• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.507-513
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• 2008

In this study, we develope an ambulatory ECG acquisition system by implementing a patch-style and wireless electrode. To alleviate the inherent noisy characteristics of the mobile signal, we apply a matched filter and concurrently detect R-peak values. Moreover, the measure for resolving shape distance is computed to estimate the relative similarity between two ECG signals and to decide whether the abnormal characteristics in ECG exist or not.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.52-55
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• 2001

This paper is to see the availability of electrical signatures as a means for evaluating the performance and monitoring mechanical anomalies of (MOVs). To estimate motor torque, two methods such as d-q frame conversion and air-gap method are suggested and estimated results are compared with measured values. The error between measured and estimated torques is within acceptable error bound with below $1\%$ under varied load. Frequency domain analysis of calculated torque has been done as well. It is shown that monitoring of peak frequency could give useful clues to detect anomalies of MOV. As results, electrical signatures at MOV motor is expected to be an available tool for estimation of motor capacity and monitoring of electrical and mechanical abnormalities.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.762-766
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• 1998

Mechanical valve is one of the most widely used implantable artificial organs, Since its failure (mechanical failures and thrombosis to name two representative example) means the death of patient, its reliability is very important and early noninvasive detection is essential requirement . This paper will explain the method to detect the thrombosis formation by spectral analysis and neural network. In order quantitatively to distinguish peak of a normal valve from that of a thrombotic valve, a 3 layer backpropagation neural network, which contains 7,000 input nodes, 20 hidden layer and 1output , was employed. The trained neural network can distinguish normal and thrombotic valve with a probability that is higher than 90% . In conclusion, the acoustical spectrum analysis coupled with a neural network algorithm lent itself to the noninvasive monitoring of implanted mechanical valves. This method will be applied to be applied to the performance evaluation of other implantable rtificial organs.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1298-1305
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• 2016

This paper presents the development of a short-circuit protection mechanism on a high voltage switch (HVS) board which is built by a series connection of semiconductor switches. The HVS board is able to quickly detect and limit the peak fault current before the signal board triggers off a gate signal. Voltage clamping techniques are used to safely turn off the short-circuit current and to prevent overvoltage of the series-connected switches. The selection method of the main devices and the development of the HVS board are described in detail. Experimental results have demonstrated that the HVS board is capable of withstanding a short-circuit current at a rated voltage of 10kV without a di/dt slowing down inductor. The corresponding short-circuit current is restricted to 125 A within 100 ns and can safely turn off within 120 ns.

• Journal of Power System Engineering
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• v.19 no.2
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• pp.33-39
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• 2015

In conducting indoor positioning by code division multiple access using spread spectrum ultrasonic waves, it is required to detect signals under the influence of near-far problem occurred by difference on signal power, caused by distance between transmitter and receiver. For discussing robustness to the problem, we verified measuring accuracy on distance from an experiment on a real space with a hardware device where our proposed method is mounted. The proposed method performs automatic signal detection by setting threshold level dynamically. As an experimental result, measurable distance were improved by the proposed method, and measurement errors were up to 50mm in distances from 1000mm to 6000mm; therefore, enough accuracy to realize self-localization or navigation for autonomous mobile robot or human was obtained.

• Journal of Sensor Science and Technology
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• v.26 no.3
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• pp.173-178
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• 2017

In this paper, we newly developed an omnidirectional receiver for visible light communication (VLC). The omnidirectional receiver was composed of a flexible solar cell attached on a cylindrical surface with its axis in vertical direction. The solar cell surface was symmetrical and showed an almost uniform receiving pattern in a horizontal plane. The maximum difference in a receiving pattern was within 7% of its peak value in a horizontal plane. This configuration is very easy to fabricate and useful in constructing wireless sensor networks in which one receiver needs to detect multiple LED signals in different directions.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.160-162
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• 2007

Switched-reluctance motor(SRM) has advantages such as simple structure, low cost and so on compared with induction motor. This paper proposes a new sensorless method that is based on the impressed voltage pulse method to estimate rotor position. Current sensors detect the SRM currents in the unenergised phases and output the voltage. The rotor position can be inferred by the above calculations when the peak values exceed a fixed threshold value.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.264-270
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• 2017

A Doppler radar sensor was applied to detect respirations and heartbeats of persons who were lying on a bed. This study is preliminary study aiming at non-contact and non-intrusive respiration and heart rate monitoring during sleep in daily life. For the experiments, 10GHz Doppler radar with patch-type antenna was used and installed on the upper right and the distance between the body and the antenna was 1 m. The results show that each signal of respiration and heartbeat is observed in each frequency band however the frequency band and the waveform vary according to the subjects and the posture. The results show that the heartbeats can be detected with the peak detection in some frequency band. This study shows the feasibility of applying the Doppler radar to detection of heartbeat and respiration during sleep and further studies about heartbeat detection algorithm are required.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.80-87
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• 1994

Fetal monitoring is a routine procedure to obtain a record of physiologic functions during pregnancy and labor. It is required to determine fetal heart frequency accurately. There are various types of fetal heart rate(FHR) determination and the most frequently applied method is transabdominal Doppler ultrasound. However, in the case of weak or noise corrupted Doppler ultrasound signals, conventional peak detections and the autocorrelation function method have many difficulties to determine FHR precisely. Also the autocorrelation function is effected by threshold level and window size. To solve these problems, the high resolution pitch determination algorinthm is introduced to detect FHR from Doppler ultrasound signals. This scheme digitally processes Doppler ultrasound signal for digital rectification, envelope detection, decimation and correlation calculation of two interconnected segments and then FHR is determined by its maximal value. Even in the case of a greatly smeared noise signal, this algorithm is able to search FHR more accurately than autocorrelation function by means of compensating FHR with a constant correlation threshold. This algorithm is simulated by 386-MATLAB on PC 486/DX and verified that it is superior to the autocorrelation function method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1108-1113
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• 2000

A condition monitoring methodology for rotating machinery is proposed based on multivariate statistical analysis. The CMS usually are using the vibration signal amplitude such as acceleration RMS, peak and velocity RMS to detect machine faults but the information is not so enough that CMS cannot perform reliable monitoring. So new parameters are added such as shape factor, crest factor, kurtosis and skewness as time domain parameters and spectrum amplitude of rotating frequency, $2^{nd}$ harmonics and gear mesh frequency etc. as frequency domain parameters. Many parameters are combined to represent the machine state using the Hotelling's $T^2$ statistics. The proposed methodology is tested in laboratory and the on-line experiment has shown that the proposed methodology offers a reliable monitoring for rotating machinery.