• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.205-209
• /
• 2002

인체의 피부온도는 쾌적성과 감성에 크게 영향을 미치며 의류의 개발이나 건축환경의 설계 등에 활용되고 있다. 단순히 몇몇 측정점에서의 피부온도 데이터가 아니라 인체표면에 걸친 온도분포를 파악함으로써 다양한 정보를 이용하여 보다 광범위한 응용분야에 활용될 수 있을 것이다. 현재 인체표면의 온도분포를 측정하기 위하여 대부분 적외선 열화상 카메라를 활용하고 있다 그러나 열화상 카메라는 서미스터 등을 이용한 피부온 센서에 비하여 온도분해능이 떨어지며 특히 의복내의 피부온을 측정하는 것이 불가능하고 노출된 인체표면에 대해서만 측정이 가능하다. 따라서 본 연구에서는 피부온 센서를 이용한 인체표면 온도분포 측정시스템을 개발하기 위하여 각 센서의 위치와 간격, 그리고 인체 곡면을 따라서 보간법에 따라 온도분포 결과에 미치는 영향을 파악하고 적외선 화상 결과와 비교하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.11
• /
• pp.2008-2013
• /
• 2006

In numerical analysis on evaluating the thermal performance of the thermal equipment, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table itself cannot be used without modelling. In this study applicability of neural networks in modelling the wide temperature range of wet saturated vapor region was examined. the multi-layer neural network consists of a input layer with 1 node, two hidden layers with 10 and 20 nodes respectively and a output layer with 6 nodes. Quadratic and cubic spline interpoations methods were also applied for comparison. Neural network model revealed similar percentage error to spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the wide range of the steam table.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.4
• /
• pp.685-690
• /
• 2008

In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.43 no.9
• /
• pp.805-813
• /
• 2015

This paper introduces the development of temperature mapping code between thermal mesh and structural mesh in KARI Satellite Design Software. Generally, temperature distribution of a satellite varies with the time by the space environment of the orbit, so thermal expansion of the structure should be analysed in design of the satellite. For the sake of the coupled thermal structural analysis, an interpolation algorithm between two finite element heterogeneous grids has been proposed by which temperature transfer is successively conducted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.246-249
• /
• 2007

In numerical analysis for phase change material, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be used without modelling. In this study applicability of neural networks in modelling superheated vapor region of water was examined by comparing with the quadratic spline. neural network consists of an input layer with 2 nodes, two hidden layers and an output layer with 3 nodes. Quadratic spline interpoation method was also applied for comparison. Neural network model revealed smaller percentage error to quadratic spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the superheated range of the steam table.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.437-439
• /
• 1999

적외선 열 화상에는 물체 내부의 결함과 그 물체 표면의 이물질 등의 효과가 모두 포함된 상태이므로 적외선 열 화상 자체만으로는 비정상적인 부분들을 찾아내기 어렵다. 따라서 본 논문에서는 평행 이동 관계에 있는 두 가시광선 영상으로부터 열 화상에 대응하는 보간 영상을 생성하고, 이것을 열 화상과 중첩시킴으로써 가시화하는 방법을 연구한다. 이를 위해서 적외선 센서에 의해 감지된 온도를 매핑한 열 화상을 적외선 카메라로부터 얻고, 적외선 카메라의 양쪽에 부착된 CCD 카메라로부터 좌우의 가시광선 영상을 얻는다. 보간 영상 생성을 위해서 블록 매칭을 이용한 모션 정보를 사용하고, 생성된 보간 영상에서 생기는 구멍(hole)을 메우는 방법을 소개한다. 또한 생성된 보간 영상과 열 화상을 중첩시켜 가시화하는 방법을 기술한다. 이렇게 함으로써 본 논문에서 제안한 가시화 기법은 재해방지를 위한 비파괴 검사 등에 이용될 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.1
• /
• pp.434-439
• /
• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.205-208
• /
• 2008

In numerical analysis numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But most of the thermodynamic properties of the steam table are determined by experiment. Therefore they are supposed to have measurement errors. In order to make noised thermodynamic properties corresponding to errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. the neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure. It was proved that the neural networks give smaller percentage error compared with quadratic spline interpolation. From this fact it was confirmed that the neural networks trace the original values of thermodynamic properties better than the quadratic interpolation method.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.8
• /
• pp.45-54
• /
• 2014

In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.1
• /
• pp.80-87
• /
• 2016

In this work, we conduct a thermal pointing error analysis of the observation satellites considering seasonal and daily temperature variation with interpolated temperature based on prescribed average temperature (PAT) method. Maximum 200 degree temperature excursion is applied to the observation satellites during on-orbit operation, which cause the line of sight (LOS) to deviate from the designated pointing direction due to thermo-elastic deformation. To predict and adjust such deviation, the thermo-elastic deformation analysis with a fine structural finite element model is accomplished with interpolated thermal maps calculated from the results of on-station thermal analysis with a coarse thermal model. After verifying the interpolated temperatures by PAT with two benchmark problems, we evaluate the thermal pointing error.