• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.1100-1102
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• 1998

This paper presents the Two-Phase Neural Network(TPNN) to slove the Optimal Economic Environmental Dispatch problem of thermal generating units in electric power system. The TPNN, Compared with other Neural Networks, is very accurate and it takes smaller computer time for a optimization problem to converge. In this work, in order to provide useful information to the system operator, we are used the total environmental weight and relative weighting of individual insults(e.g., $SO_2$, $NO_X$ and $CO_2$) also, presented the simulation results of the dispatch changes according to the weights. The Two-Phase Neural Network is tested on a 11-unit 3-pollutant system to prove of effectiveness and applicability.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1993년도 추계학술대회논문집
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• pp.21-30
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• 1993

This paper describes the development of a simulation model of nuclear power plant operators including cognitive aspects by using a network modeling soft ware, Micro-SAINT (System Analysis of Integrated Networks of Tasks) for the analysis of operator performance. Network model description based on Micro-SAINT includes tasks, resources, precedence relations among tasks, flow of information and PSFs (Performance Shaping Factors) on task performance. We have tried to evaluate the performance with several performance measures such as the number of tasks allocated, relative time presure among operators within a shift, for the selected test accident scenarior; small-break LOCA (Loss of Coolant Accident) in a PWR (Pressurized Water Reactor) type nuclear power plant.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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• pp.109-112
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• 2002

SNMP is generally used protocol for network management. SNMP need MIB for exchanging management information But, method for sharing MIB is not automatic. General MIB sharing architecture is done by network management operator by manually. In this paper we describe exchanging MIB automatically using meta-MIB. We will formalize SMI as MIB structure. This meta MIB represent information about MIB of NE Agent. Meta MIB has Information of object in the MIB, Structure and index information fur columnar object, meaning of subtype at INTEGER syntax. Also, trap related information is represented too. In this paper, MIB information is represented as instance of meta MIB. This architecture will provide a method for automatic MIB exchanging

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.91-102
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• 1999

Fieldbus provides real-time data communication among field devices in the manufacturing automation and process control systems. In this study, an experimental model of fieldbus-based manufacturing automation system is developed. Experimental model consists of two robots, two conveyor belts, NC machine, PLC, sensors and operator station. These machines are interconnected into the Profibus network, and exchange their data through the services provided by FMS(Fieldbus Message Specification), which is the application layer protocol of Profibus. The experimental model is used to measure the network-induced delay of variable and file data transmitted through FMS services. Network-induced delays are collected and analyzed on each sublayer of Profibus protocol stack. The results obtained from the experiment of this study can be effectively utilized when fieldbus is implemented on the practical manufacturing automation systems.

• 한국산업융합학회 논문집
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• 제25권2_2호
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• pp.193-198
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• 2022

In this paper, we introduce the improved control method are communicated between a master and a slave robot in the teleoperation systems. When the master and slave robots are located in different places, time delay is unavoidable under the network environment and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The time delay may cause instability in teleoperation systems especially if those systems include haptic feedback. This paper presents a control scheme based on the estimator with virtual master model in teleoperation systems over the network. As the behavior of virtual model is tracking the one of master model, the operator can control real master robot by manipulating the virtual robot. And LQG/LTR scheme was adopted for the compensation of un-modeled dynamics. The approach is based on virtual master model, which has been implemented on a robot over the network. Its performance is verified by the computer simulation and the experiment.

• 로봇학회논문지
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• 제17권2호
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• pp.118-123
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• 2022

We implemented a real-time cloud robotics application by offloading robot navigation engine over to 5G Mobile Edge Computing (MEC) sever. We also ran a fleet management system (FMS) in the server and controlled the movements of multiple robots at the same time. The mobile robots under the test were connected to the server through 5G SA network. Public 5G network, which is already commercialized, has been temporarily modified to support this validation by the network operator. Robot engines are containerized based on micro-service architecture and have been deployed using Kubernetes - a container orchestration tool. We successfully demonstrated that mobile robots are able to avoid obstacles in real-time when the engines are remotely running in 5G MEC server. Test results are compared with 5G Public Cloud and 4G (LTE) Public Cloud as well.

• 한국가스학회지
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• 제21권4호
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• pp.47-61
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• 2017

대규모 플랜트에서 조업자 안전훈련 모델의 전제조건은 조업에 관련된 다양한 위험의 상세분석 및 지식표현으로 얻어진 운영절차의 범용성과 정확성이다. 본 연구에서는 조업절차의 생성을 위해 인공지능 플래닝 기법을 고려하여 조업자의 일반행위와 조치행위 그리고 기술용어 등을 분류하고, 지식의 공유 및 재사용을 고려하여 플랜트의 운영과정과 관련된 조업행위 및 용어의 확장을 지식표현 온톨로지 형태로 정의하였다. 또한 조업의 일반적인 행위의 구체화를 위해 Hierarchical Task Network (HTN)기반의 행위계획을 적용하여 목표와 실행이 가능한 수준까지 분할하여 여러 상황에 따른 절차를 생성하도록 설계하였다. 이후 실제 보일러 설비의 사례연구를 통해 조업조건과 운전상태 그리고 장치들 간의 운전목적에 따라 구성설비의 역할을 분류하고, 비상정지절차를 생성하였으며, 제안한 방법의 실제 플랜트 적용 가능성을 확인하였다. 체계적인 지식표현에 기초한 지식베이스 구축은 일반적인 플랜트 운영절차 및 조업자 안전훈련 시나리오의 생성에도 활용이 가능할 것이며, 향후 자동생성 등에도 활용될 수 있을 것으로 판단된다.

• 제어로봇시스템학회논문지
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• 제16권9호
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• pp.898-904
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• 2010

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control and so on. Implementation, which is often neglected, is one of practical issues in developing such an autonomous device. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. Another requirement on the integration is that the system should allow changes in the system design so that modification and addition of system components can be accommodated without too much effort. This paper presents a network-based distributed approach where system components are connected to a shared CAN network, and control functions are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. This approach is successfully applied to develop an unmanned forklift.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 C
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• pp.910-912
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• 1998

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime, by introduction a neural network. In the proposed method, Ire use acoustic emission sensing system and calculate a fixed quantity statistic operator by pulse number and amplitude. Using statically operators such as the center of gravity(G) and the gradient of the discharge distribute(C), we analyzed the early stage and the middle stage. the fixed quantity statistic operators are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.1051-1058
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• 2011

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.