Improved Measurement on Calorific Value of Pulverized Coal Particle Flow by Laser-induced Breakdown Spectroscopy (LIBS)
The real-time quantitative analysis of the calorific value of pulverized coal particle flow is important for efficient and clean combustion of coal. A piezoelectric vibratory feeder produced continuous flow of pulverized coal particles, which were detected by laser-induced breakdown spectroscopy (LIBS), and corresponding spectral information was collected. The obtained data matrices, after removing abnormal data, were treated with normalization in row-wise to improve signal repeatability. Then, the second convolution derivative was conducted on LIBS spectra to correct spectral interference. To acquire the appropriate number and type of variables for PLS quantitative model, the variables selection methods of genetic algorithm (GA) and synergy interval partial least squares (siPLS) on the quantitative model were analyzed and compared. The results showed that the spectral correction can be used to improve the predictive precision and accuracy of quantitative model based on the full spectrum. The predictive accuracy of the model with variables selected by siPLS has been further improved. The minimum average relative error (RE) of the predictive values for the validation samples was 1.53%, and the average error of the proposed model for calorific value quantitative analysis was 0.22 MJ/kg. The measurement indicated that LIBS can realize accurate and precise real-time quantitative analysis of pulverized coal particle flow.