• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.4
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• pp.81-88
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.626-632
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• 2017

Since natural disaster occurs increasingly and becomes complicated, it causes deaths, disappearances, and damage to property. As a result, there is a growing interest in the development of ICT-based natural disaster response technology which can minimize economic and social losses. In this letter, we introduce the main functions of the forest fire management platform by using images from an UAV. In addition, we propose a disaster image analysis technology based on the deep learning which is a key element technology for disaster detection. The proposed deep learning based disaster image analysis learns repeatedly generated images from the past, then it is possible to detect the disaster situation of forest-fire similar to a person. The validity of the proposed method is verified through the experimental performance of the proposed disaster image analysis technique.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.261-274
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• 2019

This paper aims to develop an appropriate methodology for establishing an investment strategy for 'demonstration of artificial rainfall technology using UAV' and that include establishment of a technology classification, set of indicators for technology evaluation, suggestion of final key technology as a whole study area. It is designed to complement the latest research trend analysis results and expert committee opinions using quantitative analysis. The key indicators for technology evaluation consisted of three major items (activity, technology, marketability) and 10 detailed indicators. The AHP questionnaire was conducted to analyze the importance of indicators. As a result, it was analyzed that the attribute of the technology itself is most important, and the order of closeness to the implementation of the core function (centrality), feasibility (feasibility). Among the 16 technology groups, top investment priority groups were analyzed as ground seeding, artificial rainfall verification, spreading and diffusion of seeding material, artificial rainfall numerical modeling, and UAV sensor technology.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.114-124
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• 2019

The drone market, an unmanned aerial vehicle, is rapidly expanding and developing into an important area related to the huge changes in the traffic system of the future. With various technologies on the fourth industrial revolution, including drones, mentioned at the Davos Forum in January 2016, interest in drones is emerging as an explosive demand for national certificates. The number of drone pilots, which was only 400 in 2015, is continuing to surpass 17,000 as of 2018. Therefore, this study analyzed the safety perception of the pilots based on the DREEM (Dundee ready environmental assessment) model designed to evaluate the educational environment along with the current state of drone education in Korea. This led to the conclusion that the high level of satisfaction of the pilot with the educational environment contributes to the overall safety perception, including compliance with procedures.

• Journal of the Korea Institute of Building Construction
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• v.19 no.3
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• pp.239-246
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• 2019

According to the survey on the status of aged buildings in Korea, A number of concrete buildings deterioration such as houses and apartment buildings has been increased rapidly. To solve this problem, the research related to the facility management, that is one of the importance factor, for monitoring buildings has been increased. The research is divided into Survey-based and Technique-based. However, the problem is that Survey-based research is required a lot of time, money and manpower for management. Also, safety cannot be guaranteed in the case of high-rise buildings. Technique-based research has limitations to applying to the current facility maintenance system, as detailed information of deteriorated facilities is difficult to grasp and errors in accuracy are feared. Therefore, this paper contribute to improve the environment of facility management by 4D maps using UAV, camera and Pix4D mapper program to make 3D model. In addition, it is expected to suggest that residents will be offered easy verification to their buildings deterioration.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.273-279
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• 2021

A flight control computer(FLCC) applied to an unmanned aerial vehicle(UAV) is a safety-critical item, and which is designed in a multiple structure to increase the reliability of operation by securing fault tolerance. These FLCC of multiple structure should be designed so that each independent processing/control components can perform the same operation at the same time. And for this reason, a synchronization algorithm for synchronizing the operation between FLCCs should be included in an operational flight program. In this paper, we propose a software design method for synchronization between dual FLCCs applied to UAVs. The proposed synchronization method is designed to synchronize using only the minimum hardware resources to reduce a failure rate. In addition, the proposed synchronization method is designed to minimized synchronization errors due to a timer operation by designing in consideration of operation characteristics of the hardware timer used for the synchronization.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.6
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• pp.473-480
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• 2021

In this paper, We analyze and present improvements to problems in software quality through Static Analysis for Open Source, which is widely used as the Flight Controller software for small unmanned aerial vehicle drones. MISRA coding rules, which are widely applied based on software quality, have been selected. Static analysis tools were used by LDRA tools certified international tools used in all industries, including automobiles, railways, nuclear power and healthcare, as well as aviation. We have identified some safety-threatening problems across the quality of the software, such as structure of open source modules, analysis of usage data, compliance with coding rules, and quality indicators (complexity and testability), and have presented improvements.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.90-103
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• 2017

This study analyzed the surface temperature characteristics of urban green spaces under high summer temperatures to clarify the functions of green spaces in reducing urban temperatures. We obtained accurate surface temperature data using highresolution unmanned aerial vehicle images of the survey site, which was an isolated green space in the city. We analyzed differences in the surface temperature by land cover type, vegetation type, species type, and the relationship between surface temperature and vegetation volume. Based on the results, among the land cover types, wetlands and forests had low temperatures and paving areas had very high temperatures. Regarding vegetation type, broad-leaved trees had lower temperatures than coniferous trees in forests. However, in planted areas, coniferous trees had lower temperatures than broad-leaved trees. The temperature of long grass was higher than that of short grass, which suggested that the volume of grass affected the temperature. Regarding forest species type, the temperature of broad-leaved Robinia pseudoacacia forest and mixed broad-leaved forest was lower than coniferous Pinus densiflora forest. There was a slight difference in temperature between R. pseudoacacia forest and mixed broad-leaved forest. The analysis of the relationship between vegetation volume and temperature by forest species type indicated a negative correlation, where the temperature decreased with increasing vegetation volume, similar to the results of previous studies. However, we found a weak positive correlation in R. pseudoacacia forest; therefore, an increase in volume may not reduce the surface temperature depending on the dominant species.