• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.6
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• pp.475-479
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• 2021

There are many difficulties in the applications of smart manufacturing technology in the era of the 4th industrial revolution. In this paper, a test bed was built to aim for acquiring smart manufacturing technology, and the test bed was designed to acquire basic technologies necessary for PLC (Programmable Logic Controller), HMI, Internet of Things (IoT), artificial intelligence (AI) and big data. By building a vehicle maintenance lift that can be easily accessed by the general public, PLC control technology and HMI drawing technology can be acquired, and by using cloud services, workers can respond to emergencies and alarms regardless of time and space. In addition, by managing and monitoring data for smart manufacturing, it is possible to acquire basic technologies necessary for embedded systems, the Internet of Things, artificial intelligence, and big data. It is expected that the improvement of smart manufacturing technology capability according to the results of this study will contribute to the effect of creating added value according to the applications of smart manufacturing technology in the future.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.380-385
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• 2018

Recently, interest in baseball has been increasing as the level of international baseball games, the popularity of domestic leagues, and the number of players entering the MLB has increased. In this paper, we propose a pitching system that can be applied to both professional and amateur baseball. The pitching system consists of a control module using MSB764T PLC, a pitching mechanism including AC motors and a ball feed rail, an HMI using the CHA-070WR model, inverter, etc. To pitch the breaking balls, the two AC motors each use an inverter to independently control the speed. The implemented pitching system was experimented on, investigating ball speed and ball movement according to RPM using the BUSHNELL Velocity Speed Gun. Experimental results on ball speed are similar to the theoretical data and the measured data. From the experimental data, it is confirmed that the damping coefficient value for the pitching ball is about 0.98. In the case of the breaking ball, the larger the difference between the speeds on the sides of the ball and the faster the ball speed, the larger the bending degree.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.280-283
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• 2021

SME(small and medium sized enterprise) 환경의 스마트공장 환경에서는 실제 제조라인에서 동작하는 센서(Sensor) 및 액추에이터(Actuator)와 이를 관리하는 PLC(Programmable Logic Controller), 더불어 그러한 PLC를 제어 및 관리하는 HMI(Human-Machine Interface), 그리고 다시 PLC와 HMI를 관리하는 OT(Operational Technology)서버로 구성되어 있으며, 제어자동화를 담당하는 PLC 및 HMI는 공장운영을 위한 응용시스템인 OT서버 및 현장 자동화를 위한 로봇, 생산설비와의 직접적인 연결을 수행하고 있어서 스마트공장 환경에서 보안 기술의 개발이 중점적으로 필요한 영역이다. 이러한 SME 환경의 스마트공장 보안 내재화를 이루기 위해서는, 스마트공장 SW 및 HW 개발 단계에서 IEC 62443-4-1 Secure Product Development Lifecycle에 따른 프로세스 정립 및 IEC 62443-4-2 Component 보안 요구사항과 IEC 62443-3-3 System 보안 요구사항에 적합한 개발 방법론의 도입이 필요하다.

• Journal of Wind Energy
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• v.15 no.1
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• pp.60-68
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• 2024

In this study, a hardware-in-the-loop simulation (HILS) environment was established using MATLAB/Simulink to simulate and verify the power performance of a wind turbine. The target wind turbine was selected as the NREL 5 MW model, and modeling was performed based on the disclosed specifications. The HILS environment consists of a PC equipped with a MATLAB/Simulink program, a programmable logic controller (PLC) for uploading and linking control algorithms, and data acquisition (DAQ) equipment to manage wind turbine data input and output. The operation of the HILS environment was carried out as a procedure of operation (PC) of the target wind turbine modeled based on MATLAB/Simulink, data acquisition (PLC) of control algorithms, control command calculation (PLC), and control command input (PC). The simulation was performed using the HILS environment under turbulent wind conditions and compared with the simulation results performed under the same conditions in the HILS environment using the commercial program Bladed for performance verification. From the comparison, it was found that the dynamic simulation results of the Bladed HILS and the MATLAB HILS were close in power performances and the errors in the average values of rotor rotation speed and power generation between the two simulations were about 0.44 % and 3.3 %, respectively.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.1-11
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• 2009

This paper illustrates a case study of PLC logic simulation in a car manufacturing system. It was developed to simulate and verify PLC control program for automobile panel AS/RS. Because car models become varied, the complexity of supply problem is increasing in the car manufacturing system. To cope with this problem, companies use the AS (automated storage) and RS (retrieval system) but it has logical complexity. Industrial automated process uses PLC code to control the AS/RS, however control information and control codes (PLC code) are difficult to understand. This paper suggests a PLC simulation environment, using 3D models and PLC code with realistic data. Data used in this simulation is based on realistic 3D model and I/O model, using actual size and PLC signals, respectively. The environment is similar to a real factory; users can verify and test the PLC code using this simulation before the implementation of AS/RS. Proposed simulation environment can be used for test run of AS/RS to reduce implementation time and cost.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.6
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• pp.193-204
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• 2022

In a smart factory environment in a small and medium-sized enterprise (SME) environment, sensors and actuators operating on actual manufacturing lines, programmable logic controllers (PLCs) to manage them, human-machine interface (HMI) to control and manage such PLCs, and consists of operational technology server to manage PLCs and HMI again. PLC and HMI, which are in charge of control automation, perform direct connection with OT servers, application systems for factory operation, robots for on-site automation, and production facilities, so the development of security technology in a smart factory environment is demanded. However, smart factories in the SME environment are often composed of systems that used to operate in closed environments in the past, so there exist a vulnerable part to security in the current environment where they operate in conjunction with the outside through the Internet. In order to achieve the internalization of smart factory security in this SME environment, it is necessary to establish a process according to the IEC 62443-4-1 Secure Product Development Life cycle at the stage of smart factory SW and HW development. In addition, it is necessary to introduce a suitable development methodology that considers IEC 62443-4-2 Component security requirements and IEC 62443-3 System security requirements. Therefore, this paper proposes an application plan for the IEC 62443 based development security process to provide security internalization to smart factories in an SME environment.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.818-819
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• 2015

PAL-XFEL 장치에 사용 할 고전압 펄스 모듈레이터 출력파워는 수 ${\mu}s$ 범위의 짧은 고전압(400 kV), 대전류(500 A) 펄스를 요구한다. 이러한 펄스파워를 얻기 위해서 PFN(Pulse Forming Network)에 에너지를 축적하고, 플라즈마 스위치인 싸이라트론을 통하여 에너지를 신속하게 클라이스트론 쪽으로 전달한다. 클라이스트론은 모듈레이터에서 공급하는 펄스 전원을 이용하여 RF를 증폭하는 대출력 고주파 증폭장치이다. 고전압 펄스 모듈레이터 제어기는 고속펄스 신호처리 모듈(Fast Pulse Signal Conditioning Module), PLC(Programmable Logic Controller)로 구성되어 있다. 고전압 펄스 모듈레이터에 사용하는 대용량 싸이라트론은 고전력을 스위칭 할 때 발생하는 스위칭 노이즈는 매우 크다. 이러한 노이즈는 모듈레이터의 출력 시그널인 빔 전압, 빔 전류, EOLC(End of Line Clipper) 전류, DC high voltage에 섞여 있으면서 신호 왜곡 및 제어장치의 고장을 유발시킨다. 이처럼 노이즈가 많이 포함되어 있는 아닐로그 신호를 깨끗한 신호(a clean signal)로 바꾸어주는 노이즈 필터링 장치인 고속펄스 신호처리 모듈을 제작하여 실험한 결과를 알아보고 모듈레이터 인터록 시스템인 PLC에서 Dynamic Interlock의 응답시간을 빠르게 하기위한 회로 수정에 대한 결과에 관하여 기술하고자 한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.115-123
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• 2021

A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.447-453
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• 2004

In the case of a capsule that can acquire and transmit images from the intestines, the size of the module and the battery capacity in the capsule are subject to restriction. The capsule must be swallowable and the battery must maintain the stable power during the capsule travels in the gastrointestinal tract. Therefore, it is important to control the endoscope using bi-directional wireless communication. In this study, encoder and decoder CPLD modules for bi-directional capsule endoscopes were designed and implemented. The designed controller for capsule endoscope can transmit the images of GI-track from inside to outside of the body and the capsules can be controlled by external controller simultaneously. The designed and implemented controller was verified by an in-vivo animal experiments. From these experiments, it was verified that the CPLD module for bi-directional capsule endoscope satisfied the design specifications.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.511-519
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• 2017

This Paper introduces the design and communication method between PLC (Programmable Logic Controller) and Arduino based on MODBUS Protocol. MODBUS connection can be established in a new or existing system very easily, therefore we used this protocol in our proposed system. In the field of automatic devices, multi-function serial port such as RS232, RS422, RS485, and so on creates a great convenience to the developer. This proposed system used RS485 as a key mediator for data exchanging on a connected network. We also believe that it will reduce the development cost in various automated industry because this system can be reused or can be implemented any such PLC installed machines. RS485 is used as a communication interface between PLC (as a slave) and Arduino (as a master), through which a reliable network is created for safe and fast communication. Furthermore, RS485 allows multiple devices(up to 32) to communicate at half duplex on a single pair of wires and provides a long connectivity area (up to 1200 meters) as compare to other device, which makes it a user-friendly for various devices in the automated industry. Moreover, Arduino can play as a mediator by connecting third party device and setup a communication network with PLC.