• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3233-3235
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• 2000

A new method for HRV(heart rate variability} detection from the R-wave signal, based on the IPFM (integral pulse frequency modulation) model and its similarity to pulse position modulation, is presented. The proposed method exert lowpass filtering with a Kaiser window. In this paper, The proposed method presents a powerful, but simple, tool for investigation of HRV. It also guarantees real-time behavior, simplicity in design, and phase linearity. Even without the basic assumption of IPFM model, the new algorithm can still be used on-line and with higher performance. It is thoroughly proved that lowpass filtering is an ideal method for PSD (Power Spectrum Density) analysis of HRV.

• Journal of the Korean Society of Combustion
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• v.9 no.3
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• pp.27-35
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• 2004

Diode laser absorption sensors are advantageous because they may provide fast, sensitive, absolute, and selective measurements of species concentration. These systems are very attractive for practical applications owing to its compactness, resonable cost, robustness, and ease of use. In addition, diode lasers are fiber-optic compatible and thus enable simultaneous measurements of multiple species along a line-of-sight. Recent advances of room-temperature, near-IR and visible diode laser sources for telecommunication, optical data storage applications make it possible to be applied for combustion diagnostics based on diode laser absorption spectroscopy. Therefore, combined with fiber-optics and high sensitive detection strategies, compact and portable sensor systems are now appearing for variety of applications. The objectives of this research are to develope a new gas sensing system and to verify feasibility of this system. Wavelength and power characteristics as a function of injection current and temperature are experimentally found out. Direct absorption spectroscopy has been demonstrated in these experiments and has a bright prospect to this diode laser system.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.175-178
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• 1996

The purpose of this thesis is the propose of various signal processing algorithm for the ECG(electrocardiogram) and the design of realtime automated ECG analyzer feasible with these algorithms. The algorithms are composed of (1)filtering procedure fer the estimation and removal of baseline drift, 60Hz power line interference, and muscle artifacts (2)detection procedure of QRS complex and P wave (3)typification procedure for the pattern classification according to the morphologies (4) selection of representative beat, significant point and wave boundary decision procedure and (5) parameter extraction and diagnosis procedure. All verifications are carried out between the algorithms proposed in this paper and other algorithms already proposed by many researchers, for the objective comparison in each procedure. The efficiency of proposed algorithms are demonstrated with the aid of internationally validated CSE database and the performances of filtering procedure are compared on artificial noise signal as well as actual ECG signals with appropriate noise components. for the comparison on the performance of designed automated ECG analyzer, the diagnosis results were compared with ECG analyzer manufactered by Fukuda denshi in Japan.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.621-622
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• 2012

The thermal over-current relay or electronic motor protection relay is mostly used as the open-phase detection device of the three-phase motor or load. When the over-current or overheat of electric line is generated, it detects and operates circuit breaker, but there is the defect that the sensing speed is slow, the operation can be sometimes failed, and the precision is decreased. In order to improve these problems, this paper is proposed a new control circuit topology for open-phase protection using semiconductor devices. Therefore, the proposed open-phase protection device enhances the sensing speed and precision, and has the advantage of simple fitting in the three-phase motor control panel in the field, as it manufactures into small size and light weight.

• Journal of the Korean Society of Safety
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• v.37 no.4
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• pp.28-35
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• 2022

This study is aimed to develop a safety diagnosis system for fire pumps that detects normal and abnormal signals for the stable operation of the system. Hence, the following activities were carried out: first, a threshold value was identified for the normal operation and six abnormal operations (adherence of impeller, absence of water source, separation of pump and motor, run-stop operation, air inflow into the casing, and reverse-phase loss of the power line) reflecting changes in the current, flow and pressure of fire pumps; secondly, based on the identified signals, an algorithm capable of detecting three abnormal signals was developed and in terms of hardware, a current, pressure and flow sensor suitable for the analogue input values of NI-6009 was designed and installed. This combination of the hardware and software is applicable as a diagnosis system to ensure the stable operation of fire pumps.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.315-330
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• 2017

Halo coronal mass ejections (CMEs) originating from solar activities give rise to geomagnetic storms when they reach the Earth. Variations in the geomagnetic field during a geomagnetic storm can damage satellites, communication systems, electrical power grids, and power systems, and induce currents. Therefore, automated techniques for detecting and analyzing halo CMEs have been eliciting increasing attention for the monitoring and prediction of the space weather environment. In this study, we developed an algorithm to sense and detect halo CMEs using large angle and spectrometric coronagraph (LASCO) C3 coronagraph images from the solar and heliospheric observatory (SOHO) satellite. In addition, we developed an image processing technique to derive the morphological and dynamical characteristics of halo CMEs, namely, the source location, width, actual CME speed, and arrival time at a 21.5 solar radius. The proposed halo CME automatic analysis model was validated using a model of the past three halo CME events. As a result, a solar event that occurred at 03:38 UT on Mar. 23, 2014 was predicted to arrive at Earth at 23:00 UT on Mar. 25, whereas the actual arrival time was at 04:30 UT on Mar. 26, which is a difference of 5 hr and 30 min. In addition, a solar event that occurred at 12:55 UT on Apr. 18, 2014 was estimated to arrive at Earth at 16:00 UT on Apr. 20, which is 4 hr ahead of the actual arrival time of 20:00 UT on the same day. However, the estimation error was reduced significantly compared to the ENLIL model. As a further study, the model will be applied to many more events for validation and testing, and after such tests are completed, on-line service will be provided at the Korean Space Weather Center to detect halo CMEs and derive the model parameters.

• Fire Science and Engineering
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• v.26 no.1
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• pp.61-67
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• 2012

In the three-phase power system using the three-phase motor, when any one-phase is open-phase, the unbalanced current flows and the single-phase power supplied by power supply produces overcurrent to motor coil. As a result, the enormous damage and electrical fire can be given to the power system. Recently, the thermal over-current relay (THR) or electronic motor protection relay (EMPR) is mostly used as the open-phase detection device of the three-phase motor. When the over-current or overheat of electric line is generated, it detects and operates circuit breaker, but there is the defect that the sensing speed is slow, the operation can be sometimes failed, and the precision is decreased. In order to improve these problems, this paper is proposed a new control circuit topology for openphase protection using semiconductor devices. Therefore, the proposed open-phase protection device (OPPD) enhances the sensing speed and precision, and has the advantage of simple fitting in the three-phase motor control panel in the field, as it manufactures into small size and light weight. As a result, the proposed OPPD protects the three-phase motor, minimizes the electrical fire from openphase, and contributes for the stable driving of the power system. The performance and confidence of the proposed OPPD is confirmed by a great variety of the experiments of operation characteristic.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• Analytical Science and Technology
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• v.16 no.5
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• pp.1041-1051
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• 2003

Neutron induced prompt gamma activation analysis (PGAA) offers a nondestructive, sensitive and relatively rapid method for the determination of trace and major elements and is proven to be convenient for online analysis of minerals, metals, coal, cement, petrochemical, coating, paper as well as many other materials and products. The technique has found many uses in medicine, industry, research, security and the detection of contraband items. This report reviews the present status and future trends of the PGAA techniques. Requirements for the system are neutron source, high resolution HPGe detectors with a high-voltage power supply, an amplifier, analog-to-digital converter, and a multichannel analyzer for the detection and measurement of prompt ${\gamma}$-ray emit form the neutron capture elements. Introducing a ${\gamma}$-${\gamma}$ coincidence system also improves the quality of the ${\gamma}$-ray spectrum by suppressing the background created from the Compton scattering of high energy prompt ${\gamma}$-rays. A PGAA system using a $^{252}Cf$ neutron source is currently under construction for the on-line measurement of several elements in aqueous samples at KAERI. The system can be applied for the detection of chemical weapons and explosives as well as various narcotics.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.