XU Lin, ZHANG Qiang, DONG Ya-nan, JING Yi-fan, LI Jun-hui, ZHANG Hong-song, AN Le-le. Direct Resolution of Cotton/Polyester Blend Proportions Using Near-infrared Spectroscopy of Pure Fabrics and Formula Regression Algorithm[J/OL]. Journal of Instrumental Analysis, 2026, 1-8.
DOI:
XU Lin, ZHANG Qiang, DONG Ya-nan, JING Yi-fan, LI Jun-hui, ZHANG Hong-song, AN Le-le. Direct Resolution of Cotton/Polyester Blend Proportions Using Near-infrared Spectroscopy of Pure Fabrics and Formula Regression Algorithm[J/OL]. Journal of Instrumental Analysis, 2026, 1-8. DOI: 10.12452/j.fxcsxb.26012603.
Direct Resolution of Cotton/Polyester Blend Proportions Using Near-infrared Spectroscopy of Pure Fabrics and Formula Regression Algorithm
Quantitative analysis of textile blends is key to industrial quality control. Addressing the problem that traditional partial least squares(PLS) modeling requires support from a large number of samples, this study proposes a quantitative analysis method for blended fabrics based on near-infrared (NIR) spectroscopy and formula regression algorithm. In the experiment, 45 cotton/polyester blend samples, along with 10 pure cotton and 10 pure polyester fabric samples, were selected to compare the performance of absorbance and Kubelka-Munk(K-M) values in modeling. The research results indicate that the modeling effect based on K-M values(
R
2
=0.96, RMSEP=4.18%) is significantly superior to that of absorbance (
R
2
=0.82, RMSEP=9.10%), meeting the requirements for fiber content tolerance in the national standard GB/T 29862-2013. Compared with traditional analytical methods, the core advantage of this method lies in the elimination of the need for large-scale blend sample modeling; accurate prediction of cotton/polyester blend proportions can be achieved using only a small number of pure component fabric spectra. This study provides a low-cost, high-efficiency simplified modeling scheme for the rapid quantitative analysis of textile components, possessing strong practical application value.
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