CN115144490B - Identification method of natural ester insulating oil genus - Google Patents
Identification method of natural ester insulating oil genus Download PDFInfo
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Abstract
The invention belongs to the technical field of insulating oil detection, and particularly relates to a method for identifying a natural ester insulating oil group. The invention utilizes an adsorption column to adsorb the additive in the natural ester insulating oil sample, separates the additive and the natural ester insulating oil from the natural ester insulating oil sample, quantitatively and qualitatively analyzes the type and the content of fatty acid methyl ester in the natural ester insulating oil through gas chromatography, and quantitatively and qualitatively analyzes the composition parameters of fatty acid components in the natural ester insulating oil sample through gas chromatography after methyl esterification treatment of the natural ester insulating oil. And then, at least one of the content of the additive, the composition parameters of the fatty acid methyl ester component and the composition parameters of the fatty acid component is used as a group of characteristic data, the characteristic data is input into an insulating oil genus evaluation model to obtain an output result of the insulating oil genus evaluation model, so that the purpose of identifying the natural ester insulating oil genus is realized, and the accuracy of the basic genus identification is high.
Description
Technical Field
The invention belongs to the technical field of insulating oil detection, and relates to a method for identifying a natural ester insulating oil.
Background
In recent years, the application of the natural ester insulating oil is more and more wide, the natural ester insulating oil has good biodegradability and fireproof performance, and the natural ester insulating oil can be applied to high-overload power equipment by being matched with high-heat-stability paper. As an important insulating medium for power transformers, the natural ester insulating oils widely used at present are mainly soybean-based and rapeseed-based. Wherein soy-based natural ester insulating oil has been used in 420kV transformers, whereas rapeseed-based natural ester insulating oil has been used in 220kV transformers. In large transformers, the quality of the natural ester insulating oil is critical to the safe and stable operation of the equipment. The DL/T1811-2018 'the guidance rules for the selection of natural ester insulating oil for power transformers' has indexes of kinematic viscosity, moisture, pour point, density, breakdown voltage, dielectric loss factor, acid value, corrosive sulfur, total additive content, oxidation stability, fire point, flash point and biodegradability for the natural ester insulating oil.
The prior art generally only aims at the electrical property, physical and chemical properties and health properties of the natural ester insulating oil, but at present, no method for accurately judging the base of the natural ester insulating oil exists, which causes great inconvenience to equipment maintainers and oil quality acceptance personnel, and cannot accurately judge the authenticity of the oil quality.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for identifying the natural ester insulating oil, which can accurately identify the base of the natural ester insulating oil, has high identification accuracy and can accurately identify the authenticity of the oil.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides a method for identifying the genus natural ester insulator, comprising the steps of:
(1) Mixing and diluting a natural ester insulating oil sample with an organic solvent to obtain a sample diluent, passing the sample diluent through an adsorption column, eluting to obtain a sample liquid containing the natural ester insulating oil and an eluent containing an additive, diluting the sample liquid containing the natural ester insulating oil to obtain a sample liquid to be tested, drying the eluent containing the additive to obtain a solid additive, weighing and calculating to obtain the content of the additive in the natural ester insulating oil sample;
(2) Measuring the sample liquid to be detected obtained in the step (1), carrying out qualitative and quantitative analysis and determination on the sample liquid to be detected by utilizing a gas chromatograph, and calculating to obtain the composition parameters of the fatty acid methyl ester component in the natural ester insulating oil sample according to qualitative and quantitative analysis results;
(3) Measuring the sample liquid to be detected obtained in the step (1), diluting the sample liquid to be detected to obtain a sample diluent to be detected, performing methyl esterification treatment on the sample diluent to be detected to obtain a methyl esterification sample liquid, performing qualitative and quantitative analysis and determination on the methyl esterification sample liquid by using a gas chromatograph, calculating the content of each fatty acid methyl ester in the methyl esterification sample liquid according to qualitative and quantitative analysis results, and further calculating the composition parameters of fatty acid components in the natural ester insulating oil sample;
(4) And inputting the characteristic data into an insulating oil genus evaluation model by taking at least one of the content of the additive, the composition parameters of the fatty acid methyl ester component and the composition parameters of the fatty acid component as the characteristic data of the natural ester insulating oil, so as to obtain an output result of the insulating oil genus evaluation model.
In the invention, the additive in the natural ester insulating oil sample is adsorbed by utilizing an adsorption column, so that the additive and the natural ester insulating oil are separated from the natural ester insulating oil sample, the type and the content of fatty acid methyl ester in the natural ester insulating oil are obtained through quantitative and qualitative analysis of gas chromatography, and the composition parameters of fatty acid components in the natural ester insulating oil sample are obtained through quantitative and qualitative analysis of gas chromatography after the methyl esterification treatment of the natural ester insulating oil. And then taking at least one of the content of the additive, the composition parameters of the fatty acid methyl ester component and the composition parameters of the fatty acid component as characteristic data, and inputting the characteristic data into an insulating oil genus evaluation model to obtain an output result of the insulating oil genus evaluation model, thereby realizing the purpose of identifying the basic genus of the natural ester insulating oil.
Preferably, the step (1) specifically includes: mixing and diluting a natural ester insulating oil sample with an organic solvent to obtain a sample diluent, passing the sample diluent through an adsorption column, eluting with a first eluent, adsorbing additives in the natural ester insulating oil by using the adsorption column, collecting effluent and eluent, combining the effluent and the eluent, diluting with the organic solvent to obtain a sample liquid to be tested, drying the eluted adsorption column, eluting the dried adsorption column with a second eluent, collecting the eluent containing the additives, drying the eluent containing the additives to obtain solid additives, weighing, and calculating to obtain the content of the additives in the natural ester insulating oil sample.
Further preferably, the organic solvent includes at least one of isooctane, isopentane, isobutane, and isohexane.
Further preferably, the adsorption column is filled with iron-based modified activated carbon, metal organic framework material and silica gel in sequence from bottom to top, and the mass ratio of the iron-based modified activated carbon, the metal organic framework material and the silica gel is the iron-based modified activated carbon: metal organic framework material: silica gel = (1-3): (0.5-2): (1-3).
Still more preferably, the metal-organic framework material is a Cu-BTC metal-organic framework material.
Further preferably, the first eluent comprises at least one of isooctane, isopentane, isobutane, and isohexane, and the second eluent comprises at least one of methanol, ethanol, and propanol.
Further preferably, the elution flow rate of the first eluent is 1 to 5 drops/s, and the elution flow rate of the second eluent is 1 to 5 drops/s.
In the invention, the adsorption column is composed of iron-based modified active carbon, metal organic framework material and silica gel, when a natural ester insulating oil sample flows through the packing layer, the packing layer can specifically adsorb additives (such as antioxidant, metal passivator, anticoagulant and the like) in the natural ester insulating oil sample, the adsorption column with the additives is dried to remove solvent, then the adsorption column is eluted by adopting a second eluent, the additives are eluted, eluent of the additives is collected, the eluent of the additives is rotationally evaporated and dried, and after methanol solvent is removed, solid additives are obtained, and the quality of the additives can be obtained by weighing. The selection of the organic solvent, the first eluent and the second eluent and the composition of the filler have important influence on the separation effect of the natural ester insulating oil and the additive. The research shows that the lack of any one of the iron-based modified activated carbon, the metal organic framework material and the silica gel in the adsorption column can influence the removal effect of the additive. The mass ratio of the iron-based modified activated carbon to the metal organic framework material to the silica gel is preferably the iron-based modified activated carbon: metal organic framework material: silica gel = 2:1:2, the organic solvent and the first eluent are preferably isooctane, the second eluent is preferably methanol, under the condition, the natural ester insulating oil with high purity is separated from the natural ester insulating oil sample through adsorption elution, and the removal rate of the additive can reach 97.6%.
Preferably, before the step (2) and the step (3), the method further comprises: preparing standard substances of different fatty acid methyl esters into single standard solutions and mixed standard solutions with different concentration gradients, analyzing and measuring the single standard solutions by using a gas chromatograph to obtain retention time of each standard substance, analyzing and measuring the mixed standard solutions by using the gas chromatograph to obtain a gas chromatogram of the standard substances, taking the characteristic peak area value of the standard substances in the gas chromatogram as an ordinate, taking the concentration of the standard substances in the mixed standard solutions as an abscissa, and drawing a standard curve.
Further preferably, the fatty acid standard substance comprises at least one of lauric acid, myristic acid, palmitic acid, palmitoleic acid, margaric acid, stearic acid, oleic acid, linoleic acid, linolenic acid, arachic acid, behenic acid, erucic acid, behenic acid, lignoceric acid, and lignoceric acid.
Preferably, in the step (2) and the step (3), the working parameters of the gas chromatograph are: chromatographic column: HP-5MS chromatographic column, column length 30m, internal diameter 0.25mm; the carrier gas is nitrogen, and the flow rate is 1mL/min; the column Wen Xiangwen control procedure is: the initial temperature is 100 ℃, the temperature is increased to 280 ℃ at the heating rate of 2 ℃/min, and the temperature is kept for 5min; the sample loading was 1.0. Mu.L.
Preferably, the step (2) specifically includes: measuring the sample liquid to be detected obtained in the step (1), carrying out qualitative and quantitative analysis and determination on the sample liquid to be detected by utilizing a gas chromatograph, carrying out qualitative determination according to the retention time of a standard substance, quantifying according to a standard curve, and calculating according to qualitative and quantitative results to obtain the mass concentration of each fatty acid methyl ester in the sample liquid to be detected;
the mass of the fatty acid methyl ester component in the natural ester insulating oil sample is calculated according to the following formula:
M 2 ＝V 0 ×∑(C 14:0 +C 16:0 +…+C 24:1 ) Wherein, sigma (C 14:0 +C 16:0 +…+C 24:1 ) Representing the sum of the mass concentration of each fatty acid methyl ester, namely the total mass concentration of the fatty acid methyl esters in the sample liquid to be tested, V 0 Representing the total volume of the sample liquid to be tested;
the mass percentage content of fatty acid methyl ester components in the natural ester insulating oil sample is calculated according to the following formula:
W 2 ＝M 2 /M 0 x 100%, where M 2 Represents the mass, M, of the fatty acid methyl ester component in the natural ester insulating oil sample 0 Indicating the total mass of the natural ester insulating oil sample.
Preferably, the step (3) of performing the methyl esterification treatment on the sample diluent to be tested specifically includes: and (3) performing methyl esterification reaction on the sample diluent to be detected and a methanol solution of potassium hydroxide, adding sodium bisulfate to perform neutralization reaction, and centrifuging to separate out supernatant to obtain methyl esterification sample liquid.
Further preferably, the mass concentration of potassium hydroxide in the methanol solution of potassium hydroxide is 1 to 5%.
Further preferably, the volume ratio of the methanol solution of potassium hydroxide to the sample diluent to be measured is (1-5): 100.
Further preferably, the temperature of the methyl esterification reaction is 40-60 ℃ and the time is 20-40 min.
Further preferably, the ratio of the mass of the sodium bisulfate to the volume of the dilution of the sample to be tested is 1:5g/mL.
Preferably, the composition parameters of the fatty acid component include at least one of the mass percent of saturated fatty acids, the mass percent of monounsaturated fatty acids, the mass percent of polyunsaturated fatty acids, the mass ratio of polyunsaturated fatty acids to saturated fatty acids, and the mass ratio of unsaturated fatty acids to saturated fatty acids.
Preferably, the step (3) specifically includes:
measuring a sample liquid to be measured, diluting the sample liquid with an organic solvent to obtain a sample diluent, carrying out methylation treatment on the sample diluent to obtain a methylated sample liquid, carrying out analysis and measurement on the methyl esterification sample liquid by using a gas chromatograph, carrying out qualitative analysis according to the retention time of a standard substance, quantifying according to a standard curve, analyzing according to qualitative and quantitative analysis results to obtain the mass concentration of each fatty acid methyl ester in the methyl esterification sample liquid, and calculating according to the following formula to obtain the mass concentration of each fatty acid in the sample diluent:
C acid(s) ＝C Methyl ester ×M Acid(s) /M Methyl ester Wherein M is Methyl ester Represents the molecular weight of fatty acid methyl ester, M Acid(s) Represents the molecular weight of the fatty acid corresponding to the fatty acid methyl ester, C Methyl ester Represents the mass concentration of fatty acid methyl ester;
the mass percentage content of each fatty acid in the sample liquid to be detected is calculated according to the following formula:
C′ acid(s) ＝C Acid(s) ×V 2 /V 1 Wherein V is 1 Representing the volume of the measured sample liquid, V 2 Representing the volume of the sample diluent;
the mass percentage content of each fatty acid in the fatty acid component of the natural ester insulating oil sample is calculated according to the following formula:
W′ acid(s) ＝V 0 ×C′ Acid(s) /(M 0 -M 1 -M 2 ) X 100%, where V 0 Represents the total volume of the sample liquid to be measured, M 0 Represents the total mass of the natural ester insulating oil sample, M 1 Represents the mass of the additive in the natural ester insulating oil sample, M 2 Indicating the mass of fatty acid methyl ester component in the natural ester insulating oil sample.
Further preferably, the step (3) further includes:
and summing according to the calculated mass percent of each fatty acid to obtain the mass percent of saturated fatty acid, the mass percent of monounsaturated fatty acid and the mass percent of polyunsaturated fatty acid, and further calculating to obtain the mass ratio of polyunsaturated fatty acid to saturated fatty acid and the mass ratio of unsaturated fatty acid to saturated fatty acid.
Preferably, the insulating oil genus evaluation model is characteristic data of a base of the natural ester insulating oil and a plurality of groups of natural ester insulating oil, and the characteristic data of the natural ester insulating oil and a correlation model of the natural ester insulating oil genus are established through a convolutional neural network.
Preferably, the step (4) further includes: and distinguishing the authenticity of the natural ester insulating oil according to the output result.
Preferably, the natural ester insulating oil belongs to the genus comprising soybean oil-based insulating oil, rapeseed oil-based insulating oil, palm-based insulating oil, sunflower seed-based insulating oil, palm-based methyl ester insulating oil.
Compared with the prior art, the invention has the beneficial effects that:
(1) According to the invention, the adsorption column is used for adsorbing the additive in the natural ester insulating oil sample, so that the additive and the natural ester insulating oil are separated from the natural ester insulating oil sample, the influence of the additive on the methyl esterification reaction is avoided, and the accuracy of the calculation of the composition parameters of the follow-up fatty acid components is improved;
(2) The qualitative and quantitative analysis of the fatty acid methyl ester in the natural ester insulating oil sample can be rapidly carried out by gas chromatography, and the composition parameters of the fatty acid methyl ester component can be obtained by calculation according to the qualitative and quantitative analysis results;
(3) The content of the additive, the composition parameters of the fatty acid methyl ester component and the composition parameters of the fatty acid component are input into a convolutional neural network model, the base of the natural ester insulating oil can be directly identified, and the accuracy is up to 98.8%.
Drawings
FIG. 1 is a schematic diagram of an insulating oil treatment apparatus;
FIG. 2 is an SEM image of an iron-based modified activated carbon;
FIG. 3 is an SEM image of a Cu-BTC organic framework material;
FIG. 4 is a chromatogram of a standard substance of fatty acid methyl esters;
FIG. 5 is a block diagram of a convolutional neural network;
FIG. 6 is a flowchart of a preprocessing of a convolutional neural network;
FIG. 7 is a graph of a loss function of the judgment model for 100 iterations;
FIG. 8 is a graph of the loss function of the judgment model for 200 iterations.
Detailed Description
For a better description of the objects, technical solutions and advantages of the present invention, the present invention will be further described with reference to the following specific examples. It will be appreciated by persons skilled in the art that the specific embodiments described herein are for purposes of illustration only and are not intended to be limiting.
The reagents, methods and apparatus employed in the present invention, unless otherwise specified, are all conventional in the art.
Example 1
The embodiment provides a pretreatment method of natural ester insulating oil, which comprises the following steps:
(1) 95.500g of soybean oil is weighed and the following additives are added by external addition: 1.500g of antioxidant 2, 6-di-tert-butyl-p-cresol, 1.500g of Irgamet39 metal deactivator and 1.500g of PMAA anticoagulant, and the natural ester insulating oil with the additive content of 4.5% is obtained.
(2) The insulating oil treatment device is shown in fig. 1, the insulating oil treatment device comprises a vacuum oil filtering bottle 1, an oil inlet of the vacuum oil filtering bottle 1 is sequentially connected with a first valve 3 and a vacuum pump 2 through pipelines, an oil inlet of the vacuum oil filtering bottle 1 is sequentially connected with a second valve 4 and a nitrogen bag 5 through pipelines, and an oil outlet at the bottom of the vacuum oil filtering bottle 1 is sequentially connected with a third valve 6 and an oil storage tank through pipelines.
Filtering the natural ester insulating oil obtained in the step (1), injecting the filtered natural ester insulating oil into a vacuum oil filtering bottle 1, then covering a plug 7 with a thermometer 9, placing the vacuum oil filtering bottle 1 on an S10-2 type constant temperature magnetic stirring 8, starting the constant temperature magnetic stirring 8, setting the heating temperature to 70 ℃, heating and stirring the natural ester insulating oil mixture in the vacuum oil filtering bottle 1, opening a vacuum pump 2 and a first valve 3, vacuumizing the insulating oil in the vacuum oil filtering bottle 1, wherein the air pressure in the vacuum oil filtering bottle 1 is lower than 70Pa, during the vacuumizing process, opening a second valve 4, cleaning the upper space of the vacuum oil filtering bottle 1 by utilizing nitrogen for two times, stirring and vacuumizing for 8 hours, stopping heating by the constant temperature magnetic stirring 8, keeping constant stirring, cooling the natural ester insulating oil in the bottle to room temperature, then closing the first valve 3, closing the vacuum pump 2, vacuumizing an oil storage tank and cleaning the nitrogen for two times to obtain a natural ester insulating oil sample, opening a third valve 6 and a second valve 4, and transferring the natural ester insulating oil sample into the sealed oil storage tank.
(3) 1g of a natural ester insulating oil sample was placed in a beaker having a capacity of 50mL, and 5mL of isooctane was added for dilution to obtain a natural ester insulating oil sample diluent.
(4) Immersing 5g of active carbon adsorption material in 10mL of hydrogen peroxide solution for 6h, washing with deionized water, drying at 373K for 6h to obtain a carrier material, and immersing 2.5974g of Fe (NO 3 ) 3 ·9H 2 O is dissolved in 50mL of deionized water, 3g of carrier material is added, stirred and immersed for 12 hours, and then dried for 12 hours at 393K to obtain iron-based modified activated carbon, and ICP-OES metal element test and scanning electron microscope test are carried out on the iron-based modified activated carbon. The scanning electron microscope graph is shown in FIG. 2, and the test result shows that the loading rate of the iron-based modified activated carbon is 1.96wt% and the BET specific surface area is 1353.635m 2 Per gram, average pore diameter of 3.819nm and total pore volume of 1.292cm 3 /g。
5g of Cu (NO) 3 ) 2 ·3H 2 Adding O, 2.5g of trimesic acid, 0.025g of sodium carboxymethylcellulose and 0.25g of ZSM-5 (particle size of 1.3 mm) into 288g of water, uniformly mixing, measuring the pH value of the solution to be 1.9, then performing ultrasonic oscillation treatment in a closed environment, wherein the ultrasonic frequency is 35KHz, the ultrasonic power is 160W, performing ultrasonic oscillation treatment at room temperature for 10min, centrifuging the solution, collecting upper solid (the upper solid does not contain ZSM-5, ZSM-5 enters the lower solid), and placing the upper solid into ethanol water containing ammonium chlorideIn the solution, in an ethanol aqueous solution of ammonium chloride, the mass ratio of the ammonium chloride to the volume of the ethanol aqueous solution is 1g:130mL, the volume ratio of the ethanol to the water is 1:2, the mixture is mechanically stirred at a rotating speed of 60rpm for 60min, a filter cake is obtained by suction filtration, the filter cake is placed in a blast drying box and dried at 200 ℃ for 180min, a metal organic framework material Cu-BTC is obtained, the average particle size is 7 mu m, and the metal organic framework material Cu-BTC is obtained after roasting at 300 ℃, wherein the Scanning Electron Microscope (SEM) test result is shown in figure 3.
Sequentially loading 2g of iron-based modified activated carbon, 1g of Cu-BTC metal organic framework material and 2g of silica gel into an SPE (solid-phase separation) column to form a three-layer adsorption system of the iron-based modified activated carbon, the Cu-BTC metal organic framework material and the silica gel, washing the SPE adsorption column with 10mL of isooctane, pouring an insulating oil sample diluent into the SPE adsorption column, eluting with isooctane at a flow rate of 2 drops/s, collecting effluent and eluent, combining the effluent and eluent, transferring the eluent into a volumetric flask, metering the volume of the effluent and the eluent to 25mL with isooctane to obtain a sample liquid to be tested, drying the SPE adsorption column with compressed air, eluting with methanol at a flow rate of 2 drops/s, collecting methanol eluent, spin-drying, weighing the obtained product, and recording the mass of 43.9mg.
After the three-layer adsorption system of the iron-based modified activated carbon, the Cu-BTC metal organic framework material and the silica gel is subjected to specific adsorption, the removal rate of the antioxidant, the anticoagulant and the metal passivator in the natural ester insulating oil sample reaches 97.6%.
Comparative example 1
The present comparative example provides a pretreatment method of natural ester insulating oil, and the present comparative example is different from example 1 in that the SPE adsorption column of the present comparative example is prepared by the following method: weighing 2g of silica gel, and loading into an SPE column to obtain the SPE adsorption column.
The mass of the product of the comparative example after the methanol eluent was dried by spinning was 12.7mg.
After the adsorption treatment of the SPE adsorption column of the comparative example, the removal rate of the antioxidant, the anticoagulant and the metal passivator in the insulating oil sample is 28.2%.
Comparative example 2
The present comparative example provides a pretreatment method of natural ester insulating oil, and the present comparative example is different from example 1 in that the SPE adsorption column of the present comparative example is prepared by the following method: 2g of active carbon and 2g of silica gel are respectively weighed and sequentially loaded into an SPE column to form a two-layer adsorption system from the lower part to the upper part respectively of the active carbon and the silica gel, so as to obtain the SPE adsorption column.
The mass of the product of the comparative example after the methanol eluent was dried by spinning was 16.8mg. After the adsorption treatment of the SPE adsorption column of the comparative example, the removal rate of the antioxidant, the anticoagulant and the metal passivator in the insulating oil sample is 37.3%.
Comparative example 3
The present comparative example provides a pretreatment method of natural ester insulating oil, and the present comparative example is different from example 1 in that the SPE adsorption column of the present comparative example is prepared by the following method: 2g of active carbon, 1g of Cu-BTC metal organic framework material and 2g of silica gel are respectively weighed and sequentially loaded into an SPE column to form a three-layer adsorption system of the active carbon, the metal organic framework material and the silica gel, wherein the three-layer adsorption system is sequentially arranged from bottom to top, and the SPE adsorption column is obtained.
The mass of the product of the comparative example after the methanol eluent was dried by spinning was 23.7mg. After the adsorption treatment of the SPE adsorption column of the comparative example, the removal rate of the antioxidant, the anticoagulant and the metal passivator in the insulating oil sample is 52.7%.
Comparative example 4
The present comparative example provides a pretreatment method of natural ester insulating oil, and the present comparative example is different from example 1 in that the SPE adsorption column of the present comparative example is prepared by the following method: 2g of Fe-based modified activated carbon and 2g of silica gel are respectively weighed and sequentially loaded into an SPE column to form a two-layer adsorption system of the Fe-based modified activated carbon and the silica gel sequentially arranged from bottom to top, so as to obtain the SPE adsorption column.
The mass of the product of the comparative example after spin-drying of the methanol eluent was 25.2mg. After the adsorption treatment of the SPE adsorption column of the comparative example, the removal rate of the antioxidant, the anticoagulant and the metal passivator in the insulating oil sample is 56.0%.
As can be seen from comparison of the removal rates of the additives in the samples of the natural ester insulating oil in the example 1 and the comparative examples 1 to 4, the specific three-layer adsorption system is formed by the iron-based modified activated carbon, the metal organic framework material and the silica gel in the example 1, and the removal rate of the additives reaches 97.6%; comparative example 1 forms a single layer of adsorption system with silica gel, comparative example 2 forms a two layer of adsorption system with activated carbon and silica gel, comparative example 3 forms a three layer of adsorption system with activated carbon, metal organic framework material and silica gel, comparative example 4 forms a two layer of adsorption system with Fe-based modified activated carbon and silica gel, and the removal rate of the additive in comparative examples 1-4 is obviously inferior to that in example 1, which indicates that the removal effect of the additive is affected by the lack of any one of iron-based modified activated carbon, metal organic framework material and silica gel.
Examples 2 to 11
A component detection method of natural ester insulating oil comprises the following steps:
(1) 1g (designated M) of a sample of a natural ester insulating oil as described in Table 1 was weighed 0 ) Placing in 50mL beaker, adding 5mL isooctane for dilution to obtain natural ester insulating oil sample diluent, preparing SPE adsorption column according to the procedure of example 1, washing SPE adsorption column with 10mL isooctane, pouring insulating oil sample diluent into SPE adsorption column, eluting with isooctane at 2 drop/s flow rate, collecting effluent and eluent, combining the effluent and eluent, transferring into volumetric flask, metering volume to 25mL with isooctane to obtain sample liquid to be tested (total volume of sample liquid to be tested is recorded as V 0 ) Drying SPE adsorption column with compressed air, eluting with methanol at flow rate of 2 drop/s, collecting methanol eluate, spin drying, weighing the obtained product, and recording the quality of the obtained product as additive in natural ester insulating oil sample as M 1 The mass percentage content of the additive in the natural ester insulating oil sample is calculated according to the following formula:
W 1 ＝M 1 /M 0 ×100％，
wherein M is 1 Represents the mass of the additive in the natural ester insulating oil sample, M 0 Indicating the total mass of the natural ester insulating oil sample.
(2) Preparing standard substances of different fatty acid methyl esters into single standard solutions and mixed standard solutions with different concentration gradients, analyzing and measuring the single standard solutions by using a gas chromatograph to obtain retention time (detection results are shown in figure 4) of each standard substance, analyzing and measuring the mixed standard solutions by using the gas chromatograph to obtain a gas chromatogram of the standard substances, taking characteristic peak area values of the standard substances in the gas chromatogram as ordinate, taking the concentration of the standard substances in the mixed standard solutions as abscissa, and drawing a standard curve;
the working parameters of the gas chromatograph are as follows: chromatographic column: HP-5MS chromatographic column, column length 30m, internal diameter 0.25mm; the carrier gas is nitrogen, and the flow rate is 1mL/min; the column Wen Xiangwen control procedure is: the initial temperature is 100 ℃, the temperature is increased to 280 ℃ at the heating rate of 2 ℃/min, and the temperature is kept for 5min; the sample loading was 1.0. Mu.L.
The standard substances of the fatty acid methyl ester comprise lauric acid (C12:0), myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), margaric acid (C17:0), margaric acid (C17:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), arachic acid (C20:0), arachic acid (C20:1), arachic acid (C20:2), behenic acid (C22:0), erucic acid (C22:1), behenic acid (C22:2), lignoceric acid (C24:0) and tetracosadienoic acid (C24:1).
(3) Analyzing and measuring the sample diluent by using a gas chromatograph, wherein the working parameters of the gas chromatograph are the same as those of the step (2), the gas chromatograph is qualitative according to the retention time of the standard substance, the gas chromatograph is quantitative according to the standard curve, and the mass concentration of each fatty acid methyl ester in the sample liquid to be measured is calculated according to the qualitative and quantitative results; the total mass of fatty acid methyl ester components in the natural ester insulating oil sample is calculated according to the following formula:
M 2 ＝V 0 ×∑(C 14:0 +C 16:0 +…+C 24:1 )，
wherein, sigma (C 14:0 +C 16:0 +…+C 24:1 ) Representing the sum of the mass concentration of each fatty acid methyl ester, namely the total mass concentration of the fatty acid methyl esters in the sample liquid to be tested, V 0 Representing the total volume of the sample liquid to be tested;
the mass percentage content of the fatty acid methyl ester component in the natural ester insulating oil sample is calculated according to the following formula (the calculated result is shown in table 1):
W 2 ＝M 2 /M 0 ×100％，
wherein M is 2 Represents the mass, M, of the fatty acid methyl ester component in the natural ester insulating oil sample 0 Indicating the total mass of the natural ester insulating oil sample.
(4) 1mL of the sample solution to be measured was taken (the volume of the sample solution to be measured was denoted as V 1 ) A sample diluent was obtained by dilution with 4mL of isooctane (the volume of the sample diluent was designated as V 2 ) Adding 200 mu L of potassium hydroxide methanol solution (the mass concentration of potassium hydroxide in the potassium hydroxide methanol solution is 2%) to perform methyl esterification treatment to obtain methyl esterification sample liquid, analyzing and measuring the methyl esterification sample liquid by using a gas chromatograph, wherein the working parameters of the gas chromatograph are the same as those of the step (2), the gas chromatograph is qualitative according to the retention time of standard substances, quantitative according to a standard curve, and the mass concentration of each fatty acid methyl ester in the methyl esterification sample liquid is obtained by analysis, and then the mass concentration of each fatty acid in the sample diluent is calculated according to the following formula:
C acid(s) ＝C Methyl ester ×M Acid(s) /M Methyl ester Wherein M is Methyl ester Represents the molecular weight of fatty acid methyl ester, M Acid(s) Represents the molecular weight of the fatty acid corresponding to the fatty acid methyl ester, C Methyl ester Represents the mass concentration of fatty acid methyl ester;
and calculating the mass concentration of each fatty acid in the sample liquid to be detected according to the following formula:
C′ acid(s) ＝C Acid(s) ×V 2 /V 1 Wherein V is 1 Representing the volume of the sample liquid to be measured in the step (4), V 2 Representing the volume of the sample diluent of step (4);
the mass percent content of each fatty acid in the fatty acid component of the natural ester insulating oil sample is calculated according to the following formula (the calculated result is shown in table 2):
W′ acid(s) ＝V 0 ×C′ Acid(s) /(M 0 -M 1 -M 2 ) X 100%, where V 0 Representation ofThe total volume of the sample liquid to be measured in the step (1), M 0 Representing the total mass, M, of the natural ester insulating oil sample in step (1) 1 Representing the mass, M, of the additive in the natural ester insulating oil sample of step (1) 2 The mass of the fatty acid methyl ester component in the natural ester insulating oil sample in the step (3) is represented.
For convenience of distinction, C 'is used' 14:0 、C′ 16:0 、C′ 16:1 、C′ 17:0 、C′ 17:1 、C′ 18:0 、C′ 18:1 、C′ 18:2 、C′ 18:3 、C′ 20:0 、C′ 20:1 、C′ 20:2 、C′ 22:0 、C′ 22:1 、C′ 22:2 、C′ 24:0 、C′ 24 : 1 The mass concentration of fatty acid in the sample liquid to be tested is respectively shown as follows: c14:0, C16:0, C16:1, C17:0, C17:1, C18:0, C18:1, C18:2, C18:3, C20:0, C20:1, C20:2, C22:0, C22:1, C22:2, C24:0, C24:1. W'. 14 : 0 W′ 16:0 W′ 16:1 W′ 17:0 W′ 17:1 W′ 18:0 W′ 18: 1 W′ 18:2 W′ 18:3 W ′ 2 0:0 W′ 20:1 、W′ 20:2 、W′ 22:0 、W′ 22:1 、W′ 22:2 、W′ 24:0 、W′ 24:1 The mass percentages of fatty acids in the fatty acid component of the natural ester insulating oil sample are respectively shown as follows: c14:0, C16:0, C16:1, C17:0, C17:1, C18:0, C18:1, C18:2, C18:3, C20:0, C20:1, C20:2, C22:0, C22:1, C22:2, C24:0, C24:1. For example, C14:0 mass percent of fatty acid component in the natural ester insulating oil sample is: w'. 14:0 ＝ 0 ×W′ 14:0 /(M 0 -M 1 -M 2 )×100％。
According to the calculated results of the steps, the mass percentage of saturated fatty acid, the mass percentage of monounsaturated fatty acid and the mass percentage of polyunsaturated fatty acid in the fatty acid component of the natural ester insulating oil sample are further calculated, and the mass ratio of polyunsaturated fatty acid to saturated fatty acid and the mass ratio of unsaturated fatty acid to saturated fatty acid are further calculated.
TABLE 1
TABLE 2
Example 12
The embodiment provides a method for identifying the genus of natural ester insulating oil, which comprises the following steps:
(1) Commercially available 30 kinds of soybean oil, 30 kinds of rapeseed oil, 30 kinds of palm oil, 30 kinds of sunflower seed oil and 30 kinds of palm oil methyl ester derivatives are prepared, and 400 kinds of doped oil are obtained by blending the crude oil according to a gradient of 5% by using a random method, so that 550 kinds of samples of rapeseed oil-based insulating oil, soybean oil-based insulating oil, palm-based insulating oil, sunflower seed-based insulating oil and mixed-based insulating oil are obtained. For example, soybean oil and rapeseed oil are blended in a 5% gradient: the mass percentage of the soybean oil is 95 percent as the initial, the mass percentage of the soybean oil is gradually reduced to 5 percent according to a gradient of 5 percent, correspondingly, the mass percentage of the olive oil is gradually increased to 95 percent according to a gradient of 5 percent as the initial, and the mixed base insulating oil in the co-preparation 19 is prepared. The mass percent of the additive, the composition parameter of the fatty acid methyl ester component, the composition parameter of the fatty acid component, and the mass ratio of polyunsaturated fatty acid to saturated fatty acid, and the mass ratio of unsaturated fatty acid to saturated fatty acid in the fatty acid component of the sample were determined as per the method of example 2.
(2) Deep learning is performed by using a convolutional neural network model, wherein the convolutional neural network, CNN for short, consists of one or more convolutional layers and a full-communication layer (corresponding to a classical neural network) and also comprises a downsampling layer. The convolutional neural network CNN is capable of processing input data of a two-dimensional structure. The characteristics of local connection, weight sharing and pooling or downsampling operation of the convolutional neural network can help to reduce the complexity of the model, so that the model has a certain degree of invariance to translation, distortion and scaling, has strong robustness and fault tolerance, and is easy to train and optimize the network structure.
The known base of the natural ester insulating oil (category 5) and the characteristic data of the natural ester insulating oil can be used for establishing a correlation model of the characteristic data of the natural ester insulating oil and the base of the natural ester insulating oil through a convolutional neural network, so that the aim of acquiring the base of the natural ester insulating oil through the characteristic data analysis of the natural ester insulating oil is fulfilled.
The basic structure of the convolutional neural network is set up as shown in fig. 5, in which the parameters are weights and offsets in the convolutional kernel, and similar to the fully connected feed-forward network in which the gradient is mainly returned by the error term δ of each layer, the convolutional network can also perform parameter learning by an error back propagation algorithm, and the gradient of each layer parameter is further calculated.
In convolutional neural networks, there are mainly two neural layers with different functions: a convolutional layer and a downsampling layer. Assuming no parameters are in the downsampling layer, the parameters here are convolution kernels and offsets, so only the gradient of the parameters in the convolution layer needs to be calculated. Without loss of generality, the first layer is a convolution layer, the first-1 layer is an input feature map X l-1 ∈R M×N×D Obtaining the first layer through convolution calculationFeature map net inputP (1. Ltoreq. P. Ltoreq.P) th feature map net input for layer I:
wherein W is (l,p,d) Is a convolution kernel, b (l,p) For bias, the first layer has p×d convolution kernels and P biases, whose gradients can be calculated using the chain law, respectively:
wherein the p-th offset b for the loss function with respect to layer l (l,p) The gradient of (2) is:
thus, the gradient of each layer parameter of the convolutional network also depends on the error term delta of its layer (l,p) 。
Training of the convolutional neural network requires taking the characteristic data of the preprocessed natural ester insulating oil as the input of a model, and taking the basic classification result of the corresponding natural ester insulating oil as the output of the model, as shown in fig. 6; and (3) establishing neurons and characteristic surfaces through convolution calculation, continuously updating convolution kernel weights and optimizing model parameters according to gradient change feedback of a loss function, and finally establishing a deep learning model between characteristic data of the natural ester insulating oil and the basic category of the natural ester insulating oil.
The characteristic data of the 550 samples are subjected to convolutional neural network method learning, and a correlation model of the characteristic data of the natural ester insulating oil and the natural ester insulating oil genus is established, wherein one group of characteristic data comprises: the composition parameters of the fatty acid component comprise the mass percent of saturated fatty acid in the fatty acid component of the sample, the mass percent of monounsaturated fatty acid, the mass percent of polyunsaturated fatty acid, the mass ratio of polyunsaturated fatty acid to saturated fatty acid and the mass ratio of unsaturated fatty acid to saturated fatty acid; the natural ester insulating oil belongs to the rapeseed oil-based insulating oil, soybean oil-based insulating oil, palm-based insulating oil, sunflower seed-based insulating oil and mixed-based insulating oil.
For a classified network, the network tags associated with the network are classified into only classes, so each piece of data is used as an input and the preprocessing process is as follows:
the characteristic data of each piece of natural ester insulating oil is read according to the basic category of transformer oil, corresponding category labels are bound for the characteristic data, then the data of the bound labels are arranged randomly, so that the data category and the characteristic of each extraction are balanced, and then fixed and selected quantity of data are extracted to be put into network training. The training learning rate is 0.001 to 0.1, the small batch mini-batch is 20, the down sampling layer is adopted to inhibit over fitting, 450 sample data are input for multiple times, and the training times reach 20 times.
When training, the main function operates at the cnn_test, firstly, a network structure is defined by calling the cnn_setup, the zero filling function of the convolution layer and the downsampling layer which comprise the most core, then, the number mini_batch of methods for extracting and iterating the original data each time and the training model number epochs are defined through the cnn_train, then, the change of the network loss function is obtained by calling the cnn_ff training network according to batches, and then, the gradient parameter is transmitted to the cnn_apply to help update the parameter in the network according to the change gradient of the network loss function which is obtained by calling the cnn_bp. Finally returning to the cnn_test operation classification calculation, evaluating the model effect through multiple times of cross-validation, wherein the loss functions corresponding to different iteration times are shown in fig. 7 and 8.
According to the judgment of the descending trend of the model loss function in the judgment of fig. 7-8, the model can show a better convergence effect after 300 training iterations. The error rate of the evaluation model is stabilized at 1.2% by a method of multiple cross-validation.
TABLE 3 Table 3
| Type of insulating oil | Quantity of | Accuracy rate of |
| Soybean oil-based insulating oil | 30 | 100％ |
| Rapeseed oil-based insulating oil | 30 | 100％ |
| Palm-based insulating oil | 30 | 100％ |
| Sunflower seed-based insulating oil | 30 | 100％ |
| Mixed base insulating oil | 400 | 98.8％ |
| Palm methyl ester insulating oil | 30 | 100％ |
As can be seen from Table 3, the correct recognition rate of the mixed base insulating oil was 98.8%, and the correct rate of the other base insulating oils was 100%.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted equally without departing from the spirit and scope of the technical solution of the present invention.
Claims (6)
1. The identification method of the natural ester insulating oil belongs to the genus, and is characterized by comprising the following steps:
(1) Mixing and diluting a natural ester insulating oil sample with an organic solvent to obtain a sample diluent, passing the sample diluent through an adsorption column, eluting to obtain a sample liquid containing the natural ester insulating oil and an eluent containing an additive, diluting the sample liquid containing the natural ester insulating oil to obtain a sample liquid to be tested, drying the eluent containing the additive to obtain a solid additive, weighing and calculating to obtain the content of the additive in the natural ester insulating oil sample;
(2) Measuring the sample liquid to be detected obtained in the step (1), carrying out qualitative and quantitative analysis and determination on the sample liquid to be detected by utilizing a gas chromatograph, calculating the mass concentration of each fatty acid methyl ester in the sample liquid to be detected according to qualitative and quantitative analysis results, and calculating the mass of the fatty acid methyl ester component in the natural ester insulating oil sample according to the mass concentration of each fatty acid methyl ester in the sample liquid to be detected;
the mass percentage content of fatty acid methyl ester components in the natural ester insulating oil sample is calculated according to the following formula:
wherein M is 2 Represents the mass, M, of the fatty acid methyl ester component in the natural ester insulating oil sample 0 Representing the total mass of the natural ester insulating oil sample in step (1);
(3) Measuring the sample liquid to be detected obtained in the step (1), diluting the sample liquid to be detected to obtain a sample diluent to be detected, performing methyl esterification treatment on the sample diluent to be detected to obtain a methyl esterification sample liquid, performing qualitative and quantitative analysis and determination on the methyl esterification sample liquid by using a gas chromatograph, analyzing the mass concentration of each fatty acid methyl ester in the methyl esterification sample liquid according to qualitative and quantitative analysis results, and calculating the mass concentration of each fatty acid in the sample diluent according to the following formula:
wherein->Represents the molecular weight of fatty acid methyl ester, +.>Represents the molecular weight of the fatty acid corresponding to said fatty acid methyl ester, < >>Represents the mass concentration of fatty acid methyl ester;
the mass percentage content of each fatty acid in the sample liquid to be detected is calculated according to the following formula:
wherein V is 1 Representing the volume of the measured sample liquid, V 2 Representing the volume of the sample diluent;
the mass percentage content of each fatty acid in the fatty acid component of the natural ester insulating oil sample is calculated according to the following formula:
wherein V is 0 Represents the total volume of the sample liquid to be measured, M 0 Represents the total mass of the natural ester insulating oil sample, M 1 Represents natural estersMass, M of additive in insulating oil sample 2 Representing the mass of fatty acid methyl ester component in the natural ester insulating oil sample;
summing according to the calculated mass percent of each fatty acid to obtain the mass percent of saturated fatty acid, the mass percent of monounsaturated fatty acid and the mass percent of polyunsaturated fatty acid, and further calculating to obtain the mass ratio of polyunsaturated fatty acid to saturated fatty acid and the mass ratio of unsaturated fatty acid to saturated fatty acid;
(4) At least one of the content of the additive, the composition parameter of the fatty acid methyl ester component and the composition parameter of the fatty acid component is taken as the characteristic data of the natural ester insulating oil, and the characteristic data is input into an insulating oil genus evaluation model to obtain the output result of the insulating oil genus evaluation model;
the insulating oil belongs to an evaluation model which is the basic group of the natural ester insulating oil and characteristic data of a plurality of groups of natural ester insulating oil, and the characteristic data of the natural ester insulating oil and a correlation model of the natural ester insulating oil belongs to the basic group are established through a convolutional neural network.
2. The method for identifying the genus natural ester insulating oil according to claim 1, wherein the adsorption column is filled with iron-based modified activated carbon, metal-organic framework material and silica gel in sequence from bottom to top.
3. The method for identifying the genus natural ester insulator as claimed in claim 1, wherein the step (1) specifically comprises: mixing and diluting a natural ester insulating oil sample with an organic solvent to obtain a sample diluent, passing the sample diluent through an adsorption column, eluting with a first eluent, adsorbing additives in the natural ester insulating oil by using the adsorption column, collecting effluent and eluent, combining the effluent and the eluent, diluting with the organic solvent to obtain the sample fluid, drying the eluted adsorption column, eluting the dried adsorption column with a second eluent, collecting the eluent containing the additives, drying the eluent containing the additives to obtain solid additives, weighing, and calculating to obtain the content of the additives in the natural ester insulating oil sample.
4. The method of claim 1, wherein the composition parameters of the fatty acid component comprise at least one of saturated fatty acid mass percent, monounsaturated fatty acid mass percent, polyunsaturated fatty acid to saturated fatty acid mass ratio, and unsaturated fatty acid to saturated fatty acid mass ratio.
5. The method of identifying a natural ester insulating oil genus as claimed in claim 1, wherein the step (4) further comprises: and distinguishing the authenticity of the natural ester insulating oil according to the output result.
6. The method of claim 1, wherein the natural ester insulating oil comprises soybean oil-based insulating oil, rapeseed oil-based insulating oil, palm-based insulating oil, sunflower seed-based insulating oil, palm-based methyl ester insulating oil.
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| RU2758932C1 (en) * | 2020-07-17 | 2021-11-03 | Федеральное государственное бюджетное учреждение науки Федеральный исследовательский центр комплексного изучения Арктики имени академика Н.П. Лаверова Уральского отделения Российской академии наук (ФГБУН ФИЦКИА УрО РАН) | Method for measuring mass concentration of methyl esters of fatty acids in biological media by gas-liquid chromatography method |
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| CN105044229A (en) * | 2015-06-29 | 2015-11-11 | 中国农业科学院作物科学研究所 | Gas chromatography method for qualitatively and quantitatively detecting soya fatty acid components |
| CN107362609A (en) * | 2017-08-03 | 2017-11-21 | 国网河南省电力公司电力科学研究院 | A kind of natural esters insulation oil vacuum oil-filtering apparatus |
| CN109991333A (en) * | 2019-04-23 | 2019-07-09 | 东北农业大学 | A method of utilizing fatty acid in gas chromatography combined with mass spectrometry technology analysis soya-bean milk |
| RU2758932C1 (en) * | 2020-07-17 | 2021-11-03 | Федеральное государственное бюджетное учреждение науки Федеральный исследовательский центр комплексного изучения Арктики имени академика Н.П. Лаверова Уральского отделения Российской академии наук (ФГБУН ФИЦКИА УрО РАН) | Method for measuring mass concentration of methyl esters of fatty acids in biological media by gas-liquid chromatography method |
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