An Optimization Method Based on Spatial Confinement and Spectra Data Screening for Laser-induced Breakdown Spectroscopy Quantitative Analysis of Coal Particle Flow

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    Laser-induced breakdown spectroscopy (LIBS) detection on coal in particle flow form is more real-time and beneficial for the effective use of coal. However, the inevitable instability fluctuation of particle flow affects the laser ablation and spectral collection. This work attempted to use particle flow confinement schemes and spectral screening to optimize the quantitative analysis performance of coal particle flow. A cylindrical spatial confinement was developed to stabilize the coal particle flow, laser ablation and plasma evolution. Then a relative signal-to-noise ratio (RSNR) method was proposed for spectral data screening to overcome the inadaptability of traditional signal-to-noise ratio (SNR) method to the samples with large difference in SNR. Based on the RSNR method with the optimal screening threshold obtained by cross-validation, the spectral relative standard deviation (RSD) such as C I 247.86 nm and Mg I 285.21 nm were significantly reduced. Subsequently, quantitative analysis models for coal proximate analysis indexes were established. The models employing RSNR method and spatial confinement showed the superior performance. The root mean square error of prediction (RMSEP) of ash content, fixed carbon content, volatile matter content and calorific value were improved from 3.5667%, 3.3965%, 3.0905% and 1.0188MJ/Kg to 1.6280%, 2.0344%, 1.4999% and 0.4553MJ/Kg. The proposed spatial confinement and RSNR method have applicability and mutual gain for quantitative analysis of coal particle flow.

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  • Online: June 22,2024
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