Laser-induced breakdown spectroscopy with artificial neural network processing for material identification

被引：57
作者：
Koujelev, A. [1 ]
Sabsabi, M. [2 ]
Motto-Ros, V. [1 ]
Laville, S. [2 ]
Lui, S. L. [1 ]
机构：
[1] Canadian Space Agcy, St Hubert, PQ J3Y 8Y9, Canada
[2] Natl Res Council Canada, Inst Ind Mat, Boucherville, PQ J4B 6Y4, Canada
来源：
PLANETARY AND SPACE SCIENCE | 2010年 / 58卷 / 04期
关键词：
Laser-induced breakdown spectroscopy; Artificial neural network; Material identification; Planetary exploration; Earth planetary analogue research; Qualitative LIBS; MARS; SOIL;
D O I：
10.1016/j.pss.2009.06.022
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
Laser-induced breakdown spectroscopy (LIBS) has demonstrated its high potential in measurement of material composition in many areas including space exploration. LIBS instruments will be parts of payloads for the 2011 Mars Science laboratory NASA-led mission and the ExoMars mission planned by ESA. This paper considers application of artificial neural networks (ANN) for material identification based on LIBS spectra that may be obtained with a portable instrument in ambient conditions. The several classes of materials used in this study included those selected to represent the sites analogues to Mars. In addition, metals and aluminum alloys were used to demonstrate ANN capabilities. Excellent material classification is achieved with single-shot measurements in real time. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：682 / 690
页数：9
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