...
首页> 外文期刊>Journal of Hazardous Materials >Development of a portable oil type classifier using laser-induced fluorescence spectrometer coupled with chemometrics
【24h】

Development of a portable oil type classifier using laser-induced fluorescence spectrometer coupled with chemometrics

机译:使用激光诱导的荧光光谱仪进行便携式油型分类器的开发,耦合与化学计量学

获取原文
获取原文并翻译 | 示例
           

摘要

Due to the recurrent small spills, oil pollution along coastal regions is still a major environmental issue. Standardized oil fingerprinting techniques are useful for oil spill identifications, but time- and resource-consuming. There have been ongoing needs for simple yet rapid approach for field screening of oil spill. Laser induced fluorescence (LIF) technology can be incorporated into a spectrometer, and with the integration of chemometrics can be consolidated as a potentially useful portable oil type classification device. Using a LIF spectrometer, 775 oil spectra were calibrated into supervised classification models and validated with 162 oil spectra. Reliability of the device to accurately remove background emission from fluorescence spectra was verified. Prediction performance and model robustness were further validated by comparison between commonly used classification models such as partial least square discriminant analysis (PLS-DA) and support vector machine-discriminant analysis (SVM-DA). Robustness in both models were comparable with PLS-DA having a lower number of misclassification (PLS-DA: 5.50%, SVM-DA: 13.8%) while SVM-DA having a lower number of unassigned samples (PLS-DA: 10.9%; SVM-DA: 16 1.39%). This study explicitly demonstrated the development of a new convenient and handy device which can be used as part of the screening process for oil spill fingerprinting.
机译:由于经常性的小溢出,沿着沿海地区的石油污染仍然是一个重大的环境问题。标准化的油指纹技术可用于漏油泄漏识别,但耗时量和资源。对漏油机泄漏的简单又快速的方法进行了持续的。激光诱导的荧光(LIF)技术可以掺入光谱仪中,并且通过聚化学计量学的整合可以合并为潜在的便携式油型分类装置。使用LIF光谱仪,775个油谱校准监督分类模型,并用162个油光谱验证。验证了装置的可靠性,以准确地去除荧光光谱的背景发射。通过诸如局部最小二乘判别分析(PLS-DA)的常用分类模型(PLS-DA)和支持向量机判别分析(SVM-DA),进一步验证了预测性能和模型稳健性。两种模型中的鲁棒性与PLS-DA具有较低数量的错误分类(PLS-DA:5.50%,SVM-DA:13.8%),而SVM-DA具有较少数量的未分配样品(PLS-DA:10.9%; SVM-DA:16 1.39%)。本研究明确证明了一种开发新型方便和便捷的设备,可作为漏油指纹识别筛选过程的一部分。

著录项

  • 来源
    《Journal of Hazardous Materials》 |2021年第1期|125723.1-125723.7|共7页
  • 作者单位

    Korea Inst Ocean Sci & Technol Oil & POPs Res Grp Geoje 53201 South Korea;

    Korea Inst Ocean Sci & Technol Oil & POPs Res Grp Geoje 53201 South Korea;

    Korea Inst Ocean Sci & Technol Oil & POPs Res Grp Geoje 53201 South Korea;

    Gwangju Inst Sci & Technol Mach Tech Co Ltd Gwangju 61005 South Korea;

    Gwangju Inst Sci & Technol Mach Tech Co Ltd Gwangju 61005 South Korea;

    Korea Inst Ocean Sci & Technol Oil & POPs Res Grp Geoje 53201 South Korea|Korea Univ Sci & Technol Dept Ocean Sci Daejeon 34113 South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Laser induced fluorescence; Chemometrics; Oil type classifier; Oil spill;

    机译:激光诱导荧光;化学计量学;油型分类器;漏油;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号