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。
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 1.50%. 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.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2012年第8期2080-2084,共5页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金面上项目(20773044)资助
关键词
短波近红外
温度校正
正交信号处理
广义最小二乘加权法
Short-wave near infrared
Temperature correction
Orthogonal signal correction
Generalized least squares weighting
