温度波动影响含氢基团之间的作用力, 从而影响近红外光谱的吸收强度和波峰位置等, 导致近红外测量精度的降低。 针对温度变化对近红外光谱建模精度的影响, 对全局隐含温度补偿方法进行了研究, 并对其预测精度进行了分析, 分别从预测方差和置信区间两个方面对此类模型的精度进行了理论探讨和验证。 同时通过温度的连续变化实验, 即在温度连续变化的过程中, 等时间间隔采集各样品的近红外光谱, 研究了温度变化对光谱主元的连续模式影响, 探讨了温度变化影响模型预测精度的方式和途径。 最后对某高分子聚合物的粘度测量问题进行了实验验证和误差分析, 得到标准温度下所建未经温度补偿的模型和全局隐含温度补偿模型的建模精度分别为: RMSEC=0.243 0, Rc=0.871 6, RMSEP=0.243 2, Rp=0.869 3; RMSEC=0.258 2, Rc=0.870 6, RMSEP=0.265 2, Rp=0.856 0, 而当温度变化时, 二者预测最大置信区间分别约为1.8和0.9 kPa·s。 虽然全局隐含温度补偿模型相比于标准温度模型建模精度略降低, 但预测精度提高了一倍左右。 理论分析和实验结果均表明, 全局温度补偿模型具有较高的预测精度, 且对温度的变化有较强的鲁棒性和可靠性。

Temperature fluctuations affect the action between hydrogen groups, which causes the changes of absorption intensity and peak position of the near infrared (NIR) spectrum, which results in less accuracy of the NIR analyzer. This article studies the prediction accuracy of a type of global temperature compensation models for NIR spectrometric analysis from the aspects of prediction variance and confidence limit respectively. In the designed experiments with continuous temperature changing, NIR spectra are collected with an equal time interval. Hence, the continuous impact on the principal compoments of the NIR spectra caused by temperature is observed and analyzed, which illustrates the mechanism of temperature effection to the model prediction results. As verified by the experimental, the measurement of viscosity of an industrial polymeric material is carried out combined with different modelling methods. According to the experimental verification, the accuracy of non-temperature compensation model and global temperature compensation model are as follows, respectively: RMSEC=0.243 0, Rc=0.871 6, RMSEP=0.243 2, Rp=0.869 3; RMSEC=0.258 2, Rc=0.870 6, RMSEP=0.265 2, Rp=0.856 0. The maximum prediction confidence intervals of these two types of models are about 1.8 and 0.9 kPa·s respectively. Therefore, it can be observed that the modeling accuracy of global temperature compensation model is slightly worse, but the predition precision is much better compared with non-temperature compensated model. Both results of theoretical analysis and experimental verification illustrate that the global temperature compensation modelling methods offer the more accurate models and better robustness and reliability.