黄义, 齐超越, 李佳, 公维民, 张婷婷, 王思童, 刘晓星. 基于诊断比值的Fisher判别法鉴定海上溢油[J]. 海洋环境科学, 2018, 37(2): 299-303. DOI: 10.12111/j.cnki.mes20180222
引用本文: 黄义, 齐超越, 李佳, 公维民, 张婷婷, 王思童, 刘晓星. 基于诊断比值的Fisher判别法鉴定海上溢油[J]. 海洋环境科学, 2018, 37(2): 299-303. DOI: 10.12111/j.cnki.mes20180222
HUANG Yi, QI Chao-yue, LI Jia, GONG Wei-min, ZHANG Ting-ting, WANG Si-tong, LIU Xiao-xing. Identification of marine oil spills by fisher discriminant based on the diagnostic ratios[J]. Chinese Journal of MARINE ENVIRONMENTAL SCIENCE, 2018, 37(2): 299-303. DOI: 10.12111/j.cnki.mes20180222
Citation: HUANG Yi, QI Chao-yue, LI Jia, GONG Wei-min, ZHANG Ting-ting, WANG Si-tong, LIU Xiao-xing. Identification of marine oil spills by fisher discriminant based on the diagnostic ratios[J]. Chinese Journal of MARINE ENVIRONMENTAL SCIENCE, 2018, 37(2): 299-303. DOI: 10.12111/j.cnki.mes20180222

基于诊断比值的Fisher判别法鉴定海上溢油

Identification of marine oil spills by fisher discriminant based on the diagnostic ratios

  • 摘要: 采用GC-FID检测分析了8种燃料油、8种中东原油、13种非中东原油的正构烷烃分布特征。以具有地球化学意义和较强的抗风化能力的诊断比值n-C17/Pr、n-C18/Ph、Pr/Ph、LMW/HMWCPI和(n-C19+n-C20)/(n-C19~n-C22)为建模参数,对中东原油、非中东原油和燃料油进行Fisher判别。由于n-C17/Pr和n-C18/Ph间存在共线性,且燃料油的n-C17/Pr受风化影响较大,所以将其不作为建模参数。所建模型的Wilks's lambda分布所对应的P值为0,表明判别模型是有效的,模型判别准确率达到93.1%。对短期风化30d后的油样的判别准确率也能够达到93.1%,说明模型也同样适用于风化溢油的鉴别。

     

    Abstract: The characteristic of n-alkane distributions of 8 kinds of marine fuel, 8 kinds of Middle East crude oil and 13 kinds of non-Middle East crude oil were analyzed by GC-FID.The diagnostic ratios with the geochemical significance and the strong anti-weathering such as n-C17/Pr, n-C18/Ph, Pr/Ph, LMW/HMW, CPI and (n-C19+n-C20)/(n-C19~n-C22) were used as modeling parameters, Fisher discriminant of these 29 kinds of oils were performed.Since n-C17/Pr and n-C18/Ph were collinear and n-C17/Pr of marine fuel had obviously changes during weathering, n-C17/Pr cannot be used as a modeling parameter.The Wilks's lambda distribution of modeling corresponded to P value of 0, which indicated the discriminant model was valid, and the identification accuracy of model was 93.1%.The identification accuracy of oils after short-term weathering for 30 days could also reach 93.1%, this meant that the established model was also applicable to identification of weathered oil spills.

     

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