• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.995-1000
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• 2017

In this paper, we present an electrical arc detection algorithm using the mash-up analysis technique which is the core technology for the autonomous electrical safety management system(AESMS) of the multi-unit dwellings. The mash-up analysis technique analyzes the voltage, load current, zero phase current data simultaneously to judge arc faults. In order to develop the arc fault detection algorithm, the characteristics of series arc and parallel arc were analyzed. Also, we propose the mash-up analysis technique that analyzes waveforms of voltage, load current, and zero phase current at the same time. The arc fault detection algorithm was developed using the mash-up analysis technique. The developed algorithm can prevent electrical disasters in an effective way through accident prediction, and it will be used as a basic technology to introduce an autonomous electrical safety management system.

• Journal of the Korean Society of Propulsion Engineers
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• v.24 no.6
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• pp.45-52
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• 2020

In this paper, a subminiature solid rocket motor(SSRM) was designed to develop a miniature smart-bullet and the designed propellant grain was made of thermoplastic propellant for production convenience of inner shape. The internal ballistics analysis and ground test were performed to investigate the performance of SSRM. And a numerical simulation was carried out to obtain basic data on the design of safety distance between the nozzle outlet and a gunner, the temperature distribution of exhaust gas was analyzed by comparing a numerical simulation and the results of IR camera.

• Journal of the Korean Society for Heat Treatment
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• v.35 no.1
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• pp.27-32
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• 2022

Microbubble technology has been widely applied in various industrial fields. Recently, research on many types of microbubble application technology has been conducted experimentally, but there is a limit in deriving the optimal design and operating conditions. Therefore, if the computational fluid dynamics (CFD) analysis of multiphase flow is used to supplement these experimental studies, it is expected that the time and cost required for prototype production and evaluation tests will be minimized and optimal results will be derived. However, few studies have been conducted on multiphase flow CFD analysis to interpret fluid flow in microbubble generators using swirl flow. In this study, CFD simulation of multiphase flow was performed to analyze the air-water mixing process and fluid flow characteristics in a microbubble generator with a dual-chamber structure. Based on the simulation results, it was confirmed that a negative pressure was formed on the central axis of rotation due to the strong swirling flow. And it could be seen that the air inside the suction tube was introduced into the inner chamber of the microbubble generator. In addition, as the high-speed mixed fluid collided with external water sucked by the negative pressure near the outlet, a large amount of microbubbles was ejected due to the shear force between the two flows flowing in opposite directions.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.693-699
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• 2024

The main cause of scattering dust generated by transportation equipment such as automobiles was largely due to exhaust gas from internal combustion engines in the past, but it was generally recognized that non-exhaust causes such as abrasion of the tires or brake pads were low. Accordingly, scattering dust generated by exhaust gas has consistently existed in many studies, such as technological progress and related regulations, but research on non-exhaust is relatively insignificant, and the need for research on scattering dust generated by non-exhaust is emerging. In this study, a dust collector that can be easily mounted on a caliper to collect scattering dust generated by pad wear during the brake operation of an automobile was manufactured. In this study, we developed a dust collector that is easy to mount on calipers to collect scattering dust caused by pad wear during brake operation of automobiles. According to the installation of the manufactured dust collector, the performance of scattering dust by brake operation and the temperature change characteristics of calipers according to the structure of the dust collector were evaluated.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.