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中国精品科技期刊2020
刘珊珊, 张俊, 林思寒, 刘木华, 赖曲芳, 万仁杰, 黎静, 梅宇. 猪饲料中Cu元素的双脉冲激光诱导击穿光谱检测技术研究[J]. 食品工业科技, 2017, (23): 198-202. DOI: 10.13386/j.issn1002-0306.2017.23.037
引用本文: 刘珊珊, 张俊, 林思寒, 刘木华, 赖曲芳, 万仁杰, 黎静, 梅宇. 猪饲料中Cu元素的双脉冲激光诱导击穿光谱检测技术研究[J]. 食品工业科技, 2017, (23): 198-202. DOI: 10.13386/j.issn1002-0306.2017.23.037
LIU Shan-shan, ZHANG Jun, LIN Si-han, LIU Mu-hua, LAI Qu-fang, WAN Ren-jie, LI Jing, MEI Yu. Detection of Cu element in pig feed by double pulse laser induced breakdown spectroscopy[J]. Science and Technology of Food Industry, 2017, (23): 198-202. DOI: 10.13386/j.issn1002-0306.2017.23.037
Citation: LIU Shan-shan, ZHANG Jun, LIN Si-han, LIU Mu-hua, LAI Qu-fang, WAN Ren-jie, LI Jing, MEI Yu. Detection of Cu element in pig feed by double pulse laser induced breakdown spectroscopy[J]. Science and Technology of Food Industry, 2017, (23): 198-202. DOI: 10.13386/j.issn1002-0306.2017.23.037

猪饲料中Cu元素的双脉冲激光诱导击穿光谱检测技术研究

Detection of Cu element in pig feed by double pulse laser induced breakdown spectroscopy

  • 摘要: 对猪饲料中Cu元素的双脉冲激光诱导击穿光谱(LIBS)检测技术进行了研究。结合正交实验设计对饲料样品中Cu元素进行了LIBS实验参数优化。根据正交实验的直观分析法中的指标之和得出最佳实验参数条件为:激光A能量157.77 m J,激光B能量196.87 m J,激光延迟时间450 ns,采集延时1.28μs。基于偏最小二乘(PLS),比较了不同点数平滑处理和各种预处理方法对PLS模型预测效果的影响。最后得出,结合9点平滑预处理能有效降低噪声信号,能够提高PLS模型分析LIBS光谱数据的准确性,模型预测结果:相关系数r,预测均方差RMSEP,平均相对误差ARE分别为0.9879、15.10、8.24%。 

     

    Abstract: Double pulse laser-induced breakdown spectroscopy ( LIBS) technique for the determination of Cu in pig feed was studied in this paper.Combined with orthogonal design, parameters optimization of Cu in pig feed samples, LIBS test was carried out.According to the sum of the indexes in the visual analysis of the orthogonal experiment, the best experimental parameters were obtained.The laser energy of A was 157.77 m J and B was 196.87 m J.And the delay time of laser was 450 ns and gathering was 1.28 μs.Based on partial least squares ( PLS) , the influence of different points smoothing and various pretreatment methods to the PLS model prediction effect were compared.Finally, the combination of 9 point smoothing pretreatment could effectively reduce the noise signal.It could improve the accuracy of PLS model for analyzing LIBS spectral data.Model predictions were as follows: correlation coefficient ( r) , root mean square error of prediction ( RMSEP) and average relative error ( ARE) were0.9879, 15.10, 8.24%, respectively.

     

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