Estimating Calorific Value of Coal Using Laser-Induced Breakdown Spectroscopy through Statistical Algorithms: Correlation Analysis, Partial Least Squares, and Signal-to-Noise Ratio
Source abstract
Abstract
The objective of this study was to compare different statistical algorithms for estimating the calorific value of coal based on a quantitative analysis of the elements in coal. Laser-induced breakdown spectroscopy (LIBS) was applied for the elemental analysis. Three different algorithms, including the correlation analysis (CA) method, the partial least squares (PLS) analysis method, and the signal-to-noise ratio (SNR), were adopted to accurately determine the concentrations of the elements in coal by using Dulong’s equation. Special emphasis was placed on the selection of the delay time to improve the measurement accuracy. The coefficient of determination, R2, was considered for optimizing the delay time. The intensity–concentration calibration curves were obtained for the elements in coal and the elemental concentration correlations were estimated on the basis of the calibration curves of each element. The CA showed a higher accuracy compared to PLS and the SNR. This confirmed that LIBS shows potential for the rapid determination of the calorific value of coal.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Laser-induced spectroscopy and plasma · Analytical chemistry methods development · Mineral Processing and Grinding
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Convergence Engineering, Hanyang University, Seoul 04763, Korea
Korea Authority of Land and Infrastructure Safety, Jinju 52852, Korea
Korea Automotive Technology Institute, Cheonan 31214, Korea
Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Korea
Funding
Ministry of Trade, Industry & Energy
References (26)
Show source-provided references
1. Interaction of a laser beam with metals. Part I: Quantitative studies of plasma emission10.1366/0003702914337263 ↗
2. Determination of carbon content in steel using laser-induced breakdown spectroscopy10.1366/0003702924123692 ↗
3. Direct detection of beryllium on filters using the laser spark10.1366/0003702854249349 ↗
4. Determination of uranium in solution using laser-induced breakdown spectroscopy10.1366/0003702874447897 ↗
5. Determination of heavy metals in soils by laser induced breakdown spectroscopy10.1016/S0016-7061(01)00115-X ↗
6. Laser-induced breakdown spectroscopy in water: Improvement of the detection threshold by signal processing10.1016/j.sab.2005.06.007 ↗
7. Study of the electron kinetic processes in laser-induced breakdown of electronegative gases over an extended wavelength range10.1016/S0969-806X(01)00216-X ↗
8. Application of LIBS for direct determination of volatile matter content in coal10.1039/c1ja10109a ↗
9. Analysis of a high-concentration copper in metal alloys by emission spectroscopy of a laser-produced plasma in air at atmospheric pressure10.1016/S0584-8547(00)00246-9 ↗
10. Quantitative analysis of ceramics by laser-induced breakdown spectroscopy10.1016/S0584-8547(03)00011-9 ↗
11. Coal property analysis using laser-induced breakdown spectroscopy10.1039/c3ja50097g ↗
12. LIBS limit of detection and plasma parameters of some elements in two different metallic matrices10.1039/b315588a ↗
13. Effects of experimental parameters on elemental analysis of coal by laser-induced breakdown spectroscopy10.1016/j.optlastec.2009.03.003 ↗
14. Packing density effects on the fluctuations of the emission lines in laser-induced breakdown spectroscopy10.1016/j.sab.2013.10.007 ↗
15. A PLS model based on dominant factor for coal analysis using laser-induced breakdown spectroscopy10.1007/s00216-011-4865-y ↗
16. Quantitative analysis of calorific value of coal based on spectral preprocessing by laser-induced breakdown spectroscopy (LIBS)10.1021/acs.energyfuels.7b01718 ↗
17. Laser-induced plasma emission spectra of halogens in the helium gas flow and pulsed jet10.5806/AST.2013.26.4.235 ↗
18. Cremers, D.A., and Radziemski, L.J. (2006). Handbook of Laser-Induced Breakdown Spectroscopy, John Wiley & Sons.10.1002/0470093013 ↗
19. Gazeli, O., Stefas, D., and Couris, S. (2021). Sulfur detection in soil by laser induced breakdown spectroscopy assisted by multivariate analysis. Materials, 14.10.3390/ma14030541 ↗
20. Modeling the heating value of municipal solid waste10.1016/S0016-2361(03)00009-7 ↗
21. Evaluation of the laser-induced breakdown spectroscopy technique for determination of the chemical composition of copper concentrates10.1016/j.sab.2014.05.001 ↗
22. Quantitative measurements of loss on ignition in iron ore using laser-induced breakdown spectroscopy and partial least squares regression analysis10.1366/000370210793561600 ↗
23. Partial least squares regression for problem solving in precious metal analysis by laser induced breakdown spectrometry10.1039/B000813N ↗
24. LIBS analysis of the ash content, volatile matter, and calorific value in coal by partial least squares regression based on ash classification10.1039/D0JA00186D ↗
25. Temporal gating for the optimization of laser-induced breakdown spectroscopy detection and analysis of toxic metals10.1366/0003702011953667 ↗
26. Identification of solid materials by correlation analysis using a microscopic laser-induced plasma spectrometer10.1021/ac9905524 ↗