Near Infrared Spectroscopic Modeling Method for Cement Raw Meal Components by Eliminating Background Moisture
HU Rong1,2，LIU Wen-qing2，XU Liang2*，JIN Ling2，YANG Wei-feng2，SHEN Xian-chun2，CHENG Xiao-xiao2， WANG Yu-hao2，HU Kai2，LIU Jian-guo2
1. School of Environmental Science and Optoelectronic Technology，University of Science and Technology of China，Hefei 230026，China
2. Key Laboratory of Environmental Optics and Technology，Anhui Institute of Optics and Fine Mechanics，Chinese Academy of Sciences，Hefei 230031，China
Abstract：Fourier transform infrared (FTIR) spectroscopy has great potential for on-line analysis of cement raw meal components. As the air humidity on site is not stable due to the complex environment, it will cause interference to the on-line FTIR quantitative analysis of the four key components of Fe2O3, SiO2, CaO, Al2O3 in the raw material samples. In this paper, the on-line FTIR analyzer for raw meals was used to collect near-infrared spectra of raw meal cement samples under different humidity conditions. The influences of different humidity conditions on near-infrared quantitative analysis were analyzed, and a method of eliminating the background moisture interference was proposed. The specific researches were as follows: (1) Spectra of each 50 samples at two different humidity levels were analyzed. The results were that sample spectra at high humidity level compared to that at low humidity level were similar in shape, while the absorbance intensities were deceased overall and baselines were inclined. These demonstrated that background moisture affected the near-infrared spectra of the samples. (2) Two FTIR quantitative analysis models for samples under high humidity and low humidity conditions were established respectively, and the four component contents of 8 samples in prediction set under another humidity condition were predicted. The results were that the values of the correlation coefficient (r) between the content values of the four components predicted by model under high humidity condition and the standard values in the prediction set were 83.74%～92.74%, and the values of the root mean square error (RMSE) were 0.12～0.83. The values of R obtained by model under low humidity condition were 67.32%～82.41%, and the values of RMSE were 0.12～0.84. These indicated that background moisture had affected the FTIR quantitative analysis of raw meal cement components. (3) In order to eliminate the influence of water absorption, the characteristic absorption of background moisture from the measured spectrum were removed refer to the mid-infrared spectroscopy technique. The FTIR quantitative analysis models under high humidity and low humidity conditions were established respectively, and the four components contents of samples in prediction set were predicted by these models. The results were as follows: ① Under high humidity condition, the prediction accuracy of the model with eliminating moisture absorption was improved compared with model without eliminating moisture absorption, the predicted values of r were 90.73%～97.76%, and the values of RMSE were 0.12～0.82, ② Under low humidity condition, the prediction accuracy of model with eliminating moisture absorption was higher than that of model without eliminating moisture absorption, and the predicted values of r were 94.07%～98.69%, the values of RMSE were 0.12～0.82, ③ The values of r obtained by models under high and low humidity conditions were above 90%. The experimental results showed that the method could effectively eliminate the influence of moisture absorption on the quantitative analysis model of raw material cement compositions. It provided the theoretical basis and technical support for the online analysis of raw material cement compositions based on FTIR technology.
Key words：Fourier transform infrared spectroscopy；Cement samples；Composition determination；Elimination of background moisture
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