基于GA-GRNN算法和显微拉曼光谱的城市河流微塑料识别方法研究  

Research onIdentification Method of Microplastics in Urban Rivers Based on GA-GRNN Algorithm and Micro Raman Spectroscopy

作　　者：李静[1] 张媛[1] 张莹[1] 刘家伟 LI Jing;ZHANG Yuan;ZHANG Ying;LIU Jiawei(Basic Teaching Department of Zhengzhou Railway Vocational and Technical College,Zhengzhou 451460,China;School of Information and Engineering,ZhengZhou University,ZhengZhou 450001,China)

机构地区：[1]郑州铁路职业技术学院,河南郑州451460 [2]郑州大学信息工程学院,河南郑州450001

出　　处：《光散射学报》2025年第1期69-76,共8页The Journal of Light Scattering

基　　金：河南省软科学项目(212400410321)。

摘　　要：微塑料污染已成为一个全球性的环境问题,加强对城市水域中微塑料污染的监管是解决微塑料污染的关键环节,因此本文开展了快速、实时的城市河流微塑料识别方法的研究。本工作提出了一种遗传算法优化广义回归神经网络(Genetic Algorithm-Generalized Regression Neural Network,GA-GRNN)算法结合显微拉曼光谱的技术方法,开展了微塑料颗粒的实验探测和理论计算,分析了微塑料颗粒拉曼光谱特征峰的振动模式和隐藏峰的拟合解译,评估了不同浓度微塑料悬浮液的拉曼光谱,通过GA-GRNN算法建立了微塑料识别分类模型,其模型的分类准确率为100%,实现了对河流中分离的微塑料颗粒的准确识别。本文提出将GA-GRNN算法与显微拉曼光谱相组合的技术方法非常具有实用性,在未来城市水域微塑料污染的监管指导方面具有很好的借鉴意义。Microplastic pollution has become a global environmental problem.Strengthening the supervision of microplastic pollution in urban waters is the key to solving the problem.Therefore,this paper carried out research on a rapid and real-time microplastic identification method in urban rivers.In this paper,a genetic algorithm optimized generalized regression neural network(GA-GRNN)algorithm combined with micro Raman spectroscopy was proposed.The experimental detection and theoretical calculation of microplastic powder were carried out,and the fitting interpretation of Raman spectrum characteristic peaks and hidden peaks of microplastic powder were analyzed.The Raman spectra of microplastic suspensions with different concentrations were evaluated.The GA-GRNN algorithm established the microplastic recognition and classification model.The model’s classification accuracy was 100%,which realized the accurate recognition of microplastic particles separated from the river.This paper presents a very practical technical method for combining the GA-GRNN algorithm with micro Raman spectroscopy,which has a good reference significance in the supervision and guidance of micro plastic pollution in urban waters in the future.

关 键 词：遗传算法 广义回归神经网络 拉曼光谱 微塑料 分类模型 

分 类 号：O433[机械工程—光学工程] O657.3[理学—光学]