Qualitative Discrimination Analysis of Coals Based on Their Laser Induced Breakdown Spectra

Six different coal samples (anthracite, Czech brown coal, Polish brown coal, lignite, graphite, and Pecs-vasas brown coal) were studied by using laser-induced breakdown spectroscopy (LIBS) in order to assess its capability for use in coal quality control. The spectral features of the coals as well as their correlation with the results of proximate analysis was investigated. The second part of the study deals with the classification (qualitative discrimination analysis) of coals based on their visible-range LIBS spectra using various statistical methods. Canonical linear discriminant analysis was found to be the most efficient; using five canonical variables and after reducing the spectra to 18 variables, the achieved classification accuracy was 95.33% according to the cross-validation test of the model. The described results indicate that LIBS data can be efficiently used for the quality control of coals and thus can also contribute to the indirect control of the combustion process.