• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.1
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• pp.46-54
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• 2008

In this paper, a low-cost impedance spectroscopy system(LCISS) suitable for modeling the electrochemical power sources such as fuel cells, batteries and supercapacitors is designed and implemented. Since the developed LCISS is composed of simple sensor circuits, commercial data acquisition board and LabVIEW software, a graphic language with powerful HMI(Human-Machine Interface), it is expected ta be widely used in substitution of the expensive EIS instruments. In the proposed system, the digital lock-in amplifier is adopted to achieve the accurate measurements even in the presence of the high level of noises. The developed hardware and software is applied to measure the impedance spectrum of the Ballard Nexa 1.2kW proton exchange membrane fuel cell stack and an equivalent impedance model is proposed based on the measurement results. The validity of the proposed equivalent circuit and the developed system is proven by the measurement of the ac power losses of the PEM fuel celt stack by the ripple current.

• Journal of Sensor Science and Technology
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• v.6 no.4
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• pp.258-264
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• 1997

$YBa_{2}Cu_{3}O_{7}$ single layer dc SQUID magnetometers, prepared on $1\;cm^{2}\;SrTiO_{3}$ substrates, have been fabricated and characterized. Based on the analytical description, a SQUID magnetometer design having a 8.5 mm pickup coil with 2.6 mm linewidth, and a SQUID inductance Ls = 50 pH with $3\;{\mu}m$ Josephson junctions is presented. The devices showed a maximum modulation voltage depth of $65\;{\mu}V$ and a magnetic field noise of 0.6 pT /$\sqrt{Hz}$ at 1 Hz. Clear traces of human magnetocardiogram could be obtained with the SQUID magnetometer operating at 77 K.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.376-385
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• 2017

In this paper, a method for the estimation of structural displacements using structure's mode shapes and accelerations is suggested to reduce the disadvantages of acceleration time integration method. Acceleration time integration method requires accurate information on initial conditions, and errors caused by noise can be accumulated during time integration. To avoid these problems, the method for the estimation of structural displacements based on mode superposition method is developed and two vibration experiments for cantilever beam are conducted to verify this method. Static displacements and dynamic displacements of beam structure are estimated using measured accelerations from experiments and mode shapes of cantilever beam, and they are compared with measured displacements using laser displacement sensor. From these results, the validity and usefulness of this method are verified.

• Progress in Superconductivity
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• v.14 no.1
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• pp.1-10
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• 2012

We fabricated a closed coils by using resistive-joint method and the joint resistance of the coils were estimated by field decay technique in liquid nitrogen. We used the Runge-kutta method for the numerical analysis to calculate the decay properties. The closed coil was wound by $(Bi,Pb)_2Sr_2Ca_2Cu_3O_x$/Ag tape. Both ends the tape were overlapped and soldered to each other. The current was induced in a closed coils by external magnetic flux density. Its decay characteristic was observed by means of measuring the magnetic flux density generated by induced current at the center of the closed coil with hall sensor. The joint resistance was calculated as the ratio of the inductance of the loop to the time constants. The joint resistances were evaluated as a function of critical current of loop, contact length, sweep time, and external magnetic flux density in a contact length of 7 cm. It was observed that joint resistance was dependent on contact length of a closed coil, but independent of critical current, sweep time, and external magnetic flux density. The joint resistance was measured to be higher for a standard four-probe method, compared with that for the field decay technique. This implies that noise of measurement in a standard four-probe method is larger than that of field decay technique. It was estimated that joint resistance was $8.0{\times}10^{-9}{\Omega}$ to $11.4{\times}10^{-9}{\Omega}$ for coils of contact length for 7 cm. It was found that 40Pb/60Sn solder are unsuitable for persistent mode.

• Nuclear Engineering and Technology
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• v.39 no.3
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• pp.193-206
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• 2007

The Korea Atomic Energy Research Institute has developed an advanced fast reactor concept, KALIMER-600, which satisfies the Generation IV reactor design goals of sustainability, economics, safety, and proliferation resistance. The concept enables an efficient utilization of uranium resources and a reduction of the radioactive waste. The core design has been developed with a strong emphasis on proliferation resistance by adopting a single enrichment fuel without blanket assemblies. In addition, a passive residual heat removal system, shortened intermediate heat-transport system piping and seismic isolation have been realized in the reactor system design as enhancements to its safety and economics. The inherent safety characteristics of the KALIMER-600 design have been confirmed by a safety analysis of its bounding events. Research on important thermal-hydraulic phenomena and sensing technologies were performed to support the design study. The integrity of the reactor head against creep fatigue was confirmed using a CFD method, and a model for density-wave instability in a helical-coiled steam generator was developed. Gas entrainment on an agitating pool surface was investigated and an experimental correlation on a critical entrainment condition was obtained. An experimental study on sodium-water reactions was also performed to validate the developed SELPSTA code, which predicts the data accurately. An acoustic leak detection method utilizing a neural network and signal processing units were developed and applied successfully for the detection of a signal up to a noise level of -20 dB. Waveguide sensor visualization technology is being developed to inspect the reactor internals and fuel subassemblies. These research and developmental efforts contribute significantly to enhance the safety, economics, and efficiency of the KALIMER-600 design concept.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.464-464
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• 2010

A few years ago, for maintaining high stability and production yield of production equipment in a semiconductor fab, on-line monitoring of wafers is required, so that semiconductor manufacturers are investigating a software based process controlling scheme known as virtual metrology (VM). As semiconductor technology develops, the cost of fabrication tool/facility has reached its budget limit, and reducing metrology cost can obviously help to keep semiconductor manufacturing cost. By virtue of prediction, VM enables wafer-level control (or even down to site level), reduces within-lot variability, and increases process capability, $C_{pk}$. In this research, we have practiced VM on $SiO_2$ etch rate with optical emission spectroscopy(OES) data acquired in-situ while the process parameters are simultaneously correlated. To build process model of $SiO_2$ via, we first performed a series of etch runs according to the statistically designed experiment, called design of experiments (DOE). OES data are automatically logged with etch rate, and some OES spectra that correlated with $SiO_2$ etch rate is selected. Once the feature of OES data is selected, the preprocessed OES spectra is then used for in-situ sensor based VM modeling. ICP-RIE using 葰.56MHz, manufactured by Plasmart, Ltd. is employed in this experiment, and single fiber-optic attached for in-situ OES data acquisition. Before applying statistical feature selection, empirical feature selection of OES data is initially performed in order not to fall in a statistical misleading, which causes from random noise or large variation of insignificantly correlated responses with process itself. The accuracy of the proposed VM is still need to be developed in order to successfully replace the existing metrology, but it is no doubt that VM can support engineering decision of "go or not go" in the consecutive processing step.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.811-816
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• 2011

In this paper, we analysis to consider the performance of PSPM (Phase Shift Pulse-position Modulation), the one of the low power communication technique, in near-field underwater sound channel by sea trial. PSPM is a QPSK(Quadrature Phase Shift Keying) modulation combined with PPM(Pulse Position Modulation) for low power communication in WBAN(Wireless Body Area Network). It is known that the bandwidth efficiency of PSPM is lower than conventional PSK but the power efficiency increases. In this paper, we will analyze the BER performance of PSPM using data acquired from the sea trials. The BER of QPSK was $6.04{\times}10^{-2}$, PSPM was $3.5{\times}10^{-1}$. Also, PSNR of QPSK was 9.37 dB and in case of PSPM was 9.11 dB.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.72-80
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• 2019

In this task, the tool dynamometer design and manufacture, and the Ansys S/W structural analysis program for tool attachment that satisfies the cutting force measurement requirements of the tool dynamometer system are used to determine the cutting force generated by metal cutting using 3-axis static structural analysis and the LabVIEW system. The cutting power in a cutting process using a milling tool for processing metals provides useful information for understanding the processing, optimization, tool status monitoring, and tool design. Thus, various methods of measuring cutting power have been proposed. The device consists of a strain-gauge-based sensor fitted to a new design force sensing element, which is then placed in a force reduction. The force-sensing element is designed as a symmetrical cross beam with four arms of a rectangular parallel line. Furthermore, data duplication is eliminated by the appropriate setting the strain gauge attachment position and the construction of a suitable Wheatstone full-bridge circuit. This device is intended for use with rotating spindles such as milling tools. Verification and machining tests were performed to determine the static and dynamic characteristics of the tool dynamometer. The verification tests were performed by analyzing the difference between strain data measured by weight and that derived by theoretical calculations. Processing test was performed by attaching a tool dynamometer to the MCT to analyze data generated by the measuring equipment during machining. To maintain high productivity and precision, the system monitors and suppresses process disturbances such as chatter vibration, imbalances, overload, collision, forced vibration due to tool failure, and excessive tool wear; additionally, a tool dynamometer with a high signal-to-noise ratio is provided.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.2
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• pp.71-83
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.37-45
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• 2020

The development process of deep learning is an iterative task that requires a lot of manual work. Among the steps in the development process, pre-processing of learning data is a very costly task, and is a step that significantly affects the learning results. In the early days of AI's algorithm research, learning data in the form of public DB provided mainly by data scientists were used. The learning data collected in the real environment is mostly the operational data of the sensors and inevitably contains various noises. Accordingly, various data cleaning frameworks and methods for removing noises have been studied. In this paper, we proposed a method for detecting and removing noises from time-series data, such as sensor data, that can occur in the IoT environment. In this method, the linear regression method is used so that the system repeatedly finds noises and provides data that can replace them to clean the learning data. In order to verify the effectiveness of the proposed method, a simulation method was proposed, and a method of determining factors for obtaining optimal cleaning results was proposed.