• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.35-42
• /
• 2019

Nut fasteners that require ultra-precise control are required in the overall manufacturing industry including electronic products that are currently developing with the automobile industry. Important performance factors when tightening nuts include loosening due to insufficient fastening force, breakage due to excessive fastening, Tightening torque and angle are required to maintain and improve the assembling quality and ensure the life of the product. Nut fasteners, which are now marketed under the name Nut Runner, require high torque and precision torque control, precision angle control, and high speed operation for increased production, and are required for sophisticated torque control dedicated to high output BLDC motors and nut fasteners. It is demanded to develop a high-precision torque control driver and a high-speed, low-speed, high-response precision speed control system, but it does not satisfy the high precision, high torque and high speed operation characteristics required by customers. Therefore, in this paper, we propose a control technique of BLDC motor variable speed control and nut runner based on vector control and torque control based on coordinate transformation of d axis and q axis that can realize low vibration and low noise even at accurate tightening torque and high speed rotation. The performance results were analyzed to confirm that the proposed control satisfies the nut runner performance. In addition, it is confirmed that the pattern is programmed by One-Stage operation clamping method and it is tightened to the target torque exactly after 10,000 [rpm] high speed operation. The problem of tightening torque detection by torque ripple is also solved by using disturbance observer Respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.1
• /
• pp.19-28
• /
• 2019

Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis.

• Journal of Advanced Navigation Technology
• /
• v.25 no.1
• /
• pp.115-123
• /
• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Journal of Korea Water Resources Association
• /
• v.54 no.8
• /
• pp.553-566
• /
• 2021

River confluence is often characterized by shear layer and the associated strong mixing. In natural rivers, the main channel and its tributary can be separated by the shear layer using contrasting colors. The shear layer can be easily observed using aerial images from satellite or unmanned aerial vehicles. This study proposes a low-cost identification method extracting geographic features of the shear layer using RGB aerial image. The method consists of three stages. At first, in order to identify the shear layer, it performs image segmentation using a Gaussian mixture model and extracts the water bodies of the main channel and tributary. Next, the self-organizing map simplifies the flow line of the water bodies into the 1-dimensional curve grid. After that, the curvilinear coordinate transformation is performed using the water body pixels and the curve grid. As a result, the shear layer identification method was successfully applied to the confluence between Nakdong River and Nam River to extract geometric shear layer features (confluence angle, upstream- and downstream- channel widths, shear layer length, maximum shear layer thickness).

• Journal of the Korean Institute of Landscape Architecture
• /
• v.52 no.1
• /
• pp.1-16
• /
• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.175-190
• /
• 2018

Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

• Korean Journal of Remote Sensing
• /
• v.35 no.3
• /
• pp.415-431
• /
• 2019

The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.