• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.3
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• pp.1-8
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• 2013

An application of adaptive flight controller is required for the non-linear and high uncertain system that configuration of tiltrotor aircraft is dramatically changed from rotary wing mode to fixed wing mode. In this paper, the applicable adaptive controller for the tiltrotor aircraft was designed using Neural Networks and DMI (Dynamic Model Inversion). The performance of the SCAS (Stability and Control Augmentation System) was simulated against manned military specification, using the fullscale model of 'Smart UAV(Unmanned Aerial Vehicle)' developed by Korea Aerospace Research Institute. And Neural Networks based adaptive controller was verified through its whole operating envelope using the established HQ (Handling Quality) criteria.

• Smart Structures and Systems
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• v.31 no.1
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• pp.79-88
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• 2023

As the number of deteriorated buildings increases, the importance of safety diagnosis, maintenance, and the repair of buildings also increases. Traditionally, building condition assessments are performed by one person or one company and various inspections are needed. This entails a subjective judgment by the inspector, resulting in different assessment results, poor objectivity and a lack of reliability. Therefore, this study proposed a method to bring about accurate grading results of building conditions. The limitations of visual inspection and condition assessment processes previously conducted were identified by reviewing existing studies. Building defect data was collected using the reverse-engineered three-dimensional (3D) model. The accuracy of the results was verified by comparing them with the actual evaluation results. The results show a 50% time-saving to the same area with an accuracy of approximately 90%. Consequently, defect data with high objectivity and reliability were acquired by measuring the length, area, and width. In addition, the proposed method can improve the efficiency of the building diagnosis process.

• Journal of KIBIM
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• v.13 no.4
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• pp.64-73
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• 2023

This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.65-73
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• 2006

The high temperature occurs due to the combustion gas from engine in unmanned aerial vehicles (UAV). The high temperature may cause serious damages in UAV structure. The Functionally Graded Material (FGM) is chosen as a candidate material of the engine duct structure. A functionally graded material (FGM) is a two- component mixture composed by compositional gradient materials from one material to the other. In contrast, traditional composite materials are homogeneous mixtures, and involve compositions between the desirable properties of the component materials. Since significant proportions of an FGM contain the pure form of each material, the need for compromise is eliminated. The properties of both components can be fully utilized. Thermal stress analysis of FGM layers (20, 40, 60, 80 and 100) is performed in this paper. In addition, the creep behavior of FGM applied in duct structure of an engine is analyzed for better understanding of FGM characteristics.

• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.65-72
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• 2018

The uses of unmanned aerial vehicles (UAV) have been expanding in agriculture surveys, obtaining real time updates of dangerous facilities where human access is difficult, disaster monitoring, and 3D modeling. In reality, there is an upsurge in the application of UAVs in fields like, construction, infrastructure, imaging, surveying, surveillance and transportation. Especially, when the slope failure such as landslide occurs, the uses of UAVs are increasing. Since, the UAVs can fly in three dimensions, they are able to obtain spatial data in places where human access is nearly impossible. Despite of these advantages, however, the uses of UAVs are still limited during slope failure. In order to overcome these limitations, this study computes the soil volume change during slope failure through the computation technique using photogrammetric information obtained from UAV system. Through this study, it was found that photogrammetric information from UAV can be used to acquire information on amount of earthworks required for repair works when slope collapse occurs in mountainous areas, where human access in difficult.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.4
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• pp.24-32
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• 2007

In this study, computational structural vibration analyses of a smart unmanned aerial vehicle (SUAV) with tilt-rotors due to dynamic hub loads have been conducted considering detailed supporting structures of installed equipments. Three-dimensional dynamic finite element model has been constructed for different fuel conditions and tilting angles corresponding to helicopter, transition and airplane flight modes. Practical computational procedure for modal transient response analysis is successfully established. Also, dynamic loads generated by rotating blades and wakes in the transient and forward flight conditions are calculated by unsteady computational fluid dynamics technique with sliding mesh concept. As the results of present study, transient structural displacements and accelerations of the vibration sensitive equipments are presented in detail. In addition, vibration characteristics of structures and installed equipments of which safe operation is normally limited by the vibration environment specifications are physically investigated for different flight conditions.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.104-109
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• 2007

This paper is about a redundancy management system design for the Smart UAV(unmanned aerial vehicle) which utilizes the tilt..rotor mechanism. In order to meet the safety requirement on the PLOC(probability of loss of control) of $1.7{\times}10^{-5}$ per flight hour for FCS (flight control system) failures, a digital FCS is mechanized with a dual redundant structure. A fault detection system which is composed of a CCM(cross channel monitor) and analytic redundancy using the Kalman filtering is designed, and its effectiveness is evaluated through experiments. A threshold level and persistence count for managing redundant sensors are designed based on the statistical analysis of the FCS sensors. To increase the survivability of the UAV after the loss of critical sensors in the SAS(stability augmentation system) and to provide reference information for a tie-breaking condition at which an ILM(in-line monitor) cannot distinguish the faulty channel between two operating ones, the Kalman filter approach is investigated.

• Aerospace Engineering and Technology
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• v.5 no.2
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• pp.240-247
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• 2006

Tilt rotor aircraft is a multi-configuration airplane which has three independent flight modes; helicopter, conversion, and aiplane. The control surface mixer resign is reqctired to generate and distribute efficient control forces and moments in each flight mode. In the conversion mode, the thrust vector is changed from helicopter mode to airplane, therefore the thrust vector makes undesired forces and moments which affect on pitch, roll and yaw dynamics. This paper describes the design results of control surface mixer design which minimize the undesired forces and moments due to nacelles tilting angle change for 4O% scaled model.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.889-894
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• 2017

The purpose of this paper is to implement smart farm using automatic navigation, short - range wireless communication network technology, and automatic take - off and landing system using unmanned aerial vehicle to maximize the efficiency of grazing farm management. The grazing pasture management system that integrates ICT fusion technology for the activation of the mountain ecological livestock production is expected to contribute to the improvement of the productivity of the grazing livestock, the infrastructure to produce the excellent quality, and the competitiveness of the livestock industry in response to the FTA. And it will contribute to the improvement of career force through the supply to the farmhouse.

• 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.