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CN102590132A - Method for measuring methanol content in methanol gasoline - Google Patents

Method for measuring methanol content in methanol gasoline Download PDF

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CN102590132A
CN102590132A CN2012100324868A CN201210032486A CN102590132A CN 102590132 A CN102590132 A CN 102590132A CN 2012100324868 A CN2012100324868 A CN 2012100324868A CN 201210032486 A CN201210032486 A CN 201210032486A CN 102590132 A CN102590132 A CN 102590132A
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methanol
spectrum
gasoline
content
matrix
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戴连奎
黄承伟
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Zhejiang University ZJU
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Zhejiang University ZJU
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Abstract

The invention discloses a method for measuring the methanol content in methanol gasoline, which comprises the following steps: firstly, a near-infrared measuring system is utilized to obtain the near-infrared spectroscopic data of a standard sample, then integer interpolation is carried out on a spectrum, and the baseline of each spectrum is found out and removed; secondly, the characteristic peak of unsaturated hydrocarbon in the gasoline component is utilized for normalization, so the influence which is generated by different base oil in the methanol gasoline to the spectrum is overcome; and finally, the normalized spectrum is applied, and the characteristic peak of the methanol is combined to built a model. In the test period, after the spectroscopic data of an unknown test sample is obtained, the spectrum pretreatment is also carried out according to the method, and finally, the built model is utilized to pretest on the basis of the standardized spectrum. The method not only can quickly and accurately measure the methanol content in the methanol gasoline, but also can effectively reduce the measurement error which is caused by gasoline component variation, so the measurement stability is improved.

Description

Method for rapidly measuring content of methanol in methanol gasoline
Technical Field
The invention relates to an oil product detection technology, in particular to a method for rapidly detecting the content of methanol in methanol gasoline by applying near infrared spectroscopy.
Background
Because of the increasing shortage of petroleum resources, the contradiction between supply and demand of petroleum is continuously increased, the price of petroleum is also rapidly increased, the development of novel alternative energy is accelerated in all countries in the world, and methanol and a certain proportion of gasoline are mixed to be widely applied as an alternative energy for vehicles. The methanol is mixed, so that the octane value of the gasoline can be effectively improved, the gasoline can be completely combusted, the combustion efficiency is increased, the economy is improved, and the atmospheric pollution is reduced. The methanol has low heat value, and after a large amount of methanol is mixed into gasoline, gas resistance is easily generated to influence oil supply; the methanol is easy to generate adverse effects such as corrosion, abrasion and the like on sealing systems of engines, particularly piston rings, cylinder walls and the like; the rubber and the plastic are easy to generate adverse effects such as swelling, corrosion and the like, and the sealing system of equipment such as an oil pump and the like is also influenced.
With the continuous progress of the technology, the advantages of methanol as the vehicle energy source are more obvious, and the defects are controlled. The methanol is a basic organic chemical raw material, and has important significance for accurately and quickly analyzing the components and the content of the synthetic methanol gasoline. Since 2003, methanol gasoline is popularized and used in Shaanxi, Shanxi, Heilongjiang and other places in China, the technical obstacles restricting the development of methanol gasoline are also overcome technically, and the technical indexes can be compared with the international advanced level.
In order to accelerate the pace of using methanol gasoline, relieve the production and operation dilemma faced by methanol enterprises in China at present and regulate the production of methanol gasoline, the national standardization regulatory committee issued national standard (GB/T23799) for methanol gasoline for vehicles (M85) in 7 months in 2009 (2009). In addition, relevant methanol gasoline standards are also provided in various places, such as local standards in shanxi province, namely M15 methanol gasoline for vehicles (DB61/T352-2004) and M25 methanol gasoline for vehicles (DB61/T353-2004), local standards in heilongjiang province, namely M15 methanol gasoline for vehicles (DB 23/T988-), "M15 methanol gasoline for vehicles (DB13/T1303-2010) in north river, and the like, which strictly regulate the content of methanol in methanol gasoline.
At present, the main methods for detecting the content of methanol in the methanol gasoline are gas chromatography, spectrometry and the like. The gas chromatography has short measurement time and high precision, but the method needs complicated experimental instruments and has high requirements on experimental environment, and meanwhile, the method can generate measurement waste liquid to pollute the environment, so that the method is not suitable for the requirements of industrial field on-line analysis and field environment measurement. The near infrared spectroscopy is a mature indirect measurement method, is widely applied to rapid detection of fuel quality such as gasoline octane number and the like at present, and has the advantages of high detection speed, good repeatability, easiness in operation and maintenance, low measurement cost and the like.
Disclosure of Invention
The invention aims to provide a method for quickly measuring the content of methanol in methanol gasoline so as to realize quick, accurate and stable measurement of the content of methanol.
The purpose of the invention is realized by the following technical scheme: a method for detecting the content of methanol in methanol gasoline comprises the following steps:
(1) obtaining a plurality of methanol gasoline standard samples with known methanol content, wherein the methanol content of the standard samples can cover the required detection range as much as possible;
(2) the method comprises the steps of utilizing a tungsten halogen lamp as a light source, adopting a long-wave near-infrared spectrometer to measure the near-infrared spectrum of a standard sample and carrying out integer interpolation, and recording a spectrum data matrix after interpolation as
Figure 2012100324868100002DEST_PATH_IMAGE001
WhereinpIs the number of samples to be tested,qcounting the number of spectral data points;
(3) respectively searching minimum points in two no-signal areas of the near infrared spectrum of each standard sample, and fitting a straight line with the two minimum pointsL i ,L i Namely the base line, obtaining a matrix of the base line
(4) According to the spectrum data matrix after interpolation obtained in the step 2AAnd the spectrum base line matrix obtained in step 3LCalculating the spectrum matrix after baseline correctionC = A-L
(5) Calculating the average absorbance of a plurality of points near the characteristic peak of the unsaturated carbon-hydrogen bond
Figure 2012100324868100002DEST_PATH_IMAGE003
By using
Figure 890633DEST_PATH_IMAGE003
For the product obtained in step 4CNormalization is carried out to obtain a normalized spectral data matrix
Figure 619555DEST_PATH_IMAGE004
(6) To spectral data matrixGSelecting wave bands to obtain a spectrum data matrix after the wave bands are selectedWhereinzThe number of spectral data points selected for a band,Ncan reflect the content information of the methanol;
(7) utilizing the spectrum matrix obtained in the step 6 after the wave band selectionNAnd the methanol content in the standard sampleSelecting a partial least square model for modeling;
(8) a testing stage, in which the near infrared spectrum of the unknown test sample is obtained in the step 2x test Sequentially utilizing the spectrum of the test sample in the steps 3-6x test Processing to obtain analysis model inputn test
(9) Using the model established in step 7 and the model obtained in step 8n test The methanol content of the test sample was calculated.
The invention has the beneficial effects that: the method of the invention not only can rapidly and accurately measure the content of the methanol in the methanol gasoline, but also can effectively reduce the error brought to the measurement due to the large change of the gasoline components, and improve the measurement robustness. The method can be applied to daily measurement in a laboratory and can be embedded into an analytical instrument, which has important significance for rapidly detecting the methanol content of the gasoline in industrial application.
Drawings
FIG. 1 is a flow chart of a method for rapidly detecting the methanol content in methanol gasoline;
FIG. 2 is a schematic diagram of the operation of obtaining a near infrared spectrum of a sample;
FIG. 3 is a spectrum of a near infrared absorbance spectrum of 21 samples;
FIG. 4 is a graph of the near infrared spectra of 21 samples obtained by baseline removal and normalization according to the present invention;
FIG. 5 is a graph showing the predicted results of example 1;
FIG. 6 is a graph showing the predicted results of example 2;
FIG. 7 is a graph showing the predicted results of example 3.
Detailed Description
The method for detecting the content of the methanol in the methanol gasoline comprises the following steps:
1. obtaining a plurality of methanol gasoline standard samples with known methanol content, wherein the methanol content of the standard samples can cover the required detection range as much as possible;
2. the method comprises the steps of utilizing a tungsten halogen lamp as a light source, adopting a long-wave near-infrared spectrometer to measure the near-infrared spectrum of a standard sample and carrying out integer interpolation, and recording a spectrum data matrix after interpolation as
Figure 511419DEST_PATH_IMAGE001
WhereinpIs the number of samples to be tested,qcounting the number of spectral data points;
3. respectively searching minimum points in two no-signal areas of the near infrared spectrum of each standard sample, and fitting a straight line with the two minimum pointsL i ,L i Namely the base line, obtaining a matrix of the base line
Figure 9396DEST_PATH_IMAGE002
4. According to the spectrum data matrix after interpolation obtained in the step 2AAnd the spectrum base line matrix obtained in step 3LCalculating the spectrum matrix after baseline correctionC = A-L
5. Calculating the average absorbance of a plurality of points near the characteristic peak of the unsaturated carbon-hydrogen bondBy using
Figure 793998DEST_PATH_IMAGE003
For the product obtained in step 4CNormalization is carried out to obtain a normalized spectral data matrix
Figure 988088DEST_PATH_IMAGE004
6. To spectral data matrixGSelecting wave bands to obtain a spectrum data matrix after the wave bands are selected
Figure 340572DEST_PATH_IMAGE005
WhereinzThe number of spectral data points selected for a band,Ncan reflect the content information of the methanol;
7. utilizing the spectrum matrix obtained in the step 6 after the wave band selectionNAnd the methanol content in the standard sampleSelecting a partial least square model for modeling;
8. a testing stage, in which the near infrared spectrum of the unknown test sample is obtained in the step 2x test Sequentially utilizing the spectrum of the test sample in the steps 3-6x test Processing to obtain analysis model inputn test
9. Using the model established in step 7 and the model obtained in step 8n test The methanol content of the test sample was calculated.
In step 2 of the invention, the method for measuring the near infrared spectrum of the sample comprises the following steps: the method is characterized in that a tungsten halogen light source emits stable and continuous Near Infrared (NIR), the NIR is transmitted through an optical fiber, light penetrates through a transparent container with a sample and is partially absorbed and then enters an NIR spectrometer, the NIR spectrometer converts an NIR optical signal carrying sample information into an electric signal, the electric signal is converted into a digital quantity form through an A/D converter and then is output to the NIR spectrometerAnd finally, outputting corresponding information by the analysis system to obtain a required spectrogram of the sample. Here, dark spectral data when the light source is turned off is first measureddThen, reference spectrum data when the light source works normally and the sample container is air is measuredrAnd then measuring the spectral data of the sample successivelySFinally, the absorbance spectrum is calculated using the formula (1)A
; (1)
Wherein,Sis the spectral data of the sample and is,rin order to refer to the spectral data,din order to obtain dark spectral data,0<i<p, 0<j<q, pis the number of samples to be tested,qthe number of data points of the original spectrum is the same as that of the data points of the original spectrum, and the data points correspond to the nano points one by one.
The method of the present invention is further illustrated below with reference to the figures and examples.
FIG. 1 is a flow chart of a method for rapidly detecting methanol content. The method comprises the following steps:
the sample was taken from two base oil samples of known brand from a refinery, the brands being 90# and 93#, respectively. Each base oil is respectively provided with 10 methanol gasolines, the methanol contents of the base oils are respectively M0, M10, M20, M30, M40, M50, M60, M70, M80 and M90, and a pure methanol is added to make 21 samples in total.
1. The NIR light source is a tungsten halogen light source with the model number LS-1 of American Ocean Optics Inc. (Ocean Optics Inc.), the wavelength range of emitted light is 360-2500 nm, and an SMA905 joint is configured. The spectrometer is an NIRQuest model spectrometer of the company, the wavelength range of the spectrometer is 883nm to 1700nm, and the number of data points is 512. A light source LS-1 is connected into an oil sample bottle containing a sample through an optical fiber, light is transmitted to an NIR spectrometer through the optical fiber after penetrating through the sample, the NIR spectrometer converts an NIR optical signal carrying sample information into an electric signal, the electric signal is converted into a digital form through an A/D (analog/digital) and output to an analysis system, and a spectrum of the required sample can be obtained after the signal is processed by the analysis system, as shown in figure 2;
2. turning off the light source, first measuring the dark spectrumd 1×512 Then turn on the light source to measure the air spectrumr 1×512 Then respectively measuring the near infrared spectrum of 21 methanol gasoline samplesS 21×512 Finally, calculating the absorbance spectrogram of 21 methanol gasoline samples according to the formula (1)A 21×512 As in fig. 3;
3. to spectral dataA 21×512 Performing nm integral point interpolation, selecting a wavelength range of 1101 nm-1650 nm, removing data points before 1101nm and after 1650, and obtaining 550 data points of each spectrogram corresponding to the data pointsB 21×550
4. For interpolated spectral dataB 21×550 Finding the lowest point in two non-information areas 1101 nm-1131 nm and 1261 nm-1321 nm, and fitting a straight line with the two pointsL 21×550 By usingC 21×550 = B 21×550 - L 21×550 Obtaining a baseline corrected spectrumC 21×550
5. For the spectrumC 21×550 Normalization treatment is carried out, each spectrum is divided by the average value of the absorbance with the wavelength range of 1135nm to 1145nm to obtainG 21×550 Selecting spectral data with the wavelength range of 1301nm to 1650nm for modeling to obtain the spectral data as shown in FIG. 4N 21×350
6. A suitable model is selected, which is discussed here by way of example as a partial least squares model PLS.
To verify the validity of the method of the invention, the following are verified:
here, the standard error of prediction is adopted (Standard Error of Prediction,SEP) And corresponding complex phaseCoefficient of correlation (R 2 ) To measure the accuracy of the model:
; (2)
Figure 783372DEST_PATH_IMAGE008
; (3)
here, ,n p in order to predict the number of samples,0<k<n p yfor the actual value of the property of the sample,
Figure 2012100324868100002DEST_PATH_IMAGE009
to average the actual values of all sample attributes of the prediction set,y p is a sample property prediction value.
Example 1: here, 11 samples were randomly selected from the 21 samples as standard samples and the remaining 10 samples were selected as predicted samples, the number of PLS major factors was 6, and the results obtained in one experiment are shown in FIG. 5.
Example 2: a model is built by using 10 methanol gasoline samples and pure methanol samples matched with 90# hydrocarbon gasoline, total 11 samples are used as standard samples, then 10 methanol gasoline samples matched with 93# hydrocarbon gasoline are used as prediction samples, the number of PLS main factors is 6, and the obtained result is shown in FIG. 6.
Example 3: a model is built by using 10 methanol gasoline samples and pure methanol samples matched with 93# hydrocarbon gasoline, total 11 samples are used as standard samples, 10 alcohol gasoline samples matched with 90# hydrocarbon gasoline are used as prediction samples, the number of PLS main factors is 6, and the result is shown in FIG. 7.
Table 1 shows the results of inventive examples 1-3, which demonstrate the high prediction accuracy and robustness of the inventive method.
TABLE 1 Rapid measurement of methanol content in full Range
Inspection method R2 SEP
Example 1: 11 random samples were used as standard samples 0.9990 0.6560
Example 2: the 90# prepared 10 sample plus pure methanol sample is taken as a standard sample 0.9990 0.5867
Example 3: 93# 10 sample + pure methanol sample as standard sample 0.9994 0.6749

Claims (1)

1. A method for detecting the content of methanol in methanol gasoline is characterized by comprising the following steps:
(1) obtaining a plurality of methanol gasoline standard samples with known methanol content, wherein the methanol content of the standard samples can cover the required detection range as much as possible;
(2) the method comprises the steps of utilizing a tungsten halogen lamp as a light source, adopting a long-wave near-infrared spectrometer to measure the near-infrared spectrum of a standard sample and carrying out integer interpolation, and recording a spectrum data matrix after interpolation as
Figure 2012100324868100001DEST_PATH_IMAGE001
WhereinpIs the number of samples to be tested,qcounting the number of spectral data points;
(3) respectively searching minimum points in two no-signal areas of the near infrared spectrum of each standard sample, and fitting a straight line with the two minimum pointsL i ,L i Namely the base line, obtaining a matrix of the base line
Figure 247725DEST_PATH_IMAGE002
(4) According to the spectrum data matrix after interpolation obtained in the step 2AAnd the spectrum base line matrix obtained in step 3LCalculating the spectrum matrix after baseline correctionC = A-L
(5) Calculating the average absorbance of a plurality of points near the characteristic peak of the unsaturated carbon-hydrogen bond
Figure 2012100324868100001DEST_PATH_IMAGE003
By using
Figure 551667DEST_PATH_IMAGE003
For the product obtained in step 4CNormalization is carried out to obtain a normalized spectral data matrix
(6) To spectral data matrixGSelecting wave bands to obtain a spectrum data matrix after the wave bands are selected
Figure 2012100324868100001DEST_PATH_IMAGE005
WhereinzThe number of spectral data points selected for a band,Ncan reflect the content information of the methanol;
(7) utilizing the spectrum matrix obtained in the step 6 after the wave band selectionNAnd the methanol content in the standard sampleSelectingModeling by a partial least square model;
(8) a testing stage, in which the near infrared spectrum of the unknown test sample is obtained in the step 2x test Sequentially utilizing the spectrum of the test sample in the steps 3-6x test Processing to obtain analysis model inputn test
(9) Using the model established in step 7 and the model obtained in step 8n test The methanol content of the test sample was calculated.
CN2012100324868A 2012-02-14 2012-02-14 Method for measuring methanol content in methanol gasoline Pending CN102590132A (en)

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CN102890067A (en) * 2012-09-17 2013-01-23 江苏惠通集团有限责任公司 Methanol gasoline quick detector based on near infrared rays
CN103257117A (en) * 2013-02-25 2013-08-21 中国科学院安徽光学精密机械研究所 Rapid gasoline component measurement system
CN103760131A (en) * 2014-01-17 2014-04-30 华东理工大学 Real-time gasoline product attribute prediction method based on near infrared spectrum detection
CN107037000A (en) * 2016-11-23 2017-08-11 华东交通大学 A kind of detection method of environmental-protective alcohol diesel oil
CN109374565A (en) * 2018-09-30 2019-02-22 华东交通大学 A kind of methanol gasoline ethanol petrol differentiates and content assaying method
CN109632700A (en) * 2019-01-03 2019-04-16 北京化工大学 Methanol content rapid detection method and device in a kind of biodiesel synthesis process based on near-infrared
CN111198165A (en) * 2020-01-14 2020-05-26 重庆理工大学 Method for measuring water quality parameters based on spectral data standardization
CN111309958A (en) * 2020-03-30 2020-06-19 四川长虹电器股份有限公司 Spectrum reconstruction method based on interpolation operation

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102890067A (en) * 2012-09-17 2013-01-23 江苏惠通集团有限责任公司 Methanol gasoline quick detector based on near infrared rays
CN103257117A (en) * 2013-02-25 2013-08-21 中国科学院安徽光学精密机械研究所 Rapid gasoline component measurement system
CN103760131A (en) * 2014-01-17 2014-04-30 华东理工大学 Real-time gasoline product attribute prediction method based on near infrared spectrum detection
CN107037000A (en) * 2016-11-23 2017-08-11 华东交通大学 A kind of detection method of environmental-protective alcohol diesel oil
CN109374565A (en) * 2018-09-30 2019-02-22 华东交通大学 A kind of methanol gasoline ethanol petrol differentiates and content assaying method
CN109632700A (en) * 2019-01-03 2019-04-16 北京化工大学 Methanol content rapid detection method and device in a kind of biodiesel synthesis process based on near-infrared
CN111198165A (en) * 2020-01-14 2020-05-26 重庆理工大学 Method for measuring water quality parameters based on spectral data standardization
CN111309958A (en) * 2020-03-30 2020-06-19 四川长虹电器股份有限公司 Spectrum reconstruction method based on interpolation operation

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Application publication date: 20120718