Investigation of statistics strategies for improving the discriminating power of laser-induced breakdown spectroscopy for chemical and biological warfare agent simulants

被引：109

作者：

Munson, CA ^{[1
]}

De Lucia, FC ^{[1
]}

Piehler, T ^{[1
]}

McNesby, KL ^{[1
]}

Miziolek, AW ^{[1
]}

机构：

[1] USA, Res Lab, AMSRL, WM BD, Aberdeen Proving Ground, MD 21005 USA

来源：

SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY | 2005年 / 60卷 / 7-8期

关键词：

LIBS; chemometrics; PCA; SIMCA;

D O I：

10.1016/j.sab.2005.05.017

中图分类号：

O433 [光谱学];

学科分类号：

0703 ; 070302 ;

摘要：

Laser-induced breakdown spectroscopy spectra of bacterial spores, molds, pollens and nerve agent simulants have been acquired. The performance of several statistical methodologies-linear correlation, principal components analysis, and soft independent model of class analogy-has been evaluated for their ability to differentiate between the various samples. The effect of data selection (total spectra, peak intensities, and intensity ratios) and pre-treatments (e.g., averaging) on the statistical models have also been studied. Results indicate the use of spectral averaging and weighting schemes may be used to significantly improve sample differentiation. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：1217 / 1224

页数：8

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