基于近红外光谱和变量优选的棉麻混纺织物棉含量快速检测  

Determination of Cotton Content in Cotton/Ramie Blended Fabric by NIR Spectra and Variable Selection Methods

作　　者：孙通[1] 耿响[2,3] 刘木华[1] 

机构地区：[1]江西农业大学生物光电技术及应用重点实验室,江西南昌330045 [2]江西出入境检验检疫局综合技术中心,江西南昌330038 [3]江西省红外光谱应用工程技术研究中心,江西南昌330038

出　　处：《光谱学与光谱分析》2014年第12期3257-3261,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(31271612);江西省自然科学基金项目(20132BAB214010)资助

摘　　要：纺织品纤维成分的快速检测对其生产过程质量监控、贸易和市场监督均具有重要的意义。利用近红外光谱技术联合变量优选对棉麻混纺织物中的棉含量进行快速检测研究。采用NIRFlex N-500型傅里叶近红外光谱仪在4 000~10 000cm^-1光谱范围内采集样本的反射光谱,对样本光谱进行范围初选和预处理分析。在此基础上,利用UVE（uninformative variables elimination）,SPA（successive projections algorithm）及CARS（competitive adaptive reweighted sampling）方法对光谱变量进行优选,再应用PLS（partial least squares）建立棉麻混纺织物中的棉含量预测模型。最后,采用最优预测模型对未参与建模的样本进行预测。研究结果表明,4 052~8 000cm^-1光谱范围为棉含量较优的建模光谱范围。CARS变量选择方法能较为有效地提高预测模型的精度,CARS-PLS模型的校正集、预测集相关系数和均方根误差分别为0.903,0.749和8.01%,12.93%。因此,近红外光谱联合CARS变量优选可以用于棉麻混纺织物棉含量的快速检测,CARS方法可以有效简化预测模型,提高预测模型性能。Rapid detection of textile fiber components is very important for production process of quality control,trading and market surveillance.The objective of this research was to assess cotton content in cotton/ramie blended fabric quickly by near infrared（NIR）spectrum technology and variable selection methods.Reflectance spectra of samples were acquired by a NIRFlex N-500 Fourier spectroscopy in the range of 4 000~10 000cm^-1,primary election of spectral range and pretreatment analysis were conducted first.Then,three variable selection methods such as UVE（uninformative variables elimination）,SPA（successive projections algorithm）and CARS（competitive adaptive reweighted sampling）were used to select sensitive variables.After that,PLS（partial least squares）was used to develop calibration model for cotton content of cotton/ramie blended fabric,and the best calibration model was used to predict cotton content of samples in prediction set.The result indicates that range of 4 052~8 000cm^-1 is optimal spectral range for cotton content modeling.CARS method is an efficient method to improve model performance,the correlation coefficient and root mean square error of CARS-PLS for calibration and prediction sets are 0.903,0.749and8.01%,12.93%,respectively.So NIR spectra combined with CARS method is feasible for assessing cotton content in cotton/ramie blended fabric,and CARS method can simplify model,improve model performance.

关 键 词：近红外 变量选择 棉麻混纺织物 棉含量 

分 类 号：S123[农业科学—农业基础科学]