一种锐化误差小波EDXRF光谱解析方法研究  

A New EDXRF Spectral Decomposition Method for Sharpening Error Wavelets

作　　者：杜志恒 何剑锋[1,2,3] 李卫东[1,2,3] 汪雪元[1,2,3] 叶志翔 王文[1,2,3] DU Zhi-heng;HE Jian-feng;LI Wei-dong;WANG Xue-yuan;YE Zhi-xiang;WANG Wen(Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System,East China University of Technology,Nanchang 330013,China;Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology,East China University of Technology,Nanchang 330013,China;Information Engineering College,East China University of Technology,Nanchang 330013,China)

机构地区：[1]东华理工大学江西省核地学数据科学与系统工程技术研究中心,江西南昌330013 [2]东华理工大学江西省放射性地学大数据技术工程实验室,江西南昌330013 [3]东华理工大学信息工程学院,江西南昌330013

出　　处：《光谱学与光谱分析》2023年第6期1719-1724,共6页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(11865002);江西省重点研发计划项目(20203BBG73069)资助。

摘　　要：在轻元素自身和实测元素间的特征X射线相互影响之下,受仪器能量分辨率的制约,实测X射线荧光光谱会产生严重重叠。以色谱分离度Rs判定谱峰重叠程度,针对Rs低于0.3的重叠峰,提出一种解析EDXRF光谱的新方法,并对模拟X射线荧光光谱进行了新方法的验证。首先,详细介绍基于四阶导的峰锐化法和提出误差小波变换。通过仿真结果发现:当Rs=0.27时,两种方法皆不能单独实现重叠谱峰的解析与识别;然而,原始信号在四阶峰锐化法处理后保留了峰位特征的同时,还出现了Rs明显增大的有利现象。因此,只需要通过调节四阶峰锐化法的权重完成对低分离度重叠峰的初步锐化处理,再对锐化后的信号进行误差小波变换,结果实现了对模拟重叠峰的分解,证明了结合后的新方法(锐化误差小波变换)针对极低分离度的重叠谱峰具有强大的分解能力。对两组重叠谱峰采用叠加的高斯函数进行模拟,分别是Mn的K_(β)能量峰与Fe的K_(α)能量峰的重叠光谱(Rs=0.19)以及Al的K_(α)能量峰与其K_(β)能量峰的重叠光谱(Rs=0.11)。用新方法对谱线进行处理,实现了重叠峰分解,结果表明针对极低分离度的重叠谱峰该方法具有可行性。通过锐化误差小波对实测的EDXRF光谱进行解析,通过对三组数据解析特定三种低分离度重叠峰进行对比实验,均成功解析与识别了低分离度的重叠谱峰。结果表明:针对极低分离度的重叠谱峰,锐化误差小波变换可以有效分解,具有突破性,实用性和创新性。Under the mutual influence of characteristic X-rays of the light elements and the measured elements,the measured X-rays’fluorescence spectra will be seriously overlapped due to the restricted energy resolution of the instrument.This paper proposes a new method for analyzing EDXRF spectra by taking the chromatographic resolution Rs as an index to calculate the degree of spectral peak overlap and the overlapping peaks with Rs below 0.3 as the research object.First,this thesis introduces the peak sharpening method based on the fourth derivative in detail,and proposes the error wavelet transform.In addition,the new method was verified on simulated X-ray fluorescence spectroscopy.The simulation results show that when Rs=0.27,neither of the two methods can realize the analysis and identification of the overlapping spectral peaks;however,the processing by the 4-order peak sharpening method not only retains the peak position characteristics of the original signal,but also leads to increased Rs.Therefore,the resolution of the simulated overlapping peaks can be realized by adjusting the weight of the 4-order peak sharpening method to complete the initial sharpening of the overlapping peaks with low resolution,and then performing the error wavelet transform on the sharpened signal.Moreover,the combined new method(sharpening error wavelet transform)was proved to have a strong resolution ability for overlapping spectral peaks with very low resolution.Then,the superimposed Gaussian function was used to simulate the two sets of overlapping spectral peaks,which are the overlapping spectrum of the K_(β) energy peak of Mn and the Kαenergy peak of Fe(Rs=0.19)and the overlapping spectrum of the Kαenergy peak of Al and its K_(β) energy peak(Rs=0.11).The overlapping peaks were resolved by processing the spectral lines with the new method,and the result proved that the method is feasible for overlapping spectral peaks with extremely low resolution.Finally,the measured EDXRF spectrum was analyzed by sharpening the error wavelet,an

关 键 词：X射线荧光光谱 低分离度重叠峰 峰锐化 锐化误差小波变换 重峰分解 

分 类 号：O433.4[机械工程—光学工程]