Method, device, terminal and medium for constructing digital twin simulation model of power equipment

Abstract

The present application discloses a method, device, terminal and medium for constructing a digital twin simulation model of a power device. The solution provided by the present application first constructs a geometric model of the target power device, then establishes multiple physical field models related to the target power device, determines the type of coupling relationship between different physical field models according to the field quantity change relationship between different physical field models, and then constructs a physical field coupling relational expression according to different coupling relationship types to achieve the purpose of coupling multiple physical fields. Then, through the simulation test method, the material change characteristic data of the target power device is obtained to construct the material characteristic function of the target power device, and the material characteristic function is subjected to Taylor expansion and linear approximation processing to complete the material characteristic mapping, so as to obtain the digital twin simulation model of the target power device, realize the lightweight reconstruction of the power device in the multi-physical field coupling scenario, and solve the technical problem of low modeling efficiency of the existing digital twin model of the power device.

Description

Technical Field

[0001] The present application relates to the technical field of digital twin modeling, and particularly relates to a method, device, terminal and medium for constructing a digital twin simulation model of a power device. Background Art

[0002] With the gradual transition of the digital power grid from theoretical research to application practice, higher requirements are put forward for the standardization, usability, comprehensiveness, etc. of the digitization of power devices. Studying the digital twin of power devices and creating a digital power device model system are the main directions for realizing the digital power grid.

[0003] The digital twin model of a power device needs to perform simulation analysis on the state of the device. However, the interior of the power device is affected by multiple fields, the number of control equations is large, and they are mutually coupled. If high-precision simulation is to be achieved and modeled according to the current conventional simulation modeling method, the twin model will be complex, thereby reducing the modeling efficiency of the digital twin model. Summary of the Invention

[0004] The present application provides a method, device, terminal and medium for constructing a digital twin simulation model of a power device, which are used to solve the technical problem of low modeling efficiency of the existing digital twin model of a power device.

[0005] To solve the above technical problem, the first aspect of the present application provides a method for constructing a digital twin simulation model of a power device, including:

[0006] Based on the structural characteristics of the target power device, construct a geometric model corresponding to the target power device;

[0007] Based on the geometric model, combine classical physical laws and the device characteristic working condition characteristics and material degradation characteristics of the target power device to establish multiple physical field models of the target power device;

[0008] According to the field quantity change relationship between different physical field models, determine the type of coupling relationship between the different physical field models. According to the type of coupling relationship, combine the corresponding relationship between the coupling relationship type and the physical field coupling relationship formula and the coupling variables between different physical field models to construct the physical field coupling relationship formula between the different physical field models;

[0009] Based on the physical field coupling relationship formula, through a simulation test method, obtain the material change characteristic data of the target power device, fit the material change characteristic data, and construct a material characteristic function of the target power device based on the fitting result;

[0010] The Taylor expansion of the material property function is performed according to the principle of virtual work, and then the material property function is linearly approximated according to the chain rule to obtain the digital twin simulation model of the target power equipment.

[0011] Preferably, constructing the geometric model corresponding to the target power equipment specifically includes:

[0012] Based on the structural characteristics of the target power equipment, the layout boundary and layout density are determined through a preset distance function and density function;

[0013] Based on the layout boundary and the layout density, geometric modeling layout is carried out, and then a Delaunay triangulation is formed based on the laid discrete points, and the discrete points outside the Delaunay triangulation area are updated to the boundary of the Delaunay triangulation through a preset discrete point correction formula;

[0014] According to the updated Delaunay triangulation, the edge center points and area center points of each triangular area in the Delaunay triangulation are extracted respectively;

[0015] According to each of the edge center points and each of the area center points, each triangular area is divided into multiple sub-areas;

[0016] According to the node sets and boundary information of each sub-area, the geometric model corresponding to the target power equipment is formed.

[0017] Preferably, after each triangular area is divided into multiple sub-areas, it further includes:

[0018] Calculate the distance values between each of the edge center points and the sub-area boundaries, and update the edge center points with distance values lower than the preset distance threshold to the sub-area boundaries through the discrete point correction formula.

[0019] Preferably, the types of coupling relationships include: strong coupling relationship type and weak coupling relationship type.

[0020] Preferably, the physical field coupling relational expression corresponding to the strong coupling relationship type is specifically:

[0021]

[0022] In the formula, K A is the field quantity coefficient matrix of physical field A, K B is the field quantity coefficient matrix of physical field B, C A-B is the influence coefficient matrix of physical field A on physical field B, C B-A is the influence coefficient matrix of physical field B on physical field A, f A represents the mathematical model equation of physical field A model, f BThe mathematical model equation representing the B physical field model, f A (u A ) represents the mathematical model equation in the A physical field affected by the parameter u, f B (u B ) represents the mathematical model equation in the B physical field affected by the parameter u.

[0023] Preferably, the physical field coupling relation formula corresponding to the weak coupling relation type is specifically:

[0024] K B u B = f B + f A (u A )

[0025] In the formula, K B is the field quantity coefficient matrix of the B physical field, f A represents the mathematical model equation of the A physical field model, f B represents the mathematical model equation of the B physical field model, f A (u A ) represents the mathematical model equation in the A physical field affected by the parameter u.

[0026] Preferably, before constructing the material characteristic function of the target power equipment, it further includes:

[0027] Performing error verification on the material characteristic function. If the error verification result meets the preset error requirements, output the material characteristic function. If the error verification result does not meet the preset error requirements, perform conformal interpolation fitting on the material change characteristic data, and reconstruct the material characteristic function of the target power equipment based on the fitting result.

[0028] The second aspect of the present application provides a power equipment digital twin simulation model construction device, including:

[0029] A geometric model construction unit, configured to construct the geometric model corresponding to the target power equipment based on the structural characteristics of the target power equipment;

[0030] A physical field model construction unit, configured to establish multiple physical field models of the target power equipment based on the geometric model, in combination with classical physical laws and the equipment characteristic working conditions and material degradation characteristics of the target power equipment;

[0031] A physical field coupling relationship determination unit is configured to determine the coupling relationship type between different physical field models according to the field quantity change relationship between different physical field models, and construct the physical field coupling relationship between different physical field models according to the coupling relationship type, in combination with the corresponding relationship between the coupling relationship type and the physical field coupling relationship formula and the coupling variables between different physical field models;

[0032] A material property change function construction unit is configured to obtain the material change property data of a target power device through a simulation test method based on the physical field coupling relationship formula, fit the material change property data, and construct the material property function of the target power device based on the fitting result;

[0033] A material property mapping unit is configured to perform Taylor expansion on the material property function according to the principle of virtual work, and then perform linear approximation processing on the material property function according to the chain rule to obtain the digital twin simulation model of the target power device.

[0034] The third aspect of the present application provides a terminal for constructing a digital twin simulation model of a power device, including: a memory and a processor;

[0035] The memory is used to store program codes corresponding to a method for constructing a digital twin simulation model of a power device as described in the first aspect of the present application;

[0036] The processor is used to execute the program codes.

[0037] The fourth aspect of the present application provides a computer-readable storage medium, in which program codes corresponding to a method for constructing a digital twin simulation model of a power device as described in the first aspect of the present application are stored.

[0038] From the above technical solutions, it can be seen that the present application has the following advantages:

[0039] The simulation model construction method provided by this application is divided into a geometric model construction stage, a physical field coupling relationship establishment stage, and a material property mapping stage. First, based on the structural characteristics of the target power equipment, the corresponding geometric model is constructed. Then, combined with classical physical laws and the equipment characteristic operating conditions and material degradation characteristics of the target power equipment, multiple physical field models related to the target power equipment are established. According to the field quantity change relationship between different physical field models, the coupling relationship type between different physical field models is determined. Then, according to different coupling relationship types, physical field coupling relational expressions are constructed to achieve the purpose of coupling multiple physical fields. Furthermore, through simulation test methods, the material change characteristic data of the target power equipment are obtained to construct the material property function of the target power equipment. The Taylor expansion and linear approximation processing of this material property function are performed to complete the material property mapping, so as to obtain the digital twin simulation model of the target power equipment. Moreover, the model constructed by the technical solution of this application controls the simulation quantity more simply, realizes the lightweight reconstruction of the heating power equipment in a multi-physical field coupling scenario, and solves the technical problem of the low modeling efficiency of the existing digital twin model of power equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a schematic flowchart of an embodiment of a method for constructing a digital twin simulation model of power equipment provided by this application.

[0042] Figure 2 It is a schematic flowchart of an embodiment of the geometric model construction process of a method for constructing a digital twin simulation model of power equipment provided by this application.

[0043] Figure 3 It is a schematic diagram of the correlation relationships of various physical fields related to power equipment.

[0044] Figure 4 It is a schematic diagram of the multi-physical field coupling equation relationship of the electric field, temperature field, and moisture field of a transformer bushing.

[0045] Figure 5 It is a schematic structural diagram of an embodiment of a device for constructing a digital twin simulation model of power equipment provided by this application.

[0046] Figure 6 It is a schematic structural diagram of an embodiment of a terminal for constructing a digital twin simulation model of power equipment provided by this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The embodiments of the present application provide a method, device, terminal and medium for constructing a digital twin simulation model of a power device, which are used to solve the technical problem of low modeling efficiency of the existing digital twin model of a power device.

[0048] In order to make the objectives, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the embodiments described below are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0049] First, a detailed description of an embodiment of the method for constructing a digital twin simulation model of a power device provided by the present application is as follows:

[0050] Please refer to Figure 1 , a method for constructing a digital twin simulation model provided by this embodiment includes:

[0051] Step 101: Based on the structural characteristics of the target power device, construct a geometric model corresponding to the target power device.

[0052] It should be noted that step 101 of this embodiment corresponds to the geometric model construction stage of this simulation model construction method. For the target power device to be modeled, such as umbrella skirts, transformer bushings, etc., based on the structural characteristics of the target power device, a geometric model corresponding to the target power device is constructed.

[0053] More specifically, as Figure 2 shown, the process of constructing a geometric model corresponding to the target power device may specifically include:

[0054] Step 1011: Based on the structural characteristics of the target power device, determine the point distribution boundary and point distribution density through preset distance functions and density functions;

[0055] Step 1012: Perform geometric modeling point distribution based on the point distribution boundary and point distribution density, then form a Delaunay triangulation based on the distributed discrete points, and update the discrete points outside the Delaunay triangulation region to the boundary of the Delaunay triangulation through a preset discrete point correction formula;

[0056] Step 1013: According to the updated Delaunay triangulation, extract the edge center points and region center points of each triangular region in the Delaunay triangulation respectively;

[0057] Step 1014: Divide each triangular region into multiple sub-regions according to each edge center point and each region center point;

[0058] Step 1015: Based on the node sets and boundary information of each sub-region, form the geometric model corresponding to the target power equipment.

[0059] It should be noted that the geometric model construction process in step 101 of this embodiment can be divided into three stages: point distribution, triangulation, and geometric dissection. Among them, step 1011 corresponds to the point distribution stage, and the boundary is defined by using a distance function: fd(x) = 0 is the boundary; fd(x) < 0 is the solution region; fd(x) > 0 is the non-solution region. The density of points is controlled by using a density function: fh(x) > 0 represents the minimum distance between points and is the density of control points. Two methods of adaptive density are proposed, one is distance adaptive density and the other is width adaptive density. For distance adaptive density, the closer to the boundary, the greater the density; for width adaptive density, the narrower the place, the greater the density.

[0060] Step 1012 corresponds to the triangulation stage, and form a Delaunay triangulation network based on the discrete points in step 1011. Then, according to the discrete point correction formula, the points outside the region are modified and updated to the boundary. The specific expression of the discrete point correction formula is as follows:

[0061]

[0062]

[0063] In the formula, fd(x e ,y e ,z e ) represents the point with coordinate value (x e ,y e ,z e ). Δx, Δy, and Δz are the offsets of the coordinate point fd(x e ,y e ,z e ) from the boundary. (x e ,y e ,z e ) is the coordinate point before update, is the coordinate point after update.

[0064] Steps 1013 to 1015 correspond to the geometric dissection stage. The specific process can be referred to the following example:

[0065] 1) Extract the triangular mesh edge information in step 1012 to obtain triEdg.

[0066] 2) Add new nodes, calculate the center of each triangle side and put it into the new point set point_middle; calculate the center of each triangle and put it into the new point set point_center.

[0067] 3) Mesh conversion: loop through each new triangular element, divide it into three quadrilaterals. The nodes of the quadrilaterals include the center point of the triangle in the point set point_center, the nodes of the corresponding angles of the triangle, and the midpoints of the corresponding sides in the point set point_middle, to obtain the element list elequad.

[0068] 4) Extract the boundary: arrange the elements of each row in the elequad list in order and remove duplicate rows, calculate the distance function of the midpoints of the edges. Add the edges with a function value of 0 to the boundary list bdy.

[0069] 5) Result output: output the node set of the quadrilateral nquad = (ntri, npoint_middle, npoint_center), the element list elequad, and the boundary list bdy to form the geometric model corresponding to the target power equipment.

[0070] Furthermore, after the mesh conversion in step 1014, it can further include:

[0071] Step 10140: Calculate the distance values between the center points of each edge and the boundary of the sub-region, and update the center points of the edges with distance values lower than the preset distance threshold to the boundary of the sub-region through the discrete point correction formula.

[0072] It should be noted that in the point set point_middle, search for the nodes with distance values lower than a certain threshold from the boundary of the sub-region according to the distance function fd, and move the nodes near the boundary to the boundary according to the discrete point correction formula in step 1012 to obtain a better boundary approximation.

[0073] Step 102: Based on the geometric model, combined with the classical physical laws and the equipment characteristic operating conditions and material degradation characteristics of the target power equipment, establish multiple physical field models of the target power equipment.

[0074] Step 103: Determine the type of coupling relationship between different physical field models according to the field quantity change relationship between different physical field models. According to the type of coupling relationship, combined with the corresponding relationship between the type of coupling relationship and the physical field coupling formula and the coupling variables between different physical field models, construct the physical field coupling formula between different physical field models.

[0075] It should be noted that steps 102 and 103 of this embodiment correspond to the physical field coupling relationship establishment stage. Based on the geometric model constructed in step 101, multiple physical field models of the target power equipment are established by combining classical physical laws and the equipment characteristic operating conditions and material degradation characteristics of the target power equipment, including but not limited to: structural field, temperature field, electric field, magnetic field, etc. The specific physical field type can be determined according to the physical properties involved in the specific target power equipment and will not be limited here.

[0076] Analyze the coupling action relationship and their correlation patterns among the multi-physical fields of the equipment. It can be known from the theory of mathematical physics equations that a physical field is determined by control equations (including constitutive relations, excitation sources), boundary conditions, etc. The coupling of multiple physical fields also occurs through the coupling of these elements and affects each other. Taking the internal insulation structure of the bushing as an example, affected by multiple physical fields, single field quantity analysis cannot meet the requirements of the project. This requires determining the coupling relationship between each physical field, such as Figure 3 shown, the coupling action can be divided into two types. One is that physical field A will change the source term or excitation of physical field B, which belongs to the weak coupling relationship. For example, the heat generated by the internal electromagnetic field of the bushing will become the excitation source term of the thermal field. The other is that the change of the field quantity of physical field A will cause the change of the material parameters of physical field B, which belongs to the strong coupling relationship. For example, when the internal temperature of GIS changes, it will change the electromagnetic parameters of the material, such as the conductivity or dielectric coefficient of SF6.

[0077] For the first type of coupling relationship where physical field A changes the source term or excitation of physical field B, analyze the influence of each coupling variable on the external characteristics, clarify the excitation methods between each physical field, and accurately model the key coupling variables according to the mutual influence relationship and correlation pattern between different physical fields and in combination with the weak coupling physical field coupling relational expression of this embodiment.

[0078] Among them, the weak coupling physical field coupling relational expression is specifically as follows:

[0079] K B u B =f B +f A (u A )

[0080] In the formula, K B is the field quantity coefficient matrix of physical field B, f A represents the mathematical model equation of physical field A model, f B represents the mathematical model equation of physical field B model, f A (u A ) represents the mathematical model equation affected by the parameter u in physical field A, where the parameter u includes but is not limited to: Poisson's ratio ν, elastic modulus E, thermal conductivity k, specific heat capacity C, electrical conductivity σ, heat conductance δ, density ρ, thermal conductivity κ.

[0081] For the calculation of the thermal field and force field, since the force field hardly affects the distribution of the temperature field, while heat generates thermal stress, a weak coupling method is adopted in the multi-physics field calculation of the thermal field and force field.

[0082] First, without considering the force field equation and the action of force, according to the distribution of temperature T is calculated. Then, the calculation results of the temperature field are used as the excitation of the force field and the source term of the equation, which are incorporated into the force field equation for calculation, obtaining the relational expression of the force field F + F(T) = 0, and calculating the force field distribution F(T) as thermal stress based on this. This weak coupling method usually has fewer iteration times, and the calculation amount is much lower than that of the strong coupling method, so as to reduce the resources consumed by the multi-physics field calculation.

[0083] Regarding the second form of the coupling effect between multi-physics fields, the insulating structure material changes with the physical field quantities, thereby affecting the spatio-temporal distribution forms of each physical field. Taking the coupling relationship between the moisture field, electric field and temperature field inside the transformer bushing as an example, as Figure 4 shown, among them, in the temperature field calculation, the specific heat capacity C and the thermal conductivity λ are functions of the moisture content; in the electric field calculation, the electrical conductivity of the material is a function of temperature, and the influence of temperature on the electric field should be considered when solving the Poisson equation of the electric field. Secondly, the change of the field quantity itself in the temperature field will also affect the specific heat capacity C and the thermal conductivity λ. Therefore, when building the material constitutive model, not only the influence of other field quantities on the material parameters needs to be considered, but also the influence of the change of its own field quantity on the material parameters should be considered. Study the change law of the material parameters of the insulating structure under different working conditions, analyze the sensitivity relationship between the parameters and different field quantities, and establish an effective and reliable digital constitutive model. As Figure 3 shown, in the GIS twin model, the electro-thermal relationship is closely related under the strong electromagnetic environment. Therefore, in the physical field simulation calculation of establishing the electric field and thermal field, a strong coupling method should be adopted, and the electric equation and the thermal equation are coupled in one equation for simultaneous calculation.

[0084] Among them, the control equation of the heat conduction process is

[0085]

[0086] ρ is the density, C is the specific heat, T is the temperature, t is the time, and q is the heat.

[0087] The current control equation is:

[0088]

[0089] J is the current density and D is the electric displacement vector.

[0090] The electro-thermal coupling relationship is:

[0091]

[0092] E is the electric field, J is the current density, q is the heat, σ is the conductivity, ε is the permittivity, and T is the temperature.

[0093] Construct a second-order partial differential equation according to the control equation and the strong coupling relationship:

[0094]

[0095] The meanings of the parameters are the same as above, and σ(T), ε(T) represent the material parameters affected by temperature.

[0096] Use the variational method to assemble the electrothermal equation into a linear system for calculation, as shown in the following formula:

[0097]

[0098] C and K are coefficient matrices, Q J is the heat generated by the current, E is the electric field, J is the current density, T is the temperature, V is the voltage, I is the current, and Q is the heat generated by the thermal field.

[0099] Step 104: Based on the physical field coupling relationship formula, obtain the material change characteristic data of the target power equipment through a simulation test method, fit the material change characteristic data, and construct a material characteristic function of the target power equipment based on the fitting result.

[0100] Step 105: Perform a Taylor expansion on the material characteristic function according to the principle of virtual work, and then perform a linear approximation on the material characteristic function according to the chain rule to obtain a digital twin simulation model of the target power equipment.

[0101] It should be noted that steps 104 and 105 of this embodiment correspond to the material characteristic mapping stage. In this stage, based on the multiple physical field models and physical field coupling relationship formulas obtained in the previous steps, the material change characteristics of the equipment are obtained through experiments, such as the change of the permittivity of the insulating material with temperature. Then, the obtained experimental data are non-linearly fitted to obtain a fitted material characteristic function. The obtained material characteristic function is Taylor-expanded using the principle of virtual work, and the material function is linearly approximated according to the chain rule to complete the mapping of the material characteristics. Finally, by adding an excitation as the model load / boundary, the obtained digital twin simulation model of the target power equipment can be used to solve the problems of actual working conditions.

[0102] The above is a detailed description of an embodiment of a method for constructing a digital twin simulation model of a power equipment provided by this application. The following is a detailed description of an embodiment of a device for constructing a digital twin simulation model of a power equipment provided by this application.

[0103] Please refer to Figure 5, this embodiment provides a device for constructing a digital twin simulation model of a power device, including:

[0104] A geometric model construction unit 201, configured to construct a geometric model corresponding to the target power device based on the structural characteristics of the target power device;

[0105] A physical field model construction unit 202, configured to establish multiple physical field models of the target power device based on the geometric model, in combination with classical physical laws and the equipment characteristic working conditions and material degradation characteristics of the target power device;

[0106] A physical field coupling relationship determination unit 203, configured to determine the type of coupling relationship between different physical field models according to the field quantity change relationship between different physical field models, and construct a physical field coupling relationship formula between different physical field models according to the coupling relationship type, in combination with the corresponding relationship between the coupling relationship type and the physical field coupling relationship formula and the coupling variables between different physical field models;

[0107] A material characteristic change function construction unit 204, configured to obtain the material change characteristic data of the target power device through simulation experiments based on the physical field coupling relationship formula, fit the material change characteristic data, and construct a material characteristic function of the target power device based on the fitting result;

[0108] A material characteristic mapping unit 205, configured to perform a Taylor expansion on the material characteristic function according to the principle of virtual work, and then perform a linear approximation process on the material characteristic function according to the chain rule to obtain a digital twin simulation model of the target power device.

[0109] In addition, this application also provides a detailed description of an embodiment of a terminal for constructing a digital twin simulation model of a power device and an embodiment of a computer-readable storage medium.

[0110] Please refer to Figure 6 , this embodiment of this application provides a terminal for constructing a digital twin simulation model of a power device, and the types of terminals include but are not limited to: personal computers, industrial computers, servers, and embedded intelligent devices, including: a memory 33 and a processor 31, where the memory 33 and the processor 31 can be communicatively connected through a communication bus 34;

[0111] The memory 33 is used to store program codes corresponding to a method for constructing a digital twin simulation model of a power device provided in the foregoing embodiment;

[0112] The processor 31 is configured to execute the program codes in the memory 33 to implement the method for constructing a digital twin simulation model of a power device provided in this application.

[0113] The fourth aspect of the present application provides a computer-readable storage medium, in which program code corresponding to a method for constructing a digital twin simulation model of a power device provided in the foregoing embodiments is stored.

[0114] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described terminals, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0115] In several embodiments provided by the present application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0116] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device including a series of steps or units does not necessarily need to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0117] It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expression means any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0118] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0120] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an 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. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0121] As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of various embodiments of the present application.

Claims

1. A method for constructing a digital twin simulation model of a power device, characterized in that, Including: Based on the structural characteristics of the target power equipment, construct the corresponding geometric model of the target power equipment; Based on the geometric model, combined with classical physical laws and the equipment characteristic working conditions and material change characteristics of the target power equipment, establish multiple physical field models of the target power equipment; According to the field quantity change relationship between different physical field models, determine the type of coupling relationship between the different physical field models. According to the type of coupling relationship, combined with the corresponding relationship between the coupling relationship type and the physical field coupling relational formula and the coupling variables between different physical field models, construct the physical field coupling relational formula between the different physical field models; Based on the physical field coupling relational formula, through simulation test methods, obtain the material change characteristic data of the target power equipment, and fit the material change characteristic data. Based on the fitting result, construct the material characteristic function of the target power equipment; Perform Taylor expansion on the material characteristic function according to the principle of virtual work, and then perform linear approximation processing on the material characteristic function according to the chain rule to obtain the digital twin simulation model of the target power equipment.

2. The method for constructing a digital twin simulation model of a power device according to claim 1, characterized in that The constructing the corresponding geometric model of the target power equipment based on the target power equipment specifically includes: Based on the structural characteristics of the target power equipment, determine the layout boundary and layout density through preset distance functions and density functions; Perform geometric modeling layout based on the layout boundary and the layout density, then form a Delaunay triangulation based on the laid discrete points, and update the discrete points outside the Delaunay triangulation area to the boundary of the Delaunay triangulation through a preset discrete point correction formula; According to the updated Delaunay triangulation, extract the edge center points and area center points of each triangular area in the Delaunay triangulation respectively; According to each of the edge center points and each of the area center points, divide each triangular area into multiple sub-areas; According to the node sets and boundary information of each sub-area, form the corresponding geometric model of the target power equipment.

3. A method for constructing a digital twin simulation model of a power device according to claim 2, characterized in that After dividing each triangular area into multiple sub-areas, it further includes: Calculate the distance values between each of the edge center points and the sub-area boundaries, and update the edge center points with distance values lower than the preset distance threshold to the sub-area boundaries through the discrete point correction formula.

4. A method for constructing a digital twin simulation model of a power device according to claim 1, characterized in that The types of coupling relationships include: strong coupling relationship type and weak coupling relationship type.

5. A method for constructing a digital twin simulation model of a power device according to claim 4, characterized in that, The physical field coupling relational formula corresponding to the strong coupling relationship type is specifically: Where, K A is the field quantity coefficient matrix of physical field A, K B is the field quantity coefficient matrix of physical field B, C A-B is the influence coefficient matrix of physical field A on physical field B, C B-A is the influence coefficient matrix of physical field B on physical field A, f A represents the mathematical model equation of physical field A model, f B represents the mathematical model equation of physical field B model, f A (u A ) represents the mathematical model equation in physical field A affected by parameter u, f B (u B ) represents the mathematical model equation in physical field B affected by parameter u.

6. A method for constructing a digital twin simulation model of a power device according to claim 4, characterized in that, The physical field coupling relational formula corresponding to the weak coupling relationship type is specifically: K B u B = f B + f A (u A ) Where, K B is the field quantity coefficient matrix of the B physical field, and f A represents the mathematical model equation of the A physical field model, and f B represents the mathematical model equation of the B physical field model, and f A (u A ) represents the mathematical model equation in the A physical field affected by the parameter u.

7. A method for constructing a digital twin simulation model of a power device according to claim 1, characterized in that, Before constructing the material characteristic function of the target power equipment, it further includes: Perform error verification on the material characteristic function. If the error verification result meets the preset error requirements, output the material characteristic function. If the error verification result does not meet the preset error requirements, perform conformal interpolation fitting on the material change characteristic data, and reconstruct the material characteristic function of the target power equipment based on the fitting result.

8. A device for constructing a digital twin simulation model of a power equipment, characterized in that, Including: A geometric model construction unit for constructing the corresponding geometric model of the target power equipment based on the structural characteristics of the target power equipment; A physical field model construction unit, configured to establish multiple physical field models of the target power equipment based on the geometric model, in combination with classical physical laws and the equipment characteristic operating conditions and material change characteristics of the target power equipment; A physical field coupling relationship determination unit, configured to determine the type of coupling relationship between different physical field models according to the field quantity change relationship between different physical field models, and construct a physical field coupling relationship formula between different physical field models based on the type of coupling relationship, in combination with the corresponding relationship between the coupling relationship type and the physical field coupling relationship formula and the coupling variables between different physical field models; A material characteristic change function construction unit, configured to obtain material change characteristic data of the target power equipment through a simulation test method based on the physical field coupling relationship formula, fit the material change characteristic data, and construct a material characteristic function of the target power equipment based on the fitting result; A material characteristic mapping unit, configured to perform Taylor expansion on the material characteristic function according to the principle of virtual work, and then perform linear approximation processing on the material characteristic function according to the chain rule to obtain a digital twin simulation model of the target power equipment.

9. A terminal for constructing a digital twin simulation model of a power device, characterized in that, Comprising: A memory and a processor; The memory is configured to store program codes corresponding to a method for constructing a digital twin simulation model of a power equipment according to any one of claims 1 to 7; The processor is configured to execute the program codes.

10. A computer-readable storage medium, characterized in that, Program codes corresponding to a method for constructing a digital twin simulation model of a power equipment according to any one of claims 1 to 7 are stored in the computer storage medium.

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