• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.604-608
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• 2004

In this paper, an efficient method is proposed to analyze the radial error of a miniaturized-high speed spindle system. Initially, a device is constructed for measuring the radial error motion using capacitance sensors. The capacitance sensors are placed perpendicular to the axis of the shaft and at 90o to each other. The spindle is rotated at high speed and the profile of the spindle is recorded. An algorithm is developed for analyzing the spindle data and determining the radial error of spindle. The present algorithm uses homogeneous transform matrix (HTM) method and iterative process for determining the radial error. The analysis procedure is performed for different speeds of the spindle. The data obtained from the present system and the results of evaluation are also presented in this paper. It is observed that this method is effective in determining and analyzing the spindle errors for high speed miniaturized spindle.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.261-270
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• 1999

Sintering transforms powdered ore into lumped ore so that the latter can be used in a blast furnace. The powdered or combined with coke and other materials is loaded into a container and moved along by a pallet while the ignited coke burns. The speed by which the pallet moves determines how much sintering takes place. Since the process is complicated and lacks an accurate mathematical model, human operators manually control the speed by monitoring various factors in the plant. In this paper, we propose a neural network-based pallet speed controller which copies human operator knowledge. Actual process data were collected from a sintering plant for eight months and preprocessed to remove noisy and inconsistent data. A multilayer perceptron was trained using a back-propagation learning algorithm. In on-line testing at the sinter plant, the proposed model reliably controlled pallet speed during normal operation without the help of human operators. Moreover, the quality and productivity was as good as with human operators.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.805-809
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• 2002

The support bearing requires high DN to raise specific energy efficiency for the state of the art rotating machine with high speed. Especially for the system has a big rotor(670 kgf) with high speed(about one million DNs) such as the pulsed generator, the selection of the bearing and lubrication method are very important. So the study for the critical speed of hollow rotor as well in accordance with high speed rotor and a full analysis are needed for rotor bearing system. This paper describes the analysis for rotor bearing system of pulsed generator compared with experimental data. The bearing and lubrication method are discussed as well with experimental data.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.199-207
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• 2008

A linear wind prediction program, WAsP, was employed to predict wind speed at two different sites located in complex terrain in South Korea. The reference data obtained at locations more than 7 kilometers away from the prediction sites were used for prediction. The predictions from the linear model were compared with the measured data at the two prediction sites. Two compensation methods such as a self-prediction error method and a delta ruggedness index (RIX) method were used to improve the wind speed prediction from WAsP and showed a good possibility. The wind speed prediction errors reached within 3.5 % with the self prediction error method, and within 10% with the delta RIX method. The self prediction error method can be used as a compensation method to reduce the wind speed prediction error in WAsP.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.1
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• pp.50-58
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• 2003

An analytical study was carried out to investigate the performance of an oil pumping system of a variable speed compressor using a commercial CFD program. The simulations for the oil supplying system with the oil and air mixture were performed by varying compressor speed from 40 Hz to 90 Hz. Comparing the predicted with the measured data on the modified scroll compressor validated the simulation model. The predicted results were consistent with the test data with a maximum deviation of 12.8%. The oil flow rate significantly increased with a rise of compressor speed due to a higher oil flow rate from the swing pump and a greater centrifugal force on oil gallery.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.1-8
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• 2004

Thermal distortion is a critical issue in machine tools, especially in high speed machining. This is the reason why recent machine tools have thermal compensation function. To compensate thermal distortion, it is necessary to make a model that has some relationship between temperature and deformation. Various experimental methods ye widely been used in thermal test: constant spindle speed, unit step speed increase, random spindle speed, etc. This paper focuses on which type of spindle operation condition is good for thermal experiment. Also, experimental data is modeled using multiple linear regression models and compared each other to select a method. Consequently, it turned out at e condition of 75％ constant of maximum spindle speed is good enough to generate temperature and distortion data.

• 한국연소학회:학술대회논문집
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• 2012.04a
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• pp.181-183
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• 2012

Syngas laminar flame speed measurements were carried out at atmospheric pressure and ambient temperature using the Bunsen flame configuration with nozzle burner as a fundamental study on flame stability of syngas. Representative syngas mixture compositions ($H_2:CO$) such as 25:75%, 50:50% and 70:25% and equivalence ratios from 0.5 to 1.4 were investigated. The measured laminar flame speeds were in good agreement with the previous numerical data as well as experimental data available in the literatures over a wide range of equivalence ratio tested. It was reconfirmed that the laminar flame speed gradually increased with the increase in $H_2$ content in a fuel mixture. In particular, the significant increasing rate of flame speed was observed with the increase in equivalence ratio.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.268-273
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• 2008

A linear wind prediction program, WAsP, was employed to predict wind speed at two different sites located in complex terrain in South Korea. The reference data obtained at locations more than 7 kilometers away from the prediction sites were used for prediction. The predictions from the linear model were compared with the measured data at the two prediction sites. Two compensation methods such as a self-prediction error method and a delta ruggedness index (RIX) method were used to improve the wind speed prediction from WAsP and showed a good possibility. The wind speed prediction errors reached within 3.5 % with the self prediction error method, and within 10% with the delta RIX method. The self prediction error method can be used as a compensation method to reduce the wind speed prediction error in WAsP.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.32-40
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• 2003

In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.173-178
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• 2021

In this paper, we find a suitable methodology for Korean Sentiment Analysis through a comparative experiment in which methods of embedding and natural network models are learned at the highest accuracy and fastest speed. The embedding method compares word embeddeding and Word2Vec. The model compares and experiments representative neural network models CNN, RNN, LSTM, GRU, Bi-LSTM and Bi-GRU with IKEA review data. Experiments show that Word2Vec and BiGRU had the highest accuracy and second fastest speed with 94.23% accuracy and 42.30 seconds speed. Word2Vec and GRU were found to have the third highest accuracy and fastest speed with 92.53% accuracy and 26.75 seconds speed.