• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1166-1171
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• 2001

The method for output disturbance estimation is proposed. In this method, output disturbance is estimated from the closed loop system dynamics using the output and control input signals. In the closed-loop output-disturbance estimator, precise system identification is required to reduce estimation error. The realization of estimator was done by the DSP board (DSPl103), and disturbance estimation in various environments was performed： change of rotation speed, media feature and spindle motor with (or without) auto-ball balancing system (ABS). From these experiments, the disturbance characteristics of ODD under various conditions are analyzed, and the desirable servo loop configuration based these results is proposed.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.115-124
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• 2017

This paper aims to develop an SMPS topology for handling a high range of input voltages based on a DC-DC flyback converter circuit. For this purpose, 2 capacitors of the same specifications were serially connected on the input terminal side, with a flyback converter of the same circuit configuration serially connected to each of them, so as to achieve high input voltage and an effect of dividing input voltage. The serially connected flyback converters have the transformer turn ratio of 1:1, so that each coil is used for the winding of a single transformer, which is a characteristic of doubly-fed configuration and enables the correction of input capacitor voltage imbalance. In addition, a pulse transformer was designed and fabricated in a way that can achieve the isolation and noise robustness of the PWM output signal of the PWM controller that applies gate voltage to individual flyback converter switches. PSIM simulation was carried out to verify such a structure and confirm its feasibility, and a 100W class stack was fabricated and used to verify the feasibility of the proposed high voltage SMPS topology.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.353-356
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• 2009

A pivotal mechanical balance of plant for 75kW class molten carbonate fuel cells comprise of a catalytic burner and an ejector which has been designed and tested in KEPRI(Korea Electric Power Research Institute). The catalytic burner, which oxidizes residual fuel in the anode tail gas, was operated at several conditions. Some problems arose due to local overheating or auto-ignition, which could limit the catalyst life. The catalytic burner was designed by considering both gas mixing and gas velocity. Test results showed that the temperature distribution is very uniform. In addition, an ejector is a fluid machinery to be utilized for mixing fluids, maintaining vacuum, and transporting them. The ejector is placed at mixing point between the anode off gas and the cathode off gas or the fresh air Several ejectors were designed and tested to form a suction on the fuel tail gas and balance the differential pressures between anode and cathode over a range of operating conditions. The tests showed that the design of the nozzle and throat played an important role in balancing the anode tail and cathode inlet gas pressures. The 75kW MCFC system built in our ejector and catalytic burner was successfully operated from Novembe, 2008 to April, 2009. It recorded the voltage of 104V at the current of 754A and reached the maximum generating power of 78.5kW DC. The results for both stand-alone and integration into another balance of plant are discussed.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.