• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.120-124
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• 2002

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 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 variations in process factors, which include rf source power, pressure, Ar, and $O_$2 flow rates. As an input to neural networks, two means and standard deviations of positions were used as well as a reflected power. Diagnostic accuracy was measured as a function of training factors, which include the number of hidden neurons, the magnitude of initial weights, and two gradients of neuron activation functions. The accuracy was the most sensitive to the number of hidden neurons. Interaction effects on the accuracy were also examined by performing a 2$^$4 full factorial experiment. The experiments were performed on multipole inductively coupled plasma equipment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.463-469
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• 2016

This paper presents a composite camera calibration method to determine thermal degradation of power distribution equipment by combining an infrared (IR) camera and a color camera. A calibration jig was first constructed to match the properties of the two cameras. Our calibration and visualization techniques allow for the display of two images, one from the color camera and the other from the IR camera with different field of views (FOVs), on the screen at the same time. To confirm its validity, several case studies have been developed to analyze thermal deterioration limits of indoor and outdoor power distribution facilities.

• 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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• 2002.10a
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• pp.32.5-32
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• 2002

Processing plasmas are playing a crucial role in either depositing thin films or etching fine patterns. Any variability in process factors (such as radio frequency power or pressure) can cause a significant shift in plasma state. When this shift becomes large enough to change operating condition beyond an acceptable level, overall product quality can greatly be jeopardized. Thus, timely and accurate diagnosis of plasma malfunction is crucial to maintaining device yield and throughput. Many diagnostic systems have been developed, including HIPOCRATES [1] and PIES [2]. Plasma equipment was also diagnosed by combining neural network and expert system called Dempster-Schafer Theory [3]. A fact c...

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1522-1528
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• 2007

Electric Power cable is the apparatus that receives electric power from the Korea Electric Power Corporation and supplies electric power to electric train and annex facilities of each railway station. With substantial ripple effect during power blackout accidents, such power blackout accidents must be coped with by discriminating the status of insulation deterioration of electric power cable in advance. Discrimination of insulation deterioration of the electric power cable is normally executed while the power is disconnected and it is very difficult to discover, at early stage, the insulation deterioration of the power cable in operational state since the duration of inspection is limited. This research aims to consider method of diagnosing the insulation deterioration of electric power cable in On-Line state rather than diagnosis in Off-Line state in order to secure reliability of power supply by reducing duration of power blackout (accidental blackout and blackout during works) and by seeking reduction in equipment and manpower used in diagnosis of deterioration through prevention of the accident itself prior to occurrence through early restoration of accident due to insulation deterioration of the electric power cable and assessment of performance of the cable under operation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.413-416
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• 2007

If obstacle in GIS(Gas Insulted Switchgear), its affects are great are on the community and it is consequently demanded lots of difficulities to recover and repair. Accordingly, diagnosis techniques, that are able to prevent from accidents before they happen by providing more stable and highly reliable power effectively and finding sign of the accidents is very important. The strip-senser measured impedance bandwidth of the proposed antenna is from 0.5[GHz] to 2.5[GHz] with the stop band from 0.5[GHz] to 1.7[GHz] for VSWR<2. The antenna is will play an important role for the senser for insulation diagnosis system by UHF method of real site GIS and power equipment using $SF_6$ gas.

• Transactions of The Korea Fluid Power Systems Society
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• v.3 no.1
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• pp.7-14
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• 2006

In this paper, an in-process diagnosis method for performance of position control servo system was studied, which was based upon null bias, slew-rate ratio and delay time measurement. Slew-rate ratio and delay time were analyzed by theoretical analysis, computer simulation and experiment. As a result of these analysis, when spool of servovalve was weared, slew-rate ratio was decreased and delay time was increased.

• Transactions of The Korea Fluid Power Systems Society
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• v.6 no.2
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• pp.22-30
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• 2009

An in-process method of diagnosing the spool wear of hydraulic servovalves was explored. The diagnostic method discussed in this paper is for force-control hydraulic servo systems. The key principle used is that pressure sensitivity of a servovalve drops as the valve spool wears out so that it is possible to determine the spool condition by monitoring pressure sensitivity. A diagnostic algorithm was developed and evaluated through numerical simulation and experiments. Two major steps of diagnosis are the evaluation of null bias of the servovalve and the approximation of pressure sensitivity, both of which could be successfully done during normal operation of a servo system. The difference between a new servovalve and a worn valve could be clearly detected in-process, and the diagnostic test was found to be repeatable.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.115-117
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• 2005

If obstacle in GIS(Gas Insulted Switchgear), its affects are great are on the community and it is consequently demanded lots of difficulities to recover and repair. Accordingly, diagnosis techniques, that are able to prevent from accidents before they happen by providing more stable and highly reliable power effectively and finding sign of the accidents is very important. A novel UHF(Ultra High Frequency)-microstrip antenna is presented. The measured impedance bandwidth of the proposed antenna is from 0.5[GHz] to 15[GHz] with the stop band from 0.5[GHz] to 10.7[GHz] for VSWR<2. Form results of this study, The antenna is will play an important role for the sensor for insulation diagnosis system by UHF method of real site GIS and power equipment using $SF_6$ gas.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1686-1693
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• 2014

In this paper, oil-paper samples composed of transformer windings were used to investigate the insulation degradation process subjected to partial discharge (PD), with artificial defects inside to simulate the PD induced insulation degradation. To determine appropriate test voltages, the breakdown time obtained through a group of accelerated electrical degradation tests under high voltages was firstly fitted by two-parameter Weibull model to acquire the average breakdown time, which was then applied to establish the inverse power law life model to choose advisable test voltages. During the electrical degradation process, PD signals were synchronously detected by an ultra-high frequency (UHF) sensor from inception to breakdown. For PD analysis, the whole degradation process was divided into ten stages, and chaos theory was introduced to analyze the variation of three chaotic parameters with the development of electrical degradation, namely the largest Lyapunov exponent, correlation dimension and Komogorov entropy of PD amplitude time series. It is shown that deterministic chaos of PD is confirmed during the oil-paper degradation process, and the obtained results provide a new effective tool for the diagnosis of degradation of oil-paper insulation subjected to PD.