复杂体系高灵敏拉曼定量分析中的多尺度建模方法

项目名称： 复杂体系高灵敏拉曼定量分析中的多尺度建模方法

项目编号： No.21305101

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 陈达

作者单位： 天津大学

项目金额： 25万元

中文摘要： 对复杂体系微量成分进行快速无损检测，一直是分析化学所面临的挑战之一。液芯波导拉曼光谱作为一种新型高灵敏光谱技术，以其快速、无损等优点，具备微量速测的潜力。但对复杂体系的高灵敏拉曼光谱进行建模时，其模型不仅取决于待测组分浓度，还受光谱干扰、非线性效应、样品波动性等因素的影响，常规算法难以同时解决相关干扰。针对以上问题，本项目从模型驱动的多尺度模型入手，借助时/频多尺度分解和数据融合策略，解决光谱和非线性干扰；提出数据驱动新思路，以局部逼近的方式解决波动干扰。最后联合模型驱动全局优化和数据驱动局部逼近的优点，创建双驱动多尺度建模方法，同时克服相关干扰。双驱动多尺度算法充分利用光谱的时/频多尺度特性，通过数据预处理与多元校正的一体化运算避免了信息丢失，自适应地提取高灵敏拉曼光谱中的微量多组分信息，有效提高其定量分析的可靠性及预测精度，从而为复杂信号解析提供一种新手段，并促进化学计量学的推广应用。

中文关键词： 多尺度建模；模型驱动；数据驱动；双驱动；拉曼光谱

英文摘要： Rapid non-destructive detection of trace components in complex systems represents one of the challenges in analytical chemistry. Liquid core waveguide Raman spectroscopy, a novel high-sensitive Raman spectrometry technology, has the advantages of rapidness and non-destruction as well, thus possessing the potential of rapid trace analysis. However, the model of high-sensitive Raman spectra collected from complex system is determined not only by the concentrations of analytes, but also by the matrix interference, nonlinear effects and sample fluctuation presented in complex systems as well, making the conventional algorithms difficult to solve these interference simultaneously.In this regard, this project begins with the model driven multiscale modeling to solve the spectral and non-linear interference using the combined strategies of multiscale decomposition in time-frequency domains and data fusion. Then a novel method based on data driven is proposed to solve the sample fluctuation using local approximation. Finally, a novel strategy of dual driven multiscale modeling (DDMM) is established by integrating the advantages of model-driven global optimization and data-driven local approximation, and thus suppressing the interference mentioned above. DDMM fully utilizes the multiscale characteristics of time-frequenc

英文关键词： Multiscale regression；Model Driven；Data Driven；Dual Driven；Raman Spectroscopy