Abstract
Laser-induced breakdown spectroscopy with soft independent modeling of class analogy is used in the identification of a large number of unprocessed geological samples having similar components in this study. Considering a variety of data from different samples, representative spectral regions representing the major components were extracted. In addition, principal component analysis was applied to remove noninformative variables from the spectrum. The unclassification rate, misclassification rate, and average correct classification rate for 25 types of geological samples were 1.2%, 4.7%, and 94.1%, respectively. These results suggest that laser-induced breakdown spectroscopy using soft independent modeling of class analogy can be used to identify a wide variety of geological samples. Furthermore, we found that this approach can be used to identify spectral differences among similar sample types because of matrix effects and the trace element impurities.
Highlights
Laser-induced breakdown spectroscopy (LIBS) [1, 2] is a simple atomic emission technique for multiple elements and provides a semidestructive and efficient analysis, in harsh and dangerous environments. us, LIBS has been widely used for various applications, such as industry-oriented analysis [3], archaeological investigation [4], geological and environmental studies [5–7], and jewelry characterization [8]
Multivariate preprocessing methods have been increasingly studied, including approaches based on principal component analysis (PCA) [12, 13], partial least squares discriminant analysis (PLS-DA) [14], graph theory (GT) [15], independent component analysis (ICA) [16], and artificial neural networks (ANNs) [17, 18]
E selection of principal components greatly a ects the classi cation capabilities and can prevent both under- and over tting problems of classi cation. e scores and loadings of PCA for the 25 types of samples are shown in Figure 4, where the principal components PC1, PC2, and PC3 contribute 28.84%, 22.17%, and 14.34% of the overall variance, respectively
Summary
Laser-induced breakdown spectroscopy (LIBS) [1, 2] is a simple atomic emission technique for multiple elements and provides a semidestructive and efficient analysis, in harsh and dangerous environments. us, LIBS has been widely used for various applications, such as industry-oriented analysis [3], archaeological investigation [4], geological and environmental studies [5–7], and jewelry characterization [8]. Us, LIBS has been widely used for various applications, such as industry-oriented analysis [3], archaeological investigation [4], geological and environmental studies [5–7], and jewelry characterization [8]. Multivariate preprocessing methods have been increasingly studied, including approaches based on principal component analysis (PCA) [12, 13], partial least squares discriminant analysis (PLS-DA) [14], graph theory (GT) [15], independent component analysis (ICA) [16], and artificial neural networks (ANNs) [17, 18]. Such methods consider the effect of redundant information and increase the efficiency of data analysis and prevent negligible fluctuations resulting from experimental conditions and instrumental instability [19]. Suitable results have been reported in the classification of some geological materials, it is still challenging to provide a method that
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