基于GMM-ICSA的光谱重叠峰分解研究  

Research on Decomposition of Spectral Overlapping Peaks Based on GMM-ICSA

作　　者：朱丹丹[1] 孙世成 杨惠 张灿 朱奇光[2] 李康 史彦新 陈颖[1] ZHU Dan-dan;SUN Shi-cheng;YANG Hui;ZHANG Can;ZHU Qi-guang;LI Kang;SHI Yan-xin;CHEN Ying(Hebei Province Key Laboratory of Test/Measurement Technology and Instrument,School of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China;Key Laboratory of Special Fiber and Fiber Sensor of Hebei Province,School of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China;Center for Hydrogeology&Environmental Geology,Geological Environment Monitoring Engineering Technology Innovation Center of The Ministry of Natural Resources,Baoding,Hebei 071051,China)

机构地区：[1]燕山大学电气工程学院河北省测试计量技术及其仪器重点实验室,河北秦皇岛066004 [2]燕山大学信息科学与工程学院河北省特种光纤与光纤传感器重点实验室,河北秦皇岛066004 [3]自然资源部水文地质环境地质调查中心,地质环境监测工程技术创新中心,河北保定071051

出　　处：《计量学报》2021年第10期1386-1392,共7页Acta Metrologica Sinica

基　　金：国家重点研发计划(2018YFC1800903,2016YFC1400601-3);河北省重点研发计划(20373301D,19273901D);河北省自然科学基金(F2020203066);中国博士后基金(2018M630279);河北省博士后择优资助项目(D2018003028);河北省高等学校科学技术研究项目(ZD2018234,ZD2018243)。

摘　　要：针对X射线荧光光谱法(XRF)中Pb元素和As元素的重叠峰导致的元素浓度建模困难、乌鸦搜索算法(CSA)鲁棒性较弱等问题,将高斯混合模型(GMM)与改进型乌鸦算法(ICSA)相结合来实现重叠峰的分解。ICSA相比于CSA的改进主要有:引入了"乌鸦反哺"的特性,将GMM与ICSA更好的衔接在一起;将固定的意识概率更改为梯度型,使种群迭代更有多样性;适当调整了全局的优化策略,使算法更稳定收敛更快。将GMM模型与GMM-ICSA模型作对比实验,可得优化后的模型分解精度提升了4.93%;同时以均方误差和迭代时间为衡量搜索算法的标准,将ICSA与同类型的4种算法做了对比实验得出:CSA的均方误差和迭代时间均优于其他算法,从而表明改进后的算法能处理重叠峰问题的可行性。Aiming at the difficulties in modeling the element concentration caused by the overlapping peaks of Pb and As in X-ray fluorescence spectroscopy( XRF) and the weak robustness of the crow search algorithm( CSA),the Gaussian mixture model( GMM) is combined with the improved the crow search algorithm( ICSA) to achieve the decomposition of overlapping peaks. Compared with CSA,ICSA has three main improvements: the introduction of the"crow feeding"feature to better connect GMM and ICSA;the fixed probability of awareness is changed to a gradient type to make the population iteration more diverse;appropriate adjustments the global optimization strategy makes the algorithm more stable and converges faster. The comparison experiment between the GMM model and the GMM-ICSA model shows that the decomposition accuracy of the optimized model is increased by 4. 93%. At the same time,the mean square error and iteration time are used to measure the quality of the search algorithm,and ICSA is compared with the same type comparative experiments on the four algorithms show that the mean square error and iteration time of ICSA are better than other algorithms,which shows the feasibility of the improved algorithm in dealing with the problem of overlapping peaks.

关 键 词：计量学 光谱重叠峰 X射线荧光光谱法 改进型CSA 高斯混合模型 元素浓度 

分 类 号：TB99[一般工业技术—计量学]