• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.473-481
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• 2023

In this study, a simulation system was developed to verify autonomous navigation algorithm in complex maritime traffic areas. In particular, real-world maritime traffic scenario was applied by considering near real-time maritime traffic information provided by Korean e-Navigation service. For this, a navigation simulation system of Unmanned Surface Vehicle (USV) was integrated with an e-Navigation equipment, called Electronic Chart System (ECS). To verify autonomous navigation algorithm in the simulation system, initial conditions including initial position of an own ship and a set of paths for the ship to follow are assigned by an operator. Then, considering real-world maritime traffic information obtained from the service, the simulation is implemented in which the ship repeatedly travels by avoiding surrounding obstacles (e.g., approaching ships). In this paper, the developed simulation system and its application on verification of the autonomous navigation algorithm in complex maritime traffic areas are introduced.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.228-239
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• 2022

In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.973-985
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• 2019

In this paper, we propose a method to separate the ground and building areas and generate building models automatically through planarity analysis using UAV (Unmanned Aerial Vehicle) based point cloud. In this study, proposed method includes five steps. In the first step, the planes of the point cloud were extracted by analyzing the planarity of the input point cloud. In the second step, the extracted planes were analyzed to find a plane corresponding to the ground surface. Then, the points corresponding to the plane were removed from the point cloud. In the third step, we generate ortho-projected image from the point cloud ground surface removed. In the fourth step, the outline of each object was extracted from the ortho-projected image. Then, the non-building area was removed using the area, area / length ratio. Finally, the building's outer points were constructed using the building's ground height and the building's height. Then, 3D building models were created. In order to verify the proposed method, we used point clouds made using the UAV images. Through experiments, we confirmed that the 3D models of the building were generated automatically.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.46-52
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• 2018

This paper is to study the development of three dimensional Digital Surface Model (DSM) using photogrammetry technique based on self-developed Drone (Unmanned Aerial Vehicle (UAV)). To develop DSM, we selected a study area in Jeju island and took 24 pictures from the drone. The three dimensional coordinates of the photos were made by Differential Global Positioning System (DGPS) surveying with 10 ground control points (GCP). From the calculated three dimensional coordinates, we produced orthographic image and DSM. The accuracy of DSM was calculated using three GCPs. The average accuracy of X and Y was from 8.8 to 14.7 cm, and the accuracy of Z was 0.8 to 12.4 cm. The accuracy was less than the reference accuracy of 1/1,000 digital map provided by National Geographic Information Institute (NGII). From the results, we found that the self-developed drone and the photogrammetry technique are a useful tool to make DSM and digital map of Jeju.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.12
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• pp.1084-1093
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• 2017

As the survivability of an aircraft in the battlefield becomes a critical issue, there is a growing need to improve the survivability of the aircraft. In this study, the survivability of an UCAV associated with plume IR signature was investigated. In order to analyze the survivability of the aircraft, the lock-on range and the lethal envelope, defined as the IR detection distance of the aircraft and the range of shooting down by the missile, respectively, were first introduced. Further, a method to calculate the lethal envelope for the scenario of surface-to-air missiles including the vertical plane was developed. The study confirmed that the red zone of an UCAV shows a substantial difference in the zone size as well as the characteristics in the upward and downward directions.

• Composites Research
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• v.36 no.3
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• pp.211-216
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• 2023

When designing ships and aircraft structures, it is important to design them to satisfy weight reduction and strength. Currently, studies related to topology optimization using 3D printed composite materials are being actively conducted to satisfy the weight reduction and strength of the structure. In this study, structural analysis was performed to analyze the applicability of 3D printed composite materials to the flight control surface, one of the parts of an aircraft or unmanned aerial vehicle. The optimal topology shape of the flight control surface for the bending load was analyzed by considering three types (hexagonal, rectangular, triangular) of the topology shape of the flight control surface. In addition, the bending strength of the flight control surface was analyzed when four types of reinforcing materials (carbon fiber, glass fiber, high-strength high-temperature glass fiber, and kevlar) of the 3D printed composite material were applied. As a result of comparing the three-point bending test results with the finite element method results, it was confirmed that the flight control surface with hexagonal topology shape made of carbon fiber and Kevlar had excellent performance. And it is judged that the 3D printed composite can be sufficiently applied to the flight control surface.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.9-18
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• 2019

The intensity and the number of days of high temperature occurrence are also high and record heat occurred. In addition, the global warming phenomenon is intensifying globally, and especially in South Korea, the urban heat island phenomenon is also occurring due to rapid urbanization due to rapid industrial development. As the temperature of the city rises, it causes problems such as the comfort of the residential living and the cooling load. In this study, the cool roof performance is evaluated according to the roof color to reduce these problems. Unlike previous studies, UAV(Unmanned Aerial Vehicle) thermal infrared camera was used to obtain the surface temperature (white, grey, green, blue, brown, black) according to the rooftop color by remote sensing technique. As a result, the surface temperature of white color was $11{\sim}20^{\circ}C$ lower than other colors. Also air conditioning temperature of white color was $1.5{\sim}4.4^{\circ}C$ lower than other colors and the digital thermometer of white color was about $1.5{\sim}3.5^{\circ}C$ lower than other colors. It was confirmed that the white cool roof performance is the best, and the UAV and the thermal infrared camera can confirm the cool roof performa.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.332-338
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• 2017

Launch and recovery system(LARS) is required to perform an USV-based underwater exploration. Through the analysis of the requirements according to the scenario of underwater exploration, the mechanism of LARS and the conceptual design of the mechanical parts of LARS are carried out. In addition, a USV motion can be induced due to environmental disturbances such as waves, so the detailed design of LARS for recovering the underwater tow-fish stably in consideration of the USV motion is performed. To verify the performance of launch and recovery operations, LARS and test bed were developed. The results show that the proposed LARS can stably launch and recovery an underwater tow-fish.