噪声对近红外光谱分析的影响及相应的数学处理方法

The Effects of Noise on NIR Analysis and Related Mathematic Pretreatments and Models

以玉米籽粒的粉末样品为例,对噪声较高近红外光谱分析仪进行近红外分析的可行性进行了分析。结果表明,采用四次平均光谱,不采取其他数据处理,使用PLS算法,自编软件CAU-NIR可以得到很好的预测模型。通过与其他噪声较低近红外分析仪预测结果的对比,噪声较高的光栅型近红外光谱分析仪预测样品的相关系数高达98%,变异系数为6·2%。因此当近红外光谱分析仪器的信噪比低于105时,借助一定的软件技术,仍然可以用于定量分析。

The feasibility of using a relatively high noise NIR spectrometer for analysis was examined by using maize powder samples. The results showed that with four-time averaged NIR spectrum data without more pretreatments, PLS mathematic models and CAU-NIR software, the relative high noise scan NIR spectrometer could be used to get satisfied prediction results compared with other low noise NIR spectrometers. The prediction coefficient could reach 98% and the CV（variation coefficient） was 6. 2%. It was proved that when the S/N of NIR spectrometer was lower than 10^5, it still could be used for quantity analysis with the help of some mathematic pretreatments and models.