a bidirectional gated recurrent neural network to further improve the performance of sound event detection. The detected sound event result is converted into text along with the sensor position of the selected channel and provided to the hearing impaired. The experimental results show that the sound event detection method of the proposed system is superior to the existing method and can effectively deliver sound information to the hearing impaired.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1325-1328
• /
• 2007

When we visualize the sound field radiated from a spherical sound source, spherical acoustic holography is proper among acoustic holography methods. However, there are measurement errors due to sensor position mismatch, sensor mismatch, directivity of sensor, and background noise. These errors are amplified if one predicts the pressures close to the sources: backward prediction. The goal of this paper is to quantitatively examine the effects of the error due to sensor position mismatch on acoustic pressure estimation. This paper deals with the cases of which the measurement deviations are distributed irregularly on the hologram plane. In such cases, one can assume that the measurement is a sample of many measurement events, and the cause of the measurement error is white noise on the hologram plane. Then the bias and random error are derived mathematically. In the results, it is found that the random error is important in the backward prediction. The relationship between the random error amplification ratio and the measurement parameters is derived quantitatively in terms of their energies.