A method and system for screening of insulating oil base oils

Abstract

The application relates to the technical field of synthesis of power equipment insulating oil, and discloses a screening method and system for insulating oil base oil, wherein the method comprises the following steps: calculating theoretical index data corresponding to various performance indexes of a plurality of to-be-evaluated base oils according to the first principle; respectively calculating subjective weights and entropy weights corresponding to the various performance indexes; calculating a comprehensive weight index matrix of the to-be-evaluated base oils by using the subjective weights and the entropy weights; drawing radar charts corresponding to the to-be-evaluated base oils according to the comprehensive weight index matrix and the theoretical index data, and calculating evaluation values of the to-be-evaluated base oils according to the radar charts; and selecting a target base oil according to the evaluation values of the to-be-evaluated base oils. The application directly displays the various performances of different base oils in the form of the radar charts, realizes quantitative evaluation of the base oils in insulating oil synthesis raw materials, can directly screen the base oils according to the evaluation values of the base oils, and improves the screening efficiency of the insulating oil base oils.

Description

Technical Field

[0001] This invention relates to the technical field of insulating oil synthesis for power equipment, and more particularly to a method and system for screening base oils for insulating oil. Background Technology

[0002] Insulating oil is a material used for insulation and cooling of electrical equipment. It is usually synthesized from base oils, including highly refined mineral oils or synthetic oils, and special additives.

[0003] The synthesis process of insulating oil mainly includes base oil selection, additive selection, mixing and processing, as well as testing and quality control. Among these, selecting an appropriate base oil is crucial. The selection of base oil depends on many factors, including the required insulation performance, temperature range, chemical stability, availability, and cost. Depending on specific application requirements and economic considerations, choosing an appropriate base oil has a significant impact on the performance of the insulating oil and the quality of the final product.

[0004] Currently, the screening of insulating oil base oils mainly relies on human experience, which is highly subjective and random. It is easily affected by the limitations of personal experience and erroneous judgments, resulting in low efficiency in the screening of insulating oil base oils. Summary of the Invention

[0005] This invention provides a method and system for screening insulating oil base oils, which solves the technical problem that the current screening of insulating oil base oils relies on manual experience, resulting in low efficiency.

[0006] The first aspect of this invention provides a method for screening insulating oil base oils, comprising:

[0007] The theoretical index data corresponding to various performance indicators of multiple base oils to be evaluated were calculated according to first principles.

[0008] Calculate the subjective weight and entropy weight for each performance indicator separately;

[0009] The comprehensive weight index matrix of the base oil to be evaluated is calculated using the subjective weight and the entropy weight.

[0010] A radar chart is drawn for each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and the evaluation value of each base oil to be evaluated is calculated based on the radar chart.

[0011] Select the target base oil based on the stated evaluation value of each base oil to be evaluated.

[0012] Optionally, the theoretical index data corresponding to the various performance indicators of the base oil to be evaluated calculated according to first principles include:

[0013] Calculate the electron density of the base oil molecules to be evaluated according to first principles when they are distributed in the most stable structural configuration.

[0014] Based on the interaction function between electron density and electrostatic potential, the isosurface corresponding to the electron density is used to construct the molecular surface, and the electrostatic potential at each point on the molecular surface is calculated.

[0015] Based on the electron density and the electrostatic potential, calculate the microscopic data corresponding to each microscopic parameter of the base oil molecule to be evaluated;

[0016] Using the aforementioned microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil, the theoretical index data corresponding to various performance indicators of the base oil to be evaluated are calculated.

[0017] Optionally, the step of using the microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil to calculate the theoretical index data corresponding to various performance indicators of the base oil to be evaluated includes:

[0018] Obtain actual index data corresponding to various performance indicators of existing base oils and actual micro data corresponding to various micro parameters;

[0019] Calculate the Pearson correlation coefficient between the actual indicator data and the actual micro data, and remove the data in the actual micro data whose Pearson correlation coefficient meets the preset condition to obtain the sample micro data;

[0020] Based on the actual index data and the sample micro data, a preset structure-property relationship formula for various micro parameters and performance indicators of base oil is obtained by combining nonlinear regression calculation.

[0021] Using the preset structure-property relationship formula, the theoretical index data corresponding to various performance indicators of insulating oil base oil are calculated.

[0022] Optionally, the step of calculating the subjective weight and entropy weight corresponding to each performance index includes:

[0023] Construct the judgment matrix corresponding to each performance index according to the scaling method;

[0024] Using the aforementioned judgment matrix, the subjective weights corresponding to each performance index are calculated;

[0025] Based on the theoretical index data, calculate the entropy weights corresponding to each performance index.

[0026] Optionally, the formula for calculating the subjective weight includes:

[0027]

[0028]

[0029]

[0030] In the formula, D = [D1, D2, D3, ..., D n ] T Let n be the subjective weight, and a be the number of performance indicators of the base oil. ij Let be the element in the i-th row and j-th column of the judgment matrix A.

[0031] Optionally, the step of calculating the entropy weights corresponding to each performance index based on the theoretical index data includes:

[0032] The theoretical index data is standardized to obtain standardized theoretical index data.

[0033] Based on the standardized theoretical index data, calculate the entropy weights corresponding to each performance index.

[0034] Optionally, the formula for calculating the entropy weight includes:

[0035]

[0036]

[0037] In the formula, B is the entropy weight, b j Let y be the j-th column in B. ij Let m be the j-th element in the i-th row of the standardized theoretical index data, m be the number of base oils to be evaluated, and n be the number of performance indicators of the base oils.

[0038] Optionally, the calculation formula for the comprehensive weight index matrix includes:

[0039] C ij =(c ij ) 1×n =(λ1d j +λ2b j ) 1×n

[0040]

[0041] In the formula, C ij This is a comprehensive weighting index matrix, where D is the subjective weight, B is the entropy weight, λ1 is the first weight parameter, λ2 is the second weight parameter, and c... ij Let d be the element in row i and column j of C. j Let b be the j-th column in D. j Let be the j-th column in B, and n be the number of performance indicators of the base oil.

[0042] Optionally, the step of drawing a radar chart for each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and calculating the evaluation value of each of the base oils to be evaluated based on the radar chart, includes:

[0043] Based on the comprehensive weight index matrix, determine the corresponding angular region of each performance index in the radar chart;

[0044] Using the theoretical index data, points corresponding to various performance indicators of the same base oil to be evaluated are determined on the angle bisectors of each angle region of the radar chart and connected sequentially to form a radar chart corresponding to the base oil to be evaluated.

[0045] Construct radar charts for each of the base oils to be evaluated;

[0046] The evaluation value of each base oil to be evaluated is calculated based on the area and perimeter of the radar chart corresponding to each base oil to be evaluated.

[0047] A second aspect of the present invention provides a screening system for insulating oil base oils, comprising:

[0048] The theoretical data acquisition module is used to calculate the theoretical index data corresponding to various performance indicators of multiple base oils to be evaluated according to first principles.

[0049] The project weight calculation module is used to calculate the subjective weight and entropy weight corresponding to each performance indicator respectively;

[0050] The comprehensive weight calculation module is used to calculate the comprehensive weight index matrix of the base oil to be evaluated using the subjective weight and the entropy weight.

[0051] The evaluation value calculation module is used to draw radar charts corresponding to each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and to calculate the evaluation value of each of the base oils to be evaluated based on the radar charts.

[0052] The screening module is used to select target base oils based on the evaluation values ​​of each base oil to be evaluated.

[0053] As can be seen from the above technical solutions, the present invention has the following advantages:

[0054] This invention provides a method and system for screening base oils for insulating oils. The method includes calculating theoretical index data corresponding to various performance indicators of multiple base oils to be evaluated according to first principles; calculating subjective weights and entropy weights corresponding to each performance indicator; calculating a comprehensive weight index matrix of the base oils to be evaluated using subjective weights and entropy weights; drawing radar charts for each base oil to be evaluated based on the comprehensive weight index matrix and theoretical index data, and calculating the evaluation value of each base oil to be evaluated based on the radar charts; and selecting target base oils based on the evaluation values ​​of each base oil to be evaluated. This invention visually displays the various properties of different base oils through radar charts and achieves quantitative evaluation of base oils in the synthetic raw materials of insulating oils. It allows for direct screening of base oils based on their evaluation values, improving the efficiency of base oil screening for insulating oils. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 A flowchart illustrating the steps of a method for screening insulating base oils according to an embodiment of the present invention;

[0057] Figure 2 Radar charts for different base oils to be evaluated provided in embodiments of the present invention;

[0058] Figure 3 This is a structural block diagram of a screening system for insulating oil base oil provided in an embodiment of the present invention. Detailed Implementation

[0059] This invention provides a method and system for screening insulating oil base oils, which solves the technical problem that the current screening of insulating oil base oils relies on manual experience, resulting in low efficiency.

[0060] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0061] Please see Figure 1 , Figure 1This is a flowchart illustrating the steps of a method for screening insulating base oils according to Embodiment 1 of the present invention.

[0062] The present invention provides a method for screening insulating oil base oils, comprising the following steps 101 to 105:

[0063] Step 101: Calculate the theoretical index data corresponding to various performance indicators of the base oils to be evaluated according to first principles.

[0064] Understandably, the performance indicators of base oils can include indicators that affect the performance of synthesized insulating oils, such as relative insulation strength, molecular diffusion coefficient, heat dissipation performance, and molecular thermodynamic free energy.

[0065] In a preferred embodiment, step 101 includes the following sub-steps S11 to S14:

[0066] S11. Calculate the electron density of the base oil molecules to be evaluated according to first principles when they are distributed in the most stable structure.

[0067] The first-principles principles used in this invention are based on quantum chemical methods, and the functionals used are as follows:

[0068]

[0069] In the formula, For the local approximate electron kinetic energy, ∫d 3 rV ext ρ(r) is the external field energy. For related exchange items, E is the interaction energy between electrons. TF [ρ] represents the electron density of the most stable molecular structure of the base oil. By minimizing the above functional, we can obtain the electron density of the insulating oil molecules according to their most stable molecular structure.

[0070] S12. Based on the interaction function between electron density and electrostatic potential, construct the molecular surface by taking the isosurface corresponding to the electron density, and calculate the electrostatic potential at each point on the molecular surface.

[0071] Based on the general interaction properties function (GIPF) of electron density and electrostatic potential, an isosurface with a specific electron density is constructed to form a molecular surface. The electrostatic potential at each point r on this surface is:

[0072]

[0073] In the formula, v(r) is the electrostatic potential at each point r on the molecular surface, and Z... A R is the nuclear charge number.A Let r be the coordinates of atomic nucleus A, ρ(r') be the electron density at coordinate r', r be the spatial point being integrated, and r' be the position of each charge in the charge distribution.

[0074] S13. Based on the electron density and electrostatic potential, calculate the microscopic data corresponding to the various microscopic parameters of the base oil molecules to be evaluated.

[0075] It is understandable that, based on the electron density and electrostatic potential of the most stable structure distribution of base oil molecules, various microscopic parameters of the molecules can be calculated, including electrostatic surface area, van der Waals volume, molecular surface electrostatic potential, electrostatic potential energy deviation, positive and negative electrostatic potential balance parameters, diffusion coefficient, and molecular thermodynamic free energy.

[0076] Specifically, by comparing the electron density distribution with a given cutoff value, the electrostatic surface area within that cutoff range can be calculated; according to Barder's definition, the charge volume density is 1.08 × 10⁻⁶. 9 C / m 3 The isosurface is the van der Waals surface, from which the van der Waals volume of the molecule can be calculated. Based on the obtained electron density distribution, an electric multipole expansion is performed, decomposing the total volume charge of the molecule into different unipolar, bipolar, and tripolar electric multipole moments. These electric multipole moments are calculated using quantum chemistry software packages (such as Gaussian and GAMESS). A spherical grid or coordinate lattice is established around the molecule. For each point on the grid, the potential for interaction between the point and the various electric multipole moments within the molecule is calculated. Finally, the potential surface composed of the potential values ​​at all points is plotted, yielding the electrostatic potential map of the molecular surface of the substance. The electron density is used to simulate the molecular model of the base oil. In the simulation, the... Molecules move through collisions under certain temperature and pressure conditions. Tracking and recording the positions and interactions of molecules allows for the calculation of their average displacement by collecting position and velocity information during the simulation. Using classical mechanical motion theory, the relationship between the average displacement and time can be analyzed to calculate the diffusion coefficient. After calculating the most stable conformation after structural optimization, the molecular thermodynamic free energy ΔG can be calculated based on molecular structure, optimized vibrational frequencies, atomic mass, spin multiplicity, and other information (which can be obtained through quantum chemistry software). The balance of positive and negative electrostatic potentials in the base oil molecule's electrostatic potential equilibrium parameters can be calculated using the following formula:

[0077]

[0078] In the formula, ν represents the balance between positive and negative electrostatic potentials. These represent the positive and negative variances of the electrostatic potential and the total variance, respectively.

[0079] S14. Using microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil, calculate the theoretical index data corresponding to various performance indicators of the base oil to be evaluated.

[0080] It is understood that the pre-defined structure-property relationship formula refers to a structure-property relationship formula constructed using known data on various microscopic parameters and performance indicators of the base oil, which can characterize the relationship between various microscopic parameters and performance indicators of the base oil; specifically, step S14 may include the following sub-steps S141 to S144:

[0081] S141. Obtain the actual performance data of existing base oil and the actual micro data of its various micro parameters.

[0082] S142. Calculate the Pearson correlation coefficient between the actual indicator data and the actual micro data, remove the data in the actual micro data whose Pearson correlation coefficient meets the preset conditions, and obtain the sample micro data.

[0083] Specifically, removing data in the actual micro-data that meet the preset conditions for Pearson correlation coefficient can be done by deleting micro-data that contradicts the structure-activity relationship (low Pearson correlation coefficient), and / or deleting the item with the lower Pearson correlation coefficient among micro-data that have consistent pairwise correlation, and retaining only the item with stronger correlation.

[0084] S143. Based on actual index data and sample micro data, and combined with nonlinear regression calculation, the preset structure-property relationship formulas of various micro parameters and various performance indicators of base oil are obtained.

[0085] S144. Using the preset structure-property relationship formula, calculate the theoretical index data corresponding to various performance indicators of the insulating oil base oil.

[0086] Step 102: Calculate the subjective weight and entropy weight corresponding to each performance index.

[0087] Specifically, step 102 includes:

[0088] S21. Construct the judgment matrix corresponding to each performance index according to the scaling method.

[0089] The evaluation object layer is determined to be the insulating liquid base oil. The quality of the target layer insulating oil is then clearly defined. An evaluation index layer for the subsystem is established. The importance of each performance index under the target is compared pairwise using a scaling method, and a value of 'a' is assigned. ij This indicates the relative importance of the i-th performance indicator compared to the j-th performance indicator, resulting in the judgment matrix A.

[0090] S22. Using a judgment matrix, calculate the subjective weights corresponding to each performance index.

[0091] The formulas for calculating subjective weights include:

[0092]

[0093]

[0094]

[0095] In the formula, D = [D1, D2, D3, ..., D n ] T For subjective weights, n is the number of performance indicators of the base oil, and a is the number of indicators. ij To determine the element in the i-th row and j-th column of matrix A;

[0096] It should be noted that after constructing the judgment matrix A and calculating the subjective weights, a consistency check can be performed on the judgment matrix, as shown in the following formula:

[0097]

[0098]

[0099] In the formula, λ is the eigenvalue, and AI is the consistency check index. If AI = 0, then there is complete consistency; otherwise, it is 1.

[0100] S23. Based on the theoretical index data, calculate the entropy weights corresponding to each performance index.

[0101] Specifically, step S23 includes the following sub-steps S231 to S232:

[0102] S231. Standardize the theoretical index data to obtain standardized theoretical index data:

[0103] The original data sample matrix of the theoretical indicator data is: X ij =(x ij ) m×n The standardized calculation formula is as follows:

[0104]

[0105] In the formula, Y ij For standardized theoretical index data, m is the number of base oils to be evaluated, and n is the number of performance indicators of the base oils.

[0106] S232. Calculate the entropy weights corresponding to each performance index based on standardized theoretical index data.

[0107] The formula for calculating entropy weight includes:

[0108]

[0109]

[0110] In the formula, B is the entropy weight, b j Let y be the j-th column in B. ij Let m be the j-th element in the i-th row of the standardized theoretical index data, m be the number of base oils to be evaluated, and n be the number of performance indicators of the base oils.

[0111] Step 103: Calculate the comprehensive weighting index matrix of the base oil to be evaluated using subjective weighting and entropy weighting:

[0112] The formula for calculating the comprehensive weight index matrix includes:

[0113] C ij =(c ij ) 1×n =(λ1d j +λ2b j ) 1×n

[0114]

[0115] In the formula, C ij This is a comprehensive weighting index matrix, where D represents subjective weights, B represents entropy weights, λ1 is the first weight parameter, λ2 is the second weight parameter, and c... ij Let d be the element in row i and column j of C. j Let b be the j-th column in D. j Let be the j-th column in B, and n be the number of performance indicators of the base oil.

[0116] Step 104: Draw a radar chart for each base oil to be evaluated according to the comprehensive weight index matrix and theoretical index data, and calculate the evaluation value of each base oil to be evaluated based on the radar chart.

[0117] Specifically, step 104 includes the following sub-steps S41 to S44:

[0118] S41. Based on the comprehensive weight index matrix, determine the corresponding angular region of each performance index in the radar chart.

[0119] Determine the center point of the radar chart, and draw a ray of one unit length vertically upward from the center point. Based on the first ray, convert the comprehensive weight index value corresponding to the first performance index in the comprehensive weight index matrix into an angle θ1. Use this angle to draw the second ray, and similarly draw the remaining rays. The formula for calculating the angle θ converted from the comprehensive weight index value is as follows:

[0120] θ = 360°C

[0121] S42. Using theoretical index data, determine the points corresponding to various performance indicators of the same base oil to be evaluated on the angle bisectors of each angular region of the radar chart, and connect them sequentially to form the radar chart corresponding to the base oil to be evaluated.

[0122] Starting from the center point, draw the angle bisectors of each sector's angle region. The length of the angle bisector is the theoretical performance index data of the base oil to be evaluated for that angle region. Connect the end points of the angle bisectors of each angle region in sequence to form a radar chart for the base oil to be evaluated. The radar chart can intuitively display the performance of the base oil to be evaluated.

[0123] S43. Construct radar charts for each base oil to be evaluated.

[0124] S44. Calculate the evaluation value of each base oil to be evaluated based on the area and perimeter of the radar chart corresponding to each base oil to be evaluated.

[0125] The formula for calculating the evaluation value is as follows:

[0126]

[0127] In the formula, t is the evaluation value, L is the perimeter of the radar image, and S is the area of ​​the radar image.

[0128] Step 105: Select the target base oil based on the evaluation value of each base oil to be evaluated.

[0129] Understandably, the base oil with the highest evaluation value among the base oils to be evaluated can be selected as the raw material for synthetic insulating oil, i.e., the target base oil.

[0130] In Embodiment 1 of this invention, theoretical index data of various performance indicators of the base oil to be evaluated are first obtained through first-principles calculations. Then, radar charts corresponding to different base oils to be evaluated are drawn based on the theoretical index data. The evaluation values ​​of different base oils to be evaluated are then calculated based on the corresponding radar charts, thereby screening multiple base oils to be evaluated. The radar charts intuitively display the various properties of different base oils and realize the quantitative evaluation of base oils in insulating oil synthesis raw materials. Base oils can be directly screened based on the evaluation values, thus improving the efficiency of insulating oil base oil screening.

[0131] In a specific embodiment, taking the selection of soybean oil, rapeseed oil, cottonseed oil, and peanut oil as an example, the screening method for insulating oil base oil provided by the present invention includes:

[0132] Step 201: Based on first principles, use quantum chemical methods to calculate the theoretical index data corresponding to various performance indicators of base oils for various insulating oils. The calculation formulas are as follows:

[0133]

[0134] in, For the local approximate electron kinetic energy, ∫d 3 rV ext ρ(r) is the external field energy. For related exchange items, E is the interaction energy between electrons. TF [ρ] represents the electron density of the base oil molecules in their most stable structural distribution. Minimizing the above functional yields the electron density of the base oil molecules in their most stable structural distribution.

[0135] Based on the general interaction properties function (GIPF) of electron density and electrostatic potential, an isosurface with a specific electron density is constructed to form a molecular surface. The electrostatic potential at each point r on this surface is...

[0136]

[0137] In the formula: v(r) is the electrostatic potential at each point r on the molecular surface, Z A R is the nuclear charge number. A Let r be the coordinates of atomic nucleus A, ρ(r') be the electron density at coordinate r', r be the spatial point being integrated, and r' be the position of each charge in the charge distribution.

[0138] It is understandable that, based on the electron density of the most stable molecular structure of the base oil, various microscopic parameters of the molecule can be calculated, including electrostatic surface area, van der Waals volume, molecular surface electrostatic potential, electrostatic potential energy deviation, positive and negative electrostatic potential balance parameters, diffusion coefficient, and molecular thermodynamic free energy. Based on first principles, the structure-property relationship formulas between base oil performance indicators and microscopic parameters can be used to calculate the various performance indicators of the base oil in the examples. In this example, some of the calculation formulas used are as follows:

[0139]

[0140] FP = 0.3180ΔG + 4.406μ - 103.6

[0141] In the formula, Er is the relative insulation strength. The surface area represents the molecular electrostatic potential. The balance between positive and negative electrostatic potentials. Let F be the variance of the molecular surface electrostatic potential, π be the average variance of the molecular electrostatic potential, and F be the variance of the surface electrostatic potential. P The heat dissipation performance of the base oil is given by ΔG, where ΔG is the molecular thermodynamic free energy and μ is the molecular dipole moment.

[0142] It is understandable that, due to different base oil databases, the actual index data corresponding to the various performance indicators of existing base oils and the actual microscopic data corresponding to various microscopic parameters may be different. The optimal structure and frequency constructed by calculating the molecular structure may be different, and the selected microscopic parameter data may also be different, resulting in different formulas for obtaining the structure-property relationship. However, the method is consistent, and the structure-property relationship obtained under the same conditions, as well as the data and conclusions obtained, are also consistent.

[0143] Step 202: Construct the judgment matrix corresponding to each performance index according to the scaling method, including the following steps:

[0144] The evaluation target layer is determined to be the synthetic base oil of the insulating fluid. The quality of the target layer insulating oil is then clearly defined, and an evaluation index layer for the subsystem is established, including relative insulation strength, molecular diffusion coefficient, relative heat dissipation performance, and molecular thermodynamic free energy. Specific theoretical index data X are also provided. ij The (normalized values) are as follows:

[0145] Table 1. Theoretical data of various performance indicators for soybean oil, rapeseed oil, cottonseed oil, and peanut oil.

[0146] Relative insulation strength Molecular diffusion coefficient Heat dissipation performance Molecular thermodynamic free energy soybean oil 1 0.6854 1 0.9825 rapeseed oil 0.9917 0.8714 0.8142 0.9649 cottonseed oil 0.8725 1 0.9418 0.9825 Peanut oil 0.9553 0.4621 0.9212 1

[0147] The importance of each performance indicator under the target is compared pairwise using a scaling method, and a value of a is assigned to each. ij Let represent the relative importance of the i-th performance metric compared to the j-th performance metric, and construct a judgment matrix A. Here, we define a... 12 =2.448, a 23 =1.44, a 34 =1.1, then the judgment matrix A is as follows:

[0148] Table 2 Judgment Matrix Between Various Performance Indicators

[0149]

[0150] Step 203: Calculate the subjective weights of each performance index based on the judgment matrix A, and perform a consistency check on the judgment matrix A using the following formula:

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] In the formula, D = [D1, D2, D3, ..., D n ] T For subjective weights, n is the number of performance indicators of the base oil, and a is the number of indicators. ij To determine the element in the i-th row and j-th column of matrix A, λ is the eigenvalue, and AI is the consistency check index. If AI = 0, then it has complete consistency; otherwise, it is 1.

[0157] The calculated value is D = [0.5128, 0.2096, 0.1454, 0.1322]. T .

[0158] Step 204: Based on the theoretical index data, calculate the entropy weights corresponding to each performance index, including the following steps:

[0159] The theoretical index data is standardized to obtain standardized theoretical index data:

[0160] The original data sample matrix of the theoretical indicator data is: X ij =(x ij ) m×n The standardized calculation formula is as follows:

[0161]

[0162] In the formula, Y ij For standardized theoretical index data, m is the number of base oils to be evaluated, and n is the number of performance indicators of the base oils.

[0163] The calculated standardized matrix Y is as follows:

[0164] Table 3 Standardization Theoretical Indicator Data

[0165] 0.2618 0.2270 0.2719 0.2500 0.2596 0.2886 0.2214 0.2455 0.2284 0.3119 0.2561 0.2500 0.2502 0.1725 0.2506 0.2545

[0166] The entropy weights corresponding to each performance index are calculated using the following formula:

[0167]

[0168]

[0169] In the formula, B is the entropy weight, b j Let y be the j-th column in B. ij Let m be the number of base oils to be evaluated, n be the number of performance indicators of the base oils, and H be the element in the i-th row and j-th position of the standardized theoretical index data. j for.

[0170] The calculated value is B = [0.9989, 0.9823, 0.9331, 0.9999]. T .

[0171] Step 205: Using subjective weighting and entropy weighting, calculate the comprehensive weight index matrix of the base oil to be evaluated. The calculation formula is as follows:

[0172] C j =(c j ) 1×n =(λ1d j +λ2b j ) 1×n

[0173]

[0174] In the formula, C j This is a comprehensive weighting index matrix, where D represents subjective weights, B represents entropy weights, λ1 is the first weight parameter, λ2 is the second weight parameter, and c... j Let d be the element in the j-th column of C. j Let b be the j-th column in D. j Let be the j-th column in B, and n be the number of performance indicators of the base oil.

[0175] The calculated comprehensive weight index matrix C = [0.5122, 0.2059, 0.1497, 0.1422] T .

[0176] Step 206: Visually represent the comprehensive weight index matrix C using the radar chart method, and use the geometric mean of the two characteristic quantities of the radar chart, area S and perimeter L, as the final evaluation value. This includes the following steps:

[0177] Determine the center point of the radar chart, and draw a ray of unit length vertically upwards from the center point. Based on the first ray, convert the comprehensive weight index value corresponding to the first performance index in the comprehensive weight index matrix into an angle θ1. Draw the second ray using this angle, and similarly draw the remaining rays. The rays can be denoted as OA, OB, ... The formula for calculating the angle θ converted from the comprehensive weight index value is as follows:

[0178] θ = 360°C

[0179] Starting from the center point, draw the angle bisectors of each sector's angle region. The length of the angle bisector is the theoretical performance index data of the base oil to be evaluated for that angle region. The angle bisectors can be denoted as OP1, OP2, ...;

[0180] Connect the endpoints of the angle bisectors of each angular region sequentially to form the radar chart corresponding to the base oil to be evaluated. Calculate the area S and perimeter L of the radar chart, and form the final judgment index t. The calculation formula is as follows:

[0181]

[0182] For radar charts of each base oil to be evaluated, please refer to [link / reference]. Figure 2 The evaluation values ​​for soybean oil, rapeseed oil, cottonseed oil, and peanut oil were t1 = 7.183, t2 = 6.962, t3 = 7.696, and t4 = 5.727, respectively. The final order of suitable insulating oil selection was cottonseed oil > soybean oil > rapeseed oil > peanut oil.

[0183] Please see Figure 3 Embodiment 2 of the present invention provides a screening system for insulating oil base oil, comprising:

[0184] The theoretical data acquisition module 301 is used to calculate the theoretical index data corresponding to various performance indicators of various base oils to be evaluated according to first principles.

[0185] Project weight calculation module 302 is used to calculate the subjective weight and entropy weight corresponding to each performance indicator respectively;

[0186] The comprehensive weight calculation module 303 is used to calculate the comprehensive weight index matrix of the base oil to be evaluated using subjective weight and entropy weight.

[0187] The evaluation value calculation module 304 is used to draw a radar chart corresponding to each base oil to be evaluated according to the comprehensive weight index matrix and theoretical index data, and to calculate the evaluation value of each base oil to be evaluated based on the radar chart.

[0188] The screening module 305 is used to select the target base oil based on the evaluation value of each base oil to be evaluated.

[0189] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0190] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0191] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0192] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0193] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0194] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening insulating oil base oils, characterized in that, include: The theoretical index data corresponding to various performance indicators of multiple base oils to be evaluated were calculated according to first principles. Calculate the subjective weight and entropy weight for each performance indicator separately; The comprehensive weight index matrix of the base oil to be evaluated is calculated using the subjective weight and the entropy weight. A radar chart is drawn for each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and the evaluation value of each base oil to be evaluated is calculated based on the radar chart. Select the target base oil based on the stated evaluation value of each base oil to be evaluated; The theoretical performance data corresponding to the various performance indicators of the base oil to be evaluated were calculated according to first principles, including: Calculate the electron density of the base oil molecules to be evaluated according to first principles when they are distributed in the most stable structural configuration. Based on the interaction function between electron density and electrostatic potential, the isosurface corresponding to the electron density is used to construct the molecular surface, and the electrostatic potential at each point on the molecular surface is calculated. Based on the electron density and the electrostatic potential, calculate the microscopic data corresponding to each microscopic parameter of the base oil molecule to be evaluated; Using the aforementioned microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil, the theoretical index data corresponding to various performance indicators of the base oil to be evaluated are calculated. The performance indicators include relative insulation strength, molecular diffusion coefficient, heat dissipation performance, and molecular thermodynamic free energy; the microscopic parameters include electrostatic surface area, van der Waals volume, molecular surface electrostatic potential, electrostatic potential energy deviation, positive and negative electrostatic potential balance parameters, diffusion coefficient, and molecular thermodynamic free energy.

2. The method for screening insulating oil base oil according to claim 1, characterized in that, The process involves using the microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil to calculate the theoretical index data corresponding to each performance indicator of the base oil to be evaluated, including: Obtain actual index data corresponding to various performance indicators of existing base oils and actual micro data corresponding to various micro parameters; Calculate the Pearson correlation coefficient between the actual indicator data and the actual micro data, and remove the data in the actual micro data whose Pearson correlation coefficient meets the preset condition to obtain the sample micro data; Based on the actual index data and the sample micro data, a preset structure-property relationship formula for various micro parameters and performance indicators of base oil is obtained by combining nonlinear regression calculation. Using the preset structure-property relationship formula, the theoretical index data corresponding to various performance indicators of insulating oil base oil are calculated.

3. The method for screening insulating oil base oil according to claim 1, characterized in that, The calculation of the subjective weight and entropy weight corresponding to each performance index includes: Construct the judgment matrix corresponding to each performance index according to the scaling method; Using the aforementioned judgment matrix, the subjective weights corresponding to each performance index are calculated; Based on the theoretical index data, calculate the entropy weights corresponding to each performance index.

4. The method for screening insulating oil base oil according to claim 3, characterized in that, The formula for calculating the subjective weight includes: In the formula, D =[ D 1 , D 2 , D 3 , … , D n ] T The subjective weight, n These are the numbers of performance indicators for base oils. a ij The judgment matrix A The Middle i Line 1 j The elements of the column.

5. The method for screening insulating oil base oil according to claim 3, characterized in that, The step of calculating the entropy weights corresponding to each performance index based on the theoretical index data includes: The theoretical index data is standardized to obtain standardized theoretical index data. Based on the standardized theoretical index data, calculate the entropy weights corresponding to each performance index.

6. The method for screening insulating oil base oil according to claim 5, characterized in that, The formula for calculating the entropy weight includes: In the formula, B For the entropy weight, b j for B The first in j List, y ij The first of the standardized theoretical index data i Line 1 j One element, m The number of base oils to be evaluated. n These are the numbers of performance indicators for base oils.

7. The method for screening insulating oil base oil according to claim 1, characterized in that, The calculation formula for the comprehensive weight index matrix includes: In the formula, C ij This is a comprehensive weighted index matrix. D The subjective weight, B For the entropy weight, λ 1 is the first weight parameter. λ 2 is the second weighting parameter, c ij for C The Middle i Line 1 j Column elements, d j for D The first in j List, b j for B The first in j List, n These are the numbers of performance indicators for base oils.

8. The method for screening insulating oil base oil according to claim 1, characterized in that, The step of drawing radar charts for each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and calculating the evaluation value of each of the base oils to be evaluated based on the radar charts, includes: Based on the comprehensive weight index matrix, determine the corresponding angular region of each performance index in the radar chart; Using the theoretical index data, points corresponding to various performance indicators of the same base oil to be evaluated are determined on the angle bisectors of each angle region of the radar chart and connected sequentially to form a radar chart corresponding to the base oil to be evaluated. Construct radar charts for each of the base oils to be evaluated; The evaluation value of each base oil to be evaluated is calculated based on the area and perimeter of the radar chart corresponding to each base oil to be evaluated.

9. A screening system for insulating oil base oils, characterized in that, include: The theoretical data acquisition module is used to calculate the theoretical index data corresponding to various performance indicators of multiple base oils to be evaluated according to first principles. The project weight calculation module is used to calculate the subjective weight and entropy weight corresponding to each performance indicator respectively. The comprehensive weight calculation module is used to calculate the comprehensive weight index matrix of the base oil to be evaluated using the subjective weight and the entropy weight. The evaluation value calculation module is used to draw radar charts corresponding to each of the base oils to be evaluated according to the comprehensive weight index matrix and the theoretical index data, and to calculate the evaluation value of each of the base oils to be evaluated based on the radar charts. A screening module is used to select target base oils based on the evaluation values ​​of each base oil to be evaluated; The theoretical data acquisition module is specifically used for: Calculate the electron density of the base oil molecules to be evaluated according to first principles when they are distributed in the most stable structural configuration. Based on the interaction function between electron density and electrostatic potential, the isosurface corresponding to the electron density is used to construct the molecular surface, and the electrostatic potential at each point on the molecular surface is calculated. Based on the electron density and the electrostatic potential, calculate the microscopic data corresponding to each microscopic parameter of the base oil molecule to be evaluated; Using the aforementioned microscopic data and the preset structure-property relationship formulas for various microscopic parameters and performance indicators of the base oil, the theoretical index data corresponding to various performance indicators of the base oil to be evaluated are calculated. The performance indicators include relative insulation strength, molecular diffusion coefficient, heat dissipation performance, and molecular thermodynamic free energy; the microscopic parameters include electrostatic surface area, van der Waals volume, molecular surface electrostatic potential, electrostatic potential energy deviation, positive and negative electrostatic potential balance parameters, diffusion coefficient, and molecular thermodynamic free energy.

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