• Journal of Power System Engineering
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• v.2 no.2
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.148-154
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• 2009

In recent days, large-sized flat-panel display (FPD) has been increasingly applied to computer monitors and TVs. Mura defects, appearing as low contrast or non-uniform brightness region, sometimes occur in manufacturing of the Thin-Film Transistor Liquid-Crystal Displays (TFT-LCD). Implementation of automatic Mura inspection methods is necessary for TFT-LCD production. Various existing Mura detection methods based on regression diagnostics, surface fitting and data transformation have been presented with good performance. This paper proposes an efficient Mura detection method that is based on a regression diagnostics using studentized residuals for automatic Mura inspection of FPD. The input image is estimated by a linear model and then the studentized residuals are calculated for filtering Mura regions. After image dilation, the proposed threshold is determined for detecting the non-uniform brightness region in TFT-LCD by means of monitoring the every pixel in the image. The experimental results obtained from several test images are used to illustrate the effectiveness and efficiency of the proposed method for Mura detection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.971-974
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• 2001

In this study, the static and dynamic characteristics of endmilling process was modelled and the analytic realization of chatter mechanism was discussed. In this regard, We have discussed on the comparative assessment of recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental work were performed to show the malfunctional behaviors. For this purpose, new recursive(RLSM) were adopted for the on-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, the stability lobe of chatter was analysed by varying parameter of cutting dynamices in regenerative chatter mechanics.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.2008-2009
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• 2007

The paper considers the relation between on-line monitoring and diagnostics on the one hand and high-voltage (HV) withstand and partial discharge (PD) on-site testing on the other. HV testing supplies the basic data (fingerprints) for diagnostics. In case of warnings by on-line diagnostic systems, off-line withstand and PD testing delivers the best possible information about defects and enables the classification of the risk. Because alternating voltage (AC) is the most important test voltage, the AC generation on site is considered. Frequency tuned resonant (ACRF) test systems are best adapted to on-site conditions. They can be simply combined with PD measuring equipment. The available ACRF test systems and their application to electric power equipment -from cable systems to power transformers - is introduced.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.807-812
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• 2009

An ICRF discharge cleaning and a fast wave electron heating experiment were performed. For automated operation and providing the diagnostics of the ICRF system, the ICRF local network was designed and implemented. This internal network provides monitoring, RF protection, remote control, and RF diagnostics. All the functions of the control system were realized by customized DSP units. The DSP units were tied by a local network in parallel. Owing to the distributed feature of the control system, the ICRF local control system is quite flexible to maintain. Developing the subsystem is a more effective approach compared to developing a large controller that governs the entire system. During the first experimental campaign of the KSTAR tokamak, the control system operated as expected without any major problems that would affect the tokamak operation. The transmitter was protected from harmful over-voltage events through reliable operation of the system.

• Journal of the Korean Vacuum Society
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• v.15 no.4
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• pp.421-426
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• 2006

In examining particulate deposits in the pipes of a chemical vapor deposition (CVD) system, vibration diagnostics is compared and studied against ultrasonic diagnostics, The latter method involves pulsing the outer wall of pipes with an ultrasonic sensor and analyzing the resulting echo to observe particulate deposits inside pipes. Vibration diagnostics examines the existence of particulate deposits by analyzing the difference in the frequencies generated when a vibrator is adhered to the outer wall of pipes. With ultrasonic diagnostics, good test results were obtained only when particulate deposits were attached to the inner wall of the pipes, After some time, however, particulate deposits were not detected properly, as the ultrasonic wave failed to cross the fine gaps created between the inner wall of the pipe and the deposits. The ultrasonic wave bounced back because of the dried particulate deposits on the wall. Thus, it has been proven that the ultrasonic diagnostics is not an appropriate means of examining the particulate deposits in a vacuum, On the other hand, vibration diagnostics succeeded in detecting the particulate deposits regardless of the lapsed time. In conclusion, the vibration diagnostics is being expected as the effective method in monitoring the particulate deposits inside pipes in the CVD system where the desired behavior is reduced frequency along with the particulate deposits in comparison to the case where the pipe is clean.

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.651-658
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• 2005

The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1407-1410
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• 1997

Advanced sensor design and filtering technology have been studied to obtain information for condition monitoring and diagnostics inmachining processes. To develope and economic monitoring system in end milling processes, indirect and reliable type of cutting force estimators were required. In this paper, an estimation method of cutting forces during end milling processes was studied through the measurement of current signals obtained from spindle and feeddrive motors. Cutting force and torque models were derived from the cutting geometry in down milling processes. Relationships between motor currents and cutting forces were also developed in the form of AC and DC components from the developed force models. The validity of the cutting force estimator was confirmed by the experiments under various cutting conditions.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection