• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.34-39
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• 2010

In order to achieve and maintain dimensional accuracy in laser micro-machining, dominant parameters such as laser power and laser focus position need to be monitored and controlled real time. Also, in order to selectively machine multi-layered materials, the material being presently machined need to be recognized. This paper presents an auto-focusing (AF) module to keep laser focus on a large-area surface; a real-time laser power stabilizing module based on optical attenuation; and a laser-induced breakdown spectroscopy (LIBS) module. With these monitoring modules, position error in laser focus on a 4" silicon wafer was kept below $4{\mu}m$, initially $51{\mu}m$, and laser power stability of a UV laser source was improved from 1.6% to 0.3%. Also, the material transition from polyimide to copper in machining of FCCL (flexible copper clad laminate) was successfully observed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.496-501
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• 2018

In this study, we prepared 40, 45, 50, 55, 60, 65, and 70 wt% content composites filled in epoxy matrix for two micro silica and three micro alumina types for use as a GIS heavy electric machine. As a filler type of epoxy composite, micro silica composites showed excellent AC breakdown strength properties compared to micro alumina composites in the case of electrical properties of micro silica and alumina. The electrical breakdown properties of micro silica composites increased with increasing filler content, whereas those of micro alumina decreased with increasing filler content. In the case of mechanical properties, the micro silica composite showed improved tensile strength and flexural strength compared with the micro alumina composite. In addition, mechanical properties such as tensile strength and flexural strength of micro silica and alumina composites decreased with increasing filler content. This is probably because O-H groups are present on the surface of silica in the case of micro silica but are not present on the surface of alumina in the case of micro alumina.

• Progress in Superconductivity and Cryogenics
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• v.16 no.1
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• pp.14-18
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• 2014

The mechanical, electrical and thermal characteristics of insulating materials may significantly affect the performance and reliability of electrical devices using superconductors. General method to provide insulating layer between coated conductors is wrapping coated conductor with Kapton tape. But uniform and compact wrapping without failure or delamination in whole coverage for long length conductor is not a simple task and need careful control. Coating of insulating layer directly on coated conductor is desirable for providing compact insulating layer rather than wrapping insulating layers around conductor. Ceramic added polymer has been widely used as an insulating material for electric machine because of its good electrical insulating properties as well as excellent heat resistance and fairy good mechanical properties. The insulating layer of coated conductor should have high breakdown voltage and possesses suitable mechanical strength and maintain adhesiveness at the cryogenic temperature where it is used and withstand stress from thermal cycling. The insulating and mechanical properties of polymer can be improved by adding functional filler. In this study, insulating layer has been made by adding ceramic particles such as $SiO_2$ to a polymer resin. The size, amount and morphology of added ceramic powder was controlled and their effect on dielectric property of the final composite was measured and discussed for optimum composite fabrication.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.446-459
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• 2000

This study was carried out in order to find out an effective machinery utilization strategy by conducting a survey on utilization and maintenance of agricultural machinery. The survey showed that the no. of utilization hours for power tiller in a year was 190.2hrs, 208.6hrs for tractor, 59.1hrs for rice transplanter, 74.0 hrs for combine, 44.6 cultivator and 254.4hrs for 4.4hrs for grain dryer. The period covered the time the machine was until it became unserviceable. The results are as follows: 10.0yrs for power tiller, 7.5yrs for tractor, 7.4yrs for rice transplanter and 5.4yrs for combine. This indicate that the actual period of use for power tiller and rice transplanter was longer than the expected period of duration years so there is a need for adjustment. The factors considered by the farmers for purchasing agricultural machine were: farm size(32%), machine operation (26.0%), performance(l4.0%) and post or after sales service(12.6%), according to the survey. It showed that repair cost rate in a year was classified into major agricultural machine; 4.8% for combine; 3.9% for tractor; 3.5% for rice transplanter; 2.0% for power tiller; 1.6% for grain dryer; and 1.2% for cultivator. The reasons for poor maintenance were insufficient after sales service(25%) and difficulty in buying parts(75%) because of the unavailability of parts in local shops(55%), imported models(30%) and outmoded model(15%).

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1326-1336
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• 2018

This paper proposes a numerical approach to predict the critical flashover voltages of air gaps under lightning impulses. For an air gap, the impulse voltage waveform features and electric field features are defined to characterize its energy storage status before the initiation of breakdown. These features are taken as the input parameters of the predictive model established by support vector machine (SVM). Given an applied voltage range, the golden section search method is used to compute the prediction results efficiently. This method was applied to predict the critical flashover voltages of rod-rod, rod-plane and sphere-plane gaps over a wide range of gap lengths and impulse voltage waveshapes. The predicted results coincide well with the experimental data, with the same trends and acceptable errors. The mean absolute percentage errors of 6 groups of test samples are within 4.6%, which demonstrates the validity and accuracy of the predictive model. This method provides an effectual way to obtain the critical flashover voltage and might be helpful to estimate the safe clearances of air gaps for insulation design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.89-92
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• 2021

In a manufacturing fields, an abnormality or breakdown of equipment is a factor that causes product defects. Recently, with the spread of smart factory services, a lot of research to predict and prevent machine's failures is actively ongoing. However, there is a big difficulty in developing a classification model because the number of abnormal or failure data of the machine is severely smaller than normal data. In this paper, we present an algorithm for detecting abnormalities in an MCT at manufacturing work site depending on the differences between inputs and outputs of Autoencoder model and analyze its performance. The algorithm detects abnormalities using only features of normal data from manufacturing data of the MCT in which abnormal data does not exist.

• Advanced Industrial SCIence
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• v.2 no.4
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• pp.11-16
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• 2023

The subway is a means of public transportation that plays an important role in the transportation system of modern cities. However, congestion often occurs due to sudden breakdowns and system outages, causing inconvenience. Therefore, in this paper, we conducted a study on failure prediction and prevention using machine learning to efficiently operate the subway system. Using UC Irvine's MetroPT-3 dataset, we built a subway breakdown prediction model using logistic regression. The model predicted the non-failure state with a high accuracy of 0.991. However, precision and recall are relatively low, suggesting the possibility of error in failure prediction. The ROC_AUC value is 0.901, indicating that the model can classify better than random guessing. The constructed model is useful for stable operation of the subway system, but additional research is needed to improve performance. Therefore, in the future, if there is a lot of learning data and the data is well purified, failure can be prevented by pre-inspection through prediction.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.147-150
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• 2006

The thin film of PbTiO3 is fabricated at substrate temperature of 100-150$^{\circ}C$. The infrared spectrum of the ferroelectric thin film is measured as temperature of thermal treatment, 400 - 550$^{\circ}C$. According to infrared spectrum analysis, there are absorption bands at a nearby wave number of 1000 $\sim$ 400 cm-l and the thin film treated by temperature of 550$^{\circ}C$ has absorption bands of wave number 500 cm-l similar to infrared response property of PbTiO3 powder. The pyroelectric infrared detector is fabricated after deposition of Pt and PbTiO3 thin film on Si wafer by sputtering machine. The measured remnant polarization are 11.5-12.5$\muC/cm2$, breakdown electric field Ec is 100-120KV/cm, and voltage responsivity and detectivity is -280V/W, -108cm Hz/W.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.2
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• pp.145-155
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• 2004

From the cooking data, Japanese rice showed higher water uptake but lower expansion volume, pH and iodine blue value than those of Korean rice. Japanese rice had higher maximum viscosity, breakdown viscosity and pasting temperature but lower final viscosity and setback viscosity than those of Korean rice by RVA analysis. Japanese rice had higher LC (low compression) hardness, U stickiness and HC (high compression) stickiness, LC balance and HC balance, but had lower HC hardness and thickness in the tensipresser data. Also Japanese rice had higher stickiness and balance, and lower hardness from the texturometer analysis. Japanese rice showed higher a cooked taste score than that of the Satake cooked taste machine. The various mean values of Japanese rice after cooking showed better cooking characteristics than the Korean rice. These results might be caused because Japanese rice had a little lower amylose and protein content, but higher tat acidity content.