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ISSN Online: 2377-424X

ISBN Print: 978-1-56700-474-8

ISBN Online: 978-1-56700-473-1

International Heat Transfer Conference 16
August, 10-15, 2018, Beijing, China

A CALIBRATION TECHNIQUE OF THERMOCHROMIC LIQUID CRYSTAL SHEETS USING ARTIFICIAL NEURAL NETWORKS – A NOVEL ALTERNATIVE

Get access (open in a dialog) DOI: 10.1615/IHTC16.tpm.022438
pages 8651-8660

Sinopsis

Liquid crystal thermography is a non-intrusive/semi-intrusive temperature measurement technique which is being increasingly used nowadays in fields like inverse heat transfer and in the field of bio and medical applications as well. Thermochromic liquid crystal (TLC) is a cholesteric liquid crystal material, which under different temperatures, orients the adjacent liquid crystal molecule planes at certain angles. This results in the reflection of different wavelengths of the visible spectrum of light when illuminated with white light and shows different colours. Such optical characteristics of the TLC are repeatable and reversible. The red (R), green (G) and blue (B) values obtained from the image are converted to Hue (H), Saturation (S) and Intensity (S). An appropriate polynomial fit is then used to describe a relationship between the measured temperatures and the corresponding hue values. This is the conventional methodology followed by most of the researchers for the calibration of the TLC. However, it is observed that the value of hue has a discontinuity near the event point (the temperature at which the colour of TLC sheets start turning red) and the clearing point temperatures (temperature at which the color changes from blue to black). The value of hue has also been observed to change with a change in factors like the angle and intensity of the light source. In this study, an Artificial Neural Network (ANN) is developed which inherently accounts for these and other sources of uncertainties.