中国塑料 ›› 2021, Vol. 35 ›› Issue (5): 72-78.DOI: 10.19491/j.issn.1001-9278.2021.05.012

• 加工与应用 • 上一篇    下一篇

基于种属差异性利用XRF对塑钢窗的分类研究

姜红(), 张岚泽, 刘津彤, 苑志豪   

  1. 中国人民公安大学侦查学院,北京 100038
  • 收稿日期:2020-11-03 出版日期:2021-05-26 发布日期:2021-05-24
  • 基金资助:
    中国人民公安大学2021年基科费重点项目(2021JKF212)

Research on Clustering Plastic Steel Windows by X⁃ray Fluorescence Spectrometry Based on Species Difference

JIANG Hong(), ZHANG Lanze, LIU Jintong, YUAN Zhihao   

  1. School of Investigation,People’s Public Security University of China,Beijing 100038,China
  • Received:2020-11-03 Online:2021-05-26 Published:2021-05-24
  • Contact: JIANG Hong E-mail:jiangh2001@163.com

摘要:

建立了一种对未知产品信息的塑钢窗样本的快速分类方法。利用X射线荧光光谱法(XRF),采用手持式荧光光谱仪,以Ag作阳极靶、电压为50 kV、电流为200 μA、采集时间为70 s,对40个不同产地、不同品牌、不同用途的塑钢窗进行元素分析。依据实验结果筛选出具有种属差异性的指标元素Pb、Ti、Cl,同时依据“含量标准偏差和”,综合考虑“品牌、产地、用途”之间的相对显著性关系,实现对塑钢窗样本的分类。结果表明,该方法可对样本进行完全分类,为现场勘查所采集的检材分类提供了新模式,具有一定的实战意义。

关键词: 塑钢窗, X射线荧光光谱法, 指标元素, 种属差异性, 含量标准偏差和

Abstract:

A fast clustering method was established for plastic steel window samples with unknown product information under the three indicators including product source, brand, and use purpose. The element contents of 40 plastic steel window samples with different brands, different use purposes and different sources were analyzed by X?ray fluorescence spectrometry and a handheld fluorescence spectrometer under the experimental conditions of Ag as anode target, voltage of 50 kV, current of 200 μA and acquisition time of 70 s. According to the experimental results, the index elements of Pb, Ti, Cl with species difference were selected. Through calculating the sum of standard deviation of the samples and considering the relative significant relationship among the brand, source and use purpose, the clustering results of 40 samples of plastic steel windows were obtained. This method can provide a new model for the clustering of samples collected in field investigation, indicating a certain practical significance.

Key words: plastic steel window, X-ray fluorescence spectrometry, index element, species difference, sum of standard deviation

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