• Proceedings of the Korean Society of Laser Processing Conference
• /
• 1998.11a
• /
• pp.0-0
• /
• 1998

-Part I- As market needs become more various, the production of smaller quantities of a wider variety of products becomes increasingly important. In addition, in order to meet demands for more efficient production, long-term unmanned factory operation is prevailing at a remarkable pace. Within this context, laser machines are gaining increasing popularity for use in applications such as cutting and welding metallic and ceramic materials. FANUC supplies four models of $CO_2$ laser oscillators with laser power ranging from 1.5㎾ to 6㎾ on an OEM basis to machine tool builders. However, FANUC has been requested to produce laser oscillators that allow more compact and lower-cost laser machines to be built. To meet such demands, FANUC has developed six models of Slab type YAG laser oscillators with output power ranging from 150W to 2㎾. These oscillators are designed mainly fur cutting and welding sheet metals. The oscillator has an exceptionally superior laser beam quality compared to conventional YAG laser oscillators, thus providing significantly improved machining capability. In addition, the laser beam of the oscillator can be efficiently transmitted through quartz optical fibers, enabling laser machines to be simplified and made more compact. This paper introduces the features of FANUC’s developed Slab type YAG laser oscillators and their applications. - Part II - All-solid-state lasers employing laser diodes (LD) as a source of pumping solid-state laser feature high efficiency, compactness, and high reliability. Thus, they are expected to provide a new generation of processing tools in various fields, especially in automobile and aircraft industries where great hopes are being placed on laser welding technology for steel plates and aluminum materials for which a significant growth in demand is expected. Also, in power plants, it is hoped that reliability and safety will be improved by using the laser welding technology. As in the above, the advent of high-power all-solid-state lasers may not only bring a great technological innovation to existing industry, but also create new industry. This is the background for this project, which has set its sights on the development of high-power, all-solid-state lasers with an average output of over 10㎾, an oscillation efficiency of over 20%, and a laser head volume of below 0.05㎥. FANUC Ltd. is responsible for the research and development of slab type lasers, and TOSHIBA Corp. far rod type lasers. By pumping slab type Nd: YAG crystal and by using quasi-continuous wave (QCW) type LD stacks, FANUC has already obtained an average output power of 1.7㎾, an optical conversion efficiency of 42%, and an electro-optical conversion efficiency of 16%. These conversion efficiencies are the best results the world has ever seen in the field of high-power all-solid-state lasers. TOSHIBA Corp. has also obtained an output power of 1.2㎾, an optical conversion efficiency of 30％, and an electro-optical conversion efficiency of 12%, by pumping the rod type Nd: YAG crystal by continuous wave (CW) type LD stacks. The laser power achieved by TOSHIBA Corp. is also a new world record in the field of rod type all-solid-state lasers. This report provides details of the above results and some information on future development plans.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.8
• /
• pp.359-368
• /
• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.111-118
• /
• 2016

This paper presents an X-band (9.375 GHz) $1{\times}2$ array microstrip antenna which is capable of active beam compensation for installation of an unmanned aerial vehicle (UAV). First of all, a basic $1{\times}2$ array microstrip antenna incorporated with wilkinson power divider was designed and performance of the array antenna was verified. Next, to verify beam steering performance of the designed array microstrip antenna, we fabricated a phase shifter, and the wilkinson power divider as module structure and measured characteristics of beam steering according to phase shifting. The main lobe is 0.6 dBi at $0^{\circ}$, and the side lobe decreased 18.8 dB. The reliable radiation pattern was achieved. Finally, an active beam steering microstrip array antenna attached with the phase shifter and the power divider on the back side of the antenna was designed and fabricated to install wing of UAV for compactness. The maximum gain is 0.1 dBi. Therefore, we obtained a basic antenna technology for compensating beam error according to wing deformation of an UAV installed array antennas.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.114-123
• /
• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.681-692
• /
• 2019

In this paper, a hybrid deep learning model, called 2D convolution with bidirectional long short-term memory (2DCBLSTM), is presented that can effectively combine both spatial and temporal features for crop classification. In the proposed model, 2D convolution operators are first applied to extract spatial features of crops and the extracted spatial features are then used as inputs for a bidirectional LSTM model that can effectively process temporal features. To evaluate the classification performance of the proposed model, a case study of crop classification was carried out using multi-temporal unmanned aerial vehicle images acquired in Anbandegi, Korea. For comparison purposes, we applied conventional deep learning models including two-dimensional convolutional neural network (CNN) using spatial features, LSTM using temporal features, and three-dimensional CNN using spatio-temporal features. Through the impact analysis of hyper-parameters on the classification performance, the use of both spatial and temporal features greatly reduced misclassification patterns of crops and the proposed hybrid model showed the best classification accuracy, compared to the conventional deep learning models that considered either spatial features or temporal features. Therefore, it is expected that the proposed model can be effectively applied to crop classification owing to its ability to consider spatio-temporal features of crops.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_2
• /
• pp.819-829
• /
• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_2
• /
• pp.841-850
• /
• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of Convergence for Information Technology
• /
• v.9 no.12
• /
• pp.141-146
• /
• 2019

Economic analysis predicts that the drone market will grow, and the growth of the toy and hobby drone market is expected to gradually expand. Drone expectations are rising due to the net economic function of drone market growth, but accidents due to improper management and operations are also increasing. The difference in toy drone performance is incomparably small compared to industrial drone performance, but the ordinary buyer can not know whether the difference can cause an accident during use. The toy drones used in this study were obtained from KC and CE certification, and 20 kinds of drones were used. The flight time ranged from a minimum of 3 minutes to a maximum of 12 minutes, and the control distance ranged from a minimum of 20m to a maximum of 380m. Therefore, it is necessary to secure product safety through sampling inspection of the radio wave output of toy drones, and it is also necessary to mount an algorithm that automatically lowers the altitude or hover when exceeding the limit flight distance. For future research, we will build data to establish toy drone safety standards through a altitude testing and impact testing of toy drone.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.9
• /
• pp.57-65
• /
• 2010

This paper describes the method of efficient container number recognition in colored container image with number plate at ATC(Automatic Transfer Crane) in container terminal yard. At the Sinseondae terminal gate in Busan, the container number recognition system is installed by "intelligent port-logistics system technology development", that is government research and development project. It is the method that it sets up the tunnel structure inside camera on the gate and it recognizes the container number in order to recognize the export container cargo automatically. However, as the automation equipment is introduced to the container terminal and the unmanned of a task is gradually accomplished, the container number recognition system for the confirmation of the object of work is required at ATC in container terminal yard. Therefore, the container number recognition system fitted for it is necessary for ATC in container terminal yard in which there are many intrusive of the character recognition through image including a sunlight, rain, snow, shadow, and etc. unlike the gate. In this paper, hardware components of the camera, illumination, and sensor lamp were altered and software elements of an algorithm were changed. that is, the difference of the brightness of the surrounding environment, and etc. were regulated for recognize a container number. Through this, a shadow problem, and etc. that it is thickly below hung with the sunlight or the cargo equipment were solved and the recognition time was shortened and the recognition rate was raised.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1731-1738
• /
• 2021

The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.