CN112129729A - Method for rapidly analyzing content of hydrocarbons and dimethyl ether in liquefied petroleum gas - Google Patents
Method for rapidly analyzing content of hydrocarbons and dimethyl ether in liquefied petroleum gas Download PDFInfo
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Abstract
The invention relates to the technical field of a method for rapidly detecting components of liquefied petroleum gas, in particular to a method for rapidly analyzing the contents of hydrocarbons and dimethyl ether in the liquefied petroleum gas, which comprises the following specific operation steps: the method comprises the steps of collecting a sample, measuring the components of the sample by using a standard method, building a detection system, carrying out spectrum scanning on the sample by using the detection system to obtain and process spectrum data, establishing a mathematical model according to the spectrum data and the component data, and realizing rapid analysis on the position sample by using the mathematical model to obtain a rapid detection report. The invention can realize the rapid, accurate and safe detection and analysis of the hydrocarbon composition of C3 and C4 and dimethyl ether of the liquefied petroleum gas, solves the problems of complex chromatographic analysis operation and long detection time, can obtain the detection result within minutes, can be applied in laboratories, can realize on-site or on-line analysis, and can be used for quality monitoring in the field of liquefied petroleum gas circulation and in the production process.
Description
Technical Field
The invention relates to the technical field of a method for quickly detecting components of liquefied petroleum gas, in particular to a method for quickly analyzing the contents of hydrocarbons and dimethyl ether in the liquefied petroleum gas.
Background
Liquefied petroleum gas is one of petroleum products, and is colorless and volatile gas obtained by pressurizing, cooling and liquefying refinery gas or natural gas (including oilfield associated gas). The liquefied petroleum gas obtained from refinery gas contains propane, propylene, butane and butylene as main components and a small amount of pentane and pentene, so that the C3 and C4 hydrocarbons constitute the main components of the liquefied petroleum gas, the proportion of the C3 and C4 hydrocarbons affects the product quality of the liquefied petroleum gas, dimethyl ether is also called dimethyl ether (DME for short) which is a colorless gas or compressed liquid at normal pressure, has light ether fragrance, is easy to compress, store, high in combustion efficiency and low in pollution, can replace coal gas and liquefied petroleum gas as civil fuel, but as the dimethyl ether has strong corrosivity to plastic substances, a civil liquefied petroleum gas steel cylinder used on the market is not suitable for filling dimethyl ether, the national quality inspection bureau clearly shows that the liquefied petroleum gas steel cylinder is filled after the dimethyl ether is strictly forbidden to be mixed into the civil liquefied petroleum gas, but the market price of the dimethyl ether is much cheaper than the liquefied petroleum gas, and the dimethyl ether mixed into the liquefied petroleum gas has great space profit, many gas stations go away to risk regardless of the life safety of people, and in order to protect the life and property safety of people and master the quality condition of liquefied petroleum gas, the content of dimethyl ether in the liquefied petroleum gas needs to be detected;
at present, new research achievements are continuously provided in the technical field of near infrared spectrum analysis at home and abroad, the achievements play an important role in industrial production of food, medicine, tobacco and the like, the near infrared spectrum analysis technology is a modern high-tech analysis and test technology, is an analysis method for analyzing substance information by using Near Infrared (NIR) photophoresis, is mainly used for qualitative and quantitative analysis of organic matters, and has the biggest characteristics that: the method has the advantages of no damage to the sample, simple and convenient operation and rapid analysis, the measurement signal can be transmitted and analyzed in a long distance, particularly, the method is combined with a computer technology and an optical fiber technology, and the sample can be directly analyzed by adopting an NIR transmission optical detection method;
the existing national standard GB/T32492-2016 gas chromatography for the content of dimethyl ether in liquefied petroleum gas and the industry standard NB/SH/T0230-2019 gas chromatography for the composition of liquefied petroleum gas all adopt gas chromatography to analyze the hydrocarbon composition and the content of dimethyl ether of the liquefied petroleum gas, have the disadvantages of complex operation, high analysis cost and long detection time, and cannot realize rapid detection. Accordingly, one skilled in the art provides a method for rapidly analyzing the contents of hydrocarbons and dimethyl ether in liquefied petroleum gas to solve the problems set forth in the above background art.
Disclosure of Invention
The invention aims to provide a method for rapidly analyzing the contents of hydrocarbons and dimethyl ether in liquefied petroleum gas, so as to solve the problems of complex chromatographic analysis operation and long detection time in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a method for rapidly analyzing the content of hydrocarbons and dimethyl ether in liquefied petroleum gas comprises the following specific operation steps:
s1, collecting a liquefied petroleum gas sample;
s2, utilizing an industry standard method to carry out C3 and C4 hydrocarbon composition and dimethyl ether component determination on the collected sample;
s3, selecting Fourier transform near infrared spectrometer, gas flow cell, optical fiber, computer, liquefied gas pipeline, valve, etc
Building a detection system;
s4, performing spectrum scanning on the collected sample by using the system to obtain spectrum data, and processing the obtained spectrum data;
s5, correlating the spectrum data of each sample with the C3 and C4 hydrocarbon composition and dimethyl ether composition data in one-to-one correspondence
Establishing a mathematical model through chemometrics software;
and S6, rapidly analyzing the unknown sample by using the established mathematical model, and printing a rapid inspection report on site after the analysis is finished.
As a further scheme of the invention: the samples collected in S1 should be representative, and the range of chemical and physical properties of the samples in the calibration set must cover all possible ranges of the samples to be tested, and the chemical data should be distributed in a gradient as much as possible, and the calibration set is generally composed of at least 50 samples.
As a still further scheme of the invention: the standard method in S2 refers to the industry standard NB/SH/T0230-2019 liquefied petroleum gas composition determination gas chromatography.
As a still further scheme of the invention: and the collected spectral data in the S4 is obtained by introducing gaseous liquefied petroleum gas into a gas flow cell through a pipeline, introducing an exhaust pipe of the flow cell into water, and when the exhaust is finished, keeping the sample in the flow cell at normal pressure by virtue of the sealing effect of the water and the principle of a communicating vessel.
As a still further scheme of the invention: the spectral data processing in S4 is to perform spectral processing on the original transmission spectrum obtained by scanning in chemometrics software, and first or second derivative processing is performed to eliminate the influence of noise and baseline drift.
As a still further scheme of the invention: the S5 specifically refers to correlating the processed spectral data with the standard method analysis data in the NIRSA chemometrics software, corresponding one to one, and establishing a mathematical model by using a partial least square method and a cross-validation method and using the metrology analysis software;
using complex correlation coefficient (R2), internal cross validation mean square error (RMSECV), predicted absolute deviation
To examine the performance and the prediction effect of the established model, the calculation formula is as follows:
wherein, CiIs a value measured by a standard method,
is the near-infrared predicted value of the infrared ray,
is the average value, n is the number of samples in the calibration set, and m is the number of samples in the prediction set.
As a still further scheme of the invention: in the step S6, the unknown sample analysis is to call the established calibration model to quickly predict the near infrared spectrum of the scanned sample to be detected, so as to obtain an analysis result, and the quick detection report is to quickly issue a detection report as a law enforcement basis.
Compared with the prior art, the invention has the beneficial effects that:
1. the established new analysis method has the characteristics of simple and convenient operation, rapid analysis and the like, solves the problems of chemical pretreatment, complex operation and the like of a sample in the traditional quantitative analysis, greatly improves the working efficiency, reduces the running cost, and shortens the time of half an hour of the traditional analysis to two minutes;
2. the analysis method can be applied in a laboratory, can realize field or on-line analysis, can be used for quality monitoring in the field of liquefied petroleum gas circulation and in the production process, plays an important role in controlling the quality of the liquefied petroleum gas, and improves the analysis and detection level of the liquefied petroleum gas;
3. the mathematical model established by the method adopts a second-order differential processing algorithm, and the model has very good universality and can be universally used among different instruments of the same model, which is very favorable for the rapid popularization of the method;
4. the built liquefied gas quick detection system can realize vehicle-mounted application, mainly because the core equipment adopts a high-speed dynamic collimation design, has good shock resistance and can stably work in a vehicle running environment;
5. the self-made gas flow cell is made of all-copper materials, corrosion resistance is good, the light path collimating lens of the gas flow cell adopts ultraviolet fused quartz, light loss is little, and the liquefied petroleum gas information acquisition is facilitated.
Drawings
FIG. 1 is a schematic diagram of a liquefied gas analysis system according to the method of the present invention;
FIG. 2 is a graph of the original absorption spectrum of a liquefied gas;
FIG. 3 is a second order differential spectroscopy plot;
FIG. 4 is a model correlation diagram for C3, C4 hydrocarbons;
FIG. 5 is a model correlation diagram of dimethyl ether.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 to 5, in an embodiment of the present invention, a method for rapidly analyzing the content of hydrocarbons and dimethyl ether in liquefied petroleum gas includes the following specific operation steps:
s1, collecting samples of liquefied petroleum gas, wherein the collected samples are representative, the chemical and physical property ranges of the samples in the correction set must cover all possible ranges of the samples to be detected, and the chemical data are required to be distributed in a certain gradient as much as possible, and the general correction set at least comprises more than 50 samples;
s2, measuring the composition of C3 and C4 hydrocarbons and the composition of dimethyl ether of the collected sample by using an industrial standard method, wherein the standard method is 'NB/SH/T0230-2019 liquefied petroleum gas composition measuring gas chromatography' which is an industrial standard;
s3, selecting a Fourier transform near-infrared spectrometer, a gas flow cell, an optical fiber, a computer, a liquefied gas pipeline, a valve and the like to build a detection system, wherein the Fourier transform near-infrared spectrometer is connected with an external computer;
s4, performing spectrum scanning on the collected sample by using the system to obtain spectrum data, wherein the spectrum data is obtained by introducing gaseous liquefied petroleum gas into a gas flow cell through a pipeline, introducing a flow cell exhaust pipe into water, and when the exhaust is finished, keeping the sample in the flow cell at normal pressure by virtue of the sealing effect of the water and the principle of a communicating vessel;
the obtained spectral data are processed, and the specific steps are as follows: performing spectrum processing on an original transmission spectrum obtained by scanning in chemometrics software, and performing first-order or second-order derivative processing to eliminate the influence of noise and baseline drift;
s5, carrying out one-to-one correspondence correlation on the spectrum data of each sample, the hydrocarbon composition of C3 and C4 and the dimethyl ether composition data, and establishing a mathematical model through chemometrics software;
the method specifically comprises the following steps: in the NIRSA chemometrics software, the processed spectral data and the standard method analysis data are associated and correspond to each other one by one, and a mathematical model is established by using the metrology analysis software by adopting a partial least square method and a cross-validation method;
using complex correlation coefficient (R2), internal cross validation mean square error (RMSECV), predicted absolute deviation
To examine the performance and the prediction effect of the established model, the calculation formula is as follows:
wherein, CiIs a value measured by a standard method,
is the near-infrared predicted value of the infrared ray,
is the average value, n is the number of samples in the correction set, and m is the number of samples in the prediction set;
s6, the established mathematical model is utilized to realize the rapid analysis of the unknown sample, and the method specifically comprises the following steps: calling the established correction model to quickly predict the near infrared spectrum of the scanned sample to be detected to obtain an analysis result;
and after the analysis is finished, rapidly issuing a detection report as a law enforcement basis site.
Example one
The embodiment further illustrates the detection of the invention, but is not limited thereto, and a fast detection method for chemical components of liquefied petroleum gas is established by adopting a fourier transform near-infrared spectrometer technology, and the method can directly realize vehicle-mounted application and comprises the following steps:
70 liquefied petroleum gas samples are collected to serve as correction set samples for establishing a model, the correction set samples are representative, and chemical data have certain gradient distribution;
② the C3 and C4 hydrocarbon compositions and dimethyl ether content are measured by adopting the industry standard 'NB/SH/T0230-2019 liquefied petroleum gas composition measuring gas chromatography';
thirdly, a detection system is built by the Fourier transform near infrared spectrometer, the gas flow cell, the optical fiber, the computer, the liquefied gas pipeline, the valve and the like, as shown in figure 1;
the specific operation is as follows: opening two valves on the gas flow cell, introducing gaseous liquefied gas into a pipeline, exhausting for 30 seconds, then closing a left valve, opening a right valve, automatically balancing a sample in the gas flow cell to a normal pressure state when the exhaust pipeline is in water, collecting spectral data of the sample in the gas flow cell by using a Fourier transform near-infrared spectrometer, and collecting the spectral data in a transmission mode;
the spectral parameters used were: spectral range of 4500-8600cm-1Average order of 64, resolution 16cm-1；
Carrying out spectrum processing on the original absorption spectrogram obtained by scanning (shown in figure 2), and carrying out second-order differential processing to eliminate the influence of noise and baseline drift (shown in figure 3);
in the NIRSA chemometrics software, correlating the processed spectral data with standard test data in a one-to-one correspondence manner, and establishing a mathematical model by adopting a partial least squares method (PLS1) and a cross-validation method (cross-validation);
using complex correlation coefficients (R)2) Internal cross-validation mean square error (RMSECV), predicted absolute deviation
To examine the performance and the prediction effect of the established model, the calculation formula is as follows:
wherein, CiIs a value measured by a standard method,
is the near-infrared predicted value of the infrared ray,
is the average value, n is the number of samples in the correction set, and m is the number of samples in the prediction set;
the results of the investigation model can be applied, the model is stored in the computer as shown in the relevant figures of fig. 4 and 5, and the following table is the mathematical model parameters:
| model (model) | Correlation coefficient | Determining coefficients | RMSECV |
| C3, C4 hydrocarbons | 0.9787 | 0.9577 | 1.0000 |
| Dimethyl ether | 0.9819 | 0.9640 | 1.0381 |
Sixthly, calling the established correction model to predict the near infrared spectrum of the 7 verification set samples to obtain an analysis result; as shown in the following table, the predicted value errors of all mathematical models are within the allowable error range of the industry standard NB/SH/T0230-2019):
in conclusion, a Fourier transform near infrared spectrometer, a self-made gas flow cell, a computer and other related equipment are utilized to combine near infrared spectrum with liquefied petroleum gas information, the near infrared spectrometer is utilized to collect near infrared spectrum data of the liquefied petroleum gas, related conventional chemical analysis instruments are utilized to measure C3 and C4 hydrocarbon composition and dimethyl ether chemical data in the liquefied petroleum gas, based on a functional relation formed between the two, the spectral data and the composition data are associated through a mathematical method, and a Partial Least Squares (PLS) method is adopted to establish a mathematical model of the hydrocarbon composition and the dimethyl ether content; according to the quantitative model, rapid quantitative analysis can be realized, and on the basis of the dynamic collimation technology of the Fourier transform near-infrared spectrometer, the dynamic collimation system can be applied to a laboratory, can also realize vehicle-mounted detection of a detection system, realizes mobile quick detection of liquefied petroleum gas, realizes quick impact detection of each gas station, and can effectively frighten and purify the market environment.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (7)
1. A method for rapidly analyzing the content of hydrocarbons and dimethyl ether in liquefied petroleum gas is characterized by comprising the following specific operation steps:
s1, collecting a liquefied petroleum gas sample;
s2, utilizing an industry standard method to carry out C3 and C4 hydrocarbon composition and dimethyl ether component determination on the collected sample;
s3, selecting a Fourier transform near-infrared spectrometer, a gas flow cell, an optical fiber, a computer, a liquefied gas pipeline, a valve and the like to build a detection system;
s4, performing spectrum scanning on the collected sample by using the system to obtain spectrum data, and processing the obtained spectrum data;
s5, carrying out one-to-one correspondence correlation on the spectrum data of each sample, the hydrocarbon composition of C3 and C4 and the dimethyl ether composition data, and establishing a mathematical model through chemometrics software;
and S6, rapidly analyzing the unknown sample by using the established mathematical model, and printing a rapid inspection report on site after the analysis is finished.
2. The method as claimed in claim 1, wherein the sample collected in S1 is representative, the range of chemical and physical properties of the sample in the calibration set must cover all possible ranges of the sample to be tested, and the chemical data is required to be distributed in a gradient as much as possible, and the calibration set is generally composed of at least 50 samples.
3. The method for rapidly analyzing the content of the hydrocarbons and the dimethyl ether in the liquefied petroleum gas as claimed in claim 1, wherein the standard method in S2 refers to the industry standard "NB/SH/T0230-2019 liquefied petroleum gas composition determination gas chromatography".
4. The method as claimed in claim 1, wherein the step of collecting the spectral data in S4 comprises introducing the liquefied petroleum gas into a gas flow cell through a pipeline, introducing an exhaust pipe of the flow cell into water, and maintaining the sample in the flow cell at normal pressure by the sealing effect of water and the principle of a communicating vessel when the exhaust is finished.
5. The method as claimed in claim 1, wherein the processing of the spectral data in S4 is to perform spectral processing on the original transmission spectrum obtained by scanning in the chemometrics software, and first perform derivative processing or second derivative processing to eliminate the influence of noise and baseline shift.
6. The method according to claim 1, wherein the step S5 is performed by associating the processed spectrum data with the standard method analysis data in the NIRSA chemometrics software, and establishing a mathematical model by using a partial least squares method, a cross-validation method, and a metrology analysis software, wherein the mathematical model is a one-to-one correspondence method;
and (3) observing the performance and the prediction effect of the established model by using the complex correlation coefficient (R2), the internal cross validation mean square error (RMSECV) and the prediction absolute deviation (d), wherein the calculation formula is as follows:
wherein, CiIs a value measured by a standard method,
is the near-infrared predicted value of the infrared ray,
is the average value, n is the number of samples in the calibration set, and m is the number of samples in the prediction set.
7. The method as claimed in claim 1, wherein the analysis of the unknown sample in S6 is to call the established calibration model to rapidly predict the near infrared spectrum of the scanned sample to be tested, so as to obtain an analysis result, and the rapid inspection report is a report that can be rapidly issued as a law enforcement basis.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1283791A (en) * | 1999-07-06 | 2001-02-14 | 中国石油化工集团公司 | Method for measuring contents of components in oil residue |
| CN1979132A (en) * | 2006-11-20 | 2007-06-13 | 扬子石油化工股份有限公司 | Method for detecting hydrogenated tail-oil cyclanes and arene composition using near infrared spectrum |
| 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 |
| CN110987858A (en) * | 2019-11-30 | 2020-04-10 | 江苏万标检测有限公司 | Method for rapidly detecting oil product by using neural network data model |
| CN111650324A (en) * | 2019-03-04 | 2020-09-11 | 内蒙古伊泰煤基新材料研究院有限公司 | Online detection method for hydrocarbon content |
-
2020
- 2020-10-22 CN CN202011135526.2A patent/CN112129729A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1283791A (en) * | 1999-07-06 | 2001-02-14 | 中国石油化工集团公司 | Method for measuring contents of components in oil residue |
| CN1979132A (en) * | 2006-11-20 | 2007-06-13 | 扬子石油化工股份有限公司 | Method for detecting hydrogenated tail-oil cyclanes and arene composition using near infrared spectrum |
| 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 |
| CN111650324A (en) * | 2019-03-04 | 2020-09-11 | 内蒙古伊泰煤基新材料研究院有限公司 | Online detection method for hydrocarbon content |
| CN110987858A (en) * | 2019-11-30 | 2020-04-10 | 江苏万标检测有限公司 | Method for rapidly detecting oil product by using neural network data model |
Non-Patent Citations (2)
| Title |
|---|
| 张凤利;: "傅立叶红外光谱法快速测定液化石油气中二甲醚的含量", 低温与特气, no. 03, pages 31 - 34 * |
| 朱志强;袁洪福;胡爱琴;宋春风;李效玉;吴明清;: "液化石油气中二甲醚含量快速测定方法研究", 光谱学与光谱分析, no. 04, pages 74 - 76 * |
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