文档介绍：纺织品中棉含量的近红外光谱快速测定
摘要
本文建立了分析精度较高的用于检测纺织品里含棉量的近红外光谱分析模型。选择了138个纺织品样品作为对象,利用布鲁克TENSOR37型傅里叶红外光谱仪采集其近红外光谱;然后,分别经SNV和小波变换方法预处理,结合偏最小二乘法(PLS)建立了棉成分的定量分析模型。结果表明:经SNV预处理后的光谱数据结合偏最小二乘法(PLS)建立的模型具有较高的分析精度,模型的交叉验证均方根误差(RMSECV)和预测均方根误差(RMSEP)。。基本满足了纺织品领域快速定量检测的精度要求,可以作为纺织品棉含量检测的有效手段。
关键词:近红外光谱;纺织品;棉含量;偏最小二乘法;预处理
Rapid determination of cotton content in textile by near-infrared spectroscopy technology
Abstract
In this work, a calibration model for determining the content in textile precisely was established. The near infrared spectra of 138 textile samples were collected using TENSOR 37 fourier transform near infrared spectrometer, and SNV and wavelet transform were used to pretreat the spectra. Calibration models for cotton content were established with partial least squares(PLS) method. The experimental results indicate that the model was established by the spectral date after SNV pretreament with partial least squares(PLS) method has higher analysis accuracy. With the model, the Root Mean Square Error Of Cross Validation(RMSECV) and Root Mean Square Error Of Prediction(RMSEP) are and , respectively. And a good correlation between reference concentrations and predicted values(R=) was obtained. The proposed approach can basically meet the accuracy requirement of the rapid quantitative detection in the textile field and can appear to be a valid alterative for detection of cotton content in textile.
Keywords:near infrared (NIR) spectroscopy;textile;cotton content;Partial Least Square(PLS) method; pretreament
目录
摘要 I
Abstract II
第一章绪论 1
纺织品行业概述 1
纺织品检测技术的研究进展 2
本课题的研究目的和意义 2
本论文研究内容 3
第二章近红外光谱分析技术概述 4
近红外光谱分析技术简介 4
近红外光谱分析技术的发展回顾 4
近红外光谱技术国内外研究现状 5
近红外光谱技术的特点 5
近红外光谱的工作原理 6
近红外光谱分析基本步骤 6
代表性样品的收集 7
样品的近红外光谱数据的采集 7
利用标准的化学方法对样品进行化学成分测定 7
利用化学计量方法建立校正模型 7
未知样品的分析 7
近红外光谱技术中的化学计量学方法 8
光谱预处理方法 8
多元校正 9