基于DE算法和NURBS曲线的ICP-AES光谱基线校正方法研究  

Research on ICP-AES Spectral Baseline Correction Method Based on DE Algorithm and NURBS Curve

作　　者：廉小亲[1,2] 陈彦铭 王宇乔 刘钰 LIAN Xiao-qin;CHEN Yan-ming;WANG Yu-qiao;LIU Yu(School of Artificial Intelligence,Beijing Technology and Business University,Beijing 100048,China;China Light Industry Key Laboratory of Industrial Internet and Big Data,Beijing Technology and Business University,Beijing 100048,China)

机构地区：[1]北京工商大学人工智能学院,北京100048 [2]北京工商大学中国轻工业工业互联网与大数据重点实验室,北京100048

出　　处：《光谱学与光谱分析》2023年第1期260-267,共8页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(61807001)资助。

摘　　要：电感耦合等离子体原子发射光谱(ICP-AES)分析法是一种常用的溶液元素浓度分析方法,但在ICP-AES测量过程中,由于温度漂移、杂散光和仪器暗电流等原因,光谱往往会存在一定程度的基线漂移,导致元素光谱强度值的测量结果存在误差,进而影响元素浓度的定量分析结果,因此基线校正是ICP-AES分析法中的必要环节之一。对传统光谱基线校正方法进行简要分析,在此基础上设计了一种基于非均匀B样条曲线和差分进化算法的ICP-AES光谱基线漂移校正方法;首先验证了光谱信号中噪声的概率密度分布服从高斯分布,然后对原始光谱进行预处理,通过高斯滤波对光谱信号去噪;然后以光谱基线校正过程中极小值序列的标准偏差作为评价指标,以非均匀B样条曲线作为基线模型,以曲线的控制点序列C和内接点序列T作为评价函数特征参数,建立ICP-AES光谱基线校正评价函数,将光谱基线校正问题转换为求解评价函数特征参数全局最优解的问题;最后简要介绍了差分进化算法的流程,通过差分进化算法求解使得评价函数取得最小值时的特征参数的全局最优解,即非均匀B样条曲线的控制点序列C与内接点序列T的取值,并以此拟合相应的非均匀B样条曲线作为光谱基线,实现对ICP-AES光谱的基线校正。利用一组实测的ICP-AES光谱数据对本文提出的基线漂移校正方法进行验证,实验结果表明,提出的基于差分进化算法和非均匀B样条曲线的ICP-AES光谱基线校正方法能够准确地计算出非均匀B样条曲线的控制点序列C与内接点序列T,并拟合出理想的光谱基线,从而实现ICP-AES光谱的基线校正,该方法能够克服非均匀B样条曲线在光谱基线校正领域应用的局限性,为后续的元素含量定量分析提供了技术基础。Inductively Coupled Plasma Atomic Emission Spectroscopy(ICP-AES)analysis method is a commonly used solution element concentration analysis method.However,in the process of ICP-AES measurement,due to temperature drift,stray light and instrument dark current,etc.,the spectrum often has a certain degree of the baseline drift phenomenon,resulting in errors in the measurement results of element spectral intensity values,which in turn affects the quantification of element concentrations.Therefore,baseline correction is one of the necessary links in the ICP-AES analysis method.In this paper,the traditional spectral baseline correction method is briefly analyzed,and on this basis,a ICP-AES spectral baseline drift correction method based on non-uniform B-spline curve and differential evolution algorithm is designed;Firstly,it is verified that the probability density distribution of noise in the spectral signal obeys the Gaussian distribution,then the original spectrum is preprocessed,and the spectral signal is denoised by Gaussian filtering;Then,the standard deviation of the minimum value sequence in the process of spectral baseline correction is used as the evaluation index,the non-uniform B-spline curve is used as the baseline model,and the control point sequence C and the internal point sequence T of the curve are used as the characteristic parameters of the evaluation function to establish the ICP-AES spectral baseline correction evaluation function,so that the spectral baseline correction problem can be converted into the problem of solving the global optimal solution of the characteristic parameters of the evaluation function;Finally,this paper briefly introduces the process of the differential evolution algorithm,and uses the differential evolution algorithm to solve the global optimal solution of the characteristic parameters when the evaluation function achieves the minimum value,that is,the control point sequence C and the interior point sequence T of the non-uniform B-spline curve,and fit the corresponding non-

关 键 词：光谱基线 基线校正 差分进化算法 非均匀B样条 电感耦合等离子体 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]