硫酸羟氯喹颗粒水分近红外光谱在线定量模型的建立

目的为实时检测硫酸羟氯喹颗粒在流化床干燥过程中的水分含量变化,建立颗粒水分的在线近红外光谱定量模型。方法物料颗粒在流化床的干燥过程中,实时取样并用水分测定仪测量颗粒水分,采用多元散射校正(multiplicative signal correction,MSC)、一阶导数和Karl Norris平滑的光谱预处理方法,选择近红外4935~5336 cm?1和6911~7297 cm?1两个波段,运用偏最小二乘回归(partial least squares,PLS)建立基于近红外光谱的水分定量分析模型。结果所建模型的校正误差均方根(RMSEC)为0.408,相关系数Rc为0.9529。预测误差均方根(RMSEP)为0.435,相关系数Rp为0.9366,验证集标准偏差与预测标准偏差的比值(RPD)为5.18。并将该模型应用于车间生产过程中,t检验结果表明,预测值与参考值之间无显著性差异。结论该法所建立的在线水分定量模型准确度较高且较为可靠稳定,该模型可应用于生产过程,以在线监测物料颗粒的水分变化。

Establishment of online quantitative model for moisture content determination of hydroxychloroquine sulfate particles by near infrared spectroscopy

Objective To establish an online quantitative analysis model for moisture content assay of hydroxychloroquine sulfate particles by near infrared (NIR) spectroscopy.Methods The NIR spectra were collected in real time when the material particles were dried in the fluidized bed. Meanwhile the water content of the particles was measured with the standard moisture tester. The multiplicative signal correction (MSC) and first derivative followed by Karl Norris smoothing were used for spectra pretreatment. Two spectral range (4 935-5 336 cm^-1 and 6 911-7 297 cm^-1) were selected for the quantitative model with the partial least squares (PLS) regression.Results The quantitative calibration model had good correlation coefficients with Rc value=0.952 9 and Rp value=0.936 6. The root mean square error of calibration (RMSEC) was 0.408 and the root mean square error of prediction error (RMSEP) was 0.435. The ratio of standard deviation of validation set to prediction standard deviation (RPD) was 5.18. There was no significant difference between the predicted value and the reference value by t test when the established model was applied in large-scale production.Conclusion The online model established for monitoring water content has high accuracy and stability, which can be applied in industrial scale process to monitor the particle moisture in real time.