Laser-induced breakdown spectroscopy （LIBS） has become a powerful technology in geological applications. The correct identification of rocks and soils is critical to many geological projects. In this study, LIBS dat...Laser-induced breakdown spectroscopy （LIBS） has become a powerful technology in geological applications. The correct identification of rocks and soils is critical to many geological projects. In this study, LIBS database software with a user-friendly and intuitive interface is developed based on Windows, consisting of a database module and a sample identification module. The database module includes a basic database containing LIBS persistent lines for elements and a dedicated geological database containing LIBS emission lines for several rock and soil reference standards. The module allows easy use of the data. A sample identification module based on partial least squares discriminant analysis （PLS-DA） or support vector machine （SVM） algorithms enables users to classify groups of unknown spectra. The developed system was used to classify rock and soil data sets in a dedicated database and the results demonstrate that the system is capable of fast and accurate classification of rocks and soils, and is thus useful for the detection of geological materials.展开更多
采用傅里叶变换红外光谱结合多元统计分析方法快速鉴别不同种类食用牛肝菌。采集10个不同种类93个牛肝菌子实体的红外光谱,分析食用牛肝菌的红外光谱特征;用多元散射校正(multiplicative signal correction,MSC)、标准正态变量(standard...采用傅里叶变换红外光谱结合多元统计分析方法快速鉴别不同种类食用牛肝菌。采集10个不同种类93个牛肝菌子实体的红外光谱,分析食用牛肝菌的红外光谱特征;用多元散射校正(multiplicative signal correction,MSC)、标准正态变量(standard normal variate,SNV)、二阶导数(second derivative,SD)、Norris平滑(ND)、正交信号校正(orthogonal signal correction,OSC)、小波压缩等方法对光谱进行优化处理;经优化处理的光谱数据分别建立马氏距离分类模型及偏最小二乘判别分析(partial least squares discriminant analysis,PLSDA)。结果显示,牛肝菌在3 325、2 934、2 927、1 637、1 547、1 402、1 375、1 259、1 453、1 081、1 029 cm-1等附近有多个吸收峰,主要归属为蛋白质、多糖、氨基酸等的特征吸收峰。MSC+SD+ND(15∶5)和SNV+SD+ND(15∶5)两种预处理方式前10个主成分累积贡献率分别为95.58%、95.54%,基于两种预处理方法建立马氏距离分类模型,验证集预测准确率分别为90%和95%。PLS-DA结果显示经MSC+SD+ND(15∶5)和SNV+SD+ND(15∶5)预处理不易于区分牛肝菌种类;原始光谱经正交信号校正及小波压缩(orthogonal signal correction wavelet compression,OSCW)、优化处理并进行PLS-DA分析,能够很好地区分不同种类牛肝菌。马氏距离分类模型不仅能反映样品的分类情况,同时计算出与测试样品相似度最大的物种,可为食用菌种类鉴别和未知物种鉴定提供可靠依据;OSCW预处理后进行PLS-DA分析能有效鉴别不同种类牛肝菌,为野生食用菌的鉴别分类提供一种辅助方法。展开更多
Our recent work on the detection of explosives by laser-induced breakdown spectroscopy （LIBS） is reviewed in this paper. We have studied the physical mechanism of laser-induced plasma of an organic explosive, TNT. T...Our recent work on the detection of explosives by laser-induced breakdown spectroscopy （LIBS） is reviewed in this paper. We have studied the physical mechanism of laser-induced plasma of an organic explosive, TNT. The LIBS spectra of TNT under single-photon excitation are simulated using MATLAB. The variations of the atomic emission lines intensities of carbon, hydrogen, oxygen, and nitrogen versus the plasma temperature are simulated too. We also investigate the time-resolved LIBS spectra of a common inorganic explosive, black powder, in two kinds of surrounding atmospheres, air and argon, and find that the maximum value of the O atomic emission line SBR of black powder occurs at a gate delay of 596 ns. Another focus of our work is on using chemometic methods such as principle component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） to distinguish the organic explosives from organic materials such as plastics. A PLS-DA model for classification is built. TNT and seven types of plastics are chosen as samples to test the model. The experimental results demonstrate that LIBS coupled with the chemometric techniques has the capacity to discriminate organic explosive from plastics.展开更多
基金supported by National Major Scientific Instruments and Equipment Development Special Funds,China(No.2011YQ030113)
文摘Laser-induced breakdown spectroscopy （LIBS） has become a powerful technology in geological applications. The correct identification of rocks and soils is critical to many geological projects. In this study, LIBS database software with a user-friendly and intuitive interface is developed based on Windows, consisting of a database module and a sample identification module. The database module includes a basic database containing LIBS persistent lines for elements and a dedicated geological database containing LIBS emission lines for several rock and soil reference standards. The module allows easy use of the data. A sample identification module based on partial least squares discriminant analysis （PLS-DA） or support vector machine （SVM） algorithms enables users to classify groups of unknown spectra. The developed system was used to classify rock and soil data sets in a dedicated database and the results demonstrate that the system is capable of fast and accurate classification of rocks and soils, and is thus useful for the detection of geological materials.
基金Acknowledgements This work has been carried out with a financial grant from the National Natural Science Foundation of China （Grant No. 60978035）. The authors would like to thank Fraunhofer Institute of Laser Technology in Germany for providing some experimental equipments and TNT samples.
文摘Our recent work on the detection of explosives by laser-induced breakdown spectroscopy （LIBS） is reviewed in this paper. We have studied the physical mechanism of laser-induced plasma of an organic explosive, TNT. The LIBS spectra of TNT under single-photon excitation are simulated using MATLAB. The variations of the atomic emission lines intensities of carbon, hydrogen, oxygen, and nitrogen versus the plasma temperature are simulated too. We also investigate the time-resolved LIBS spectra of a common inorganic explosive, black powder, in two kinds of surrounding atmospheres, air and argon, and find that the maximum value of the O atomic emission line SBR of black powder occurs at a gate delay of 596 ns. Another focus of our work is on using chemometic methods such as principle component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） to distinguish the organic explosives from organic materials such as plastics. A PLS-DA model for classification is built. TNT and seven types of plastics are chosen as samples to test the model. The experimental results demonstrate that LIBS coupled with the chemometric techniques has the capacity to discriminate organic explosive from plastics.
