• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1019-1022
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• 2005

본 논문에서는 현재 활발한 연구개발이 이루어지고 있는 유비쿼터스 컴퓨팅, 센서 네트워크 기술을 적용한 무인 감시/추적 시스템을 제시한다. 본 논문의 무인 감시/추적 시스템은 센서네트워크 기술, 다중센서 융합에 의한 탐지 및 위치 인식기술, 무인 감시/추적 알고리즘으로 구성되어 있다. 센서네트워크는 센싱 데이터를 실시간으로 전송하기 위해 노드의 주소를 기반으로 하는 계층적 멀티홉 라우팅 기법을 제안하였다. 침입자와 추적자의 위치 인식은 자기센서 및 초음파센서를 가진 센서모듈들로부터 얻어진 센싱 정보를 융합하고, 이를 확률적으로 침입자 및 추적자의 위치를 결정하는 Particle Filter를 적용한 위치인식 알고리즘을 통해 이루어진다. 추적 알고리즘은 무인 자율 추적을 위해 이동벡터에 기반한 알고리즘이다.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.26-33
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• 1999

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, basic methods which use the acoustic emission (AE) signals and cutting forces were proposed to monitor flank wear (width of flank wear) quantiatively. First, in order to detect flank wear, it was investigated that the influence of cutting conditions, that is, cutting velocity, feed and depth of cut, on AE signals (${AE_rms}$) and cutting forces. Furthermore, the relation between flank wear and the measured signals (${AE_rms}$, cutting force) was discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.95-100
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• 1995

Automatic monitoring of cutting process is one of the most important technology for increasing the stability and the reliability of unmanned manufacturing system. In this study, basic methods which use the acoustic emission (AE) signals and sutting forces proposed to monitor tool wear (flank wear) quantitatively. Fist, in order to detect flank wear, it was investigated influence of cutting conditions, that is, cutting velocity, feed and depth of cut, on AE signals (AErems) and cutting forces. Furthermore,the relationship flank wear between AErems and cutting forces were discussed.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1013-1025
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• 2020

Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.393-406
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• 2018

Every year in the ocean, various accidents occur frequently and illegal fishing is rampant. Moreover, their size and frequency are also increasing. In order to reduce losses of life or property caused by these, it is necessary to have a means to perform remote monitoring quickly. As an effective platform of such monitoring means, an Unmanned Aerial Vehicle (UAV) is receiving the spotlight. In these situations where marine accidents or illegal fishing occur, main targets of monitoring are ships. In this study, we propose a UAV based ship monitoring system and suggest a method of determining ship positions using UAV multi-sensory data. In the proposed method, firstly, the position and attitude of individual images are determined by using the pre-performed system calibration results and GPS/INS data obtained at the time when images were acquired. In addition, after the ship being detected automatically or semi-automatically from the individual images, the absolute coordinates of the detected ships are determined. The proposed method was applied to actual data measured at 200 m, 350 m, and 500 m altitude, the ship position can be determined with accuracy of 4.068 m, 8.916 m, and 13.734 m, respectively. According to the minimum standard of a hydrographical survey, the ship positioning results of 200 m and 350 m data satisfy grade S and the results of 500 m data do grade 1a, where the accuracy is required for positioning the coastline and topography less significant to navigation order. Therefore, it is expected that the proposed method can be effectively used for various purposes of marine monitoring or surveying.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.441-444
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• 2008

This paper describes the development of a circularly polarized microstrip antenna, as a part of the Circularly Polarized Synthetic Aperture Radar (CP-SAR) sensor which is currently under developed at the Microwave Remote Sensing Laboratory (MRSL) in Chiba University. CP-SAR is a new type of sensor developed for the purpose of remote sensing. With this sensor, lower-noise data/image will be obtained due to the absence of depolarization problems from propagation encounter in linearly polarized synthetic aperture radar. As well the data/images obtained will be investigated as the Axial Ratio Image (ARI), which is a new data that hopefully will reveal unique various backscattering characteristics. The sensor will be mounted on an Unmanned Aerial Vehicle (UAV) which will be aimed for fundamental research and applications. The microstrip antenna works in the frequency of 1.27 GHz (L-Band). The microstrip antenna utilized the proximity-coupled method of feeding. Initially, the optimization process of the single patch antenna design involving modifying the microstrip line feed to yield a high gain (above 5 dBi) and low return loss (below -10 dB). A minimum of 10 MHz bandwidth is targeted at below 3 dB of Axial Ratio for the circularly polarized antenna. A planar array from the single patch is formed next. Consideration for the array design is the beam radiation pattern in the azimuth and elevation plane which is specified based on the electrical and mechanical constraints of the UAV CP-SAR system. This research will contribute in the field of radar for remote sensing technology. The potential application is for landcover, disaster monitoring, snow cover, and oceanography mapping.

• 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 Advanced Navigation Technology
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• v.24 no.6
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• pp.465-470
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• 2020

Complex materials are widely used in aviation industries where lightweighting is essential because they have lighter properties than metals. However, composite materials can cause defects such as internal void formation, poor adhesive mixing, and non-adhesive parts during the production process, and there is a risk of micro-cracking and interlayer separation due to low energy impact. Therefore, a structural damage test is essential. As a result, structural integrity monitoring using FBG is drawing attention. Compared to conventional electrical sensors, FBG has the advantage of being more corrosion-resistant and multiplexed without being affected by electrical noise. However, interloggers measuring FBG are expensive and have a large disadvantage because they are made on the premise of measuring large structures. In this paper, low-cost interloggers were designed for use in unmanned or small aircraft using optical switche, WDM filter, and LTFs, and compared to conventional high-priced interrogator.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.87-95
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• 2024

This research explores the utilization of Unmanned Aircraft Systems(UAS), or drones, within the construction industry, aiming to assess their current use and forecast their potential impacts. The study endeavors to present a comprehensive overview of approaches to overcome existing barriers to drone implementation. Through the analysis of survey responses and focus group discussions with 21 industry experts, the study reveals a significant recognition among participants of the need for drone adoption and the potential for technological advancement, despite the current limited deployment on construction sites. Participants predict that drones will substantially enhance construction safety and efficiency. The study identifies three primary obstacles to drone integration: 1) the expense associated with setting up a UAS monitoring framework; 2) challenges related to data exchange and management; 3) the necessity for professional training in drone operation. This research contributes valuable insights into the present usage of drones at construction sites, elucidating the anticipated advantages, current impediments, and prospective solutions for drone utilization.