形态学方法用于三维荧光光谱化学秩的确定  

Determination of Chemical Rank of Three-Dimensional Fluorescence Spectra Using Mathematical Morphology Method

作　　者：余晓娅[1] 张玉钧[1] 殷高方[1] 肖雪[1] 赵南京[1] 刘文清[1] 

机构地区：[1]中国科学院安徽光学精密机械研究所、中国科学院环境光学与技术重点实验室,安徽合肥230031

出　　处：《光谱学与光谱分析》2014年第7期1881-1885,共5页Spectroscopy and Spectral Analysis

基　　金：安徽省杰出青年科学基金项目(1108085J19);国家(863计划)项目(2013AA065502);安徽省自然科学基金项目(11040606M26);安徽光学精密机械研究所所长基金项目(Y03AG31144);中国科学院仪器设备功能开发技术创新项目(yg2012071)资助

摘　　要：确定化学秩是解析化学体系的第一步,正确确定化学体系的组分数对后续的解析异常重要。由于实测的三维荧光光谱不可避免地受到噪声的干扰,传统的化学秩估计方法常常失效。首先根据三维荧光光谱信号与噪声信号的形态差异,选用正弦形结构元素,对信号进行先开启后闭合运算,用形态学方法对实测三维荧光光谱进行去噪,然后对去噪后的光谱进行奇异值分解(SVD),联合分解得到的奇异值和奇异向量进行化学秩的确定。主要讨论了形态滤波方法的理论基础,先用模拟数据说明了文中所提方法的必要性和有效性,然后又把此方法用在酚类化合物三维荧光光谱的组分数检测上,并与传统的蒙特卡罗方法做了对比。实验结果表明,提出的方法更具有实用性,能够正确估计出化学秩。The present paper firstly denoises the signal with morphological method ,selecting sine-shaped structure element ,using the morphological difference in waveform between the three-dimensional fluorescence and noise signal ,then singular value decomposition is applied to the denoised data ,and finally the chemical rank is determinated jointing eigenvalues and eigenvectors form singular value decomposition .This paper principally discusses the theory basis of morphological filtering method ,firstly simulated data is analysed by morphological filtering method to confirm the necessity and effectiveness of proposed method ,then the feasibility and practicability of the proposed method is verified by the determination of components number of phenols mixture three-dimensional fluorescence spectra compared with traditional Monte Carlo method .The experiments demonstrate that the proposed method is able to estimate the chemical rank correctly .

关 键 词：形态学 化学秩 去噪 三维荧光光谱 奇异值分解 

分 类 号：O433.4[机械工程—光学工程]