典型固体废物的XRF-XRD耦合光谱指纹特征识别

黄瑞潇, 卢永琦, 郑志敏, 杨玉飞, 杨金忠, 黄启飞

中国环境科学 ›› 2025, Vol. 45 ›› Issue (10) : 5585-5595.

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中国环境科学 ›› 2025, Vol. 45 ›› Issue (10) : 5585-5595.
固体废物

典型固体废物的XRF-XRD耦合光谱指纹特征识别

  • 黄瑞潇, 卢永琦, 郑志敏, 杨玉飞, 杨金忠, 黄启飞
作者信息 +

Identification of XRF-XRD coupled spectral fingerprint characteristics of typical solid waste

  • HUANG Rui-xiao, LU Yong-qi, ZHENG Zhi-min, YANG Yu-fei, YANG Jin-zhong, HUANG Qi-fei
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文章历史 +

摘要

针对常见的10类固体废物开展X射线荧光(XRF)与X射线衍射(XRD)实验,通过非参数检验提取固体废物的XRF与XRD指纹特征,并采用归一化的方式结合两种指纹特征形成XRF-XRD耦合光谱指纹特征,以三种指纹特征为数据集训练机器学习分类模型,发现随机森林模型分类识别效果最好,验证集分类精确度、召回率、准确率分别达98.0%、97.5%、97.6%,证实耦合光谱指纹特征分类效果优于单一光谱指纹特征.形成了固体废物XRF-XRD多维指纹特征提取方法,为固体废物指纹特征识别奠定方法基础.

Abstract

This study conducted X-ray fluorescence (XRF) and X-ray diffraction (XRD) experiments on 10 common types of solid waste. By employing non-parametric tests, the XRF and XRD fingerprint characteristics of solid waste were extracted. A normalized approach was adopted to combine the two fingerprint characteristics to form XRF-XRD coupled spectral fingerprint characteristics. A machine learning classification model was trained using the three fingerprint characteristics as a dataset. It was found that the random forest model exhibited the best classification recognition performance, with classification accuracy, recall rate, and precision rate in the validation set reaching 98.0%, 97.5%, and 97.6%, respectively. This confirmed that the classification performance of coupled spectral fingerprint characteristics was superior to that of single spectral fingerprint characteristics. A method for extracting multi-dimensional fingerprint characteristics of solid waste using XRF-XRD was developed, laying a methodological foundation for the identification of fingerprint characteristics of solid waste.

关键词

指纹特征 / 固体废物 / XRF / XRD

Key words

fingerprint features / solid waste / XRF / XRD

引用本文

导出引用
黄瑞潇, 卢永琦, 郑志敏, 杨玉飞, 杨金忠, 黄启飞. 典型固体废物的XRF-XRD耦合光谱指纹特征识别[J]. 中国环境科学. 2025, 45(10): 5585-5595
HUANG Rui-xiao, LU Yong-qi, ZHENG Zhi-min, YANG Yu-fei, YANG Jin-zhong, HUANG Qi-fei. Identification of XRF-XRD coupled spectral fingerprint characteristics of typical solid waste[J]. China Environmental Science. 2025, 45(10): 5585-5595
中图分类号: X705   

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基金

国家重点研发计划项目(2024YFC3906401);黄河流域生态保护和高质量发展联合研究项目(2022-YRUC-01-0303)

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