Jin Xiaoke, Memon Hafeezullah, Tian Wei, Yin Qinli, Zhan Xiaofang, Zhu Chengyan
Appl Opt. 2017 Apr 20;56(12):3570-3576. doi: 10.1364/AO.56.003570.
Synthetic fibers account for about half of all fiber usage, with applications in every textile field. The phenomenon of fiber composition not matching the label harms consumer interests and impedes market development. Hyperspectral imaging technology as a potential technique can be utilized to discriminate mass synthetic fibers rapidly and nondestructively and achieves the functions that traditional Fourier transform infrared instruments do not have. On the basis of investigating the impact of dope-dyeing and wrapping processes on spectra, the spectral features (from 900 to 2500 nm) of six categories of synthetic fibers were extracted with a hyperspectral imaging system. A principal component analysis-linear discriminant analysis model was developed to discriminate the chemical content of fibers in different colors and structures, which showed 100% discrimination accuracy. Results demonstrated the feasibility of a hyperspectral imaging system in synthetic fiber discrimination. Therefore, this method offers a more convenient alternative for textile industry on-site discrimination.
合成纤维约占所有纤维使用量的一半，应用于各个纺织领域。纤维成分与标签不符的现象损害了消费者利益，阻碍了市场发展。高光谱成像技术作为一种潜在技术，可用于快速、无损地鉴别大量合成纤维，并实现传统傅里叶变换红外仪器所不具备的功能。在研究原液染色和包覆工艺对光谱影响的基础上，利用高光谱成像系统提取了六类合成纤维的光谱特征（900至2500纳米）。建立了主成分分析-线性判别分析模型，以鉴别不同颜色和结构纤维的化学成分，其判别准确率达100%。结果证明了高光谱成像系统在合成纤维鉴别中的可行性。因此，该方法为纺织行业现场鉴别提供了一种更便捷的选择。
