A study of the effect of moisture on the near infrared spectroscopic detection modeling of cement raw materials

Cement is a crucial building material, and its quality is significantly impacted by the quality of the raw materials used. Thus, testing the content of cement raw materials is vital for cement production. This paper examines the influence of water content on the near-infrared spectroscopy detection model for cement raw material composition. The NIR spectra of cement raw materials were adjusted and modeled using the PDS and EPO algorithms, respectively, and the results were compared with those from the original spectral modeling. The findings indicate that the PDS correction algorithm effectively addresses the impact of water content on the NIR spectral detection of cement raw material components. The validation set RMSEP for the four components can be reduced to 0.096,0.047,0.019,0.112. The results of this paper help to realize the online detection of near infrared spectroscopy and help to intelligentize cement production.