• 전기학회논문지
• /
• 제66권6호
• /
• pp.995-1000
• /
• 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.

• 한국추진공학회지
• /
• 제24권6호
• /
• pp.45-52
• /
• 2020

초소형 스마트탄의 개발을 위해 초소형 추진기관을 설계하고 그레인은 내부 형상의 제작 용이성을 고려하여 열가소성 추진제로 제작하였다. 추진기관의 성능분석을 위해 지상연소시험과 내탄도 해석이 수행되었다. 그리고 사수와 추진기관 간 안전거리 설계에 대한 기초자료를 획득하기 위하여 수치해석을 수행하였으며, 배기가스의 온도분포는 수치해석과 IR 카메라의 측정결과를 비교하여 분석되었다.

• 열처리공학회지
• /
• 제35권1호
• /
• pp.27-32
• /
• 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.

• 한국산업융합학회 논문집
• /
• 제27권3호
• /
• pp.693-699
• /
• 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.

• 한국농공학회논문집
• /
• 제66권4호
• /
• pp.51-57
• /
• 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.

• 한국인터넷방송통신학회논문지
• /
• 제18권1호
• /
• pp.135-141
• /
• 2018

본 논문에서는 최적의 스마트 홈 제어 시스템의 설계 및 구현 방법에 대해 설명한다. 최근 센서와 통신과 같은 기술들을 발전으로 사물인터넷은 전구, 콘센트, 옷과 같은 다양한 사물을 제어할 수 있게 되었으며, 다양한 기업에서는 사물간의 협업을 통해 사용자의 삶을 향상 시킬 수 있는 서비스들을 출시되고 있다. 하지만, 기존 사물인터넷 시스템에서는 엔드 투 엔드 디바이스인 경우 다양한 프로토콜을 통해 데이터를 전송하지만 서버 및 게이트웨이는 단일 프로토콜을 지원하는 경우가 빈번하다. 또한, 사물인터넷 시스템의 제조사에 따라서 전용 어플리케이션이 존재하며, 여러 사물인터넷 디바이스들을 등록하고 제어하는데 있어서 높은 복잡성을 가지고 있다. 증강현실 사물인터넷 시스템인 경우 사물들을 검출하기 위해 OpenCV 또는 OpenGL을 사용하여 특징점 및 엣지 추출 기술을 사용 하지만 사물의 인식률이 샘플링 데이터에 따라서 편차가 크게 존재하며, 비교적 낮은 문제점이 존재한다. 제안하는 최적의 스마트 홈 시스템에서는 기존의 문제점을 보완하기 위해 OneM2M을 기반으로 사물인터넷 게이트웨이를 구현하여 엔드 투 엔드 디바이스의 다양한 프로토콜들을 지원하고, 단일 어플리케이션을 통해 다양한 사물을 제어 등 사용자의 접근성을 향상시켰다. 또한, 인공지능 분야의 딥러닝을 사용하여 디바이스들을 학습시키고 추론 및 검출을 통해 기존 시스템의 사물 인식률 향상과 인식률의 편차를 낮추었다.