APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO CLASSIFY TEXTILE FIBERS BASED ON UV-Vis DIFFUSE REFLECTANCE SPECTROSCOPY

作者：Wang, C.; Chen, Q.; Hussain, M.; Wu, S.; Chen, J.; Tang, Z.^*

来源：Journal of Applied Spectroscopy, 2017, 84(3): 391-395.

DOI：10.1007/s10812-017-0481-8

• textile fiber
• identification
• principal component analysis
• UV-Vis diffuse reflectance spectroscopy

This study provides a new approach to the classification of textile fibers by using principal component analysis (PCA), based on UV-Vis diffuse reflectance spectroscopy (UV-Vis DRS). Different natural and synthetic fibers such as cotton, wool, silk, linen, viscose, and polyester were used. The spectrum of each kind of fiber was scanned by a spectrometer equipped with an integrating sphere. The characteristics of their UV-Vis diffuse reflectance spectra were analyzed. PCA revealed that the first three components represented 99.17% of the total variability in the ultraviolet region. Principal component score scatter plot (PC1 x PC2) of each fiber indicated the accuracy of this classification for these six varieties of fibers. Therefore, it was demonstrated that UV diffuse reflectance spectroscopy can be used as a novel approach to rapid, real-time, fiber identification.

• 出版日期2017-7
• 单位浙江理工大学