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主成分分析在光全散射特征波长选择中的应用 被引量:10

Application of principal component analysis to selection of characteristic wavelengths with total light scattering
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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。 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 informa- tion about the particle size distribution.
出处 《光学精密工程》 EI CAS CSCD 北大核心 2010年第8期1691-1698,共8页 Optics and Precision Engineering
基金 国家自然科学基金专项资助项目(No.10947154)
关键词 粒径测量 光全散射 特征波长选择 主成分分析 particle size measurement total light scattering selection of characteristic wavelength Principal Component Analysis(PCA)
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