• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.995-998
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• 1995

As the modern industrial processes become more complex, it is getting more difficult to model and control the processes. Naturally, an advanced type of DCS(Distributed Control System) with higher level functions is being sought Advanced DCS is a DCS with advanced functions such as fault diagnosis, GPC(Generalized Predictive Control), NN(Neural Network), and Fuzzy Control. In this thesis, we have studied a fuzzy control algorithm for realizing an advanced DCS. Its algorithm is implemented in a form of function code which is a process control language, being used by the industrial engineers. To verify the realized function code of the fuzzy control, the function code is applied to a continuous casting process of the Pohang Iron & Steel Works in Kwangyang. The rules of the fuzzy control were collected via interviews of the field operators and their operation documents. Finally, usability of the function code of the fuzzy control is shown via simulation for the continuous casting process model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1021-1024
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• 1993

System identification is a major component for a control system. In biosystems, which is nonlinear and dynamic, precise identification would be very helpful for implementing a control system. It is difficult to precisely identify such non-linear systems. The measurable data on products from 2,3-butanediol fermentation could not be included in a process model based on kinetic approach. Meanwhile, a predictive capability is required in developing a control system. A neural network (NN) dynamic identifier with a by/(1＋ t ) transfer function was therefore designed being able to predict this fermentation. This modified inverse NN identifier differs from traditional models in which it is not only able to see but also able to predict the system. A moving window, with a dimension of 11 and a fixed data size of seven, was properly designed. One-step ahead identification/prediction by an 11-3-1 BPNN is demonstrated. Even under process fault, this neural network is still able to perform several-step ahead prediction.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.189-192
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• 2000

High-temperature superconductor of Bi-2212 system was fabricated by CFP(centrifugal forming process). To make a uniform specimen slurry was prepared in the ratio of 7:3(powder:binder) and ball milled for 24 hours. Milled slurry was charged into a rotating mold with 450 rpm and dried at room temperature. Then the specimen was performed binder burn-out at 35$0^{\circ}C$ and heated for partial melting to 86$0^{\circ}C$. XRD analysis of most specimens were shown 2212 phase and observed a local plate shaped microstructure with a well aligned c-axis direction from SEM images. T$_{c}$(Critical temperature) of Bi-2212 was 64K.K.

• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.91-98
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• 2009

The "3+3 Process" for safety critical software for nuclear power plants' I&C (Instrumentation and Control system) has been developed in this work. The main idea of the "3+3 Process" is both to simplify the software development and safety analysis in three steps to fulfill the requirements of a software safety plan [1]. The "3-Step" software development process consists of formal modeling and simulation, automated code generation and coverage analysis between the model and the generated source codes. The "3-Step" safety analysis consists of HAZOP (hazard and operability analysis), FTA (fault tree analysis), and DV (design validation). Put together, these steps are called the "3+3 Process". This scheme of development and safety analysis minimizes the V&V work while increasing the safety and reliability of the software product. For assessment of this process, validation has been done through prototyping of the SDS (safety shut-down system) #1 for PHWR (Pressurized Heavy Water Reactor).

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.85-88
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• 2000

Distributed Control System(DCS) is one of the best solutions to implement control systems because it provides continuous observation of control process and execution of commands to induce proper operations. In this paper, a design of control network for DCS in nuclear power plant is proposed. The proposed control network on DCS has a simple architecture and deterministic property. Thus, the proposed control network offers hard real-time periodic service. It also has redundant media for the fault-tolerance. As a result, high safety and reliability required in nuclear power plant are guaranteed.

• 한국가스학회:학술대회논문집
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• 2001.10a
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• pp.145-149
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• 2001

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.443-446
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• 2003

프로세스 복구 기법은 장시간 실행을 요하는 프로세스에서 시스템 결함으로 인하여 발생하는 심각한 피해를 최소화하기 위하여 절대적으로 요구된다. 프로세스의 무결성을 지원하기 위한 예방 및 회피책은 결함 발생의 원인 규명과 예측에 의한 오버헤드가 있다. 본 논문에서는 이러한 오버헤드를 최소화하기 위한 결함 허용 프로세스 복구 기법을 제시한다. 제시한 기법은 프로세스의 실행 상태 저장 및 복구 기능을 위한 두 개의 시스템 호출을 설계하고, 리눅스 커널 2.4.18 내부에 구현하여 그 타당성을 검토하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.157.1-157
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• 2001

A new methodology is presented to diagnose faults in equipment plasma. This is accomplished by using neural networks as a pattern recognizer of radio frequency(rf) impedance match data. Using a realtime match monitor system, the match data were collected. The monitor system consisted mainly of a multifunction board and a signal flow diagram coded by Visual Designer. Plasma anomaly was effectively represented by electrical match positions. Twenty sets of fault-symptom patterns were experimentally simulated with experimental variations in process factors, which include rf source power, pressure, Ar and O$_2$ flow rates. As the inputs to neural networks, two means and standard deviations of positions were used ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.157.4-157
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• 2001

An effective approach to detect and diagnose multiple failures in a dynamic system is proposed for the case where the measurement noise is correlated sequentially in time. It is based on the modified interacting multiple-model (MIMM) estimation algorithm in which a generalized decorrelation process is developed by employing the autoregressive (AR) model for the correlated measurement noise. Numerical example for the nuclear steam generator is provided to illustrate the enhanced performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.281-286
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• 1992

This paper describes a duplexed process control system for a boiler-turbine system of power plant, which is composed of supervisor, controller, and simulater subsystems. Its embeded POL(Problem oriented language) as a structured control language enables this system to do a real-time distributed control and fault diagnosis by simple programming with the actual implementation of advanced control algorithms such as PID autotuning and GPC, etc, the performance of overall system has been greatly enhanced.