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Crude oil type near infrared spectrum identification method

A near-infrared spectroscopy and identification method technology, which is applied in the field of identifying crude oil types by near-infrared spectroscopy, can solve the problems of limited application, long calculation time, and large amount of mathematical calculation, and achieves the effect of reducing the amount of calculation and improving the identification speed.

Active Publication Date: 2016-03-23
CHINA PETROLEUM & CHEM CORP +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method has a large amount of mathematical calculations and takes a long time to calculate. For a database containing thousands of crude oil spectra, it often takes 5 minutes to identify a crude oil, which limits the application of this method.

Method used

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  • Crude oil type near infrared spectrum identification method
  • Crude oil type near infrared spectrum identification method
  • Crude oil type near infrared spectrum identification method

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0044] Establishment of near-infrared spectrum database of crude oil samples

[0045] 655 representative crude oil samples were collected, and the crude oil varieties basically covered the world's major crude oil producing areas. Measure the near-infrared spectrum of the crude oil sample, carry out the second order differential, take 6076.0~5556.0cm -1 and 4628.0~4000.0cm -1 For the absorbance in the spectral range, the near-infrared spectrum database X of crude oil samples was established. The dimension of X is 655×289, where 655 is the number of samples collected for crude oil, and 289 is the number of sampling points for the near-infrared spectrum absorbance.

[0046] Perform principal component analysis on X to obtain the spectral library score matrix T and spectral library load matrix P. The dimension of T is 655×15, of which 655 is the number of samples of crude oil collected, and 15 is the number of main factors; the dimension of P is 289 ×15, where 289 is the number ...

example 2

[0048] The following examples identify unknown crude oil samples according to the method of the present invention.

[0049] (1) Build a neighboring spectral database

[0050] According to the same conditions as the establishment of the near-infrared spectrum database X, the near-infrared spectrum of the unknown crude oil A in Table 1 was measured, and the second-order differential was performed on it, taking 6076.0 to 5556.0 cm -1 and 4628.0~4000.0cm -1 The absorbance of the spectral range constitutes the vector x A , whose dimension is 1×289. Multiply the vector x by the spectral library loading matrix P A Obtain the score vector t of crude oil A to be identified, whose dimension is 1×15.

[0051] With the score vector t as the feature, calculate the Euclidean distance between the score vector t and each sample in the spectral library score matrix T according to formula ②, k=15 in formula ②.

[0052] From the spectral library score matrix T, select 30 samples with the sm...

example 3

[0058] (1) Build a neighboring spectral database

[0059] According to the same conditions as the establishment of the near-infrared spectrum database X, the near-infrared spectrum of the unknown crude oil B in Table 1 was measured, and the second-order differential was performed on it, taking 6076.0 to 5556.0 cm -1 and 4628.0~4000.0cm -1 The absorbance of the spectral range constitutes the vector x B , whose dimension is 1×289. Multiply the vector x by the spectral library loading matrix P B Obtain the score vector t of crude oil B to be identified, and its dimension is 1×15.

[0060] With the score vector t as the feature, calculate the Euclidean distance between the score vector t and each sample in the spectral library score matrix T according to formula ②, k=15 in formula ②.

[0061] From the spectral library score matrix T, select 20 samples with the smallest distance from t, and the corresponding sample numbers in the near-infrared spectral database X are: 201, 111,...

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Abstract

The invention relates to a crude oil type near infrared spectrum identification method, which comprises that various crude oil samples are collected; after a second order differentiation treatment, the absorbance of the spectrum regions 4628-4000 cm<-1> and 6076-5556 cm<-1> are taken to establish a crude oil sample near infrared spectrum database; the near infrared spectrum database is subjected to main component analysis, and the spectrum database scoring matrixes T and the spectrum database loading matrixes P of the first 14-16 main components are taken; after the second order differentiation treatment, the absorbance of a crude oil sample to be identified in the characteristic spectrum regions form vector x, the main component scoring vector t is calculated, 10-14 crude oil samples having the similar scoring vector t are selected from the spectrum database scoring matrixes T, the spectrums of the samples form an adjacent spectrum database, and the identification parameters of various samples in the adjacent spectrum database on the x are calculated; and the sample same to the crude oil to be identified does not exist if all Qi values are not more than Qi, and if Qi is more than Qt and each mobile correlation coefficients of the sample i is not less than 0.9900, the crude oil to be identified and the sample i in the adjacent database are the same. With the method of the present invention, the identification speed of the unknown crude oil sample can be improved.

Description

technical field [0001] The invention is a spectral identification method for crude oil samples, in particular, a method for identifying crude oil types with near-infrared spectroscopy. Background technique [0002] Crude oil evaluation plays a very important role in various aspects such as crude oil exploitation, crude oil trade, and crude oil processing. Can not meet the needs of practical applications. Therefore, at present, large petrochemical companies are developing and establishing crude oil rapid evaluation technologies based on a variety of modern instrumental analysis methods, including color-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), near-infrared spectroscopy (NIR) and infrared spectroscopy ( IR), etc., among which the NIR method is favored because of its convenient measurement, fast speed, and can be used for on-site or on-line analysis. [0003] Different from other oil products such as gasoline and diesel measured by NIR, there are many eval...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/3577G01N21/359G06F17/30
Inventor 褚小立许育鹏陈瀑李敬岩
Owner CHINA PETROLEUM & CHEM CORP
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