A temporal and spatial dual-dimension fusion spectra mapping method for rapid detection of coal quality in laser-induced breakdown spectroscopy.

Coal analysis is essential in mitigating pollutant emissions and optimizing energy efficiency. Laser-induced breakdown spectroscopy (LIBS) has been a promising candidate for coal analysis because of its uniquely fast, minimally destructive, and online capabilities. However, the complex composition of coal leads to matrix effect, which poses a significant challenge to precise quantification by conventional LIBS. Acquiring the multi-dimensional spectral information has the potential to identify solutions, which contributes to understanding the evolution of plasma, and decoupling the influence of matrix effect. In this study, to achieve high-precision quantitative analysis in coal, a novel method named the temporal and spatial dual-dimension fusion spectra mapping method (TSDD-SM) was introduced. It fuses temporal and spatial dimensions into spectra to construct hyperspectral maps, enriches plasma features, and overcomes conventional information limitations for spectral quantification. To verify the feasibility of TSDD-SM, both element and proximate analysis of coal were carried out. For the elemental analysis, after correction by TSDD-SM, the average R was increased to 0.99, RMSEp and AREp of the validation set were reduced by 78 % and 75 %, respectively. For the proximate analysis, the average R was also increased to 0.99, RMSEp and AREp were decreased by 66 % and 71 %, respectively. These experimental results demonstrate that TSDD-SM could be well applied to the rapid and accurate detection of various indicators in coal. In summary, TSDD-SM exhibits immense potential for the real-world coal industry.