【摘要】 短波近红外光谱结合多元校正方法测量酒精度具有快速、无损的特点,可以现场应用和在线检测。但是温度对预测模型的性能影响很大。作者研究了温度变化对乙醇水溶液的短波近红外光谱的影响,采用四种方法建立了温度变化下的偏最小二乘(PLS)传递校正模型:直接校正、全局校正、正交信号处理(OSC)和广义最小二乘加权法(GLSW)。结果表明,温度变化时直接传递校正存在很大的预测系统偏差,而采用全局校正、OSC和GLSW均能在一定程度上减小系统误差。全局校正需要较多的建模样品数量,得到的模型也更为复杂。而OSC和GLSW方法能得到更为简洁的模型和优良的预测结果。相比之下,GLSW算法得到的预测误差和使用的建模隐含变量数目均小于OSC方法,能够建立更为稳健的传递校正模型。更多还原

【Abstract】 The authors studied the temperature influence on short-wave near-infrared spectra of ethanol aquatic solution and utilized four methods to establish the transfer partial least squares(PLS) calibration model: direct transfer calibration,global calibration,orthogonal signal correction(OSC) and generalized least squares weighting(GLSW).The PLS models were built at four temperatures: 15,25,35 and 40 ℃.The results showed that direct calibration provided high prediction bias: significantly high positive prediction bias for a temperature lower than calibration temperature and negative bias for higher temperatures.By using the global correction,OSC and GLSW,the systematic errors could be reduced.However,the global correction needed more calibration samples and built a more complex model.The OSC and GLSW methods provided better predictions using fewer latent variables.By using the GLSW method,prediction bias less than 0.1% and RMSEP less than 0.9% were obtained.The absolute prediction error of GLSW method was less than 1.5%.Additionally,the GLSW provided smaller prediction error at every researched temperature using fewer latent variables than OSC.Thus,GLSW was superior to OSC and could establish more robust transfer calibration model.更多还原