Study on prediction model of slurry concentration of low-rank coal and anionic sulfonate additives

In this work, eight kinds of low-rank coal and four kinds of anionic sulfonate additives including lignin series, naphthalene series, humic acid series, and aliphatic series dispersants were selected for slurry experiments. The Spearman correlation analysis method was used to investigate the influence of coal quality factors including moisture, ash, volatile matter, fixed carbon, O/C value, and peak area ratio C--O/C-O value on the slurry ability of low-rank coal under different dispersant conditions. The results show that moisture, volatile matter, O/C value, and C--O/C-O value in coal are negatively correlated with slurry ability, while ash and fixed carbon are positively correlated with slurry ability. According to the Spearman correlation coefficient, moisture, volatile matter, O/C value, and C--O/C-O value in coal are closely related to the slurry ability of low-rank coal. The prediction model of slurry concentration of low-rank coal and anionic sulfonic acid additive based on coal characteristic factors is established by partial least squares (PLS):ySLS = 75.859 - 0.498x1 + 0.566x2- 5.786x3- 157.895x4yNSF = 79.706 - 0.123x1 + 0.567x2- 7.123x3- 182.900x4ySHS = 80.642 + 0.012x1 + 0.387x2 + 4.503x3- 180.657x4ySAF = 80.702 + 0.271x1 + 0.508x2- 18.743x3- 182.057x4Where yi is the constant-viscosity concentration, the unit is %; x1 is moisture (Mad), the unit is %; x2 is volatile (Vdaf), the unit is %; x3 is the O/C value; x4 is C--O/C-O value. By comparing the experimental value with the predicted value, the R2 value of the linear regression fitting is larger than 0.95, the error rate is within +/- 3 %, and while using the constant-viscosity concentration to determine the matching performance of coal and dispersant, the predicted value is consistent with the experimental value, which verifies the rationality and accuracy of the model.