• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(2)
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• pp.41-44
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• 2002

The Semiconductor Industrial are developed after 1940. It was called “Rice of Industrial”. It needs great effect in Electronics. It was developed highly in recent several years with semiconductor manufacturing equipments. Semiconductor manufacturing devices are developed “In-line” type in the first stage. But It was non-effective in modem many type process. Because this reason, Cluster type manufacturing equipments are proposed. Cluster have ability of many-type-process and effective-scheduling by circular type process chamber In this paper. we propose a real-time 3D monitoring and simulation of this semiconductor manufacturing equipments. By proposed monitoring method, we have capability real visual maintanance & virtual simulation. This effective visual 3D monitoring could apply another dangerous environment in entire industrial.

• 디지털콘텐츠학회 논문지
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• 제7권3호
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• pp.193-197
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• 2006

본 논문에서는 무선 통신망과 향후 발전 가능성이 예상되는 가상현실 기술을 이용하여 특수환경에 적용되는 관제분야에서 사고상황 검증 및 사후 교육용도로 적용이 가능한 가상현실 시뮬레이션 기법을 이용한 관제상황 검증 시스템을 제안하였다. 또한, 제안 시스템의 정의와 동작원리를 살펴보고 제안 시스템에서 요구되는 기술사항에 관하여 분석하였다. 본 논문에서 제안한 무선 통신망을 활용한 관제상황 검증 시스템은 이동 전동차량의 기관실 모니터링 뿐만 아니라 의료분야 혹은 특수 위험물 처리를 수행하는 관제실에서도 그 적용이 가능하리라 예상된다.

• 디지털산업정보학회논문지
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• 제7권4호
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• pp.15-22
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• 2011

U-Healthcare service is a real-time service using the vital signs which are continuously transferred from monitoring sensors attached to mobile patients under the wireless network environments. It should monitor the health condition of mobile patients everywhere at any time. In this paper, we have improved two features of the three layered mobile patient monitoring system with load balancing ability. First, the simulation process has been improved by allowing the number of related nodes to be changed. Secondly, we have modified S node to which queue is added to reduce the loss rate of collecting data from patients during the delay of S node process. And the data from the patient with high priority can be transferred to the server immediately through the filtering function. Furthermore, we have solved the problem of redundancy in sharing information among S nodes by differentiating process time to each S node. By performing a DEVS Java-based system simulation, we have verified the efficiency of this improved system.

• 한국시뮬레이션학회논문지
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• 제12권3호
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• pp.69-81
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• 2003

To manage a cluster of distributed server systems, a number of management aspects should be considered in terms of configuration management, fault management, performance management, and user management. System performance monitoring and reporting take an important role for performance and fault management. In this paper, we present distributed system architecture modeling of a performance monitoring and reporting tool. Modeling architecture of four subsystems are introduced: node agent, data collection, performance management & report, and DB schema. The performance-related information collected from distributed servers are categorized into performance counters, event data for system status changes, service quality, and system configuration data. In order to analyze those performance information, we use a number of ways to evaluate data corelation. By using some results from a real site of a company and from simulation of artificial workload, we show the example of performance collection and analysis. Since our report tool detects system fault or node component failure and analyzes performances through resource usage and service quality, we are able to provide information for server load balancing, in short term view, and the cause of system faults and decision for system scale-out and scale-up, in long term view.

• 한국시뮬레이션학회논문지
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• 제7권2호
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권5호
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• pp.617-628
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• 2018

Several techniques have been developed in the last years for energy conversion and aeronautic propulsion plants monitoring and diagnostics, to ensure non-stop availability and safety, mainly based on machine learning and pattern recognition methods, which need large databases of measures. This paper aims to describe a simulation based monitoring and diagnostic method to overcome the lack of data. An application on a gas turbine powered frigate is shown. A MATLAB-SIMULINK(R) model of the frigate propulsion system has been used to generate a database of different faulty conditions of the plant. A monitoring and diagnostic system, based on Mahalanobis distance and artificial neural networks have been developed. Experimental data measured during the sea trials have been used for model calibration and validation. Test runs of the procedure have been carried out in a number of simulated degradation cases: in all the considered cases, malfunctions have been successfully detected by the developed model.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 추계학술대회 논문집
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• pp.85-86
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• 2013

This paper describes the physical configuration and features of the advanced control and protection devices, and operation control and monitoring system that are connected to a real time simulator for LS Industrial System 80kV 60 MW Jeju HVDC Pilot Project. Highlight of simulation result are provided to demonstrate the control and protection functionality.

• 비파괴검사학회지
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• 제32권3호
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• pp.241-262
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• 2012

Some applications require structural health monitoring in inaccessible components. This paper presents a technique useful for Structural Health Monitoring of double wall structures, such as double wall steam pipes and double wall pressure vessels separated from an ultrasonic transducer by three layers. Detection has been demonstrated at distances in excess of one meter for a fixed transducer. The case presented here is for one of the layers, the middle layer, being a fluid. For certain transducer configurations the wave propagating in the fluid is a wave with low velocity and attenuation. The paper presents a model based on wave theory and finite element simulation; the experimental set-up and observations, and comparison between theory and experiment. The results provide a description of the technique, understanding of the phenomenon and its possible applications in Structural Health Monitoring.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.311-315
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• 2000

In thls paper, a remote machine monitoring system for a vimal machine is proposed. The monltonng system is one of the core functmns of a vimd machne that provides a modeling and simulation environment for machining processes and management of the machine life cycle. The proposed system contains the modules for investigating tool wear using neural network and web-based real time process monitoring. An example implementation for tool wear and machining status monitoring is illustrated

• Tribology and Lubricants
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• 제32권6호
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• pp.189-194
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• 2016

Wear debris in lubricating oil can be indicative of potential damage to mechanical parts in rotating and reciprocating machinery. Therefore, on-line or in-line monitoring of lubricating components in machinery is of great importance. This work presents a device based on inductive measurement of lubricating oil to detect magnetic wear particles in a tested volume. The circuit in the device consists of Maxwell Bridge and LVDT to measure inductance differences between pure and contaminated oil. The device detects the passage of ferrous particles by monitoring inductance change in a coil. The sensing principle is initially demonstrated at the microscale using a solenoid. The device is then tested using iron particles ranging from $50{\mu}m$ to $100{\mu}m$, which are often found in severely worn mechanical components. The test results show that the device is capable of detecting and distinguishing ferrous particles in lubricating oil. The design concept demonstrated here can be extended to an in-line monitoring device for real-time monitoring of ferrous debris particles. A simulation using the CST code is performed to better understand the inductive response in the presence of magnetic bodies in the oil. The CST simulation further verifies the effectiveness of inductance measurement for monitoring magnetic particles within a tube.