Characteristic wavelength of textile fiber in near infrared spectroscopy

Abstract

Near Infrared (NIR) spectroscopy in the region from 1300 to 1700nm, coupled with multivariate analytic statistical techniques, have been used to predict the chemical properties of textile fiber. Molecule absorbs electromagnetic wave with especial wavelength, which leads to bring characteristic absorption spectrum. Characteristic wavelength is the most important parameter in NIR detection. How to select characteristic wavelength is the key to NIR measure. Different mathematical methods are used to find relationship between the NIR absorption spectrum and the chemical properties of the textile fiber. We adopt stepwise multiple linear regression (SMLR) to select characteristic wavelength. As objective condition is limited, this article only refers to cotton and terylene. By computing correlation coefficient, we establish calibration equation with the smoothed absorbance data. Finally, the bias was controlled under 6%. Then, we find that NIR can be used to carry on qualitative analysis and quantitative analysis of the textile.