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류지수(Ji-Su Ryu),이기상(Kee-Sang Lee) 전력전자학회 2002 전력전자학술대회 논문집 Vol.- No.-
In this paper, the effects of encoder fault and current sensor fault in direct torque controlled induction motor drives are analyzed on the basis of the analyzed results, a observer based fault detection and isolation scheme is presented<br/> To verify the performance of proposed algorithms, the speed control system is designed for induction motor and evaluated by experimental study Experimental results various type of sensor faults show the detection and isolation performance of the SFDIS and the applicability of this scheme to fault tolerant control system design.
유도전동기 직접토크제어를 위한 새로운 퍼지 가변스위칭 섹터기법
류지수(Ji-Su Ryu),이기상(Kee-Sang Lee),홍순찬(Soon-Chan Hong) 전력전자학회 2001 전력전자학술대회 논문집 Vol.2001 No.-
Direct torque control (DTC) scheme provides a very quick torque response without the complex field-orientation block and inner current regulation loop DTC is known as an appropriate scheme for high power induction motor drives because It can be used at lower switching frequency. There are a major drawbacks with the application of DTC schemes˙ it is large current harmonic due to flux drooping in a low speed range In order to solve the problem, the fuzzy variable switching sector scheme are adopted in this paper A meaningful contribution of this paper is to propose a simple realization scheme of the fuzzy variable switching sector technique. Experimental results show the effectiveness of this proposition.<br/> <br/>
고로슬래그 미분말과 플라이애시를 사용한 비소성 시멘트 모르타르의 촉진 탄산화에 따른 압축 강도 특성
류지수 ( Ryu Ji-su ),나형원 ( Na Hyeong-won ),형원길 ( Hyung Won-gil ) 한국건축시공학회 2023 한국건축시공학회 학술발표대회 논문집 Vol.23 No.1
In the concrete industry, efforts are being made to reduce CO<sub>2</sub> emissions, and technologies that collect, store, and utilize CO<sub>2</sub> have recently been studied. This study analyzed the change in compressive strength after the accelerated carbonation test of Non-Sintered Cement(NSC) mortar. Type C Fly Ash and Type F Fly Ash were mixed in a 1:1 ratio and then mixed with Blast Furnace Slag fine powder to produce NSC. The mortar produced was cured underwater until the target age. In addition, an accelerated carbonation test was conducted under the condition of a concentration of 5 (±1.0%) of CO<sub>2</sub> gas for 14 days. The mortar compressive strength was measured before and after 14 days of accelerated carbonation test based on the 7th and 28th days of age. As a result of the experiment, the compressive strength was improved in all binder. In general, the compressive strength of NSC mortar subjected to the accelerated carbonation test was similar to that of Ordinary Portland Cement(OPC) mortar not subjected to the accelerated carbonation test.
류지수(Ji-Su Ryu),바이사(Bayasgalan),이상호(Sang-Ho Lee) 전력전자학회 2010 전력전자학술대회 논문집 Vol.2010 No.7
In this paper, a sturdy on the controller for super high speed PMSM is described. To drive PMSM at 60000rpm, the MRAS based sensorless control algorithm is applied. The control board was designed using TMS320F28335 and the performance verified by experiments.
CCW 알고리즘 기반 꿀벌 카운팅 시스템 및 꿀벌 분류 시스템
류지수(Ji-Su Ryu),염수형(Soo-Hyung Yeom),강준영(Junyeong Kang),최병조(Byoung-Jo Choi),이명렬(Myeong-Lyeol Lee) 한국정보기술학회 2022 Proceedings of KIIT Conference Vol.2022 No.6
대표적인 화분매개곤충인 꿀벌의 경제적 가치는 전 세계적으로 농작물 화수분 면에서 매우 크다. 하지만 농약, 기후변화 등 환경문제로 꿀벌의 개체 수가 감소하고 있다. 따라서 꿀벌의 감소량을 파악한 후 더 큰 감소로 이어지는 사태를 조기에 방지하는 것이 중요하다. 본 논문에서는 선분 교차 판별 알고리즘인 CCW(Counter-ClockWise)를 이용해 출입하는 꿀벌의 수를 자동으로 계산해주는 딥 러닝 기반 꿀벌 카운팅 시스템을 구현하였다. 또한, 벌의 종류에 따른 개체 수 자동 집계를 위해 직접 촬영한 여왕벌, 일벌, 수벌의 이미지를 사용하여 개체별 학습을 진행하였다. 총 600장의 이미지 데이터를 이용하여 다중객체 인식 면에서 0.03%의 loss rate를 얻을 수 있었다. 본 연구결과를 활용하면 분봉을 예측하여 꿀벌 개체 수 감소를 최소화하는 시스템을 구축할 수 있을 것으로 기대된다. The economic value of honeybees, a representative pollinating insect, is very large in terms of crop pollination worldwide. However, the number of honeybees is decreasing due to environmental problems such as pesticides and climate change. Therefore, it is important to identify the amount of decrease in honeybees and prevent the situation leading to a greater decrease in early stage. In this paper, we implement a deep learning-based honeybee counting system that automatically calculates the number of honeybees entering and leaving employing CCW (Counter-ClockWise), a line segment cross-determination algorithm. Our deep learning process utilized the image data of queen bees, worker bees, and drones for classification of the bees. Using 600 images, it was possible to obtain a loss rate 0.03% accuracy in terms of multi-class recognition. It is expected that our automatic honeybee counting system may be used to reduce the colony collapse disorder by giving an early warning to the beekeepers.