• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_2
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• pp.285-291
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• 2023

In this paper, in order to secure the safety and productivity of pine cone harvest, modeling and structural analysis of the hammering system for pine cone harvest drone that can easily access pine cone of Pinus koraiensis and collide with them to harvest them was performed. It calculate the equivalent stress for the structure of the hammering system and the yield strength of the applied material by applying the shear force of the stalk at which the pine cone is separated from the branch, and it is to verify the safety of the structure and propose an optimal design through appropriate factor of safety and design change. The shear force of the stalk at which the pine cone was separated from the branch was 468 N, and was applied to both ends of the hammering system. The yield strength of SS400 steel used in the hammering system is 245 ㎫, and the design change and structural analysis were performed so that the Von Mises stress could be less than 122.5 ㎫ by applying the factor of safety of 2.0 or more. As a result of the structural analysis of the frist modeling, the Von Mises stress was 220.3 ㎫, the factor of safety was 1.12, and the stress was concentrated in the screw fastening holes. As a result of the design change of the screw fastening holes, the Von Mises stress was 169.4 ㎫, the factor of safety was 1.45, and the stress was concentrated on the side part. As a result of the design change by changing screw fastening holes and adding ribs, the Von Mises stress was 121.6 ㎫, and the factor of safety was 2.02. The safety of the hammering system was secured with an optimal design with little change in mass. There was no deformation or damage as a result of experimenting on pine cone harvest by manufacturing the hammering system with an optimal design.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.1
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• pp.1-7
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• 2017

Most conventional processors execute program instructions in a sequential manner. On the other hand, VLIW processor can execute multiple instructions at the same time. It exploits instruction level parallelism to improve system performance. To that end, program code should be rearranged to VLIW instruction format by a compiler. The compiler determine an optimal execution order of instructions of a program code. This instruction ordering is also called instruction scheduling. The scheduling is an algorithm that decides the execution order for instruction codes in loop parts of a program so that the instruction level parallelism can be maximized. In this research, we apply an existing scheduling algorithm to a VLIW FCC and describe analysis results to further improve its performance. And, we present a solution to solve some limitation of the existing scheduling technique. By using our solution, FCC's performance can be improved upto 32% compared to the existing scheduling only setting.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.649-656
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• 2023

Recently, global warming has become severe, and regulation is established for carbon savings each field. its regulation is applied to various fields using IC engine such as automobile, ship, agricultural machine. Therefore engine block applied Common Rail Direct Injection(CRDI) technology, that carry out thermal-structure analysis to examine design. The thermal load about 900℃ by explosion was applied in cylinder. And pressure about 9 MPa(90 Bar) was applied to structure analysis. As a result, it was the highest at 185.99℃ at the top of cylinder. Static-structure analysis applied thermal load, that was shown maximum equivalent stress at 142.59 Mpa and Maximum principal stress 145.03 MPa, Minimum principal stress -149 MPa. When compare analysis results to material property, it design is safety structurally.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1073-1082
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• 2023

Thermal sensors, also called thermal infrared wavelength sensors, measure temperature based on the intensity of infrared signals that reach the sensor. The infrared signals recognized by the sensor include infrared wavelength(0.7~3.0㎛) and radiant infrared wavelength(3.0~100㎛). Infrared(IR) wavelengths are divided into five bands: near infrared(NIR), shortwave infrared(SWIR), midwave infrared(MWIR), longwave infrared(LWIR), and far infrared(FIR). Most thermal sensors use the LWIR to capture images. Thermal sensors measure the temperature of the target in a non-contact manner, and the data can be affected by the sensor's viewing angle between the target and the sensor, the amount of atmospheric water vapor (humidity), air temperature, and ground conditions. In this study, the characteristics of three thermal imaging sensor models that are widely used for observation using unmanned aerial vehicles were evaluated, and the optimal application field was determined.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.83-92
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• 2018

This paper uses the Apollonius Circle technique to estimate the position of a target that generates a specific signal by using a drone, which is rapidly becoming a rapidly expanding industry. The existing direction finding method is performed through the vehicle on the ground or installed the antenna at a high position to detect the position of the target. However, the conventional direction finding method is difficult to configure the reception environment of the LOS signal, It is difficult. However, the direction finding using the drone is easy to construct and measure the LOS signal receiving environment using the drone flying at high altitude. In this study, we use the 3D 800MHz Path-Loss Model to reconstruct the signal by using the measurement data of the ground direction finding, reconstruct the signal by using the 3-D 800MHz Path-Loss Model, and use the Apollonius Circle method to estimate the position of the target. A simulation was performed to estimate the position of the target. Simulation was performed to determine the target position estimation performance by configuring the ground direction finding and the dron direction finding.

• Korean Journal of Agricultural Science
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• v.47 no.2
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• pp.349-360
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• 2020

Fire-blight disease is a kind of contagious disease affecting apples, pears, and some other members of the family Rosaceae. Due to its extremely strong infectivity, once an orchard is confirmed to be infected, all of the orchards located within 100 m must be buried under the ground, and the sites are prohibited to cultivate any fruit trees for 5 years. In South Korea, fire-blight was confirmed for the first time in the Ansung area in 2015, and the infection is still being identified every year. Traditional approaches to detect fire-blight are expensive and require much time, additionally, also the inspectors have the potential to transmit the pathogen, Thus, it is necessary to develop a remote, unmanned monitoring system for fire-blight to prevent the spread of the disease. This study was conducted to detect fire-blight on pear trees using discriminant analysis with color information collected from a rotary-wing drone. The images of the infected trees were obtained at a pear orchard in Cheonan using an RGB camera attached to a rotary-wing drone at an altitude of 4 m, and also using a smart phone RGB camera on the ground. RGB and Lab color spaces and discriminant analysis were used to develop the image processing algorithm. As a result, the proposed method had an accuracy of approximately 75% although the system still requires many flaws to be improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.175-182
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• 2021

The purpose of this paper is to develop a machine learning-based marine drone to prevent the farming from harmful birds such as ducks. Existing drones have been developed as marine drones to solve the problem of being lost if they collide with birds in the air or are in the sea. We designed a CNN-based learning algorithm to judge harmful birds that appear on the sea by maritime drones operating by autonomous driving. It is designed to transmit video to the control PC by connecting the Raspberry Pi to the camera for location recognition and tracking of harmful birds. After creating a map linked with the location GPS coordinates in advance at the mobile-based control center, the GPS location value for the location of the harmful bird is received and provided, so that a marine drone is dispatched to combat the harmful bird. A bird fighting drone system was designed and implemented.

• The Korean Journal of Air & Space Law and Policy
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• v.35 no.2
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• pp.75-111
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• 2020

The civilian drone world has evolved in recent years from one dominated by hobbyists to growing involvement by companies seeking to profit from unmanned flight in everything from infrastructure inspections to drone deliveries that are already subject to regulations. Drone flight under the property right relation with the land owner would be deemed legal on the condition that expeditious and innocent passage of drone flight over the land be assured. The United Nations Convention on the Law of the Sea (UNCLOS) enshrines the concept of innocent passage through a coastal state's territorial sea. Passage is innocent so long as it is not prejudicial to the peace, good order or security of the coastal state. A vessel in innocent passage may traverse the coastal state's territorial sea continuously and expeditiously, not stopping or anchoring except in force majeure situations. However, the disturbances caused by drone flight may be removed, which is defined as infringement against the constitutional interest of personal rights. For example, aggressive infringement against privacy and personal freedom may be committed by drone more easily than ever before, and than other means. The cost-benefit analysis, however, has been recognjzed as effective criteria regarding the removal of disturbances or injunction decision. Applying that analysis, the civil action against such infringement may not find suitable basis for making a good case. Because the removal of such infringement through civil actions may result in only the deletion of journal article. The injunction of drone flight before taking the information would not be obtainable through civil action, Therefore, more detailed and meticulous regulation and criteria in public law domain may be preferable than civil action, at present time. It may be suitable for legal stability and drone industry to set up the detailed public regulations restricting the free flight of drone capable of acquiring visual information amounting to the infrigement against the right of personal information security.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.239-240
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• 2023

Construction site management involves overseeing tasks from the construction phase to the maintenance stage, and digitalization of construction sites is necessary for digital construction site management. In this study, we aim to conduct research on object recognition at construction sites using drones. Images of construction sites captured by drones are reconstructed into BIM (Building Information Modeling) models, and objects are recognized after partially rendering the models using artificial intelligence. For the photorealistic rendering of the BIM models, both traditional filtering techniques and the generative adversarial network (GAN) model were used, while the YOLO (You Only Look Once) model was employed for object recognition. This study is expected to provide insights into the research direction of digital construction site management and help assess the potential and future value of introducing artificial intelligence in the construction industry.