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이 재 성,유 준 혁 대구대학교 정보통신연구소 2014 情報通信硏究 Vol.10 No.1
본 논문은 자율 이동 로봇의 장애물 회피와 관련된 기술동향을 분석하였다. 산업현장, 공공 및 개인 서비스 분야에서 다양하게 사용 중인 이동 로봇에서 안전과 가장 밀접된 장애물 충돌 회피를 위해 사용하는 다양한 기법들을 소개하고, 특히 인공전위계 알고리즘(Artificial Potential Field), 가상역장(Virtual Force Field) 알고리즘, 탄성력(Elastic Force) 알고리즘 등을 분석하고 각각의 장·단점을 도출하였다. This paper presents, the trend of technology regarding obstacle avoidance for autonomous mobile robots. The mobile robots are widely used in various fields such as industry and public personal service area. This paper introduces several techniques of the collision avoidance sith obstacles, which is closely related to the safety, especially three algorithms of artificial potential filed, virtual force field and elastic force are analyzed by figuring out pros and cons of each one.
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전기안전 IoT장치 적용을 위한 LoRa 자가망 시스템 구현 및 성능 측정
홍 성 준,정 용 욱,강 석 우,김 태 원,김 재 현,박 광 묵,박 진 영,이 상 익,방 선 배 대한전기학회 2019 전기학회논문지 P Vol.68 No.1
With the spread of embedded systems, there is a growing interest and demand for Internet of things. Technologies such as Wi-Fi, Zig-Bee, and Bluetooth can transmit relatively large amounts of data, but consume high power and have a narrow communication range. As a result, LPWAN technologies such as LoRa, Sigfox, NB-IoT, and Wi-SUN are emerging as attractive communication methods in the Internet of things. In this paper, we use LoRa, one of the low power long distance wireless communication technologies, to construct the self wireless network including gateways and measure the performance to transmit data of electric safety IoT devices. Instead of using the existing commercial network, we used the 900MHz frequency band to communicate with the gateway. In order to evaluate the performance of the implemented system, we verified the packet SNR and the RSSI value by changing the communication between the electric safety IoT device and the gateway inside and outside, inside and outside of the distribution panel, and distance.
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방사기저함수를 이용한 태양광 일사량 센서 고장진단 알고리즘
지평식,이 창 성,임 재 윤 대한전기학회 2019 전기학회논문지 P Vol.68 No.1
Most photovoltaic power prediction model has been developed considering solar radiation and temperature. Therefore, the reliability of measured radiation value is considered to be a very important factor in the performance of the predictive model. In this paper, we have developed a diagnostic method of solar radiation sensor based on solar power prediction model constructed by RBFN(Radial Basis Fuction Networks). The developed fault diagnosis method is performed by using the difference between power calculated by the solar power prediction model and the actual generation amount. To construct the model, we selected the data with higher correlation coefficients between irradiation and PV power. In the diagnosis process, the diagnosis is made by using the error between the power generation predicted value calculated by the RBFN and the actual power generation. We verified the usefulness of the proposed method through various experiments.
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