• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.975-985
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• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• Journal of Sensor Science and Technology
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• v.28 no.6
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• pp.371-376
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• 2019

We have developed an acoustic resonance inspection system to inspect the welding defects in the mechanical parts fabricated using friction stir welding method. The inspection system was consisted of a DAQ board, a microphone sensor, an impact hammer, and controlled by a PC software. The system was developed to collect and analyze the sound signal generated by hitting the sample with an impact hammer to determine whether it is defective. In this study, 100% welded good samples were compared with 95%, 90%, and 85% welded samples, respectively. The variation of the completeness in welding did not affect the visual appearance in the samples. As a result of analyzing the natural frequencies of the good samples, the five natural frequency peaks were identified. In the case of the defective samples, the frequency change was observed. The welding failure detection time was fast enough to be only 0.7 seconds. Employing our welding defect inspection system to the actual industrial field will maximize the efficiency of quality inspection and thus improve the productivity.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.20-25
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• 2012

The oscillometric method and Korotkoff sound method are the most common ways to measure the blood pressure. A new automatic blood pressure measurement device, which uses both oscillometric method and Korotkoff method, was developed. A pressure sensor was used to obtain cuff pressure and oscillation signal, and a microphone was used to detect Korotkoff sounds. Forty-five measurements from fifteen subjects were used for analysis. Correlation coefficients between the traditional auscultatory method and Korotkoff sound method were 0.9820 and 0.9721 for the systolic and diastolic blood pressure values, respectively. Standard deviations of differences for the systolic and diastolic blood pressure values were 1.3019 and 1.4495, respectively. Correspondingly, correlation coefficients between the traditional auscultatory method and oscillometric method using newly developed algorithm were 0.9651 and 0.9136 for the systolic and diastolic blood pressure values, with the standard deviations of 1.42 and 1.73, respectively. The results showed that the newly developed algorithm for oscillometirc method provide accurate blood pressure values, moreover, Korotkoff sound method using microphone provides even higher accuracy. Therefore, a new automatic device which utilizes both oscillometric method and Korotkoff sound method would provide the accurate and reliable blood pressure values.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.141-146
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• 2015

In order to classify and analyze variously compounded sound and voice signal from FPGA microphone, there are numerous systems to detect abnormality signal, however, they have a lot of problems to implement the abnormality signal detection efficiently and effectively. Therefore, we proposed a method that implements classifying the signal effectively and outputting the detection efficiently based on the algorithm applied FIFO structure (First-in First-out) by using microphone sensor which able to input the sound signal, and statistical variance and coefficient of variation (CV). The result showed 96.3% detection when the experiment was performed more than 100 times with the proposed algorithm applied system.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.7
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• pp.1030-1037
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• 2013

Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.81-84
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• 2007

In this paper, fiber optic sound and vibration monitoring sensor which is latticed shape structure based on Sagnac interferometer is fabricated and tested in laboratory conditions. To detect external vibrations surface mounted fibers on the latticed steel wire fence with a dimension of 170cm by 180cm is used. To detect external sound frequency the tightened fiber optic itself wire netting fence with a dimension of 50cm by 50cm is used. Experiments for the detection of the excited vibration and sound signals were performed. A small vibrator induced external vibration signal and it is applied to the latticed structure in the range of 100Hz to several kHz. External sound signal applied to the fiber optic sensor net using non-directional sound speaker. The detected optical signals were compared and analyzed to the detected both accelerometer and microphone signals in the time and frequency domain. Based on the experimental results, distributed fiber optic sensor using Sagnac interferometer detected effectively external vibration and sound signal and had a good performance. This system can be expanded to the monitoring of a significant system and to the structural health monitoring system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.481-485
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• 2014

In service robots, a number of human movements are analyzed using a variety of sensors. Vibration signals from walking movements of a human provide useful information about the distance and the movement direction of the human. In this paper, we measure the intensity of vibrations and detect both human walking pace and direction. In our experiments, vibration signals detected by microphone sensors provide good estimation of the distance and direction of a human movement. This can be applied to HRI (Human-Robot Interaction) technology.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.390-397
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• 2003

We propose a humanoid active audition system which detects the direction of sound using just three microphones. Compared with previous researches, this system which has a simpler algorithm and less microphone shows better performance. Moreover, it uses the fuzzy logic system to remove the reflective sound and makes the resultant improvement of confidence. In order to verify our system's performance, we install the proposed active audition system to the home service robot, called hombot II, which has been developed at the KIST(Korea Institute of Science and Technology), and confirm its excellent performance through the experiment.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.101-107
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• 1997

In order to detect and suppress chatter in turning process, a stability control methodology was studied through manipulation of spindle speeds regarding to chatter frequencies, The chatter frequency was identified by monitoring and signal processing of sound pressure during turing on a lathe. The stability control methodology can select stable spindle speeds without knowing a prior knowledge of machine compliances and cutting dynamics. Reliability of the developed stability control methodology was verified through turing experiments on an engine lathe. Experimental results show that a microphone is an excellent sensor for chatter detection and control .

• Proceedings of the KSPS conference
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• 2006.05a
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• pp.127-130
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• 2006

This paper suggests an algorithm that can estimate the direction of the sound source with three microphones arranged on a circle. The algorithm is robust to microphones' gains because it uses only the time differences between microphones. To make this possible, a cost function which normalizes the microphone's gains is utilized and a procedure to detect the rough position of the sound source is also proposed. Through our experiments, we obtained significant performance improvement compared with the energy-based localizer.