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样本质量对近红外法预测远红外纤维含量的影响 被引量:2

Influence of sample weight on prediction of far-infrared fiber content based on near-infrared spectroscopy
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摘要 传统的纤维定量方法不能满足远红外纤维与其基体普通纤维之间的定量分析,由此提出采用近红外光谱分析技术。选用常见的远红外涤纶、远红外丙纶、普通涤纶和丙纶作为研究对象,利用人为自主混合取样的方法,采用偏最小二乘法(PLS),结合样本质量对所建模型的影响,建立了有关远红外纤维含量的远红外涤纶/涤纶,远红外丙纶/丙纶2个校正模型,发现2个模型都能达到比较好的预测效果。结果显示:远红外涤纶/涤纶定量校正模型的远红外涤纶含量的平均相对误差为2.03%;远红外丙纶/丙纶定量校正模型的远红外丙纶含量的平均相对误差为3.76%。认为近红外光谱分析技术可以用于远红外纤维的定量分析。 The convenional methods can not meet the infraed fiber and the common fiber of the substrate, so requirement on quantitative analysis of the far- the near-infrared spectrum analysis technique is presented. Common far-infrared polyester, far-infrared polypropylene fibers, polyester and polypropylene fibers are chosen as the research object. In this reseach, taking into consideration the influence of sample weight on the established model, the far-infrared polyester/polyester and far-infrared polypropylene/ polypropylene models which can achieve good prediction results are established by manual sampling and PLS method. Results show that the average relative errors of the far-infrared polyester and far-infrared polypropylene content are 2.03% and 3.76%. The research shows that the near-infrared spectrum technique can be used as a method for quantitative analysis of far-infrared fibers.
出处 《纺织学报》 EI CAS CSCD 北大核心 2014年第5期19-22,共4页 Journal of Textile Research
基金 国家质检总局科技计划项目(2010QK310)
关键词 近红外光谱 远红外纤维 定量分析 偏最小二乘法 near-infrared spectrum far-infrared fiber quantitative analysis PLS
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