• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.161-163
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• 1987

An FTCS is developed for the purpose of improving the reliability of a process control system. The proposed FTCS has capabilities of failure detection, back-up control, graphic display, and self-checking. Also the FTCS is combined with the process simulator to experiment in laboratory for the evaluation of performance of operation. The FTCS is applied to Thermal Power Plant .

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.147-153
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• 1997

Fault diagnosis technique in machining system which is one of engineering techniques absolutely necessary to automation of manufacturing system has been proposed. As a whole, diagnosis process is explained by two steps: sensor data acquisition and reasoning current state of system with the given sensor data. Flexible disk grinding process implemented in milling machine was employed in order to obtain empirical manufacturing process information. Resistance force data during machining were acquired using tool dynamometer known as sensor which is comparably accurate and reliable in operation. Tool status during the process was analyzed using influnece diagram assigning probability from the statistical analysis procedure.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.473-474
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• 2008

This paper proposes that the relative transmittance and emission intensity measured via optical emission spectroscopy (OES) is a useful for fault detection of reactive ion etch process. With the increased requests for non-invasive as well as real-time plasma process monitoring for fault detection and classification (FDC), OES is suggested as a useful diagnostic tool that satisfies both of the requirements. Relative optical transmittance and emission intensity of oxygen plasma acquired from various process conditions are directly compared with the process variables, such as RF power, oxygen flow and chamber pressure. The changes of RF power and Pressure are linearly proportional to the emission intensity while the change of gas flow can be detected with the relative transmittance.

• Korean Management Science Review
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• v.12 no.1
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• pp.19-34
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• 1995

The objective of this paper is to present a framework for an expert system for fault diagnosis in an FMS (Flexible Manufacturing Systyem). First, a system is analyzed structurally and functionally, giving the relationships between the system's components. These relationships, represented by strata, are are then stored in a deep knowledge base (DKB). Next, the specific knowledge, represented by echelons, about the symptoms and their probable causes for each component is stored in a shallow knowledge base (SKB) in the form of rule. When the fault diagnosis process begins, it starts to search the DKB and then the SKB, which is called hybrid reasoning in artificial intelligence.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.372-375
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• 1989

In this paper, a new FTCS with the ability to perform original control objective without considerable loss of control performance in the face of any fault is proposed. The FTCS is composed of two interacting units, Adaptive Controller Unit and Fault Detection/Classification, where ACU performs primary control objective with basic process information(I/O) and environmental information fed by FDU and where FDU detect and classify faults and make decision on remidial action by the use of information provided by ACU.

• Progress in Superconductivity and Cryogenics
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• v.5 no.2
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• pp.16-19
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• 2003

Quench and recovery process of high-temperature-superconductor (HTS) film deposited on the sapphire substrate is studied numerically. The quench is developed by fault current and the superconductivity is recovered by convection of heat into coolant. After the fault current. the HTS film experiences the quench state. current sharing state. and finally recovers the superconductivity. Numerical results of this study are compared to the previous experimental results. and shows that this numerical work can explain the mechanism of quench/recovery characteristics of HTS film.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.15-19
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• 1994

The application of neural network for fault dection of cutting force in turning was introduced. This monitoring system consist of a RBF predicton model and a ART-1 pattern classifier. RBF prediction model predict a cutting force signal. Prediction error of predictor is used for a input vector of ART-1 pattern classifier. Prediction error could be successfully performed to fault signal monitoring of ART-1 pattern classifier.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2003.02a
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• pp.272-275
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• 2003

Quench and recovery process of high-temperature-superconductor(HTS) film deposited on the sapphire substrate is studied numerically. The quench is developed by fault current and the superconductivity is recovered by convection of heat into coolant. After the fault current, the HTS film experiences the quench state, current sharing state, and finally recovers the superconductivity. Numerical results of this study are compared to the previous experimental results, and shows that this numerical work can explain the mechanism of quench/recovery characteristics of HTS film.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2003.10a
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• pp.181-184
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• 2003

Quench and recovery process of high-temperature -superconductor (HTS) film deposited on the sapphire substrate is studied numerically. The quench is developed by fault current and the superconductivity is recovered by convection of heat into coolant. After the fault current, the HTS film experiences the quench state, current sharing state, and finally recovers the superconductivity. Numerical results of this study are compared to the previous experimental results, and shows that this numerical work can explain the mechanism of quench/recovery characteristics of HTS film.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.1-8
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• 2016

As demand for paper cups markedly increases, this has brought about a requirement to develop fast paper cup forming machines. However, the fast manufacturing speed of these machines causes faults to occur more frequently in the final product. To reduce the possibility of producing faulty products, it is necessary to develop technologies to monitor the manufacturing process and diagnose the machine status. In this research, we selected the main driving axis of the forming machine for fault diagnosis. We searched the states of rotational elements related to the driving axis and suggested a fault diagnostic system based on spectrum analysis consisting of a real-time data acquisition device, accelerometers, and a diagnosis algorithm. To evaluate the developed fault diagnostic system, we performed experiments using a test station which resembles the actual paper cup forming machine. As a result, we were able to confirm that the proposed system was sufficiently feasible to diagnose any abnormalities in the operation of the paper cup forming machine.