Method for discriminating offshore oil spill types based on multi-dimensional chemical fingerprint quantification model

A technology of chemical fingerprints and quantitative models, applied in measuring devices, scientific instruments, color/spectral characteristic measurement, etc., can solve the problems of complex and uncertain oil spill components, achieve the effect of increasing reliability and reducing the number of variables

Active Publication Date: 2020-03-24
DALIAN MARITIME UNIVERSITY
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AI Technical Summary

Problems solved by technology

At present, the identification of oil spills is mostly single-dimensional oil fingerprints, but the components of oil spills in the marine environment are extremely complex, and this type of single-dimensional analysis and identification methods have uncertainties and limitations in the identification of weathered oil spills

Method used

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  • Method for discriminating offshore oil spill types based on multi-dimensional chemical fingerprint quantification model
  • Method for discriminating offshore oil spill types based on multi-dimensional chemical fingerprint quantification model
  • Method for discriminating offshore oil spill types based on multi-dimensional chemical fingerprint quantification model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0101] Example 1: Verification of Oman crude oil before and after weathering

[0102] Table 1: Eight diagnostic ratios, d3 detail coefficients and Ni / V of unweathered Oman crude oil

[0103]

[0104] Substitute the diagnostic ratios in Table 1 into the following formula to calculate the first principal component PL1:

[0105] CPI'=(CPI-1.031058) / 0.108341;

[0106] L / H'=(L / H-3.510389) / 4.785483;

[0107] C 19-20 / C 19-22 '=(C 19-20 / C 19-22 -0.57226) / 0.133963;

[0108] C 17 / Pr'=(C 17 / Pr-2.733146) / 1.410578;

[0109] C 18 / Ph'=(C 18 / Ph-2.598895) / 1.343894;

[0110] Pr / Ph'=(Pr / Ph-1.150927) / 0.606687;

[0111] OEP1'=(OEP1-0.965601) / 0.056963;

[0112] OEP2'=(OEP2-1.039489) / 0.079082;

[0113] PL1=0.2928CPI'-0.2662L / H'+0.0577C 19-20 / C 19-22 '-0.7019C 17 / Pr'-0.2624C 18 / Ph’+0.5097Pr / Ph’-0.1251OEP1’+0.0563OEP2’;

[0114] Set PL1, d3 (332±2nm) and Ni / V into the following formula:

[0115] Y 1 =1.323*X 1 -0.174*X 2 +0.057*X 3 +1.052;

[0116] Y 2 =0.131*X ...

Embodiment 2

[0134] Embodiment 2: Verification of 180 fuel oil 1# before and after weathering

[0135] Table 3 Eight diagnostic ratios, d3 detail coefficient and Ni / V of unweathered 180 fuel oil 1#

[0136]

[0137] Substitute the diagnostic ratio in Table 3 into the formula in Example 1 to calculate (Y 1 , Y 2 ).

[0138] (Y 1 , Y 2 ) and fuel oil group centroid O 1 (-1.608, 0.664), the center of mass of Middle East crude oil group O 2 (-0.613, -0.81), non-Middle East crude group centroid O 3 The Euclidean distances of (1.743, 0.21) are 1.143253354, 1.348392131, and 2.238644396, respectively. From this we can see that with O 1 The closest, this oil sample is fuel oil, consistent with the known situation.

[0139] Table 4: 8 diagnostic ratios, d3 detail coefficient and Ni / V of 180 fuel oil 1# weathered for 30 days

[0140]

[0141] Substitute the diagnostic ratio of Table 4 into the formula in Example 1, and calculate (Y 1 , Y 2 ).

[0142] (Y 1 , Y 2 ) and fuel oil gr...

Embodiment 3

[0143] Example 3: Validation of Malaysian crude oil before and after weathering

[0144] Table 5: Eight diagnostic ratios, d3 detail coefficients and Ni / V for unweathered Malaysian crude oil

[0145]

[0146] Substitute the diagnostic ratio of Table 5 into the formula in Example 1, and calculate (Y 1 , Y 2 ).

[0147] (Y 1 , Y 2 ) and fuel oil group centroid O 1 (-1.608, 0.664), the center of mass of Middle East crude oil group O 2 (-0.613, -0.81), non-Middle East crude group centroid O 3 The Euclidean distances of (1.743, 0.21) are 4.221683847, 3.039329744, and 1.057082446, respectively. From this we can see that with O 3 The closest, this oil sample is non-Middle Eastern crude oil, which is consistent with the known situation.

[0148] Table 6: Eight diagnostic ratios, d3 detail coefficients and Ni / V for 30-day weathered Malaysian crude oil

[0149]

[0150] Substitute the diagnostic ratio of Table 6 into the formula in Example 1, and calculate (Y 1 , Y 2 )...

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Abstract

The invention relates to a method for discriminating offshore oil spill types based on a multi-dimensional chemical fingerprint quantification model, in particular to the method for discriminating theoffshore oil spill types based on the multi-dimensional chemical fingerprint quantification model, which can be used for quickly distinguishing fuel oil, Middle East crude oil and non-Middle East crude oil, and belongs to the field of marine environmental pollution monitoring and treatment. According to the invention, the method comprises steps of selecting n-alkanes, fluorescence characteristicsand Ni / V to construct multi-dimensional chemical fingerprints; analyzing the eight diagnosis ratios of the n-alkanes by using a partial least squares algorithm to extract three main components; carrying out 6-layer discrete wavelet transform analysis on the synchronous fluorescence spectrum by using a db7 wavelet basis, extracting 5 fluorescence information under d3, and finally screening out a first principal component of a diagnosis ratio by using an exhaustion method, and taking a wavelet coefficient of d3(332+ / -2nm) and Ni / V as modeling variables. The identification accuracy of the established model on a modeled oil sample reaches 100%, and the identification accuracy on non-modeled and weathered fuel oil and crude oil reaches 88.89% and 95.50% respectively.

Description

technical field [0001] The present invention relates to a method for discriminating types of marine oil spills based on a multidimensional chemical fingerprint quantization model, in particular to a method for discriminating types of marine oil spills based on a multidimensional chemical fingerprint quantification model to quickly distinguish fuel oil, Middle Eastern crude oil and non-Middle Eastern crude oil, belonging to marine Environmental pollution monitoring and governance. Background technique [0002] In recent years, with the development of oil industry and marine transportation, sea oil spill accidents occur frequently. Oil spills at sea will cause harm to the ecosystem of nearby sea areas, cause economic losses in polluted areas, and even cause serious harm to human health. Therefore, it is particularly important to timely and accurately identify the type of oil spill and take appropriate protective measures. [1] . [0003] For decades, domestic and foreign sch...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/28G01N30/02G01N30/68G01N21/64G01N21/31
CPCG01N33/2823G01N30/02G01N30/68G01N21/64G01N21/314G01N2030/025
Inventor 刘晓星许皓伟
Owner DALIAN MARITIME UNIVERSITY
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