基于多维漫反射光谱技术的复杂混合溶液成分检测

为了进行复杂混合溶液的成分检测,该文提出了一种基于多维漫反射光谱技术的浓度检测方式,通过信号中携带的不同成分的多种光学性质来进行分析。实验设计了基于超连续谱激光光源、精密电控平移台和光谱仪的检测装置,选用Intralipid-20%溶液作为研究对象,用蒸馏水配制体积百分数1%～20%的溶液,分别测量距其入射点1.5～13mm(间隔0.5mm)范围内的24点漫反射光谱信号,以偏最小二乘回归算法对单点和多点漫反射光谱信号进行建模与预测。得到建模精度最高的为距离入射位置最近的1点～13点对应的光谱信号所建立的模型,预测精度最高的为距离入射位置最近的1点～7点对应的光谱信号所建立的模型。结果表明,增加不同位置信息的光谱信号,能够提高光谱的信噪比,与传统光谱技术仅利用吸光度或反射率等单一光学性质的方法相比,增加了被测物质散射特性的影响,利用被测物质多种光学性质的变化提高了建模及预测的精度,为基于多维光谱的复杂混合溶液检测提供了基础。

Component analysis of complex mixed solution based on multidimensional diffuse reflectance spectroscopy

In the present paper, the authors proposed a method for component analysis of complex mixed solutions based on multidimensional diffuse reflectance spectroscopy by analyzing the information carried by spectrum signals from various optical properties of various components of the analyte. The experiment instrument was designed with supercontinuum laser source, the motorized precision translation stage and the spectrometer. The Intralipid-20% was taken as an analyte, and was diluted over a range of 1%-20% in distilled water. The diffuse reflectance spectrum signal was measured at 24 points within the distance of 1.5-13 mm (at an interval of 0.5 mm) above the incidence point. The partial least squares algorithm model was used to perform a modeling and forecasting analysis for the spectral analysis data collected from single-point and multi-point. The results showed that the most accurate calibration model was created by the spectral data acquired from the nearest 1-13 points above the incident point; the most accurate prediction model was created by the spectral signal acquired from the nearest 1-7 points above the incident point. It was proved that multidimensional diffuse reflectance spectroscopy can improve the spectral signal to noise ratio. Compared with the traditional spectrum technology using a single optical property such as absorbance or reflectance, this method increased the impact of scattering characteristics of the analyte. So the use of a variety of optical properties of the analytes can make an improvement of the accuracy of the modeling and forecasting, and also provide a basis for component analysis of the complex mixed solution based on multidimensional diffuse reflectance spectroscopy.