• Title/Summary/Keyword: Operation Algorithm

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Experimental Test Results of Nine Scheduling Operational Modes of PV and Battery Hybrid System for the Development of Automatic Control Algorithm for Continual Operation without being shut-downed (태양광 배터리 Hybrid 전력공급시스템 9가지 운전 모드 시험결과 및 무고장 연속 운전을 위한 자동제어 알고리즘 개발)

  • Song, Taek Ho;Yang, Seung Kwon;Kim, Minjeong
    • KEPCO Journal on Electric Power and Energy
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    • v.5 no.1
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    • pp.25-32
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    • 2019
  • K-BEMS System was introduced to reduce peak load and to save total energy of the 200 buildings that KEPCO headquarter and branch offices use. And K-BEMS system is composed of PV, battery, and hybrid PCS. KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. In this paper, the results of the project are shown. 9 modes of test results of K-BEMS system and are operational problems were analyzed. And measures to cure the trouble are also suggested. Batteries are operated more than 20% of SOC, and less than 20% of SOC battery protection switches are automatically shutting down the system and the system no longer respond to EMS, ending the supply of PV, and so therefore to continue the PV power supply it was turn out to be necessary that the EMS should automatically change its policy to change PV only supply mode automatically when the Battery Switch automatically operated. To operate the system continuously and automatically, it is necessary to modify the minimum operational SOC value, and in addition to that the EMS computer must remember the last shut-down SOC and Voltage which interrupted the system and add some margin to reflect the measurement error in the system.

A Study on Building the HD Map Prototype Based on Web GIS for the Generation of the Precise Road Maps (정밀도로지도 제작을 위한 Web GIS 기반 HD Map 프로토타입 구축 연구)

  • KWON, Yong-Ha;CHOUNG, Yun-Jae;CHO, Hyun-Ji;GU, Bon-Yup
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.2
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    • pp.102-116
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    • 2021
  • For the safe operation of autonomous vehicles, the representative technology of the 4th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

Application of CFD to Design Procedure of Ammonia Injection System in DeNOx Facilities in a Coal-Fired Power Plant (석탄화력 발전소 탈질설비의 암모니아 분사시스템 설계를 위한 CFD 기법 적용에 관한 연구)

  • Kim, Min-Kyu;Kim, Byeong-Seok;Chung, Hee-Taeg
    • Clean Technology
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    • v.27 no.1
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    • pp.61-68
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    • 2021
  • Selective catalytic reduction (SCR) is widely used as a method of removing nitrogen oxide in large-capacity thermal power generation systems. Uniform mixing of the injected ammonia and the inlet flue gas is very important to the performance of the denitrification reduction process in the catalyst bed. In the present study, a computational analysis technique was applied to the ammonia injection system design process of a denitrification facility. The applied model is the denitrification facility of an 800 MW class coal-fired power plant currently in operation. The flow field to be solved ranges from the inlet of the ammonia injection system to the end of the catalyst bed. The flow was analyzed in the two-dimensional domain assuming incompressible. The steady-state turbulent flow was solved with the commercial software named ANSYS-Fluent. The nozzle arrangement gap and injection flow rate in the ammonia injection system were chosen as the design parameters. A total of four (4) cases were simulated and compared. The root mean square of the NH3/NO molar ratio at the inlet of the catalyst layer was chosen as the optimization parameter and the design of the experiment was used as the base of the optimization algorithm. The case where the nozzle pitch and flow rate were adjusted at the same time was the best in terms of flow uniformity.

Diagnosis of Valve Internal Leakage for Ship Piping System using Acoustic Emission Signal-based Machine Learning Approach (선박용 밸브의 내부 누설 진단을 위한 음향방출신호의 머신러닝 기법 적용 연구)

  • Lee, Jung-Hyung
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.1
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    • pp.184-192
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    • 2022
  • Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

Development and Verification of Active Vibration Control System for Helicopter (소형민수헬기 능동진동제어시스템 개발)

  • Kim, Nam-Jo;Kwak, Dong-Il;Kang, Woo-Ram;Hwang, Yoo-Sang;Kim, Do-Hyung;Kim, Chan-Dong;Lee, Ki-Jin;So, Hee-Soup
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.3
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    • pp.181-192
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    • 2022
  • Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

Direct blast suppression for bi-static sonar systems with high duty cycle based on adaptive filters (고반복률을 갖는 양상태 소나 시스템에서의 적응형 필터를 이용한 송신 직접파 제거 연구)

  • Lee, Wonnyoung;Jeong, Euicheol;Yoon, Kyungsik;Kim, Geunhwan;Kim, Dohyung;You, Yena;Lee, Seokjin
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.4
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    • pp.446-460
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    • 2022
  • In this paper, we propose an algorithm to improve target detection rate degradation due to direct blast in a bi-static sonar systems with high duty cycle using an adaptive filters. It is very important to suppress the direct blast in the aforementioned sonar systems because it has a fatal effect on the actual system operation. In this paper, the performance was evaluated by applying the Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms to the simulation and sea experimental data. The beam signals of the target and direct blast bearings were used as the input and desired signals, respectively. By optimizing the difference between the two signals, the direct blast is removed and only the target signal is remained. As a result of evaluating the results of the matched filter in the simulation, it was confirmed that the direct blast was removed to the noise level in both Linear Frequency Modultated (LFM) and Generalized Sinusoidal Frequency Modulated (GSFM), and in the case of GSFM, the target sidelobe decreased by more than 20 dB, thereby improving performance. In the sea experiment, it was confirmed that the LFM reduced the level of the transmitted direct wave by 10 dB, the GSFM reduced the level of the transmitted direct wave by about 4 dB, and the side lobe of the target decreased by about 4 dB, thereby improving the performance.

Analysis of Anti-Reversing Functionalities of VMProtect and Bypass Method Using Pin (VMProtect의 역공학 방해 기능 분석 및 Pin을 이용한 우회 방안)

  • Park, Seongwoo;Park, Yongsu
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.11
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    • pp.297-304
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    • 2021
  • Commercial obfuscation tools (protectors) aim to create difficulties in analyzing the operation process of software by applying obfuscation techniques and Anti-reversing techniques that delay and interrupt the analysis of programs in software reverse engineering process. In particular, in case of virtualization detection and anti-debugging functions, the analysis tool exits the normal execution flow and terminates the program. In this paper, we analyze Anti-reversing techniques of executables with Debugger Detection and Viralization Tools Detection options through VMProtect 3.5.0, one of the commercial obfuscation tools (protector), and address bypass methods using Pin. In addition, we predicted the location of the applied obfuscation technique by finding out a specific program termination routine through API analysis since there is a problem that the program is terminated by the Anti-VM technology and the Anti-DBI technology and drew up the algorithm flowchart for bypassing the Anti-reversing techniques. Considering compatibility problems and changes in techniques from differences in versions of the software used in experiment, it was confirmed that the bypass was successful by writing the pin automation bypass code in the latest version of the software (VMProtect, Windows, Pin) and conducting the experiment. By improving the proposed analysis method, it is possible to analyze the Anti-reversing method of the obfuscation tool for which the method is not presented so far and find a bypass method.

Design and Implementation of User-Level FileSystem in the Combat Management System

  • Kang, Seok-Hyun;Kim, Keun-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.9-16
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    • 2022
  • In this paper, we propose a plan to design and utilize the RDBS(Record Block Data file management System) so that data can be recovered when data files in the Combat Management System are mismatched. The CMS(Combat Management System) manages the same files in multiple IPN(Infomation Processing Node) repositories to support multiplexing. However, mismatches in data files can occur due to equipment maintenance or user immaturity. The existing CMS does not manage the history of changes in data files, and when a mismatch occurs, data file were synchronized based on the latest date. But, It is difficult to say that files with the latest date have the highest reliability, and once the file synchronization has progressed, it cannot be recovered with pre-synchronization data. To solve this problem, data was stored and synchronized in units of record blocks using RDBS proposed in this paper, and the Rsync algorithm was used to reduce the overhead of file synchronization due to units of record blocks. SW applied with RDBS was tested for performance in a simulated environment, and it was confirmed that it could be applied to CMS through normal operation confirmation.

A Study on Dimming Improvement and Flicker Reduction in Visible Light Communication System (가시광통신 시스템에서 디밍 향상 및 플리커 감소 방안에 대한 연구)

  • Doo-Hee, Han;Kyu-Jin, Lee
    • Journal of Industrial Convergence
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    • v.21 no.2
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    • pp.125-131
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    • 2023
  • In this paper, research was conducted to solve the problem of reducing the dimming level and flicker that occurs in the visible light communication system. Visible light communication is a convergence technology that provides both communication and lighting, and must satisfy not only communication performance but also lighting performance. However, since the existing data transmission method transmits without considering the transmission data sequence, it reduces the dimming level and causes a flicker phenomenon. To solve this problem, in this paper, the Dimming Improvement and Flicker Reduction Mapping technique was studied. Existing systems simply transmitted data of '0' and '1', but in this system, original data transmission channels and DIFR (Dimming Improvement and Flicker Reduction) transmission channels are assigned to RGB channels. Original data is allocated to the R channel and original data or inverse original data is allocated to the DIFR-G channel, and the DIFR-B channel maintains the maximum dimming level by transmitting through the logical operation of the R channel and the G channel. At the same time, the flicker phenomenon is prevented by preventing continuous occurrence of 'OFF' patterns. Through this, we proposed an adaptive data allocation algorithm that can faithfully play a role as a light as well as a communication function.

A study on the application of the agricultural reservoir water level recognition model using CCTV image data (농업용 저수지 CCTV 영상자료 기반 수위 인식 모델 적용성 검토)

  • Kwon, Soon Ho;Ha, Changyong;Lee, Seungyub
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.245-259
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    • 2023
  • The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.