Spectroscopy and Spectral Analysis, Volume. 37, Issue 2, 594(2017)
Elemental Analysis of Rock with Remote Laser Induced Breakdown Spectroscopy
As a kind of spectroscopic technique, the remote laser-induced breakdown spectroscopy (Remote LIBS) can qualitatively or quantitatively measure the elemental compositions of remote targets with high-power laser and focusing optical path. In this work, a Remote LIBS system was designed and established to probe the target from 2 to 10 meters. It is characterized with Cassegrain telescope structure and automatic focusing technique. Based on this system, a method to remotely retrieve the major elemental abundance of rocks is presented. With comparative experiment, the influences on spectral signal by pulse laser energy, acquisition delay time, integration time, accumulative pulse number are analyzed to find out the optimum parameters: the wavelength of laser is 1 064 nm, pulse energy is 120 mJ, delay time is 15 μs, integration time is 1 ms, and each spectrum data acquired with averaging 30 times detection. 48 pieces of rock specimens and 6 kinds of standard rock samples (shale, granite, andesite, basalt, gneiss and pegmatite) are selected for the experiment. As to the atomic spectra database, 8 characteristic spectral lines of the major elements (SiⅠ39055 nm, AlⅠ39440 nm, AlⅠ39615 nm, CaⅡ39685 nm, FeⅠ4046 nm, SiⅠ50060nm, MgⅠ51836nm, NaⅠ58959 nm) were extracted for analyses. Then a PLS model is constructed to quantitatively analyze the rock elements. 48 rock specimens were selected as the training sets to serve the model. The 6 standard samples were used to test the solved model. The testing results shows that the elemental abundance of Si and Al can be predicted accurately with average relative error of only 94% and 96% respectively.
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ZHANG Ting-ting, SHU Rong, LIU Peng-xi, WAN Xiong. Elemental Analysis of Rock with Remote Laser Induced Breakdown Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2017, 37(2): 594
Received: Jan. 11, 2016
Accepted: --
Published Online: Jun. 20, 2017
The Author Email: Ting-ting ZHANG (zzuztt@163com)