Improving the Analysis of Sulfur Content and Calorific Values of Blended Coals with Data Processing Methods in Laser-Induced Breakdown Spectroscopy

Abstract

In Situ monitoring of the calorific value of coal has the advantage of reducing the amount of unburned carbon by injecting an appropriate amount of combustion air immediately to induce complete combustion. High sulfur concentrations cause severe environmental problems such as acid rain. In order to estimate the calorific value and measure the sulfur concentration, a new powerful technique for mixed coals was studied. Laser-induced breakdown spectroscopy (LIBS) does not require sample preparation. Several blended coals were used for the experiment to replicate the actual coal-fired power plant conditions. Two well-known data processing methods in near-infrared spectroscopy have been adopted to enhance the weak sulfur emission lines. The performance of the partial least square regression model was established by the parameters such as coefficient of determination, R2, relative error, and root mean square error (RMSE). The RMSE average was compared with the results of previous studies. As a result, the values from this study were smaller by 6.02% for the calibration line and by 4.5% for the validation line in near-infrared spectroscopy. The RMSE average values for calorific values were calculated to be less than 1%.