• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.408-408
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• 2000

A parabolic dish concentrator used in a high temperature application of solar energy tracks the sun's movement by two axis sun tracking system. In such a system, sun tracking performance affects the system efficiency directly. Generally the higher the tracking accuracy is, the better the system performance is. A large number of parabolic dish type concentrators has been developed and implemented in the world. However none of them clearly provided a qualitative method of how the accuracy of the sun tracking system can be evaluated. The work presented here is the evaluation of sun tracking performance of parabolic dish concentrator, which follows the sun's movement by the sensor, using computer vision system. We install a camera on the parabolic dish concentrator. While the concentrator follows the sun, sun's images are captured continuously. Then the performance of sun tracking system was evaluated by analyzing the variation of the position of the sun in the images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.260-265
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• 1994

Efforts have been devoted to developing rapid and accurate methods for measuring the errors of machine tools. The method os measurement and calibration of machine tool errors should be general and efficient. The objective of this study is to show in detail the full sequence from the measurement of errors factors to the verification of the positioning accuracy after compensation for the volumetric error. In this paper, we described the steps in measuring the volumetric error parameters, a general error model composed of error parameters, temperature, and the desired position. The validity of the error calibration methods proposed in this paper was tested using a vertical 3-axis CNC machine with a laser interferometer and a ball bar.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.357-360
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• 2009

The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. In this research, we tried the back-propagation algorithm of artificial neural network to find an optimum solution in the cooling system design of injection mold. The cooling system optimization problem that was once solved by a response surface method with 4 design variables was solved by applying the back-propagation algorithm, resulting in a solution with a sufficient accuracy. Furthermore the number of training points was much reduced by applying the fractional factorial design without losing solution accuracy.

• Journal of the Korean Institute of Telematics and Electronics
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• v.8 no.5
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• pp.1-9
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• 1971

An analog to digital converter Ivhich is applicable to mass production of digital multimeter is developed. The solid state digital instrument has accuracy $\pm$0.1% of feading $\pm$1 digit over 1 mV to 1000 volts with high input impedance and automatic function. All possibility to affect the distortion of A/D converter is tudied. As a result, useful linearity with high temperature stability of integrating waveforms is achieved by the very simplified circuit configuration to assure the proposed accuracy under various ambient condition.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.6
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• pp.259-266
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• 2005

Short-term load forecasting algorithm using neural networks and the sensitivity of temperatures in the summer season is proposed. In recent 10 years, many researchers have focused on artificial neural network approach for the load forecasting. In order to improve the accuracy of the load forecasting, input parameters of neural networks are investigated for three training cases of previous 7-days, 14-days, and 30-days. As the result of the investigation, the training case of previous 7-days is selected in the proposed algorithm. Test results show that the proposed algorithm improves the accuracy of the load forecasting.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.36-40
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• 2002

The development of feed drive system with high speed and accuracy has been a major issue in the machine tool industry. Linear motors can be used as the efficient tool to achieve fast feed mechanism and high accuracy. However. a high speed feed drive system with linear motors can generate heat problems such as the variation of temperature distribution and the resultant thermal stress. In this paper, the important heat sources and the resultant thermal errors are presented. The thermal deformation characteristics of the machine tool with linear motors were identified, which are thermal expansion of linear scale, shrinkage, expansion and bending in the machine tool structure.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.91-93
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• 2004

Load forecasting is essential in order to supply electrical energy stably and economically in power systems. ANNs have flexibility to predict a nonlinear feature of load profiles. In this paper, we selected just the necessary input variables used in the paper(2) which is based on the phase-space embedding of a load time-series and reviewing others. So only 5 input variables were selected to forecast for spring, fall and winter season and another input considering temperature sensitivity is added during the summer season. The training cases are also selected from all previous data composed training cases of a 7-day, 14-day and 30-day period. Finally, we selected the training case of a 7-day period because it can be used in STLF without sacrificing the accuracy of the forecast. This allows more compact ANNs, smaller training cases. Consequently, test results show that compact neural networks can be forecasted without sacrificing the accuracy.

• Journal of Ship and Ocean Technology
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• v.7 no.4
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• pp.41-49
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• 2003

Welding deformation reduces the accuracy of ship hull blocks and decreases productivity due to the need for correction work. Preparing an error-minimizing guide at the design stage will lead to higher quality as well as higher productivity. Therefore, developing a precise method to predict the weld deformation is an essential part of it. This paper proposes an efficient method for predicting the weld deformation of complicated structures based on the inherent strain theory combined with the finite element method. A simulation of a stiffened panel confirmed the applicability of this method to simple ship hull blocks.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.8
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• pp.652-660
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• 2003

T-history method, measuring heat-of-fusion of phase change material (PCM) in sealed tubes, has the advantages of a simple experimental device and no requirements in sampling process. However, a degree of supercooling used in selecting the range of latent heat release and neglecting sensible heat during the phase change process can cause significant errors in determining the heat of fusion in the original method, which has been improved in order to predict better results by us. In the present study, the modified method was applied to a variety of PCM such as paraffin and lauric acid having very small or no supercooling with a satisfactory precision. Also the selection of inflection point and temperature measurement position was fumed out not to affect the accuracy of heat-of-fusion significantly. As a result, the method can provide an appropriate means to assess a new developed PCM by cycle test even if a very accurate value cannot be obtained.

• Analytical Science and Technology
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• v.34 no.4
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• pp.180-190
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• 2021

This study compared the efficacy of chiral GC and chiral HPLC for the analysis of nicotine. To develop a suitable dispersive liquid-liquid microextraction (DLLME) method, the following parameters were optimized: pH, extraction solvent, dispersive solvent, type and quantity of salt, and laboratory temperature. The validation of the method was carried out by the established HPLC method. The LODs were 0.11 ㎍/mL and 0.17 ㎍/mL for the (S)- and (R)- enantiomers, respectively. The LOQs were 0.30 ㎍/mL and 0.44 ㎍/mL, respectively. The optimal calibration range was between 0.30-18 ㎍/mL and 0.44-4.40 ㎍/mL, respectively, and the correlation coefficient (r²) was 0.9978-0.9996. The intra-day accuracy was 79.9-110.6 %, and the intra-day precision was 1.3-12.0 %. The inter-day accuracy was 87.8-108.0 %, and the inter-day precision was 4.0-12.8 %. E-liquid and biological fluids (urine and saliva) were analyzed using the established method.