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21 July 2010Research on content measurement of textile mixture by near infrared spectroscopy based on principal component regression
A new method for accurate measurement of content of textile mixture by use of Fourier transform near infrared
spectroscopy is put forward. The near infrared spectra of 56 samples with different cotton and polyester contents were
obtained, in which 41 samples, 10 samples and 5 samples were used for the calibration set, validation set and prediction
set respectively. Principal component analysis (PCA) was utilized for the spectra data compression. Principal component
regression (PCR) model was developed. It indicates that the MAE is within 2.9% and the RMSE is less than 3.6% for the
validation samples, which is suitable for the prediction of unknown samples. The PCR model was applied to predict
unknown samples. Experimental results show that this approach by use of Fourier transform Near Infrared Spectroscopy
can be used to quantitative analysis for textile fiber.
Li Yan andLi Liu
"Research on content measurement of textile mixture by near infrared spectroscopy based on principal component regression", Proc. SPIE 7749, 2010 International Conference on Display and Photonics, 77490D (21 July 2010); https://doi.org/10.1117/12.869396
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Li Yan, Li Liu, "Research on content measurement of textile mixture by near infrared spectroscopy based on principal component regression," Proc. SPIE 7749, 2010 International Conference on Display and Photonics, 77490D (21 July 2010); https://doi.org/10.1117/12.869396