Parametric modeling method and system for OLTC vacuum tube conductive system

Abstract

This invention discloses a parametric modeling method and system for OLTC vacuum tube conductive systems. Modeling is performed in SOLIDWORKS based on the application scenario and usage requirements of the vacuum tube, determining the geometric shapes and parameter ranges of the moving and stationary contacts. A set of parameters is selected as a reference based on the model dimensions in SOLIDWORKS, and modeling and assembly are performed in Abaqus, recording the coordinates of the starting, turning, and ending points of each component relative to the assembly reference system. Based on the recorded coordinates, the required geometric parameters are used as variables in Python to construct a parametric finite element model, generating an .inp solution file. Batch calculations are performed on the generated .inp solution file using cmd batch processing commands. Post-processing analysis of the results is performed using Python, extracting the stress during the collision process and displaying it as a cloud map. Based on the cloud map, the stress distribution is determined and related analyses are performed. This invention improves the efficiency and accuracy of modeling.

Description

Technical Field

[0001] This invention relates to the field of on-load tap changers, and more specifically to a parametric modeling method and system for OLTC vacuum tube conductive systems. Background Technology

[0002] On-load tap changers (OLTCs) achieve voltage regulation by changing the number of turns in a transformer winding without interrupting the load current. Compared to traditional on-load tap changers, vacuum on-load tap changers use vacuum interrupter contacts instead of oil-cooled contacts for arc extinguishing, confining the arc extinguishing process within a vacuum tube. This solves the problem of oil carbonization and offers advantages such as long electrical life, long mechanical life, simple maintenance, and environmental friendliness. Because on-load tap changers switch very frequently, their vacuum interrupters need to guarantee at least one million mechanical cycles, requiring extremely high mechanical strength in the vacuum interrupter's conductive system. When designing the conductive system of the vacuum interrupter, excessively large dimensions increase the non-uniformity of the electric field within the chamber and cause metal vapor and droplets generated during arcing to splash and contaminate the insulating shell, potentially leading to localized breakdown or flashover of the insulation. Conversely, excessively small dimensions result in high stress levels throughout the conductive system during the closing collision, reducing the mechanical life of the vacuum on-load tap changer. Therefore, it is necessary to examine the stress distribution during contact collision under different geometries, and determine appropriate geometric dimensions for the vacuum interrupter conductive system while ensuring current carrying capacity and service life.

[0003] Abaqus, a powerful nonlinear finite element analysis software, can analyze highly nonlinear dynamic problems using an explicit dynamic solver without needing to establish stiffness matrices and solve linear equations. This allows for better simulation of high-speed deformation and material failure processes, making it well-suited for analyzing contact collision problems. However, Abaqus lacks automated modeling and post-processing capabilities in its conventional visual interface, requiring users to manually perform each step, which is inefficient and prone to errors. Summary of the Invention

[0004] The purpose of this invention is to provide a parametric modeling method and system for OLTC vacuum tube conductive systems to overcome the shortcomings of existing technologies. This invention can use Python to realize automatic parametric modeling and post-processing, which improves the efficiency and accuracy of modeling and facilitates the analysis of stress distribution during closing collision of vacuum tube conductive systems under different geometric structures, thereby determining appropriate geometric dimensions for contact plates and conductive rods.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] The parametric modeling method for OLTC vacuum tube conductive systems includes the following steps:

[0007] Step 1: Model the vacuum tube in SOLIDWORKS according to the application scenario and usage requirements, and determine the range of geometric shapes and parameters of the moving and stationary contacts;

[0008] Step 2: Select a set of parameters based on the model dimensions in SOLIDWORKS as a reference to model and assemble in Abaqus, and record the coordinates of the start point, turning point, and end point of each component relative to the assembly reference system;

[0009] Step 3: Based on the recorded coordinates of each point, use Python to construct a parametric finite element model with the geometric parameters to be studied as variables, and generate an inp solution file;

[0010] Step 4: Use the cmd batch processing command to perform batch calculations on the generated inp solution file, use Python to perform post-processing analysis of the result file, extract the stress of the collision process and display it as a visualization cloud map, determine the stress distribution based on the cloud map and perform relevant analysis.

[0011] Furthermore, the geometric parameters of the moving and stationary contacts include: the radius, height, and surface inclination angle of the moving and stationary contacts; the diameter of the circular surface at the contact point of the moving and stationary contacts; and the height, diameter, and thread depth of the moving and stationary conductive rods.

[0012] Furthermore, step two specifically involves: firstly establishing a two-dimensional axisymmetric model or a three-dimensional model of each component, ensuring that the component coordinate system of each component is aligned with the assembly coordinate system;

[0013] During the assembly process, the component movement tool is used to move each component according to its relative position. The coordinates of the starting point, turning point, and ending point of each component relative to its respective component coordinate system and the coordinates of the movement vector reference system of each component in the assembly coordinate system are recorded.

[0014] Furthermore, the method of using Python to construct a parametric finite element model by taking the geometric parameters to be studied as variables specifically involves using Python to generate corresponding component parts, attribute parts, assembly parts, analysis step parts, interaction parts, load parts, mesh parts, operation parts, and inp solution files.

[0015] Furthermore, the component part is created using Python's Abaqus module based on given geometric parameters, with one or more component objects defined in shape and size, and added to the parametric finite element model;

[0016] The attribute section assigns material properties to each component, using Python's Abaqus module to create multiple material objects and define their elastic and plastic properties;

[0017] The assembly part is to assemble the various components according to their relative positions when the moving and stationary contacts are at a preset distance before collision. An assembly object is created using the Abaqus module of Python, and each component is instantiated and placed in the corresponding position and direction.

[0018] The analysis step section refers to creating one or more step objects using Python's Abaqus module, specifying their type as explicit kinetic analysis, setting parameters for the step objects, adding an output request object for each step object, and specifying the field variables that need to be output to the results file.

[0019] The interaction part refers to using the Abaqus module of Python to create multiple interaction objects and apply spring force to the moving contact, establishing the contact relationship between the moving and stationary contact pieces and the constraint relationship between each component;

[0020] The load section is used to apply initial velocity and force to the moving contact section, and to apply fixed constraints to the stationary contact section;

[0021] The mesh part refers to creating multiple mesh division objects using Python's Abaqus module and specifying their division parameters to adjust the mesh density and shape;

[0022] The task section is used to assign the number of CPU cores and the maximum memory usage for solving the problem.

[0023] Furthermore, the material properties include density, Young's modulus, and Poisson's ratio.

[0024] Furthermore, the parameters set for the step object include duration and initial increment.

[0025] Furthermore, the partitioning parameters include partitioning method, size, and deviation.

[0026] Furthermore, step four specifically involves: using the cmd batch processing command to perform batch calculations on the inp solution file generated in step three, and using Python to draw a contour plot of the obtained odb result file to obtain the stress distribution of the contact plate and conductive rod when the contact collides under specific geometric parameters.

[0027] The parametric modeling system for OLTC vacuum tube conductive systems includes:

[0028] Acquisition module: Used to model in SOLIDWORKS according to the application scenario and usage requirements of the vacuum tube, and to determine the range of geometric shapes and parameters of the moving and stationary contacts;

[0029] Assembly module: Used to select a set of parameters as a reference for modeling and assembling in Abaqus based on the model size in SOLIDWORKS, and record the coordinates of the start point, turning point and end point of each part relative to the assembly reference system;

[0030] Build module: Used to construct a parametric finite element model and generate an inp solution file based on the recorded coordinates of each point, using Python with the geometric parameters to be studied as variables;

[0031] Analysis module: Used to perform batch calculations on the generated inp solution files using cmd batch processing commands, use Python to perform post-processing analysis of the result files, extract the stress of the collision process and display it as a visualization cloud map, determine the stress distribution based on the cloud map and perform related analysis.

[0032] Compared with the prior art, the present invention has the following beneficial technical effects:

[0033] This invention utilizes the Python programming language to call Abaqus modules and interfaces for rapid and automatic modeling of conductive systems with different geometries, greatly improving modeling efficiency. It enables a high degree of customization of geometric structures and expansion of research content, avoiding errors and a large amount of repetitive work in the modeling process, improving work efficiency and quality, and facilitating stress analysis of conductive systems during collisions. This, in turn, is beneficial for optimizing the entire conductive system from a geometric perspective and obtaining optimized conductive system structural parameters.

[0034] This invention provides an Abaqus modeling method based on Python that automatically generates simulation models and solution files simply by inputting geometric parameters into a written function. It can also generate models in batches as needed without tedious manual operations, eliminating the time cost of repetitive modeling, greatly reducing the possibility of operational errors in the modeling process, and improving the efficiency and accuracy of modeling. Attached Figure Description

[0035] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0036] Figure 1 This is a schematic diagram of the geometric structure of the moving and stationary contacts;

[0037] Figure 2 To generate flowcharts for the corresponding component parts using Python;

[0038] Figure 3 This is a stress contour diagram of a vacuum interrupter conductive system under a certain set of geometric parameters. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] Example 1

[0042] A parametric modeling method for OLTC vacuum tube conductive systems based on Abaqus secondary development is proposed. This method utilizes the Python programming language to quickly and automatically model contact plates and conductive rods with different geometric parameters, greatly improving modeling efficiency. It enables a high degree of customization of the geometric structure and expansion of research content, avoids errors in the modeling process, improves work efficiency and quality, and facilitates the analysis of stress distribution during collisions in the conductive system, thereby obtaining optimized structural parameters of the conductive system.

[0043] Specifically, the following steps are included:

[0044] Step 1: Model the vacuum tube in SOLIDWORKS according to the application scenario and usage requirements, determining the approximate contact geometry and the range of geometric parameters, including the radius, height, surface inclination angle, circular diameter of the contact point between the moving and stationary contacts, and the height, diameter, and thread depth of the moving and stationary conductive rods, etc. Its geometric structure can be referenced from [reference needed]. Figure 1 .

[0045] Step 2: Select a set of dimensions as a reference to model and assemble in Abaqus, and record the coordinates of the starting point, turning point and ending point of each component relative to the assembly reference system.

[0046] Step 3: Based on the recorded coordinates of each point, use Python to construct a parametric finite element model with the geometric parameters to be studied as variables, and generate the inp solution file.

[0047] Step 4: Use cmd batch processing commands to calculate the inp solution file, use Python to perform post-processing analysis of the result file, extract the stress of the collision process and display it as a visualization cloud map, determine the stress distribution based on the cloud map and perform relevant analysis.

[0048] In step three, Python is used to generate the corresponding component parts, attribute parts, assembly parts, analysis step parts, interaction parts, load parts, mesh parts, job parts, and INP solution files. The implementation process can be found in [reference needed]. Figure 2 .

[0049] The component part is created using Python's Abaqus module based on given geometric parameters, with one or more component objects defined in shape and size, and then added to the model.

[0050] The attribute section assigns material properties, including physical quantities such as density, Young's modulus, and Poisson's ratio, to each component. Multiple material objects are created using Python's Abaqus module, and their elastic and plastic properties are defined. The constitutive relation used in the attribute section is a bifold elastic-plastic constitutive relation.

[0051] The assembly process involves assembling the various components according to their relative positions when the moving and stationary contacts are a certain distance apart before collision. An assembly object is created using Python's Abaqus module, and each component is instantiated and placed in the appropriate position and orientation.

[0052] The analysis step section refers to creating one or more step objects using Python's Abaqus module, specifying their type as explicit kinetic analysis, setting parameters such as duration and initial increment, adding an output request object to each step object, and specifying the field variables to be output to the results file.

[0053] The interaction part refers to the creation of multiple interaction objects using the Abaqus module of Python, which are used to apply spring force to the moving contact, the contact relationship between the moving and stationary contact pieces, and the constraint relationship between the components.

[0054] The load section is used to apply initial velocity and force to the moving contact section, and to apply fixed constraints to the stationary contact section.

[0055] The mesh component refers to creating multiple mesh objects using Python's Abaqus module, specifying parameters such as meshing method, size, and offset. Then, a seed object and a mesh control object are added to each mesh object to adjust the mesh density and shape.

[0056] The task section is used to assign the number of CPU cores and the maximum memory usage for solving the problem.

[0057] Example 2

[0058] A parametric modeling method for OLTC vacuum tube conductive systems based on Abaqus secondary development, such as Figure 2 As shown, the specific modeling process is as follows:

[0059] S1. Based on the application scenario of the vacuum tube, a model is created in SOLIDWORKS to determine the approximate shape and geometric parameter range of the contact plates and conductive rods. This includes the radius, height, surface inclination angle of the contacts, the diameter of the circular surface at the contact point between the moving and stationary contacts, and the height, diameter, and thread depth of the conductive rods. It also determines which geometric quantities need to be parameterized. Cross-sectional views of the moving and stationary contacts and conductive rods are shown below. Figure 1 As shown. In this embodiment, to simplify the explanation, the following explanation will only focus on parametric modeling of the diameter of the moving and stationary conductive rods to illustrate this method. The present invention can also perform parametric modification and modeling simulation of all model dimensions involved in the model.

[0060] S2. Based on the model dimensions in SOLIDWORKS, select a reference dimension and first establish a two-dimensional axisymmetric model of each component in Abaqus. The component coordinate system of each component needs to be consistent with the orientation of the assembly coordinate system. During assembly, according to... Figure 1 The relative positions of each component are moved using a component movement tool. The coordinates of each component's starting point, turning point, and ending point relative to its respective component coordinate system and the coordinates of the component's movement vector reference system in the assembly coordinate system are recorded. In this embodiment, a two-dimensional axisymmetric model is established to reduce computation time. This invention can perform two-dimensional axisymmetric modeling and three-dimensional modeling and simulation.

[0061] S3, based on the recorded coordinates of each point, uses Python to build each component, parameterizing the coordinates of the moving and stationary conductive rods. In the assembly section, the components are assembled according to the assembly information in S2. In the attribute section, material properties, including density, Young's modulus, and Poisson's ratio, are assigned to each component, establishing two-fold elastoplastic constitutive relations for each component. In the mesh section, the mesh type and mesh element size limits are specified for each component individually. In the analysis step section, the solution analysis step type is specified as Explicit Dynamics, and the solution time and the number of frames to be output to the odb result file are set. In the interaction section, coupling points are applied to the areas requiring force, binding constraints are applied to the moving contact plate and moving conductive rod, and to the stationary contact plate and stationary conductive rod, contact relationships are established between the moving and stationary contacts, and a spring interaction relationship is introduced to the moving end. In the load section, a fixed constraint is applied to the stationary end, and a force and initial velocity are applied to the moving end. In the operation section, the number of CPUs used and the maximum amount of memory used are specified.

[0062] The main parts are written as follows, including but not limited to the following information:

[0063] (1) Importing modules: Python script interfaces require the Abaqus module to be imported using the import statement.

[0064] The procedure is as follows:

[0065] #-*-coding:mbcs-*-

[0066] from abaqus import*

[0067] from abaqusConstants import*

[0068] session.viewports['Viewport:1'].makeCurrent()

[0069] session.viewports['Viewport:1'].maximize()

[0070] from caeModules import*

[0071] from driverUtils import executeOnCaeStartup

[0072] executeOnCaeStartup()

[0073] (2) The following are the function names written in Python. The input parameters are the model name, the job name, the radius of the moving conductive rod, the radius of the stationary conductive rod, the outer edge radius of the contact piece, and the radius of the contact point between the moving and stationary contacts. The function outputs the simulation result files for the corresponding model and job. This allows for the parameterization of the model.

[0074] The function name is as follows:

[0075] def execute_program(model_name,job_name,donggan_diameter,jinggan_diameter,inner_pian_diameter,outer_piandiameter):

[0076] (3) The following is the component modeling. Models of the moving and stationary contact plates and the conductive rod are established separately. To improve computational efficiency and reduce the solution time for a single set of geometric parameters, the contact mechanism model can be simplified to a two-dimensional axisymmetric model. If the contact mechanism model is complex, a three-dimensional model can also be directly established. This invention can... Figure 1 The model shown was created using Python for Abaqus 2D and 3D geometric modeling and finite element analysis.

[0077] Part of the code is as follows:

[0078] s=mdb.models[model_name].ConstrainedSketch(name='__profile__',sheetSize=200.0)

[0079] g, v, d, c = s.geometry, s.vertices, s.dimensions, s.constraints

[0080] s.sketchOptions.setValues(viewStyle=AXISYM)

[0081] s.setPrimaryObject(option=STANDALONE)

[0082] s.ConstructionLine(point1=(0.0,-100.0),point2=(0.0,100.0))

[0083] s.FixedConstraint(entity=g.findAt((0.0,0.0)))

[0084] s.Line(point1=(0.0,0.0),point2=(inner_pian_diameter,0.0))

[0085] s.Line(point1=(inner_pian_diameter,0.0),point2=(outer_piandiameter,-1.5))

[0086] s.Line(point1=(outer_piandiameter,-1.5),point2=(outer_piandiameter,-5.0))

[0087] s.Line(point1=(outer_piandiameter,-5.0),point2=(0.0,-5.0))

[0088] s.Line(point1=(0.0,-5.0),point2=(0.0,0.0))

[0089] p=mdb.models[model_name].Part(name='Part-1',dimensionality=AXISYMMETRIC,type=DEFORMABLE_BODY)

[0090] p=mdb.models[model_name].parts['Part-1']

[0091] p.BaseShell(sketch=s)

[0092] s.unsetPrimaryObject()

[0093] p=mdb.models[model_name].parts['Part-1']

[0094] del mdb.models[model_name].sketches['__profile__']

[0095] (4) The following are the attribute settings. The names, densities, elastic moduli, Poisson's ratio, and yield strengths of each material can be defined using Python, and corresponding material attributes can be assigned according to the component type. The constitutive relation is a two-fold elastoplastic constitutive relation, that is, using two straight lines to describe the stress-strain relationship of the material. The first straight line represents the elastic stage of the material, with the slope being the elastic modulus. The second straight line represents the plastic stage of the material, with the slope being the tangent modulus. Then, the material object is associated with the component object to form a section object. Part of the program is as follows:

[0096] mdb.models[model_name].Material(name=Material_name)

[0097] mdb.models[model_name].materials[Material_name].Density(table=((TABLE1,),))

[0098] mdb.models[model_name].materials[Material_name].Elastic(table=((TABLE2),))

[0099] mdb.models[model_name].materials[Material_name].Plastic(scaleStress=None,table=((TABLE3),))

[0100] p=mdb.models[model_name].parts[part_name]

[0101] mdb.models[model_name].HomogeneousSolidSection(name=Section_name,material=Material_name,thickness=None)

[0102] (5) Establishing Interaction Relationships and Boundary Conditions: Since the moving contact piece and the moving conductive rod, and the stationary contact piece and the stationary conductive rod are interconnected, each needs to have its own fixed constraints established. Simultaneously, to apply the spring force, spring endpoints need to be established, with one endpoint fixed and the other endpoint coupled to the moving conductive rod, applying force to the coupling point and specifying the spring stiffness. For the moving and stationary contacts, their contact and collision relationships need to be established, constructing normal and tangential contact properties. To avoid singularities in the solution matrix during collisions, the normal contact relationship needs to be specified as soft contact under specific parameters.

[0103] Part of the code is as follows:

[0104]

[0105]

[0106]

[0107]

[0108] (6) Create project files, some code is as follows:

[0109]

[0110] (7) Generate the inp solver file.

[0111] S4. Using the cmd batch processing command, the inp files generated in S3 are batch-calculated. The resulting odb files are then used to draw contour plots using Python to obtain the stress distribution of the contact plates and conductive rods during contact collision under specific geometric parameters. The stress contour plot of the vacuum interrupter's conductive system under a certain set of geometric parameters is shown below. Figure 3 As shown. Using this modeling method, parametric modeling and stress analysis of the conductive system of a vacuum interrupter can be achieved quickly and accurately, facilitating the optimized design of the contacts and conductive rods.

[0112] Part of the code is as follows:

[0113]

[0114]

[0115] Example 3

[0116] This invention provides a parametric modeling system for OLTC vacuum tube conductive systems, comprising:

[0117] Acquisition module: Used to model in SOLIDWORKS according to the application scenario and usage requirements of the vacuum tube, and to determine the range of geometric shapes and parameters of the moving and stationary contacts;

[0118] Assembly module: Used to select a set of parameters as a reference for modeling and assembling in Abaqus based on the model size in SOLIDWORKS, and record the coordinates of the start point, turning point and end point of each part relative to the assembly reference system;

[0119] Build module: Used to construct a parametric finite element model and generate an inp solution file based on the recorded coordinates of each point, using Python with the geometric parameters to be studied as variables;

[0120] Analysis module: Used to batch process the generated inp solution files using cmd batch commands, use Python to perform post-processing analysis of the result files, extract the stress of the collision process and display it as a cloud map, determine the stress distribution based on the cloud map and perform related analysis.

[0121] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0122] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the pending claims of the invention.

Claims

1. A parametric modeling method for OLTC vacuum tube conductive systems, characterized in that, Includes the following steps: Step 1: Model the vacuum tube in SOLIDWORKS according to the application scenario and usage requirements, and determine the range of geometric shapes and parameters of the moving and stationary contacts; Step 2: Select a set of parameters based on the model dimensions in SOLIDWORKS as a reference to model and assemble in Abaqus, and record the coordinates of the start point, turning point, and end point of each component relative to the assembly reference system; Step 3: Based on the recorded coordinates of each point, use Python to construct a parametric finite element model with the geometric parameters to be studied as variables, and generate an inp solution file; The method of using Python to construct a parametric finite element model by taking the geometric parameters to be studied as variables is as follows: Python is used to generate the corresponding component parts, attribute parts, assembly parts, analysis step parts, interaction parts, load parts, mesh parts, operation parts and inp solution files. The component part is created using Python's Abaqus module based on given geometric parameters, with one or more component objects defined in shape and size, and added to the parametric finite element model; The attribute section assigns material properties to each component, using Python's Abaqus module to create multiple material objects and define their elastic and plastic properties; The assembly part is to assemble the various components according to their relative positions when the moving and stationary contacts are at a preset distance before collision. An assembly object is created using the Abaqus module of Python, and each component is instantiated and placed in the corresponding position and direction. The analysis step section refers to creating one or more step objects using Python's Abaqus module, specifying their type as explicit kinetic analysis, setting parameters for the step objects, adding an output request object for each step object, and specifying the field variables that need to be output to the results file. The interaction part refers to using the Abaqus module of Python to create multiple interaction objects and apply spring force to the moving contact, establishing the contact relationship between the moving and stationary contact pieces and the constraint relationship between each component; The load section is used to apply initial velocity and force to the moving contact section, and to apply fixed constraints to the stationary contact section; The mesh part refers to creating multiple mesh division objects using Python's Abaqus module and specifying their division parameters to adjust the mesh density and shape; The task section is used to assign the number of CPU cores and the maximum memory usage for the solution; Step 4: Use the cmd batch processing command to perform batch calculations on the generated inp solution file, use Python to perform post-processing analysis of the result file, extract the stress of the collision process and display it as a visualization cloud map, determine the stress distribution based on the cloud map and perform relevant analysis.

2. The parametric modeling method for OLTC vacuum tube conductive systems according to claim 1, characterized in that, The geometric parameters of the moving and stationary contacts include: the radius, height, and surface inclination angle of the moving and stationary contacts; the diameter of the circular surface at the contact point of the moving and stationary contacts; and the height, diameter, and thread depth of the moving and stationary conductive rods.

3. The parametric modeling method for the conductive system of an OLTC vacuum tube according to claim 1, characterized in that, The second step specifically involves: firstly establishing a two-dimensional axisymmetric model or a three-dimensional model of each component, ensuring that the component coordinate system and the assembly coordinate system are aligned; During the assembly process, the component movement tool is used to move each component according to its relative position. The coordinates of the starting point, turning point, and ending point of each component relative to its respective component coordinate system and the coordinates of the movement vector reference system of each component in the assembly coordinate system are recorded.

4. The parametric modeling method for OLTC vacuum tube conductive systems according to claim 1, characterized in that, The material properties include density, Young's modulus, and Poisson's ratio.

5. The parametric modeling method for an OLTC vacuum tube conductive system according to claim 1, characterized in that, The parameters set for the step object include duration and initial increment.

6. The parametric modeling method for an OLTC vacuum tube conductive system according to claim 1, characterized in that, The partitioning parameters include partitioning method, size, and deviation.

7. The parametric modeling method for an OLTC vacuum tube conductive system according to claim 1, characterized in that, Step four specifically involves using the cmd batch processing command to perform batch calculations on the inp solution file generated in step three, and then using Python to draw a contour plot of the obtained odb result file to obtain the stress distribution of the contact plate and conductive rod during contact collision under specific geometric parameters.

8. A parametric modeling system for OLTC vacuum tube conductive systems, characterized in that, include: Acquisition module: Used to model in SOLIDWORKS according to the application scenario and usage requirements of the vacuum tube, and to determine the range of geometric shapes and parameters of the moving and stationary contacts; Assembly module: Used to select a set of parameters as a reference for modeling and assembling in Abaqus based on the model size in SOLIDWORKS, and record the coordinates of the start point, turning point and end point of each part relative to the assembly reference system; Build module: Used to construct a parametric finite element model and generate an inp solution file based on the recorded coordinates of each point, using Python with the geometric parameters to be studied as variables; The method of using Python to construct a parametric finite element model by taking the geometric parameters to be studied as variables is as follows: Python is used to generate the corresponding component parts, attribute parts, assembly parts, analysis step parts, interaction parts, load parts, mesh parts, operation parts and inp solution files. The component part is created using Python's Abaqus module based on given geometric parameters, with one or more component objects defined in shape and size, and added to the parametric finite element model; The attribute section assigns material properties to each component, using Python's Abaqus module to create multiple material objects and define their elastic and plastic properties; The assembly part is to assemble the various components according to their relative positions when the moving and stationary contacts are at a preset distance before collision. An assembly object is created using the Abaqus module of Python, and each component is instantiated and placed in the corresponding position and direction. The analysis step section refers to creating one or more step objects using Python's Abaqus module, specifying their type as explicit kinetic analysis, setting parameters for the step objects, adding an output request object for each step object, and specifying the field variables that need to be output to the results file. The interaction part refers to using the Abaqus module of Python to create multiple interaction objects and apply spring force to the moving contact, establishing the contact relationship between the moving and stationary contact pieces and the constraint relationship between each component; The load section is used to apply initial velocity and force to the moving contact section, and to apply fixed constraints to the stationary contact section; The mesh part refers to creating multiple mesh division objects using Python's Abaqus module and specifying their division parameters to adjust the mesh density and shape; The task section is used to assign the number of CPU cores and the maximum memory usage for the solution; Analysis module: Used to perform batch calculations on the generated inp solution files using cmd batch processing commands, use Python to perform post-processing analysis of the result files, extract the stress of the collision process and display it as a visualization cloud map, determine the stress distribution based on the cloud map and perform related analysis.

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