基于多元统计分析的香烟烟灰XRF快速检验

香烟烟灰是案件现场中重要的物证。为了对香烟烟灰进行快速无损检测，采用多元统计分析方法，利用能量色散型X射线荧光光谱仪对收集到的83个烟灰样品进行了理论分析和实验验证，建立了基于化学计量学的香烟烟灰分类模型。借助聚类分析对样品聚类区分，聚类结果的准确性通过回归分析进行检验；而后采用物质元素作为变量，通过判别分析建立判别分类模型。结果表明，聚类结果良好，回归分析显示聚类分析的类别与各元素可建立良好拟合关系；判别分析得到的分类模型的准确率达到100%，若想对未知香烟烟灰样品进行归类，只需要输入判别模型的相关变量，在判别分布图中会显示出其位置, 就能对样品类别进行归类。此方法简单快速、结果准确可靠，为公安基层实际办案提供了参考。

Rapid XRF test of cigarette ash based on multivariate statistical analysis

Cigarette ash is an important material evidence at the scene of the case. In order to achieve the purpose of rapid non-destructive detection of cigarette ash, 83 collected cigarette ash samples were theoretically analyzed and then tested by energy dispersive X-ray fluorescence spectrometer. A classification model of cigarette ash based on chemometrics was established. First of all, cluster analysis was used to distinguish samples, and the accuracy of clustering results was tested by regression analysis. Then, the material elements were used as variables and the discriminant classification model was established by discriminant analysis. The results show that the clustering results are good, and the regression analysis shows that the cluster analysis categories and elements can establish a good fitting relationship. The accuracy of the classification model obtained by the discriminant analysis is 100%. If you want to classify the unknown cigarette ash samples, you only need to input the relevant variables of the discriminant model, which will show its location in the discriminant distribution map, and then you can classify the samples. This method is simple, fast, accurate and reliable. This study provides a reference for the actual handling of cases at the grassroots of public security.