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亚麻纤维可与棉纤维混纺以提高织物美感,改善其性状和缝制性能.混纺机织物的质量和成本受混纺中亚麻含量的影响.显微镜分析和化学分析现被用于测定织物中亚麻的含量。本文中叙述一种方法,应用傅里叶转换近红外线(FT-NIR)光谱学,迅速地及非入侵地预测亚麻/棉混纺物中亚麻百分率.以通过重量测定的亚麻/棉纤维经磨制后的混纺物作为与NIR光谱相比较的参考样品,用部分最小二乘方回归分析法开发一个校准模式.最佳的模式是产生在校正散射的增加同由以有效的标准误差值2.2%给定的光谱数据第一次衍生过程中的结合处;而且仅用这个因素可以形成模式.用此模式预测了在亚麻和棉纤维的特定混纺物、亚麻/棉混纺纱和各种非洗涤的亚麻/棉混纺织物中的亚麻含量,给出预测值的标准误差小于3%.然而该校准模式应用于洗涤织物会产生较高的误差值.这个结果似乎是由于洗涤工艺所导致的蜡组分的损失和织物NIR吸光度值的本质变化而造成的。于是开发了一个可替换的校准模式用于洗涤和染色的织物,用该替换的模式能以4～6%的误差来预测染色织物中亚麻的含量。
Flax fibers can be blended with cotton fibers to improve the fabric’s aesthetics and to improve its properties and sewing properties The quality and cost of blended fabrics are affected by the amount of flax blended in the blends Microscopy and chemical analysis are now used to determine flax content in fabrics . This article describes a method for rapid and non-invasive prediction of flax content in flax / cotton blends using Fourier Transform Near-Infrared Spectroscopy (FT-NIR) Spectroscopy. Flax / cotton fibers The resulting blend was used as a reference sample for comparison with the NIR spectra to develop a calibration mode using partial least squares regression analysis. The best mode was to generate an increase in corrected scatter equal to the increase of corrected scatter by an effective standard error of 2.2% The combination of defined spectral data in the first derivation process and the formation of patterns using only this factor.It predicts the specific blends of linen and cotton fibers, linen / cotton blends and various non-laundered Flax / cotton blended fabric flax content, given the standard deviation of the predicted value of less than 3% However, the calibration mode applied to the washing fabric will produce higher error value.This result seems to be due to the wax component of the washing process Loss and fabric NIR absorbance values caused by the nature of change. An alternative calibration mode was then developed for washable and dyed fabrics, with which a 4 to 6% error could be used to predict flax content in dyed fabrics.