主成分分析在光全散射特征波长选择中的应用

唐 红; 郑文斌; 李宪霞

doi:10.3788/OPE.20101808.1691

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主成分分析在光全散射特征波长选择中的应用

现代应用光学 | 更新时间：2020-08-12

- 主成分分析在光全散射特征波长选择中的应用
- Application of principal component analysis to selection of characteristic wavelengths with total light scattering
- 光学精密工程 2010年18卷第8期页码：1691-1698
- 作者机构：
  
  1. 中国计量学院计量测试工程学院,浙江杭州,310018
  2. 中国计量学院信息工程学院,浙江杭州,310018
- 作者简介：
- 基金信息：
  
  国家自然科学基金专项资助项目(No.10947154)()
- DOI：10.3788/OPE.20101808.1691
  中图分类号： TB92;O436.2
- 收稿日期：2009-11-17，
  
  修回日期：2009-12-11，
  
  网络出版日期：2010-08-20，
  
  纸质出版日期：2010-08-20
- 稿件说明：
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唐红, 郑文斌, 李宪霞. 主成分分析在光全散射特征波长选择中的应用[J]. 光学精密工程, 2010,18(8): 1691-1698

TANG Hong, ZHENG Wen-bin, LI Xian-xia. Application of principal component analysis to selection of characteristic wavelengths with total light scattering[J]. 光学精密工程, 2010,18(8): 1691-1698
唐红, 郑文斌, 李宪霞. 主成分分析在光全散射特征波长选择中的应用[J]. 光学精密工程, 2010,18(8): 1691-1698 DOI： 10.3788/OPE.20101808.1691.

TANG Hong, ZHENG Wen-bin, LI Xian-xia. Application of principal component analysis to selection of characteristic wavelengths with total light scattering[J]. 光学精密工程, 2010,18(8): 1691-1698 DOI： 10.3788/OPE.20101808.1691.

摘要

为了能在用光全散射法测量颗粒粒径时选择对粒径影响较显著的特征波长进行测量

通过在可见及可见-红外波段内对粒径服从单峰R-R分布颗粒系的消光光谱

一阶微分以及二阶微分消光光谱进行主成分变换

提出一种特征波长选择方法。该方法首先对颗粒系的一阶微分消光光谱进行主成分变换

然后将每个波长下的一阶微分消光谱对主成分贡献率的大小作为特征波长选择的主要依据

并将光谱范围的边界波长也作为特征波长。分别对粒径服从单峰及双峰R-R分布的颗粒系进行数值仿真

并采用标准颗粒的实测数据进行验证。验证结果显示

采用基于主成分分析的波长选择方法计算方便、易于实现

得到的标准颗粒粒径反演误差均小于3%

表明采用提出的波长选择方法能够保证选出的光谱消光值具有较高的信息量。

Abstract

To select the characteristic wavelengths which contain important information about particle sizes and refractive indexes in a total light scattering particle sizing method

a wavelength selection method was proposed by performing the Principal Component Analysis(PCA) for the extinction spectra

the first-order differential extinction spectra and the second-order differential extinction spectra of monomodal R-R particle system in visible and visible-infrared regions. This method firstly used the principal component transform to dispose the first-order differential extinction spectra

and then regarded the contribution rate of the principal component to the first-order differential extinction spectra at each wavelength as the mainly criterion to select the characteristic wavelengths. Meanwhile

the boundary wavelengths in the spectral region were also selected as the characteristic wavelengths. The numerical simulations on the monomodal and biomodal R-R distributions were performed

and the experimental data of reference materials were also validated.Experimental results show that the inversion errors of reference materials based on the PCA selection method are less than 3%. It is concluded that the selection method has advantages of convenient computation and easy realization

and can ensure to the extinction values of selected characteristic wavelengths to show the most valuable information about the particle size distribution.

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