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Improvements of Temperature Field Measurement Technique using Neural Network  

Doh Deog Hee (한국해양대 기계정보공학부)
Kim Dong Hyuk (한국해양대 기계정보공학부)
Bang Kwang Hyun (한국해양대 기계정보공학부)
Moon Ji Seob (㈜대우일렉트로닉스)
Hong Seong Dae (한빛파워시비스㈜)
Chang Tae Hyun (경남대학교 기계자동화공학부)
Hwang Tae Gyu (한국해양대 대학원 기계공학과)
Publication Information
Journal of Advanced Marine Engineering and Technology / v.29, no.2, 2005 , pp. 209-216 More about this Journal
Abstract
Thermo-chromic Liquid Crystal(TLC) particles were used as temperature sensor for thermal fluid flow. 1K $\times$ 1K CCD color camera and Xenon Lamp(500w) were used for the visualization of a Hele-Shaw cell The characteristic between the reflected colors from the TLC and their corresponding temperature shows strong non-linearity A neural network known as having strong mapping capability for non-linearity is adopted to quantify the temperature field using the image of the flow. Improvements of color-to-temperature mapping was attained by using the local color luminance (Y) and hue (H) information as the inputs for the constructed neural network.
Keywords
감온액정입자;헤레쇼 셀;신경망;
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