LIBS结合鲸鱼优化算法对石油焦中微量元素的快速定量分析研究

doi:10.3964/j.issn.1000-0593(2025)10-2796-08

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摘要：石油焦是通过原油中重质碳氢化合物的高温裂解反应形成的碳质固体产物，因其高碳含量（80%~95%）、高热值及优异的导电性能，被广泛应用于电解铝阳极材料、冶金燃料、石墨电极及锂离子电池负极材料等领域，在工业生产中具有重要的应用价值。石油焦中，Fe和Cu等过渡金属元素不仅会降低石油焦的导电性能与热稳定性，还可能引发电极材料副反应，导致电池容量衰减。本文提出了一种基于激光诱导击穿光谱（LIBS）技术结合鲸鱼优化算法的混合建模方法，用于石油焦中Fe和Cu元素的快速定量分析。通过集成LIBS的高通量、无损检测优势，鲸鱼优化算法（WOA）的智能特征选择能力，以及偏最小二乘（PLS）回归的高维数据处理特性，构建了高效的分析模型。首先，通过采集19组石油焦样本的LIBS光谱数据，系统考察光谱数据的预处理策略，包括归一化（normalization, Nor）、多元散射校正（multiple scattering correction, MSC）、标准正态变换（standard normal variate, SNV）、一阶导数（first derivative, D1st）、二阶导数（second derivative, D2nd) 及小波变换（wavelet transform, WT）的组合优化，筛选对Fe、Cu元素定量分析最有效的预处理组合。通过实验验证，SNV-2nd-WT组合预处理显著提升了模型预测能力（Fe元素的交叉验证决定系数R²_CV=0.9464，均方根误差RMSE_CV=12.95 mg·kg^-1；Cu元素的R²_CV=0.914 6，RMSE_CV=8.84 mg·kg^-1）。进一步结合WOA算法优化特征选择与模型参数（鲸鱼数量、迭代次数、阈值），参数优化后，Fe元素和Cu元素的特征波长分别从5 784个降至88个和23个，最终模型的预测精度进一步改善：Fe元素预测集R²_P=0.947 0，RMSE_P=7.35 mg·kg^-1；Cu元素R²_P=0.953 8，RMSE_P =6.31 mg·kg^-1。该方法提供了一种高效的解决方案，能够快速检测石油焦中存在的微量金属。

关键词：激光诱导击穿光谱；化学计量学；鲸鱼优化算法；石油焦；微量元素

Abstract：Petroleum coke is a carbonaceous solid product formed by the pyrolysis of heavy hydrocarbons in crude oil. Due to its high carbon content (80%~95%), high calorific value, and excellent electrical conductivity, it is widely used in electrolytic aluminum anode materials, metallurgical fuels, graphite electrodes, and lithium-ion battery anode materials. It has important application value in industrial production. In petroleum coke, transition metal elements such as Fe and Cu not only reduce the conductivity and thermal stability of petroleum coke, but also may cause side reactions of electrode materials, resulting in battery capacity attenuation.In this paper, a hybrid modeling method based on laser-induced breakdown spectroscopy (LIBS) technology, combined with the whale optimization algorithm, is proposed for the rapid quantitative analysis of Fe and Cu elements in petroleum coke. An efficient analysis model was constructed by integrating the high-throughput and non-destructive detection advantages of LIBS, the intelligent feature selection ability of whale optimization algorithm (WOA), and the high-dimensional data processing characteristics of partial least squares (PLS) regression.Firstly, by collecting LIBS spectral data of 19 groups of petroleum coke samples, the preprocessing strategy of spectral data was systematically investigated. It includes the combination optimization of normalization (Nor), multiple scattering correction (MSC), standard normal variate (SNV), first derivative (D1st), second derivative (D2nd), and wavelet transform (WT). Screening the most effective pretreatment combination for quantitative analysis of Fe and Cu elements.Through experimental verification, the SNV-D2nd-WT combined pretreatment significantly improved the model's prediction ability (cross-validation determination coefficient R²_CV=0.946 4, root mean square error RMSE_CV=12.95 mg·kg^-1; R²_CV=0.914 6, RMSE_CV=8.84 mg·kg^-1). The WOA algorithm was further combined to optimize the feature selection and model parameters (number of whales, number of iterations, threshold). After parameter optimization, the characteristic wavelengths of Fe and Cu elements were reduced from 5 784 to 88 and 23, respectively. The prediction accuracy of the final model was further improved: Fe element prediction setR²_P=0.947 0, RMSE_P=7.35 mg·kg^-1; Cu element R²_P=0.953 8, RMSE_P=6.31 mg·kg^-1. This method offers a rapid and efficient solution for detecting trace metals in petroleum coke.

Key words：Laser-induced breakdown spectroscopy; Chemometrics; Whale optimization algorithm; Petroleum coke; Trace element

收稿日期: 2025-02-21 修订日期: 2025-05-08

中图分类号:

O657.319

基金资助: 国家自然科学基金项目(22173071)，陕西省教育厅科研计划项目(24JP141)资助

通讯作者: 李茂刚，李华 E-mail: lmglmg1995@163.com; huali@nwu.edu.cn

作者简介: 张梦璠，2000年生，西安石油大学化学化工学院硕士研究生 e-mail: 1950093230@qq.com

引用本文:

张梦璠，李茂刚，刘一江，闫春华，张天龙，李华. LIBS结合鲸鱼优化算法对石油焦中微量元素的快速定量分析研究[J]. 光谱学与光谱分析, 2025, 45(10): 2796-2803.
ZHANG Meng-fan, LI Mao-gang, LIU Yi-jiang, YAN Chun-hua, ZHANG Tian-long, LI Hua. Rapid Quantitative Analysis of Trace Elements in Petroleum Coke by LIBS Combined With Whale Optimization Algorithm. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(10): 2796-2803.

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