• Journal of Wind Energy
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• v.14 no.3
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• pp.100-108
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• 2023

The aim of this study is to develop guidelines for predicting interference between drones and wakes during non-destructive blade inspections in wind power systems. The wake generated by wind towers and blades can affect the stability of drone flights, necessitating the establishment of guidelines to ensure safe and efficient inspections. In order to predict the interference between drones and blades, environmental variables must be considered, including quantification of turbulence intensity in the wake generated by the tower and blades, as well as determining the appropriate distance between the drone and the tower/blades for flight stability. To achieve this, computational fluid dynamics (CFD) analysis was performed using cross-sectional geometries corresponding to the main wind turbine blade and tower span locations. Based on the CFD analysis results, a safe flight path for drones is proposed, which minimizes the risk of collision and interference with towers and blades during maintenance operations of wind power systems. Implementation of the proposed guidelines is expected to enhance the safety and efficiency of maintenance work.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.110-115
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• 2018

This paper introduces Korea Airport Corporation's own research and development contents and plans for navigation aids check using drone which is actively research and developed mainly in advanced countries. The hardware, algorithm, operating program of the drone system, the drone flight trajectory setting, and real-time measurement results were analyzed and verified. By securing domestic technology for the latest technology utilizing drone, we plan to promote more thorough aviation safety and advanced technology in related field and commercialized it in domestic and overseas.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.75-80
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• 2023

Unmanned drone stations for automatic charging have been developed in order to overcome the flying time limitation of rotary wing drones. Since the drone stations is an unmanned operating system, each of the drones will be required to have a high degree of landing accuracy. Drone precision landing has been mainly studied depended on image processing technologies, but the image processing systems make several problems, such as the mission weight, the drone cost, and the development complexity increases, and the flight time decrease. Thus, this paper researched accuracy of precision landing based on RTK (real time kinetics) for rotary wing drones. For the experiments of RTK based precision landing, a drone repeatedly performed three missions. The survey accuracies of the RTK about missions respectively were set as 0.3, 0.2, and 0.1 meters. Each mission has one take-off point, two way-points and one landing-point, and was repeated ten times. The experiment results revealed landing error distance means of around 0.258, 0.12 and 0.057 meters on each of RTK setting.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1080-1088
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• 2018

General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

• Journal of Aerospace System Engineering
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• v.15 no.5
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• pp.43-49
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• 2021

This research shows how is designed, and its performance is evaluated on the ground for the VTOL drone before the flight test initiates. The targeted drone weight is approximately 45 kg including battery packs, and 4 motors are utilized to produce thrust and control directions. 30 min flight schedules were simulated to estimate the total power consumptions which result in 2.4 kWh. Then, two packs of 13-cells lithium-polymer battery with operating voltage ranging between 54 V and 44 V with up to 4 C-rate were fabricated to safely operate a VTOL drone. Moreover, the battery management system was installed to prevent over and under-voltage and over-current while running a battery system. To finally verify battery's performance, we conducted a ground evaluation for discharging battery tests at -10 ℃, 25 ℃ and 40 ℃, resulting in satisfying simulated power consumption conditions for flight schedules.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.891-898
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• 2022

Along with global interest, drones are expanding the base of utilization such as transportation of goods, forest protection, and safety management, and cluster flights are being applied in various fields such as military operations and environmental monitoring. Currently, specialized networks such as e-UM 5G for services in specific industries are being established in Korea. In this regard, drone systems are also moving to establish specialized networks to provide services that are fused with AI and autonomous flight. As drones converge with various services, various security threats in various environments are also subordinated, and in response, requirements and guidelines for drone security are being prepared in Korea. In this paper, we propose a technology method for peer identification and safe information provision between cluster flight drones by utilizing a cryptographic module equipped with wireless LAN and quantum entropy-based random number generator in a cluster flight system and a mobile communication network such as e-UM 5G.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1049-1055
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• 2023

The utilization of agricultural drones for pest control operations has been increasing due to its economic efficiency. However, variations in the effectiveness of these operations occur depending on the operator's proficiency. In this study, we applied a smart operating mode to overcome the limitations of manual flight mode and proposed a numerical model. Through comparative validation with prior research, we conducted experimental verification. As a result, we determined the spray time and calculation of spray area for each drone model. We selected a drone for pest control with a high similarity to the numerical model and verified it experimentally. Through this, we confirmed that the application of the smart operating mode is more effective in terms of calculation of spray area and operational efficiency compared to manual flight mode.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.55-64
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• 2019

In drone-assisted wireless sensor networks, drones collect data from sensors in an energy-efficient manner and quickly distribute urgent information to sensor nodes. This article introduces recent communication and security schemes for drone-assisted wireless sensor networks. For the communication schemes, we introduce data collection optimization schemes, drone position and movement optimization schemes, and drone flight path optimization schemes. For the security schemes, we introduce authentication and key management schemes, cluster formation schemes, and cluster head election schemes. Then, we present some enhancement methodologies for these communication and security schemes. As a conclusion, we present some interesting future work items.

• Journal of Advanced Engineering and Technology
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• v.11 no.4
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• pp.273-277
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• 2018

In the field of forest disaster prevention, drones are expected to save higher human resources than the existing manpower has, and produce high-efficiency results over time. However, operational limitations brought by short flight times have brought the environment of limited use of the various capabilities of the drone, and the existing development systems operating the multi-drone are mainly for performance purpose, so it is a difficult to use for forest disaster prevention. The purpose of this paper is to design the concept based on multi-drone operation procedure through analysis of mission of ground control system for forest disaster prevention.