摘要
建立了分析精度较高的用于检测棉-涤混纺面料里含棉量的近红外光谱分析模型。选择了50个棉-涤混纺面料作为对象,自行设计采样装置,采集其近红外光谱;然后,经一阶导数、二阶导数、Savitzky-Golay滤波等方法预处理,结合偏最小二乘法,建立了4个棉成分的定量分析模型。结果表明:Savitzky-Golay滤波对定标结果几乎没有影响;经一阶导数预处理后的光谱数据结合偏最小二乘法建立的模型具有较高的分析精度,定标均方差和预测均方差分别达到了0.022和0.018,分析误差控制在±0.05以内,基本满足了纺织领域快速定量检测的精度需求。同时,还分析了近红外光谱技术在该应用领域的研究重点。
A calibration model for determining the cotton content in cotton-terylene textile precisely was established. The near infrared spectra of 50 cotton-terylene textile samples were collected using self-designed accessory, and Savitsky-Goaly filter smoothing, first order derivative and second order derivative were used to pretreat the spectra. Calibration models for cotton content were established with Partial Least Square(PLS). The experimental results indicate that Savitsky-Goaly filter smoot- hing spectral treatments can not affect the performance of the model in this case, but NIR technique can analyze the cotton content in the textile precisely. The Root Mean Square Error of Calibration (RMSEC) and Root Mean Square Error of Prediction(RMSEP) are 0. 022 and 0. 018 respectively,and the error of analysis is restricted in ±0.05. In addition, several key aspects of this application were expressed.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2008年第11期2051-2054,共4页
Optics and Precision Engineering
基金
浙江省科技计划重点资助项目(No.2004C21043)
关键词
近红外光谱
纺织面料
棉含量
偏最小二乘法
预处理
near infrared spectroscopy
textile
cotton content
Partial Least Square(PLS) method
pretreatment