Rapid identification of fibers from different waste fabrics using the near-infrared spectroscopy technique
Rapid identification of fibers from different waste fabrics using the near-infrared spectroscopy technique
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DOI：
10.1177/0040517518817043
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发表时间：
2019-09-01
影响因子：
2.3
通讯作者：
Jiang, Wei
中科院分区：
文献类型：
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作者：
Zhou, Chengfeng;Han, Guangting;Jiang, Wei
纤维识别是废旧纺织品回收的首要任务，对废旧纺织品的回收再利用具有重要的指导作用。以186种不同纤维品种的纯纺纺织品为原料，采集近红外光谱，研究不同纤维品种间的差异。利用近红外光谱建模技术建立了快速准确的纺织纤维分类识别模型。采用软独立建模的类类比法进行建模。结果表明，选择6800-5300 cm（-1）的波数范围，对光谱进行一阶导数处理，模型识别率可达97%。通过外部验证发现，该模型对涤纶、锦纶、腈纶、丝绸和羊毛的预测准确率为100%。对棉纤维和涤纶织物的预测准确率在90%以上。上述结果表明，本研究建立的纺织纤维识别模型可以用于快速、准确地识别和分选废旧纺织品。
Fiber identification is the primary task of waste textile recycling, which plays an important guiding role in the recovery and reuse of waste textiles. In this study, 186 pure spinning textiles with different fiber species were chosen as the raw materials, the near-infrared spectra were collected and the differences among various fibers species were also studied. The fast and accurate classification/identification model of textile fiber was established using the near-infrared spectral modeling technique. The soft independent modeling of class analogy method was used to construct the model. The results show that the model recognition rate can be up to 97% after selecting the wavenumber range of 6800-5300 cm(-1) with the first derivative treatment on the spectra. It was found by external validation that the prediction accuracy of the model was 100% for polyester, polyamide, acrylic, silk and wool. The prediction accuracy of cotton fiber and polyester fabric was higher than 90%. The above result demonstrated that the textile fiber identification model established in this study can be used for fast and accurate identification and sorting of waste textiles.