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

发布时间：2018-05-18 23:17

本文选题：激光诱导击穿光谱 + 猪饲料　；参考：《食品工业科技》2017年23期

【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]:The detection of Cu in pig feed by double pulse laser induced breakdown spectroscopy (LIBS) was studied. The LIBS parameters of Cu in feed samples were optimized by orthogonal design. According to the sum of the indexes in the visual analysis of orthogonal experiments, the optimum experimental parameters are obtained as follows: laser energy A 157.77 m J, laser B energy 196.87 m J, laser delay time 450ns, acquisition delay 1.28 渭 s. Based on the partial least square method, the effects of different number smoothing and various preprocessing methods on the prediction effect of PLS model are compared. Finally, it is concluded that the combination of 9-point smoothing pretreatment can effectively reduce the noise signal, and can improve the accuracy of the PLS model in the analysis of LIBS spectral data. The prediction results of the model are as follows: the correlation coefficient r, the predicted RMSEPs, the average relative error (ARE) is 0.987915.10 / 8.24, respectively.
【作者单位】：江西农业大学工学院;江西省现代农业装备重点实验室;江西农业大学动物科学技术学院;江西省果蔬采后处理关键技术与质量安全协同创新中心;
【基金】：国家自然科学基金项目(31460419) 猪饲料中高铜的激光诱导击穿光谱快速检测技术研究(GJJ160369) 赣鄱英才555工程
【分类号】：O657.31;S816.17

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