Yang Si Jie1,2; Feng Wei Wei2,3,4
; Cai Zong-qi2,3; Wang Qing2,3发表期刊SPECTROSCOPY AND SPECTRAL ANALYSIS
ISSN1000-0593
2021-08-01
卷号41期号:8页码:2469-2473
关键词MicroplasticsLaser RamanWavelet analysisDecision treeRandom forest
DOI10.3964/j.issn.1000-0593(2021)08-2469-05
英文摘要Due to a large amount of use and discharge of plastics, these plastics are broken into microplastics by the environmental effect and gather in the ocean in large quantities, leading to the accumulation of a large number of microplastics in the ocean, inrecent year. Microplastics are small in shape and difficult to identify their source and type. Laser Raman detection technology has been widely used in recent years which have fast, nondestructive and easy identification. In this paper, based on Raman spectral detection technology, an intelligent classification method combining wavelet processing and random forest algorithm is proposed to realize the rapid recognition of microplastics in seawater. The spectral data were collected by using laser Raman detection technology from six typical seawater microplastics standard samples(ABS, PA, PET, PP, PS, PVC), and the obtained spectra were pretreated by wavelet base DB7 and decomposition times 3 and standard deviation normalization. In order to improve the recognition speed, the spectral data is compressed at the same time. The data are respectively compressed to 64, 128, 256, 512 and 1 024 points, and their decision tree algorithm identification accuracy was 91. 51% 91. 67%, 92. 35%, 93.17% and 93. 21% respectively. The random forest algorithm identification accuracy was 93. 12%, 93. 92%, 94. 83%, 96. 81% and 96. 81% respectively. The experimental results show that the Raman spectral compression of microplastics is the best compression point for efficiency and precision when the Raman spectral compression is 512 points, which can provide a reference for the Raman data compression of microplastics in practical engineering applications. Two recognition algorithms, decision tree and random forest, were used to study the Raman spectrum recognition of microplastics. The results show that the cross-validation accuracy of the random forest is higher than that of the decision tree. In order to further improve the identification accuracy, the model parameter optimization was carried out, and the cross-validation accuracy of the random forest method for identifying microplastics could reach 97. 24% by using the optimized model parameters. It can provide a technical reference for the rapid identification of microplastics in seawater.
收录类别SCI
语种中文
研究领域[WOS]Spectroscopy
WOS记录号WOS:000696005000022
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/29777
专题中科院海岸带环境过程与生态修复重点实验室_海岸带环境过程实验室
中科院海岸带环境过程与生态修复重点实验室
海岸带生物学与生物资源利用重点实验室_海岸带生物资源高效利用研究与发展中心
通讯作者Feng Wei Wei作者单位1.Harbin Inst Technol Weihai, Weihai 264200, Peoples R China
2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714Yang Si Jie,Feng Wei Wei,Cai Zong-qi,et al. Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2021,41(8):2469-2473.
APAYang Si Jie,Feng Wei Wei,Cai Zong-qi,&Wang Qing.(2021).Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy.SPECTROSCOPY AND SPECTRAL ANALYSIS,41(8),2469-2473.
MLAYang Si Jie,et al."Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy".SPECTROSCOPY AND SPECTRAL ANALYSIS 41.8(2021):2469-2473.
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