CN118275380A - Component analysis method and device for wax oil fraction - Google Patents
Component analysis method and device for wax oil fraction Download PDFInfo
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Abstract
The invention provides a component analysis method and device of wax oil fraction, comprising the following steps: obtaining fraction infrared spectrum data of wax oil fraction; screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions; according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions; solving the weight optimization model to determine the weight of the target sample; and determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight. The corresponding analysis result of the molecular lumped components can be obtained rapidly and accurately.
Description
Technical Field
The invention relates to the technical field of oil and gas data processing, in particular to a component analysis method and device for wax oil fractions.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
The fraction is a component distilled out in a certain temperature range when liquids such as petroleum and coal tar are fractionated. The analysis of the components of heavy fractions of petroleum, which have high boiling points, high heteroatom content and complex composition, is complex.
For wax oil fractions in heavy fractions, the current scheme is mostly based on real-time component analysis by an analysis instrument, but the current instrument analysis has the problems of long analysis time, high analysis cost, high acquisition cost of instruments and equipment and the like, so that the method cannot be widely popularized and used in refining production enterprises, and the analysis requirement of the enterprises for rapidly acquiring a large amount of sample components cannot be met.
Therefore, how to provide a new solution to the above technical problem is a technical problem to be solved in the art.
Disclosure of Invention
The embodiment of the invention provides a component analysis method of wax oil fraction, which can quickly and accurately obtain a corresponding molecular lumped component analysis result by measuring infrared spectrum of fraction to be analyzed, and comprises the following steps:
obtaining fraction infrared spectrum data of wax oil fraction;
Screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
According to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions;
Solving the weight optimization model to determine the weight of the target sample;
And determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
The embodiment of the invention also provides a component analysis device of the wax oil fraction, which comprises the following components:
the data acquisition module is used for acquiring fraction infrared spectrum data of the wax oil fraction;
The target sample fraction screening module is used for screening a plurality of target sample fractions with spectrogram similarity with the fraction infrared spectrum data higher than a preset threshold value from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
the weight optimization model construction module is used for constructing a weight optimization model of the sample weight corresponding to the target sample fraction according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the fraction infrared spectrum data;
the target sample weight determining module is used for solving the weight optimizing model and determining the target sample weight;
and the component analysis result determining module is used for determining the component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
The embodiment of the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the component analysis method of the wax oil fraction when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the component analysis method of the wax oil fraction when being executed by a processor.
The embodiment of the invention also provides a computer program product, which comprises a computer program, and the computer program realizes the component analysis method of the wax oil fraction when being executed by a processor.
The component analysis method and device for wax oil fractions provided by the embodiment of the invention comprise the following steps: obtaining fraction infrared spectrum data of wax oil fraction; screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions; according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions; solving the weight optimization model to determine the weight of the target sample; and determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight. The mapping relation between the fraction to be analyzed and the sample fraction is determined based on the comparison of the fraction infrared spectrum data of the wax oil fraction to be analyzed and the sample infrared spectrum data of the sample fraction in the database by utilizing more accurate molecular lumped component data in a pre-constructed wax oil fraction molecular database, and a molecular lumped component analysis result is rapidly and accurately generated based on the known molecular lumped component data of the sample fraction.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
Fig. 1 is a schematic diagram of a method for resolving components of a wax oil fraction according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating a detailed implementation of step S150 of the component analysis method of wax oil fraction according to an embodiment of the present invention.
Fig. 3 is a flow chart showing two parallel implementation of step S220 of a method for resolving components of wax oil fraction according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating a detailed implementation of step S320 of the component analysis method of wax oil fraction according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of a computer device for carrying out a method for component analysis of a wax oil fraction according to the present invention.
Fig. 6 is a schematic diagram of a component analysis device for wax oil fraction according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present invention and their descriptions herein are for the purpose of explaining the present invention, but are not to be construed as limiting the invention.
Fig. 1 is a schematic diagram of a method for resolving components of a wax oil fraction according to an embodiment of the present invention, as shown in fig. 1, and the embodiment of the present invention provides a method for resolving components of a wax oil fraction, wherein a corresponding molecular lumped component resolving result can be obtained rapidly and accurately by measuring an infrared spectrum of a fraction to be resolved, and the method includes:
Step S110: obtaining fraction infrared spectrum data of wax oil fraction;
Step S120: screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
step S130: according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions;
step S140: solving the weight optimization model to determine the weight of the target sample;
step S150: and determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
According to the invention, by utilizing more accurate molecular lumped component data in a pre-constructed wax oil fraction molecular database, the mapping relation between the fraction to be analyzed and the sample fraction is determined based on the comparison of the fraction infrared spectrum data of the wax oil fraction to be analyzed and the sample infrared spectrum data of the sample fraction in the database, and the molecular lumped component analysis result is rapidly and accurately generated based on the known molecular lumped component data of the sample fraction, the corresponding molecular lumped component analysis result can be rapidly and accurately obtained by only measuring the infrared spectrum of the fraction to be analyzed, and the requirements of refining production enterprises on rapid and accurate acquisition of high-precision component analysis data can be effectively met.
When the method for analyzing the components of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the method comprises the following steps:
obtaining fraction infrared spectrum data of wax oil fraction;
Screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
According to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions;
Solving the weight optimization model to determine the weight of the target sample;
And determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
In the embodiment, in the step S110, the fraction infrared spectrum data of the wax oil fraction to be resolved is obtained.
For example, an infrared spectrometer tests wax oil fractions to be analyzed to obtain original infrared spectrum data, and the spectrum data obtained after preprocessing the original infrared spectrum data is fraction infrared spectrum data; the electronic equipment acquires the fraction infrared spectrum data. The acquisition mode may be various modes capable of realizing data transmission, for example, a communication connection between the electronic device and the infrared spectrometer is used for transmitting test data, or a portable storage medium (such as a USB flash disk) copies fraction infrared spectrum data of the infrared spectrometer to the electronic device.
When the component analysis method of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the fraction infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actual measurement of an infrared spectrometer; the sample infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actually measuring sample fractions; the molecular lumped component data are component analysis data of the obtained infrared spectrum data of the corresponding sample, and the component analysis data are obtained by carrying out molecular lumped component analysis on the sample fraction to be put in storage by a mass spectrometer.
When the component analysis method of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the objective function of the weight optimization model is used for minimizing the deviation between the sample infrared spectrum data of the target sample fractions and the result of weighting and calculating the corresponding sample weights and the fraction infrared spectrum data.
In step S120, a plurality of target sample fractions with a spectrum similarity higher than a preset threshold value with the infrared spectrum data of the fractions are screened from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of the sample fraction.
In an embodiment, the above fraction infrared spectrum data are the following data obtained: the spectrum data obtained by preprocessing the original infrared spectrum data obtained by actual measurement of an infrared spectrometer; correspondingly, the sample infrared spectrum data is the spectrum data of the original infrared spectrum data after the actual measurement of the sample fraction is preprocessed, and the preprocessing mode of the sample infrared spectrum data is the same as that of the fraction infrared spectrum data. Such pre-treatments include, but are not limited to, one or more of the following: the first derivative is obtained and baseline correction is performed.
The predetermined threshold may be an empirical value or may be adaptively adjusted according to the number of sample fractions to be screened. For example, in some embodiments, the predetermined threshold is any value within the interval of 85% to 95%, including the endpoint value. In other embodiments, the preset number of target sample fractions is 3-5, and the preset threshold value satisfies the number of target sample fractions selected by the screening method is 3-5.
In an embodiment, in the step S120, the screening, from a pre-constructed wax oil fraction molecular database, a plurality of target sample fractions with spectrum similarities with the infrared spectrum data of the fractions higher than a preset threshold value includes: calculating the spectrum similarity between the sample infrared spectrum data of the sample fraction and the fraction infrared spectrum data; and determining the sample fraction with the spectrogram similarity higher than a preset threshold as the target sample fraction.
In some embodiments, the molecular lumped component data is obtained from component analysis data obtained by high resolution mass spectrometry of a wax oil fraction to be put in storage.
The similarity may be calculated by using the euclidean distance or other algorithm for representing the similarity, where the euclidean distance is calculated by the following formula: the difference between the corresponding points is calculated by squaring and re-squaring.
At the molecular scale, the molecular lumped components are considered as virtual single components for their reaction kinetics.
Because the pre-constructed wax oil fraction molecular database stores the sample infrared spectrum data and the molecular lumped component data of the sample fractions, and the spectrum similarity comparison and screening are carried out based on the infrared spectrum data, a plurality of target sample fractions for representing the wax oil fraction to be analyzed can be determined in the wax oil fraction molecular database, so that the more accurate molecular lumped component data in the wax oil fraction molecular database (which can be simply called as a database) can be effectively utilized. In some embodiments, the molecular lumped component data in the database is based on component analysis data obtained by a high resolution mass spectrometer, advantageously providing more accurate base component data to characterize the wax oil fraction to be resolved.
In some embodiments, the molecular lumped component data comprises: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components. For example, the molecular formula of the molecular lumped component is expressed as: c aHbOxSyNk, wherein C, H, O, S and N have a definite element content, i.e. the values of the subscripts a, b, x, y and k are determined.
If the elemental composition of a molecule or fragment is known, its unsaturation, including cyclic, double and triple bonds, can be calculated, and thus the hydrogen deficiency index, also known as hydrogen deficiency, equivalent double bond number (DBE, double bond equivalents) or unsaturation, is a quantitative indicator of the degree of unsaturation of an organic molecule.
Types of the above molecular lumped components include, but are not limited to: alkanes, alkenes, aromatics, sulfur-containing compounds, nitrogen-containing compounds, oxygen-containing compounds, and the like.
The content of the molecular lumped component refers to the content percentage of the molecular lumped component in the sample fraction, and the volume percentage or the mass percentage can be selected.
In step S130, a weight optimization model is constructed for the sample weights corresponding to the target sample fractions based on the differences between the results of weighted sum calculation of the sample infrared spectrum data and the corresponding sample weights of the target sample fractions and the sample infrared spectrum data.
In some embodiments, the objective function of the weight optimization model includes: and minimizing the deviation between the weighted sum calculation result of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the target fractions.
For example, the objective function of the weight optimization model is expressed as the following expression:
Wherein, Fraction infrared spectrum data representing the z-th wax oil fraction to be resolved,The sample infrared spectrum data of the ith target sample fraction in the N z target sample fractions corresponding to the z-th wax oil fraction to be resolved is represented, w zi represents the sample weight corresponding to the sample infrared spectrum data of the ith target sample fraction, N z represents the total number of target sample fractions corresponding to the z-th wax oil fraction to be resolved, and I represents the absolute value.
The above-mentioned expression of the objective function of the weight optimization model is given as an example, and it will be understood by those skilled in the art that the above-mentioned expression may be modified and other parameters or data may be added according to the need, or other specific formulas may be provided, and these modifications shall fall within the protection scope of the present invention.
The objective function of the weight optimization model may take various forms, such as a linear weighted sum function or a polynomial function.
In step S140, the weight optimization model is solved to obtain the weight of the target sample.
In some embodiments, the iterative computation of the weight optimization model is performed by using a linear optimization algorithm, for example, the iterative computation solution may be performed by using an interior point method, a least square method, or the like.
In step S150, a component analysis result of the wax oil fraction is generated according to the molecular lumped component data of the target sample fraction and the target sample weight.
Based on the steps S110-S150, pre-constructed sample infrared spectrum data and molecular lumped component data of the sample fractions are stored in a wax oil fraction molecular database, spectrum similarity comparison and screening are carried out based on the infrared spectrum data, a plurality of target sample fractions for representing the wax oil fractions to be analyzed are determined in the wax oil fraction molecular database, corresponding sample weights of the target sample fractions are optimized, and weighting calculation is carried out based on the molecular lumped component data known by the target sample fractions respectively, so that a component analysis result of the wax oil fractions to be analyzed is generated; the mapping relation between the fraction to be analyzed and the sample fraction is determined based on the comparison of the fraction infrared spectrum data of the wax oil fraction to be analyzed and the sample fraction infrared spectrum data in the database by utilizing the more accurate molecular lumped component data in the constructed wax oil fraction molecular database (which can be simply called as the database), and the molecular lumped component analysis result is rapidly and accurately generated based on the known molecular lumped component data of the sample fraction.
As shown in fig. 2, when the method for resolving components of a wax oil fraction according to the embodiment of the present invention is specifically implemented, in one embodiment, determining a resolving result of components of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight includes:
carrying out weighted sum calculation on the molecular lumped component data of the target sample fraction and the corresponding target sample weight to determine a molecular lumped component weighted result;
and determining the component analysis result of the wax oil fraction according to the molecular lumped component weighting result.
In the step S150, a component analysis result of the wax oil fraction is generated according to the molecular lumped component data of the target sample fraction and the target sample weight, and the method comprises the following steps: s210, S220.
In step S210, the molecular lumped component data of the target sample fraction and the corresponding target sample weight are weighted and calculated to obtain a molecular lumped component weighted result.
In some embodiments, the molecular lumped component data comprises: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components.
The weighted sum calculation is performed on the molecular lumped component data of the target sample fraction and the corresponding target sample weight, and the weighted sum calculation is performed on the quantifiable parameter correspondence in the molecular lumped component data, for example, the weighted sum calculation is performed on the molecular formula, the weighted sum calculation is performed on the hydrogen deficiency index, the weighted sum calculation is performed on the content of the molecular lumped component, and the like. In general, the types of the plurality of target sample fractions are uniform, so weighting and calculating the types of the total components of the fractions is actually the types of the total components of the molecules of the target sample fractions. For example, the weighted sum of the contents of the molecular lumped components results in an analyzed content of the molecular lumped components contained in the wax oil fraction to be resolved; accordingly, other weighted sum results are described as analysis formula, analysis type, analysis hydrogen deficiency index, etc.
In step S220, a component analysis result of the wax oil fraction is generated according to the molecular lumped component weighting result.
Fig. 3 is a flow chart of two parallel implementations of step S220 in an embodiment of the present disclosure.
Referring to fig. 3, in the step S220, a component analysis result of the wax oil fraction is generated according to the molecular lumped component weighting result, which includes the following two steps that may be executed in parallel (alternatively): s310 or S320.
In some embodiments, step S310 is performed to determine the molecular lumped component weighted result as the component analysis result of the wax oil fraction.
In the embodiment including step S310, the component analysis data of the wax oil fraction can be accurately and rapidly obtained by the refining production enterprise using the near infrared spectrum, so that at least the technical problems of long analysis time, high analysis cost, high purchase cost of instruments and equipment and the like in the related art can be solved.
When the component analysis method of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the component analysis result of the wax oil fraction is determined according to the molecular lumped component weighting result, and the method comprises the following steps:
taking the molecular lumped component weighted result as a primary component analysis result of the wax oil fraction;
and carrying out refined analysis on the primary component analysis result at the structural unit level, and determining the component analysis result of the wax oil fraction at the structural unit level.
In a specific implementation of the component analysis method of a wax oil fraction provided by the embodiment of the present invention, in one embodiment, performing fine analysis on the primary component analysis result at the structural unit level, and determining the component analysis result of the wax oil fraction at the structural unit level includes:
Generating screening conditions according to the primary component analysis results, and screening in a pre-constructed structural unit molecular component database to obtain a matched structural unit matched with the screening conditions, wherein the matched structural unit is used for representing a type analysis result of molecular components contained in the wax oil fraction at a structural unit layer;
obtaining physical property detection data of the wax oil fraction;
Constructing a content optimization model of the component content parameters according to the physical property detection data, the physical property contribution value of the matching structural unit and the component content parameters corresponding to the matching structural unit;
solving the content optimization model to obtain a target component content parameter of the matched structural unit; the target component content parameter is used for representing a content analysis result of a molecular component contained in the wax oil fraction at a structural unit layer;
And utilizing the type analysis result and the content analysis result to form a component analysis result of the wax oil fraction on the structural unit level.
When the component analysis method of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the target component content parameter is used for enabling the difference value between the calculated physical property data of the wax oil fraction and the physical property detection data to be smaller than a preset threshold value; and calculating physical property data of the wax oil fraction according to the physical property contribution value of the matched structural unit and the corresponding component content parameter.
When the method for analyzing the components of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the primary component analysis result comprises: the wax oil fraction contains the analytical content of the molecular lumped components; the objective function of the content optimization model is used for solving the minimum value of the difference between the calculated physical property data of the wax oil fraction and the physical property detection data;
the constraint conditions of the content optimization model comprise: and aiming at one or more matching structural units corresponding to the same molecule lumped component, wherein the sum of component content parameters of the matching structural units is equal to the analysis content of the corresponding molecule lumped component.
On this basis, it was also found that: for wax oil fraction, although the embodiment of step S310 can quickly and relatively accurately obtain component analysis data with higher precision, many isomers still exist for the analysis result of the same expression, and it is difficult to realize refined characterization of the molecule lumped component. Thus, in order to further enhance the molecular management granularity of the characterization result, embodiments of the present disclosure provide a solution including the correspondence of step S320. Therefore, the production enterprises can carry out material blending optimization on wax oil fractions according to the material blending optimization, and can be used for optimizing feeding of subsequent processing devices or production blending optimization of oil products such as subsequent ship combustion and the like, and can also carry out operation optimization on production of the wax oil processing devices, and carry out adjustment of production operation aiming at a special structure of molecule lumped components and the like.
In other embodiments, step S320 is performed, where the molecular lumped component weighted result is used as a primary component analysis result of the wax oil fraction, and the primary component analysis result is subjected to refinement analysis at the structural unit level to obtain a component analysis result of the wax oil fraction at the structural unit level.
Step S320 provided by the embodiment of the present disclosure is described in detail below with reference to fig. 4.
Fig. 4 is a detailed implementation flowchart of step S320 in an embodiment of the present disclosure. Referring to fig. 4, in the step S320, the primary component analysis result is subjected to a refinement analysis at the structural unit level to obtain a component analysis result of the wax oil fraction at the structural unit level, and the method includes the following steps: s410, S420, S430 and S440.
In step S410, screening conditions are generated according to the primary component analysis result, and screening is performed on a pre-constructed structural unit molecular component database to obtain a matched structural unit matched with the screening conditions. The matching structural unit is used for representing the analysis result of the types of the molecular components contained in the wax oil fraction at the structural unit level.
The number of matching structural units may be one or more.
For example, in one embodiment, the combination of the analytical molecular formula, the analytical type, and the analytical hydrogen deficiency index of the molecular lumped component in the primary component analysis result is used as the screening condition, and the molecular formula, the type, and the hydrogen deficiency index of the matching structural unit are uniformly matched with the screening condition.
The pre-constructed structural unit molecular composition database is provided with structural units of wax oil fractions and attribute data of corresponding molecular compositions, wherein the attribute data comprise composition data and physical property data corresponding to the structural units, and the composition data comprise: molecular formula, type, hydrogen deficiency index, etc.; the attribute data and the structural unit are stored in the form of key-value pairs, and a plurality of attribute data constitute a set of keys, and the structural unit is a value corresponding to the attribute data.
In one embodiment, the building blocks may be in the form of Structure-oriented lumped (SOL) as shown in Table 1 below.
TABLE 1 structural units in SOL form and meanings thereof
Referring to table 1 above, the structural unit molecular components in the structural unit molecular component database provided in this example may be structural units based on SOL form, the structures of all hydrocarbon molecules in the oil are disassembled and arranged into 22 kinds of fragments of molecular structures, which are described as structural units, and then all hydrocarbon molecules are represented by the organic combination of these 22 structural units; aiming at the requirements of representing residual oil molecules, 22 structural units are expanded, and structural units corresponding to metallic nickel and vanadium are introduced, wherein 24 structural units are totally introduced. Based on the structural units in SOL form, the composition of each molecule in the raw material or product mixture can be described using a one-dimensional structural vector composed of the number of 24 structural units contained in the molecule.
For example, the analysis results for the primary component include: a molecular lumped component Da, the molecular formula of Da is expressed as C a1Hb1Ox1Sy1Nk1, the type is cycloparaffin, and the content of the Da molecular lumped component in the total fraction is 0.4; another molecular lumped component, db, of the formula C a2Hb2Ox2Sy2Nk2, of the type olefins, is present in a total fraction of 0.6.
Illustratively, the matching building blocks of SOL form, which are composed of molecular lumped components for characterizing Da, are respectively: sol 1、Sol2、Sol3 (e.g., N3, RN, NS); the matching structural units of SOL form composed of molecular lumped components characterizing Db are respectively: sol 4、Sol5、Sol6 (e.g., N1, KO, NO).
In step S420, physical property detection data of the wax oil fraction is obtained.
According to an embodiment of the present disclosure, in the above method, according to an embodiment of the present disclosure, the above physical property detection data includes one or more of the following physical properties: fraction density, distillation range, congealing point, refractive index, average molecular weight, viscosity.
In step S430, a content optimization model is constructed with respect to the component content parameters based on the physical property detection data, the physical property contribution value of the matching structural unit, and the component content parameters corresponding to the matching structural unit.
In step S440, the content optimization model is solved, so as to obtain a target component content parameter of the matching structural unit, where the target component content parameter is used to characterize a content analysis result of the molecular component contained in the wax oil fraction at the structural unit level. Wherein the analysis result of the type and the analysis result of the content constitute a component analysis result of the wax oil fraction at the structural unit level.
Based on the steps S410-S440, a more refined, accurate and reliable component analysis result of the structural unit layer can be obtained, and a data foundation is laid for subsequent oil blending, oil processing and utilization and other application scenes.
According to this embodiment, in the step S440, the target component content parameter is such that the difference between the calculated physical property data of the wax oil fraction and the physical property detection data is smaller than a preset threshold; the calculated physical property data of the wax oil fraction are calculated according to the physical property contribution value of the matched structural unit and the corresponding component content parameters.
According to an embodiment of the present disclosure, the primary component analysis results described above include: analytical content of the molecular lump component contained in the above wax oil fraction.
The objective function of the content optimization model is as follows: solving a minimum value of a difference between calculated physical property data of the wax oil fraction and the physical property detection data; the constraint conditions of the content optimization model include: and aiming at one or more matching structural units corresponding to the same molecule lumped component, the sum of component content parameters of the matching structural units is equal to the analysis content of the corresponding molecule lumped component.
For example, the objective function of the content optimization model is expressed as:
min(WZcal-Wztest) (2)
Wherein Wz cal represents calculated physical property data of the z-th wax oil fraction to be resolved, and Wz test represents physical property detection data of the z-th wax oil fraction to be resolved; c represents a constant, rz tj represents a component content parameter of a j-th matching structural unit in N zt matching structural units corresponding to a t-th molecular lumped component of the wax oil fraction to be analyzed, wz tj represents a physical property contribution value of a j-th matching structural unit in N zt matching structural units corresponding to the t-th molecular lumped component of the wax oil fraction to be analyzed, and N zt represents the total number of the matching structural units corresponding to the t-th molecular lumped component of the wax oil fraction to be analyzed.
Constraints of the content optimization model are expressed as follows:
wherein rz t0 represents the analyzed content of the t-th molecular lumped component corresponding to the N ze matching structural units.
For example, for a molecular lumped component Da in the primary component analysis result, the component content parameter rz tj corresponding to Da is denoted as rz 1j, provided that: For the molecular lumped component Db, the component content parameter rz tj corresponding to the Db is expressed as rz 2j, provided that
According to an embodiment of the present disclosure, solving the content optimization model includes: and carrying out iterative solution on the content optimization model based on a genetic algorithm or a simulated annealing algorithm to obtain the content parameters of the target component.
The above-mentioned objective function of the content optimization model and the expression of the constraint condition of the content optimization model are given by way of example, and those skilled in the art will understand that the above-mentioned formula may be modified and other parameters or data may be added according to the need, or other specific formulas may be provided, and these modifications shall fall within the protection scope of the present invention.
In a specific implementation of the method for analyzing components of a wax oil fraction provided by the embodiment of the present invention, in one embodiment, the physical property detection data indicates one or more of the following physical properties: fraction density, distillation range, congealing point, refractive index, average molecular weight, viscosity.
When the method for resolving components of wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the molecular lumped component data includes: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components.
Fig. 5 is a schematic diagram of a computer device for executing a method for resolving components of a wax oil fraction according to the present invention, and as shown in fig. 5, an embodiment of the present invention further provides a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored in the memory and capable of running on the processor, where the processor implements the method for resolving components of a wax oil fraction when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the component analysis method of the wax oil fraction when being executed by a processor.
The embodiment of the invention also provides a computer program product, which comprises a computer program, and the computer program realizes the component analysis method of the wax oil fraction when being executed by a processor.
The embodiment of the invention also provides a component analysis device of the wax oil fraction, as described in the following embodiment. The principle of the device for solving the problems is similar to that of a component analysis method of wax oil fraction, so that the implementation of the device can refer to the implementation of the component analysis method of wax oil fraction, and the repetition is omitted.
Fig. 6 is a schematic diagram of a component analysis device for wax oil fraction according to an embodiment of the present invention, and as shown in fig. 6, the embodiment of the present invention further provides a component analysis device for wax oil fraction.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the device may include:
The data acquisition module 601 is configured to acquire fraction infrared spectrum data of a wax oil fraction;
A target sample fraction screening module 602, configured to screen a plurality of target sample fractions with spectrum similarity with the fraction infrared spectrum data higher than a preset threshold from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
The weight optimization model construction module 603 is configured to construct a weight optimization model of a sample weight corresponding to the target sample fraction according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the sample infrared spectrum data of the target sample fractions;
The target sample weight determining module 604 is configured to solve the weight optimization model to determine a target sample weight;
and the component analysis result determining module 605 is configured to determine a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
When the component analysis device of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the fraction infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actual measurement of an infrared spectrometer; the sample infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actually measuring sample fractions; the molecular lumped component data are component analysis data of the obtained infrared spectrum data of the corresponding sample, and the component analysis data are obtained by carrying out molecular lumped component analysis on the sample fraction to be put in storage by a mass spectrometer.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the objective function of the weight optimization model is used for minimizing the deviation between the sample infrared spectrum data of the target sample fractions and the result of weighting and calculating the corresponding sample weights and the fraction infrared spectrum data.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the component analysis result determining module is specifically configured to:
carrying out weighted sum calculation on the molecular lumped component data of the target sample fraction and the corresponding target sample weight to determine a molecular lumped component weighted result;
and determining the component analysis result of the wax oil fraction according to the molecular lumped component weighting result.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the component analysis result determining module is further configured to:
taking the molecular lumped component weighted result as a primary component analysis result of the wax oil fraction;
and carrying out refined analysis on the primary component analysis result at the structural unit level, and determining the component analysis result of the wax oil fraction at the structural unit level.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the component analysis result determining module is further configured to:
Generating screening conditions according to the primary component analysis results, and screening in a pre-constructed structural unit molecular component database to obtain a matched structural unit matched with the screening conditions, wherein the matched structural unit is used for representing a type analysis result of molecular components contained in the wax oil fraction at a structural unit layer;
obtaining physical property detection data of the wax oil fraction;
Constructing a content optimization model of the component content parameters according to the physical property detection data, the physical property contribution value of the matching structural unit and the component content parameters corresponding to the matching structural unit;
solving the content optimization model to obtain a target component content parameter of the matched structural unit; the target component content parameter is used for representing a content analysis result of a molecular component contained in the wax oil fraction at a structural unit layer;
And utilizing the type analysis result and the content analysis result to form a component analysis result of the wax oil fraction on the structural unit level.
When the component analysis device of the wax oil fraction provided by the embodiment of the invention is implemented, in one embodiment, the target component content parameter is used for enabling the difference value between the calculated physical property data of the wax oil fraction and the physical property detection data to be smaller than a preset threshold value; and calculating physical property data of the wax oil fraction according to the physical property contribution value of the matched structural unit and the corresponding component content parameter.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the primary component analysis result includes: the wax oil fraction contains the analytical content of the molecular lumped components; the objective function of the content optimization model is used for solving the minimum value of the difference between the calculated physical property data of the wax oil fraction and the physical property detection data;
the constraint conditions of the content optimization model comprise: and aiming at one or more matching structural units corresponding to the same molecule lumped component, wherein the sum of component content parameters of the matching structural units is equal to the analysis content of the corresponding molecule lumped component.
In an embodiment of the device for analyzing components of a wax oil fraction provided by the embodiment of the present invention, the physical property detection data indicates one or more of the following physical properties: fraction density, distillation range, congealing point, refractive index, average molecular weight, viscosity.
When the component analysis device for wax oil fractions provided by the embodiment of the invention is implemented, in one embodiment, the molecular lumped component data includes: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components.
In summary, the method and the device for analyzing the components of the wax oil fraction provided by the embodiment of the invention comprise the following steps: obtaining fraction infrared spectrum data of wax oil fraction; screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions; according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions; solving the weight optimization model to determine the weight of the target sample; and determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight. The mapping relation between the fraction to be analyzed and the sample fraction is determined based on the comparison of the fraction infrared spectrum data of the wax oil fraction to be analyzed and the sample infrared spectrum data of the sample fraction in the database by utilizing more accurate molecular lumped component data in a pre-constructed wax oil fraction molecular database, and a molecular lumped component analysis result is rapidly and accurately generated based on the known molecular lumped component data of the sample fraction.
According to the technical scheme, the data acquisition, storage, use, processing and the like all meet the relevant regulations of national laws and regulations, and various types of data such as personal identity data, operation data, behavior data and the like related to individuals, clients, crowds and the like are obtained and authorized.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (23)
1. A method for component analysis of a wax oil fraction, comprising:
obtaining fraction infrared spectrum data of wax oil fraction;
Screening a plurality of target sample fractions with spectrogram similarity higher than a preset threshold value with the fraction infrared spectrum data from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
According to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the infrared spectrum data of the fractions, constructing a weight optimization model of the sample weights corresponding to the target sample fractions;
Solving the weight optimization model to determine the weight of the target sample;
And determining a component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
2. The method according to claim 1, wherein the fraction infrared spectrum data is spectrum data obtained by preprocessing raw infrared spectrum data obtained by actual measurement of an infrared spectrometer; the sample infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actually measuring sample fractions; the molecular lumped component data are component analysis data of the obtained infrared spectrum data of the corresponding sample, and the component analysis data are obtained by carrying out molecular lumped component analysis on the sample fraction to be put in storage by a mass spectrometer.
3. The method of claim 1, wherein the objective function of the weight optimization model is used to minimize a deviation between sample infrared spectral data of the plurality of target sample fractions and the fraction infrared spectral data as a result of a weighted sum calculation of the corresponding sample weights.
4. The method of claim 1, wherein determining the component analysis result of the wax oil fraction based on the molecular lumped component data of the target sample fraction and the target sample weight comprises:
carrying out weighted sum calculation on the molecular lumped component data of the target sample fraction and the corresponding target sample weight to determine a molecular lumped component weighted result;
and determining the component analysis result of the wax oil fraction according to the molecular lumped component weighting result.
5. The method of claim 4, wherein determining the composition analysis result of the wax oil fraction based on the molecular lumped composition weighted result comprises:
taking the molecular lumped component weighted result as a primary component analysis result of the wax oil fraction;
and carrying out refined analysis on the primary component analysis result at the structural unit level, and determining the component analysis result of the wax oil fraction at the structural unit level.
6. The method of claim 5, wherein performing a refinement of the primary component analysis results at the structural unit level to determine component analysis results of the wax oil fraction at the structural unit level comprises:
Generating screening conditions according to the primary component analysis results, and screening in a pre-constructed structural unit molecular component database to obtain a matched structural unit matched with the screening conditions, wherein the matched structural unit is used for representing a type analysis result of molecular components contained in the wax oil fraction at a structural unit layer;
obtaining physical property detection data of the wax oil fraction;
Constructing a content optimization model of the component content parameters according to the physical property detection data, the physical property contribution value of the matching structural unit and the component content parameters corresponding to the matching structural unit;
solving the content optimization model to obtain a target component content parameter of the matched structural unit; the target component content parameter is used for representing a content analysis result of a molecular component contained in the wax oil fraction at a structural unit layer;
And utilizing the type analysis result and the content analysis result to form a component analysis result of the wax oil fraction on the structural unit level.
7. The method of claim 6, wherein the target component content parameter is used to make a difference between calculated physical property data of the wax oil fraction and the physical property detection data less than a preset threshold; and calculating physical property data of the wax oil fraction according to the physical property contribution value of the matched structural unit and the corresponding component content parameter.
8. The method of claim 7, wherein the primary component analysis results comprise: the wax oil fraction contains the analytical content of the molecular lumped components; the objective function of the content optimization model is used for solving the minimum value of the difference between the calculated physical property data of the wax oil fraction and the physical property detection data;
the constraint conditions of the content optimization model comprise: and aiming at one or more matching structural units corresponding to the same molecule lumped component, wherein the sum of component content parameters of the matching structural units is equal to the analysis content of the corresponding molecule lumped component.
9. The method of claim 7, wherein the physical property detection data indicates a physical property comprising one or more of the following: fraction density, distillation range, congealing point, refractive index, average molecular weight, viscosity.
10. The method of any one of claims 1-9, wherein the molecular lumped component data comprises: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components.
11. A component analysis device for wax oil fraction, comprising:
the data acquisition module is used for acquiring fraction infrared spectrum data of the wax oil fraction;
The target sample fraction screening module is used for screening a plurality of target sample fractions with spectrogram similarity with the fraction infrared spectrum data higher than a preset threshold value from a pre-constructed wax oil fraction molecular database; the wax oil fraction molecular database stores sample infrared spectrum data and molecular lumped component data of sample fractions;
the weight optimization model construction module is used for constructing a weight optimization model of the sample weight corresponding to the target sample fraction according to the deviation between the result of weighted sum calculation of the sample infrared spectrum data of the target sample fractions and the corresponding sample weights and the fraction infrared spectrum data;
the target sample weight determining module is used for solving the weight optimizing model and determining the target sample weight;
and the component analysis result determining module is used for determining the component analysis result of the wax oil fraction according to the molecular lumped component data of the target sample fraction and the target sample weight.
12. The apparatus of claim 11, wherein the fraction infrared spectrum data is a spectrum data obtained by preprocessing raw infrared spectrum data obtained by actual measurement of an infrared spectrometer; the sample infrared spectrum data is spectrum data obtained by preprocessing original infrared spectrum data obtained by actually measuring sample fractions; the molecular lumped component data are component analysis data of the obtained infrared spectrum data of the corresponding sample, and the component analysis data are obtained by carrying out molecular lumped component analysis on the sample fraction to be put in storage by a mass spectrometer.
13. The apparatus of claim 11, wherein the objective function of the weight optimization model is configured to minimize a deviation between sample infrared spectral data of the plurality of target sample fractions and the fraction infrared spectral data as a result of a weighted sum calculation of the corresponding sample weights.
14. The apparatus of claim 11, wherein the component analysis result determining module is specifically configured to:
carrying out weighted sum calculation on the molecular lumped component data of the target sample fraction and the corresponding target sample weight to determine a molecular lumped component weighted result;
and determining the component analysis result of the wax oil fraction according to the molecular lumped component weighting result.
15. The apparatus of claim 14, wherein the component parsing result determination module is further configured to:
taking the molecular lumped component weighted result as a primary component analysis result of the wax oil fraction;
and carrying out refined analysis on the primary component analysis result at the structural unit level, and determining the component analysis result of the wax oil fraction at the structural unit level.
16. The apparatus of claim 15, wherein the component parsing result determination module is further configured to:
Generating screening conditions according to the primary component analysis results, and screening in a pre-constructed structural unit molecular component database to obtain a matched structural unit matched with the screening conditions, wherein the matched structural unit is used for representing a type analysis result of molecular components contained in the wax oil fraction at a structural unit layer;
obtaining physical property detection data of the wax oil fraction;
Constructing a content optimization model of the component content parameters according to the physical property detection data, the physical property contribution value of the matching structural unit and the component content parameters corresponding to the matching structural unit;
solving the content optimization model to obtain a target component content parameter of the matched structural unit; the target component content parameter is used for representing a content analysis result of a molecular component contained in the wax oil fraction at a structural unit layer;
And utilizing the type analysis result and the content analysis result to form a component analysis result of the wax oil fraction on the structural unit level.
17. The apparatus of claim 16, wherein the target component content parameter is used to cause a difference between calculated physical property data of the wax oil fraction and the physical property detection data to be less than a preset threshold; and calculating physical property data of the wax oil fraction according to the physical property contribution value of the matched structural unit and the corresponding component content parameter.
18. The apparatus of claim 17, wherein the primary component analysis results comprise: the wax oil fraction contains the analytical content of the molecular lumped components; the objective function of the content optimization model is used for solving the minimum value of the difference between the calculated physical property data of the wax oil fraction and the physical property detection data;
the constraint conditions of the content optimization model comprise: and aiming at one or more matching structural units corresponding to the same molecule lumped component, wherein the sum of component content parameters of the matching structural units is equal to the analysis content of the corresponding molecule lumped component.
19. The apparatus of claim 17, wherein the physical property detection data indicates a physical property comprising one or more of the following: fraction density, distillation range, congealing point, refractive index, average molecular weight, viscosity.
20. The apparatus of any one of claims 11-19, wherein the molecular lumped component data comprises: molecular formula, type, hydrogen deficiency index and content of the molecular lumped components.
21. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 10 when executing the computer program.
22. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 10.
23. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1 to 10.
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