A switch cabinet electric field reconstruction method and system based on field domain coexistence simulation

Abstract

The application belongs to the technical field of simulation optimization, and discloses a switch cabinet electric field reconstruction method and system based on field domain symbiotic simulation, which comprises the following steps: performing multi-physical field coupling simulation of electric-magnetic-thermal-flow on a reference field domain model of a target switch cabinet to generate an initial coupling field distribution dataset; generating a symbiotic evolution parameter set according to the topological form of the region with an electric field intensity value exceeding a first threshold value in the initial coupling field distribution dataset; performing directional adjustment on the geometric parameters and material layout of the corresponding region in the reference field domain model based on the symbiotic evolution parameter set to obtain an optimized field domain model; repeatedly performing multi-physical field coupling simulation on the optimized field domain model, and outputting an electric field reconstruction distribution map of the optimized field domain model when the maximum electric field intensity of the optimized field domain model is lower than the first threshold value. The application can realize automatic and refined reconstruction of the electric field of the switch cabinet, and improve the authenticity of simulation data and the electric field optimization iteration efficiency.

Description

Technical Field

[0001] This invention belongs to the field of simulation optimization technology, and in particular relates to a method and system for reconstructing the electric field of switchgear based on field symbiotic simulation. Background Technology

[0002] Currently, most field simulation analyses of high-voltage switchgear employ a single-physics-field-independent simulation approach, failing to achieve synchronous coupled calculations of the four major physical fields: electric field, magnetic field, thermal field, and fluid field. During actual switchgear operation, these physical fields interact closely. Temperature changes generated by the equipment directly alter the conductivity and permeability of various components within the cabinet, thus affecting the distribution of the electric and magnetic fields. Furthermore, the fluid field formed by gas flow inside the cabinet changes heat transfer efficiency, continuously influencing the overall temperature field distribution.

[0003] Traditional simulation methods cannot build a multi-threaded collaborative computing architecture, and cannot complete real-time interaction and parameter updates of data from various fields during simulation iteration. The resulting field distribution dataset cannot reproduce the multi-field coupling state under actual equipment operation. It is not only difficult to accurately mark the strong field distortion region and thermal anomaly region, but also unable to fully extract the spatial topological features of the electric field exceeding the standard region, resulting in insufficient authenticity and completeness of the basic simulation data.

[0004] Existing methods for optimizing the electric field of switchgear lack a systematic and directional adjustment basis. When the electric field strength is detected to exceed the safety limit, it is impossible to establish a corresponding evolution reference system based on the topological characteristics of the abnormal field strength region. When adjusting the geometric structure of equipment such as sharp corners and protrusions, as well as the material layout of interfaces between different media, staff can only rely on experience to make blind modifications. After the structural and material adjustments are completed, the optimization effect can only be verified one by one through multiple independent simulations. The entire process relies on repeated trial and error to complete the iteration, making the overall workflow cumbersome and time-consuming. This type of optimization method is difficult to specifically weaken local concentrated electric fields, and it is difficult to stably control the maximum electric field strength of the entire switchgear area within the specified threshold. At the same time, it is also impossible to generate accurate and complete electric field reconstruction distribution maps. The execution efficiency and actual control effect of electric field reconstruction work have significant defects. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a method and system for reconstructing the electric field of switchgear based on field symbiosis simulation, so as to realize the automated and refined reconstruction of the electric field of switchgear and improve the authenticity of simulation data and the efficiency of electric field optimization iteration.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for reconstructing the electric field of a switchgear based on field symbiosis simulation includes: For the reference field model of the target switchgear, perform coupled simulation of multiple physics fields including electromagnetism, heat and current to generate an initial coupled field distribution dataset; Based on the topology of the region where the electric field intensity value exceeds the first threshold in the initial coupled field distribution dataset, a set of co-evolution parameters is generated. Based on the co-evolution parameter set, the geometric parameters and material layout of the corresponding region in the benchmark field model are adjusted in a directional manner to obtain the optimized field model; The multiphysics coupling simulation is repeatedly performed on the optimized field model, and the electric field reconstruction distribution map of the optimized field model is output when the maximum electric field intensity in the optimized field model is lower than the first threshold.

[0007] In a preferred embodiment, the reference field model is specifically as follows: Obtain the initial three-dimensional structural model of the target switchgear. The initial three-dimensional structural model includes the three-phase main bus, circuit breaker poles, contact boxes, current transformers, grounding switches, and metal enclosure. The geometric dimensions of each component, the relative positions between each component, and the material properties of each component in the initial three-dimensional structural model are set as variables that can be changed independently to obtain the reference field model.

[0008] In a preferred embodiment, generating an initial coupled field distribution dataset includes: Preset boundary conditions and excitation sources are applied to the reference field model; Simultaneously start the electric field simulation thread, magnetic field simulation thread, thermal field simulation thread, and fluid field simulation thread; In each coupling iteration step, the temperature distribution obtained by the thermal field simulation thread is fed back to the electric field simulation thread and the magnetic field simulation thread to update the conductivity parameters of each component and the magnetic permeability parameters of the ferromagnetic component. Simultaneously, the gas velocity distribution obtained by the fluid field simulation thread is fed back to the thermal field simulation thread to update the convective heat transfer coefficient. When the maximum relative rate of change of the electric field intensity distribution between two adjacent iterations is lower than the preset convergence threshold, the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution and gas velocity distribution are stored together as the initial coupled field distribution dataset.

[0009] In a preferred embodiment, after storing the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution, and gas velocity distribution together as an initial coupled field distribution dataset, the method further includes: The electric field intensity sequence along the central axis of the three-phase main bus, the magnetic induction intensity sequence along the inner wall of the metal enclosed shell, and the temperature sequence on the upper surface of the circuit breaker pole were extracted from the initial coupled field distribution dataset. Determine whether the gradient between two adjacent points in the electric field intensity sequence exceeds the preset electric field distortion threshold. If so, mark the area between the two adjacent points as a potential partial discharge risk area. Determine whether the highest value of the temperature sequence exceeds the preset thermal stability threshold. If so, mark the corresponding position of the circuit breaker pole as a thermal fault candidate area. The initial coupled field distribution dataset is considered valid only if the electric field intensity sequence does not have a gradient exceeding the electric field distortion threshold and the highest value of the temperature sequence is below the thermal stability threshold.

[0010] In a preferred embodiment, generating a set of co-evolutionary parameters includes: Traverse the initial coupled field distribution dataset, filter out all spatial discrete points with electric field strength values ​​greater than a preset first threshold, and connect adjacent spatial discrete points into one or more continuous field strength distortion regions; Extract the topological features of each field strength distortion region; Spatial superposition analysis of the curvature change profile and extension direction in the topological morphology features is performed to identify the coincidence point between the abrupt curvature change on the electrode surface and the abnormal attenuation of the normal field strength at the dielectric interface, and the coincidence point is marked as the seed point of co-evolution. Based on the seed point of co-evolution, a preset buffer distance is extended outward along the edge of the projection shape to generate a joint influence domain. All topological feature data sets within the joint influence domain are stored as a co-evolution parameter set.

[0011] In a preferred embodiment, the preset first threshold is specifically: Obtain the minimum insulation withstand strength value of all insulating media in the target switchgear, as well as the maximum allowable operating field strength value corresponding to the rated voltage level of the target switchgear; Compare the minimum insulation withstand strength value with the maximum permissible working field strength value, and take the smaller of the two as the benchmark reference value; Obtain the partial discharge initiation field strength value recorded in the factory withstand voltage test of the target switchgear, and then multiply the weighted average of the partial discharge initiation field strength value and the benchmark reference value by the safety margin coefficient to generate the preset first threshold.

[0012] In a preferred embodiment, when obtaining the optimized field model, an intermediate field model is first generated, including: Extract all geometric feature sets marked as to be smoothed from the co-evolution parameter set. The geometric feature set includes the coordinate positions and curvature change contours of sharp corner regions and convex regions with a curvature radius of less than a preset curvature threshold on the electrode surface. For sharp corner regions, the corresponding electrode surface mesh nodes are found in the reference field model, and the mesh nodes are offset outward along the normal of the electrode surface by an incremental amount. For the protruding region, find the corresponding protruding vertex in the reference field model, and expand a circular region around the protruding vertex. Gradually reduce the height value of all grid nodes in the circular region to be flush with the surrounding electrode surface. The adjusted mesh nodes are refitted into a continuous electrode surface to generate an intermediate field model with optimized geometric parameters.

[0013] In a preferred embodiment, based on a set of co-evolutionary parameters, the geometric parameters and material layout of the corresponding region in the baseline field model are adjusted in a directional manner to obtain an optimized field model, including: Extract all interface feature sets marked as transition layers to be added from the symbiotic evolution parameter set; In the reference field model, locate the medium interface corresponding to the interface feature set, and insert new material layers layer by layer from one side of the medium to the other side along the normal direction of the medium interface. The dielectric constant of the new material layer is set to gradually transition from the dielectric constant value of the first side medium to the dielectric constant value of the second side medium, and the thickness of each new material layer is inversely proportional to the local gradient value of the electric field gradient abrupt change band. The inserted new material layer is fused with the original medium material at common nodes to generate an intermediate field model with optimized material layout. Then, the intermediate field model with optimized geometric parameters is merged with the intermediate field model with optimized material layout to obtain an optimized field model.

[0014] In a preferred embodiment, multiphysics coupling simulation is repeatedly performed on the optimized field model, and the electric field reconstruction distribution spectrum corresponding to the optimized field model is output when the maximum electric field intensity in the optimized field model is lower than a first threshold, including: The optimized field model is used as the current iteration field model. The current iteration field model is then subjected to a coupled simulation of the electromagnetic, thermal and fluid multiphysics fields to generate the current iteration coupled field distribution dataset. Extract the maximum electric field intensity value of the entire domain from the current iterative coupled field distribution dataset, and compare the maximum electric field intensity value with the first threshold; If the maximum electric field strength value is greater than or equal to the first threshold, the current iterative coupled field distribution dataset is used as the new initial coupled field distribution dataset, and the steps of generating the co-evolution parameter set and directional adjustment are re-executed to obtain the optimized field model for the next iteration. If the maximum electric field strength value is lower than the first threshold, the iteration stops, and the current iteration field model is output as the final reconstruction model. At the same time, electric field strength distribution data is extracted from the current iteration coupled field distribution dataset, and an electric field reconstruction distribution map is generated according to the geometric coordinate mapping of the final reconstruction model.

[0015] A switchgear electric field reconfiguration system based on field symbiosis simulation, used to implement the above method, includes: The multi-field simulation module is used to perform coupled simulation of multiple physics fields (electromagnetic, thermal, and fluid) on the reference field model of the target switchgear, and generate an initial coupled field distribution dataset. The topology parameter generation module is used to generate a set of co-evolution parameters based on the topology of the region where the electric field intensity value exceeds the first threshold in the initial coupled field distribution dataset. The model tuning module is used to make directional adjustments to the geometric parameters and material layout of the corresponding region in the benchmark field model based on the co-evolution parameter set, so as to obtain an optimized field model. The spectrum output module is used to repeatedly perform multi-physics coupling simulation on the optimized field model and output the electric field reconstruction distribution spectrum corresponding to the optimized field model when the maximum electric field intensity in the optimized field model is lower than the first threshold.

[0016] The present invention has the following beneficial effects: This invention constructs a complete reference field model and configures complete component parameters and variable variables. Relying on a multi-threaded architecture, it synchronously initiates the simulation processes of electric field, magnetic field, thermal field, and fluid field. During the simulation, real-time interaction and dynamic parameter correction of data from each field are continuously performed. The thermal field calculation results update the component's electrical conductivity and magnetic permeability in real time, while the fluid field calculation results synchronously correct the convective heat transfer coefficient. This process iterates continuously until the field distribution reaches the convergence standard, ultimately integrating to form a complete initial coupled field distribution dataset. The technical solution also extracts multiple field quantity change sequences from the dataset, identifies partial discharge risk areas and thermal fault candidate areas within the equipment according to predetermined judgment rules, verifies data validity, and comprehensively recreates the multi-field coupling state under actual operating conditions of the switchgear. It fully collects global field quantity distribution information and spatial variation characteristics, ensuring the authenticity, completeness, and usability of the simulation data.

[0017] This invention extracts topological features from the spatial morphology of areas with excessive electric field strength, accurately locates evolution seed points, delineates joint influence domains, and integrates all feature information to form a standardized set of symbiotic evolution parameters. Based on this parameter set, it smooths the surfaces of sharp corners, protrusions, and other geometric regions within the model. Simultaneously, it adds transitional material layers with varying dielectric constants at dielectric interfaces, achieving dual fine-tuning of geometric morphology and material layout. The technology employs a closed-loop iterative simulation mode to continuously verify and optimize the electric field indicators of the optimized model, constantly refining the field model until the overall electric field strength meets the specified standards. Finally, it combines the geometric coordinates of the compliant model to complete data mapping, generating a standardized and complete electric field reconstruction distribution map. The entire process forms a standardized operating system with interconnected steps, ensuring clear execution guidelines for each stage—structural optimization, material configuration, field verification, and map generation—achieving refined implementation of switchgear electric field control while guaranteeing the standardization and efficiency of the electric field reconstruction results. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of the method of the present invention; Figure 2 This is a functional block diagram of the system of the present invention; Figure 3 This is a bar chart showing the multi-factor comprehensive calculation of the first threshold for electric field reconstruction determination in Embodiment 2 of the present invention; Figure 4 This is a graph showing the effect of directional adjustment of electrode surface geometric parameters and curvature smoothing in Embodiment 2 of the present invention. Figure 5 This is a path diagram of the repeated iterative convergence process of the optimized field model in Embodiment 2 of the present invention; Figure 6 This is the reconstructed distribution map of the global electric field intensity of the switchgear in Embodiment 2 of the present invention. Detailed Implementation

[0019] The embodiments of the present invention will be further described below with reference to the accompanying drawings: Example 1: As Figure 1 As shown, a method for reconstructing the electric field of a switchgear based on field symbiosis simulation includes the following steps: For the reference field model of the target switchgear, perform coupled simulation of multiple physics fields including electromagnetism, heat and current to generate an initial coupled field distribution dataset; Based on the topology of the region where the electric field intensity value exceeds the first threshold in the initial coupled field distribution dataset, a set of co-evolution parameters is generated. Based on the co-evolution parameter set, the geometric parameters and material layout of the corresponding region in the benchmark field model are adjusted in a directional manner to obtain the optimized field model; Repeated multiphysics coupling simulations were performed on the optimized field model, and the electric field reconstruction distribution map of the optimized field model was output when the maximum electric field intensity in the optimized field model was lower than the first threshold. The specific reference field model is as follows: Obtain the initial three-dimensional structural model of the target switchgear. The initial three-dimensional structural model includes the three-phase main bus, circuit breaker poles, contact boxes, current transformers, grounding switches, and metal enclosure. The geometric dimensions of each component, the relative positions between each component, and the material properties of each component in the initial three-dimensional structural model are set as variables that can be changed independently to obtain the reference field model.

[0020] Generate an initial coupled field distribution dataset, including: Preset boundary conditions and excitation sources are applied to the reference field model; Simultaneously start the electric field simulation thread, magnetic field simulation thread, thermal field simulation thread, and fluid field simulation thread; In each coupling iteration step, the temperature distribution obtained by the thermal field simulation thread is fed back to the electric field simulation thread and the magnetic field simulation thread to update the conductivity parameters of each component and the magnetic permeability parameters of the ferromagnetic component. Simultaneously, the gas velocity distribution obtained by the fluid field simulation thread is fed back to the thermal field simulation thread to update the convective heat transfer coefficient. When the maximum relative rate of change of the electric field intensity distribution between two adjacent iterations is lower than the preset convergence threshold, the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution and gas velocity distribution are stored together as the initial coupled field distribution dataset.

[0021] After storing the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution, and gas velocity distribution together as the initial coupled field distribution dataset, the following is also included: The electric field intensity sequence along the central axis of the three-phase main bus, the magnetic induction intensity sequence along the inner wall of the metal enclosed shell, and the temperature sequence on the upper surface of the circuit breaker pole were extracted from the initial coupled field distribution dataset. Determine whether the gradient between two adjacent points in the electric field intensity sequence exceeds the preset electric field distortion threshold. If so, mark the area between the two adjacent points as a potential partial discharge risk area. Determine whether the highest value of the temperature sequence exceeds the preset thermal stability threshold. If so, mark the corresponding position of the circuit breaker pole as a thermal fault candidate area. The initial coupled field distribution dataset is considered valid only if the electric field intensity sequence does not have a gradient exceeding the electric field distortion threshold and the highest value of the temperature sequence is below the thermal stability threshold.

[0022] Based on the original design drawings, component outline drawings, and on-site assembly drawings of the target switchgear, model building work was carried out. The drawings fully marked the standard outline, solid wall thickness, corner shape, assembly reference axis and reference alignment point of each component. Each solid component was 3D shaped and constructed strictly according to the shape parameters marked in the drawings, completely restoring the real three-dimensional structure of the component. Then, according to the standard assembly sequence, assembly spacing and alignment reference specified in the drawings, all components were spatially assembled in sequence. After the assembly was completed, a complete overall structure was formed. This overall structure is the initial three-dimensional structural model. The model fully houses the three-phase main bus, circuit breaker poles, contact boxes, current transformers, grounding switches and metal enclosure. The spatial position, external dimensions and combination relationship of each component are completely consistent with the actual equipment.

[0023] Each independent component and its subdivided parts from the initial 3D structural model are individually labeled with attributes. For each component, unique attribute labels are added to all geometric dimensions such as length, width, height, radius of curvature, and wall thickness, thus breaking the fixed binding relationship between geometric dimensions and the component's 3D shape. Then, unique attribute labels are added to all relative positional relationships between components, such as axial spacing, radial distance, and spatial deflection angle, thus unlocking the locked positions of the components. Subsequently, unique attribute labels are added to all material properties corresponding to different components, such as material type, insulation level, and conductivity specifications, thus removing the fixed configuration restrictions on material properties. After completing the full-dimensional labeling and unlocking operations, geometric dimensions, relative positions of components, and material properties can all be independently adjusted or changed. The complete model after this series of standardized settings is the baseline field model.

[0024] A unified configuration standard was developed based on the rated long-term operating conditions of high-voltage switchgear and the general industry specifications for multi-physics simulation of power equipment. This standard serves as the basis for setting boundary conditions and excitation sources. The pre-defined boundary conditions are matched and deployed to the outer surface of the metal enclosure of the reference field model and the simulation space interface of the model's perimeter. The boundary conditions specifically include three categories of fixed content: forced grounding of the entire metal enclosure, delineation of the simulation space range of the model's perimeter, and fixed temperature and humidity of the external environment. The excitation sources, configured strictly according to the rated voltage and rated current electrical parameters of the switchgear, are applied one by one to all energized components inside the reference field model, such as the three-phase main busbar inlet, the conductive contacts of the circuit breaker poles, and the conductive parts of the contact box. The entire set of boundary conditions and excitation sources forms a fixed configuration template. Each simulation operation directly calls this template to complete the deployment, thereby ensuring that the input conditions of all simulation links remain completely consistent.

[0025] The electric field simulation thread is dedicated to performing electric field-related calculations on the entire space consisting of all conductive components, insulating media, and air gaps within the reference field model. The magnetic field simulation thread is dedicated to performing magnetic field-related calculations on the same entire space within the reference field model. The thermal field simulation thread is dedicated to performing temperature-related calculations on all current-carrying heating components and surrounding air regions within the model. The fluid field simulation thread is dedicated to performing gas flow-related calculations on the enclosed air space inside the metal enclosure of the switchgear. These four types of simulation threads with independent functions start running simultaneously, each occupying independent computing resources. During operation, they do not interfere with or block each other, and continuously perform their respective global field calculation tasks in a parallel operation mode.

[0026] The complete process of covering the entire domain of the model and completing the full set of field quantity derivations in a single operation is defined as a coupled iteration step. After the thermal field simulation thread completes the full domain derivation calculation within the current coupled iteration step cycle, it generates complete temperature distribution content covering the surface of each solid component, the interior of the component, and the surrounding air region of the reference field model. This temperature distribution content is completely transmitted to the electric field simulation thread and the magnetic field simulation thread according to the point-to-point correspondence rule of spatial coordinates. According to the real-time temperature state corresponding to each spatial point of the model, the electrical conductivity attribute of the component to which the point belongs and the magnetic permeability attribute of the ferromagnetic component are reconfigured one by one. When there are temperature differences at different points of the component, the electrical conductivity and magnetic permeability attributes of the corresponding material at the corresponding point are also updated independently. All component attribute update operations are completed within the predetermined operation cycle of the current coupled iteration step.

[0027] After the fluid field simulation thread completes the deduction and calculation of the gas flow state inside the metal closed shell within the current coupled iteration step cycle, it generates complete gas velocity distribution content covering all subdivided spatial units inside the shell. This gas velocity distribution content is completely delivered to the thermal field simulation thread according to the point-to-point correspondence rule of spatial unit coordinates. Based on the real-time gas flow rate and flow direction corresponding to each subdivided spatial unit in the closed space, the convective heat transfer related attributes of the solid component and air contact surface in the corresponding area are reconfigured one by one. The attribute update operations of all subdivided spatial units inside the shell are completed within the predetermined running cycle of the current coupled iteration step.

[0028] Referring to the current acceptance specifications for multiphysics coupling simulation of high-voltage electrical equipment, a fixed value is selected as the convergence threshold for the whole-domain simulation. After the completion of the entire derivation and calculation process of each coupling iteration step, the electric field intensity distribution corresponding to all spatial discrete points of the model in the current iteration step and the previous iteration step is completely extracted. The specific values ​​of the two sets of electric field intensity data are compared point by point. The field quantity change amplitude corresponding to all points in the whole domain is statistically analyzed and the maximum change amplitude is determined. When the value of the maximum change amplitude is less than the pre-set convergence threshold, the entire set of electro-magnetic-thermal-fluid multiphysics coupling simulation is determined to have officially entered the convergence state. The four types of field quantity data, namely electric field intensity distribution, magnetic induction intensity distribution, temperature distribution and gas velocity distribution, collected in the convergence state are uniformly sorted according to the spatial coordinate system. Then, the data is classified, stored and indexed in accordance with the simulation data archiving management specifications. The complete set of data after integration and archiving is the initial coupling field distribution dataset.

[0029] Based on the initial coupled field distribution dataset that has been classified, archived, and indexed, equally spaced sampling points are set along the central axial extension path of the three-phase main busbar. The electric field intensity information corresponding to each sampling point is collected one by one. The collected information is then arranged and sorted in strict accordance with the axial arrangement of the sampling points, and combined to form an electric field intensity sequence along the central axial direction of the three-phase main busbar. Equally spaced sampling points are set along the continuous contour of the inner wall of the metal enclosed shell. The magnetic induction intensity information corresponding to each sampling point is collected one by one. The collected information is then arranged and sorted in strict accordance with the extension order of the sampling points along the inner wall contour, and combined to form a magnetic induction intensity sequence along the inner wall of the metal enclosed shell. Sampling points are uniformly distributed across the entire area of ​​the upper surface of the circuit breaker pole. The temperature information corresponding to each sampling point is collected one by one. The collected information is then arranged and sorted in strict accordance with the distribution order of the sampling points on the upper surface, and combined to form a temperature sequence of the upper surface of the circuit breaker pole.

[0030] Based on the current industry standards for insulation testing of high-voltage switchgear, a fixed value is selected as the electric field distortion threshold. Data from each adjacent sampling point in the electric field intensity sequence along the central axis of the three-phase main busbar are retrieved sequentially. The degree of change in electric field quantity between two adjacent sampling points is checked one by one. When the degree of change in field quantity between two points is higher than the unified judgment standard corresponding to the electric field distortion threshold, a unique identification mark is added to the switchgear physical space area between the two sampling points. All space areas marked with the same identification mark are uniformly designated as potential partial discharge risk areas. The marking information is synchronously associated with the spatial coordinates of the corresponding area for subsequent traceability and identification.

[0031] Based on the relevant specifications for the long-term operating temperature tolerance of current-carrying components in switchgear, a fixed value is selected as the thermal stability threshold. The temperature sequence of the circuit breaker pole surface, including the temperature information of all sampling points, is sequentially reviewed. The magnitude of all temperature values ​​is compared one by one, and the sampling point with the highest temperature value in the entire set of data is selected. The actual temperature value corresponding to the sampling point is compared and verified with the thermal stability threshold. When the temperature value at this location is higher than the unified judgment standard corresponding to the thermal stability threshold, a unique identification mark is added to the physical location of the circuit breaker pole corresponding to the sampling point. All locations marked with the same identification mark are uniformly designated as thermal fault candidate areas, and the marking information is synchronously associated with the spatial coordinates of the corresponding location for subsequent traceability and identification.

[0032] The degree of field change at all adjacent sampling points along the electric field intensity sequence of the three-phase main busbar was reviewed group by group. It was confirmed that the degree of field change between all adjacent points did not reach the unified judgment standard corresponding to the electric field distortion threshold. At the same time, all temperature information contained in the temperature sequence of the upper surface of the circuit breaker pole was reviewed point by point. It was confirmed that the highest temperature value in the entire sequence did not reach the unified judgment standard corresponding to the thermal stability threshold. Under the premise that the two review results meet the established judgment requirements, the initial coupled field distribution dataset currently in use was marked with a valid data label in accordance with the simulation data hierarchical management specification. The dataset after the labeling was completed was officially judged as valid data.

[0033] Generate a set of co-evolutionary parameters, including: Traverse the initial coupled field distribution dataset, filter out all spatial discrete points with electric field strength values ​​greater than a preset first threshold, and connect adjacent spatial discrete points into one or more continuous field strength distortion regions; Extract the topological features of each field strength distortion region; Spatial superposition analysis of the curvature change profile and extension direction in the topological morphology features is performed to identify the coincidence point between the abrupt curvature change on the electrode surface and the abnormal attenuation of the normal field strength at the dielectric interface, and the coincidence point is marked as the co-evolution seed point. Based on the seed point of co-evolution, a preset buffer distance is extended outward along the edge of the projection shape to generate a joint influence domain. All topological feature data sets within the joint influence domain are stored as a co-evolution parameter set.

[0034] The preset first threshold is as follows: Obtain the minimum insulation withstand strength value of all insulating media in the target switchgear, as well as the maximum allowable operating field strength value corresponding to the rated voltage level of the target switchgear; Compare the minimum insulation withstand strength value with the maximum permissible working field strength value, and take the smaller of the two as the benchmark reference value; Obtain the partial discharge initiation field strength value recorded in the factory withstand voltage test of the target switchgear, and then multiply the weighted average of the partial discharge initiation field strength value and the benchmark reference value by the safety margin coefficient to generate the preset first threshold.

[0035] Following the natural arrangement of the three-dimensional spatial points formed by the model's meshing, each stored record in the initial coupled field distribution dataset is read one by one. For each record, the three-dimensional coordinates, electric field strength values, and associated field quantity information of the corresponding spatial point are retrieved synchronously. The first threshold defined by combining the current national standards for switchgear insulation protection and the rated insulation level of the equipment is used as the unified judgment benchmark for the entire domain. The electric field strength values ​​recorded in each record are verified one by one, and all spatial discrete points with electric field strength values ​​higher than the benchmark limit are screened out. These spatial discrete points are sampling points that exist independently after the model meshing and have unique three-dimensional coordinates. The spatial adjacency judgment regulations for high-voltage equipment are strictly implemented. Spatial discrete points that are adjacent to each other in the six directions of up, down, left, right, front, and back in the three-dimensional space are connected in series. Discrete point groups that do not have an adjacency relationship in space are divided into independent blocks. After completing the point connection and area division work, the three-dimensional spatial range with one or more continuous closed boundaries is the field strength distortion region.

[0036] For each field strength distortion region whose boundaries have been delineated and ranges distinguished, information collection work is carried out in strict accordance with the general specifications for collecting electrical field topology features. The information includes the overall three-dimensional contour of the region, the cross-sectional contour, the actual extension direction of the boundary lines inside and outside the region, the full coverage range in the three-axis direction, and the density and clustering of all spatial discrete points inside the region. All the collected morphological information is categorized and organized into contour, boundary, range, and point distribution categories. The categorized information is then uniformly collected and grouped. The complete set of morphological information content formed after the organization and collection is the unique topological morphological feature of the corresponding field strength distortion region.

[0037] Based on the unified three-dimensional coordinate system of the model, the curvature change contour information recorded in the topological morphology features and the overall extension direction information of the region are matched and compared point by point in the whole domain. The location is distinguished strictly in accordance with the high-voltage equipment medium interface field strength operation judgment standard. Various spatial points where the curvature of the electrode body surface changes stepwise are accurately identified. At the same time, various spatial points at the interface of different insulating media where the electric field strength decay rate along the interface normal direction deviates from the normal operating standard range of the equipment are identified. The three-dimensional coordinates corresponding to the above two types of abnormal positions are checked accurately group by group. Points with completely consistent three-axis coordinate values ​​are uniformly marked as coincident points. A unique identification code is compiled for all identified coincident points and a permanent position mark is added. All points that have completed the marking work are uniformly set as symbiotic evolution seed points.

[0038] Based on the optimized design specifications for electrodes and insulation structures of high-voltage switchgear, a fixed linear length is set as the buffer distance. This length matches the reasonable adjustment range of the conventional structure optimization of the equipment. Taking the precise three-dimensional spatial position corresponding to each symbiotic evolution seed point as a reference benchmark, the local solid structure where the seed point is located is mapped onto the reference projection plane to obtain the corresponding projection shape. Along the direction of all outer edge lines of the projection shape, the spatial boundary is uniformly expanded outward according to the predetermined buffer distance. The three-dimensional spatial range with a complete closed boundary formed after the expansion operation is completed is the joint influence domain. All topological feature-related content, such as contour data, curvature data, point data, and medium interface data contained within the joint influence domain, is comprehensively collected. All collected data is sorted and arranged according to the preset standardized storage format with spatial index and feature classification. Then, centralized integration and classification archiving operations are completed. The complete data set formed after the entire processing flow is the symbiotic evolution parameter set.

[0039] Retrieve the complete set of component inspection reports and insulation material performance files retained at the time of manufacture of the target switchgear. The files contain complete records of withstand voltage test data and long-term insulation withstand parameters for each type of insulating component, solid insulating medium, composite insulating material, and air insulation gap. Conduct statistical work on the insulation withstand strength index of all insulating products installed inside the switchgear, such as epoxy resin components, insulating partitions, insulating bushings, and filling media. Compare and screen all the statistical index values ​​one by one, and extract the lowest value in the whole set of indexes as the minimum insulation withstand strength value. At the same time, consult the officially effective industry operation standard documents for high-voltage switchgear of the corresponding voltage level, locate the electric field strength control item corresponding to the rated voltage level of the target switchgear in the document, and extract the upper limit of electric field strength that cannot be exceeded during the normal operation of the equipment as clearly stipulated in the item. This upper limit is the maximum allowable operating electric field strength value.

[0040] The minimum insulation withstand strength value and the maximum allowable working field strength value obtained in the early stage are compared item by item according to the high voltage insulation parameter standard comparison process. The judgment action is carried out in strict accordance with the high voltage insulation equipment field strength benchmark selection specification. Combined with the core requirements of equipment insulation safety protection, the smaller value of the two sets of values ​​is selected. The field strength value selected by the selection is the benchmark reference value used for subsequent threshold calculation.

[0041] The complete set of original monitoring records from the factory withstand voltage test of the target switchgear is retrieved. The records fully preserve the data of the entire process of the power frequency withstand voltage test and the partial discharge test, as well as the correspondence between field strength changes and discharge phenomena. The critical field strength content corresponding to the moment when the equipment is about to produce a partial discharge phenomenon is accurately extracted from the test records. This critical field strength content is the field strength value at which no partial discharge begins. A fixed value is set according to the power equipment insulation safety design specification as a safety margin coefficient. This coefficient is used to offset the influence of field strength changes caused by long-term operation and small fluctuations in operating conditions. According to the established weight allocation rules set by the industry for the insulation threshold of high-voltage switchgear, the field strength value at which no partial discharge begins, the benchmark reference value, and the corresponding values ​​of the safety margin coefficient are integrated. The entire integration process is carried out in full accordance with the industry's general operating requirements. The unified field strength judgment standard obtained after the complete integration process is the preset first threshold.

[0042] When the optimized field model is obtained, an intermediate field model is first generated, including: Extract all geometric feature sets marked as to be smoothed from the co-evolution parameter set. The geometric feature set includes the coordinate positions and curvature change contours of sharp corner regions and convex regions with a curvature radius of less than a preset curvature threshold on the electrode surface. For sharp corner regions, the corresponding electrode surface mesh nodes are found in the reference field model, and the mesh nodes are offset outward along the normal of the electrode surface by an incremental amount. For the protruding region, find the corresponding protruding vertex in the reference field model, and expand a circular region around the protruding vertex. Gradually reduce the height value of all grid nodes in the circular region to be flush with the surrounding electrode surface. The adjusted mesh nodes are refitted into a continuous electrode surface to generate an intermediate field model with optimized geometric parameters.

[0043] Based on the co-evolution parameter set, the geometric parameters and material layout of the corresponding regions in the baseline field model are adjusted in a targeted manner to obtain an optimized field model, including: Extract all interface feature sets marked as transition layers to be added from the symbiotic evolution parameter set; In the reference field model, locate the medium interface corresponding to the interface feature set, and insert new material layers layer by layer from one side of the medium to the other side along the normal direction of the medium interface. The dielectric constant of the new material layer is set to gradually transition from the dielectric constant value of the first side medium to the dielectric constant value of the second side medium, and the thickness of each new material layer is inversely proportional to the local gradient value of the electric field gradient abrupt change band. The inserted new material layer is fused with the original medium material at common nodes to generate an intermediate field model with optimized material layout. Then, the intermediate field model with optimized geometric parameters is merged with the intermediate field model with optimized material layout to obtain an optimized field model.

[0044] Based on the current industry standards for electrode structure design of high-voltage switchgear, a fixed value is set as the curvature threshold. This threshold is used to distinguish between the conventional smooth curved surface of the electrode and the irregular structure that is prone to field strength concentration. All classification records in the co-evolution parameter set are traversed one by one according to spatial region and feature type. The optimization type label attached to each data is accurately retrieved. All feature data marked with exclusive identifiers for smoothing optimization are selected. All the selected data are summarized and integrated to form an independent geometric feature set. This set fully includes the precise three-dimensional spatial coordinates, region boundary range and grid node number of the sharp corner region and convex region of the electrode surface curvature radius that does not reach the preset curvature threshold. At the same time, it fully retains the morphological information such as the continuous curvature change contour and curvature extreme point position of the entire region of the two types of regions.

[0045] Based on the complete 3D spatial coordinates and region numbering information recorded in the geometric feature set, point matching is completed within the global structured grid architecture of the reference field model. All grid nodes belonging to the electrode surface in the sharp corner region are accurately located. At the same time, grid nodes inside the electrode are distinguished and excluded. According to the high-voltage electrical equipment electrode morphology optimization operation specifications, a fixed linear scale is set as the increment. The unique outward normal is determined based on the tangent of each grid node on the electrode surface. Along this fixed spatial direction, the outward position offset operation is performed on all located grid nodes simultaneously. The offset scale of all nodes in the entire domain strictly matches the predetermined increment, and the relative topological connection relationship between nodes remains unchanged during the offset process.

[0046] Based on the precise spatial coordinate information recorded in the geometric feature set, the convex vertex corresponding to the convex region is accurately located within the electrode structure range of the reference field model. This vertex is the highest feature point of the local convex structure. Taking the three-dimensional spatial position of this convex vertex as the center, a fixed radius is selected according to the unified standard for optimizing the insulation structure of the high-voltage switchgear cabinet. A complete circular area is delineated in the projection plane of the electrode surface. All grid nodes belonging to the electrode surface within the circular area are identified and counted one by one. Starting from the central grid node corresponding to the center, the height position of each grid node is gradually adjusted according to the operation sequence from the center to the outer circumference. The height values ​​of the current node and the surrounding adjacent electrode nodes are compared in real time until the height position of each grid node in the circular area is completely aligned with the height position of the surrounding continuous adjacent electrode surfaces.

[0047] All electrode surface mesh nodes that have undergone offset and elevation changes are systematically reviewed and checked according to the original mesh topology of the model. Isolated nodes with abnormal coordinates are identified and corrected. Referring to the spatial surface orientation, interlayer connection logic, and global curvature variation law of the original electrode design, continuous surface connection reconstruction is carried out on the discretely distributed mesh nodes to ensure that all mesh nodes are smoothly connected to each other, forming a complete continuous electrode surface without discontinuities, steps, or abrupt changes in shape. The overall model obtained after the global electrode surface reconstruction is completed is the intermediate field model with optimized geometric parameters.

[0048] The system systematically organizes all feature data entries stored within the symbiotic evolution parameter set according to topological characteristics and optimization directions. It identifies the functional identifiers attached to each data entry, filters out all data content marked with exclusive identifiers for the transition layer to be added, and then partitions, classifies, and unifies the selected medium interface spatial coordinates, interface extension contours, local field association information, and medium category information on both sides. It supplements the standardized spatial index coding to complete the data collection. After the entire process, a complete interface feature set with clear indexes is formed.

[0049] Based on the complete 3D spatial coordinates, interface extension contours, and orientation information recorded in the interface feature set, each medium interface to be optimized is precisely located in the overall 3D spatial structure of the reference field model. Using the cross-section of the medium interface as a reference, a fixed direction perpendicular to the cross-section is determined as the normal direction. Along this normal direction, the process extends from the original medium area on the first side of the interface to the original medium area on the second side, following a unified layer sequence rule of arranging layers from near to far. The new material layers are then laid out and inserted sequentially throughout the entire area of ​​the medium interface, with the outline of each new material layer perfectly matching the outline of the medium interface.

[0050] Following the high-voltage insulation dielectric matching design specifications, the dielectric properties of each newly inserted material layer are configured to ensure that the dielectric constant of each new material layer changes smoothly along the normal direction of the dielectric transition. The parameter value gradually transitions from the inherent dielectric constant of the original dielectric on the first side to the inherent dielectric constant of the original dielectric on the second side, without any parameter jumps. The electric field gradient abrupt change zone identified in the previous simulation is used as the dividing range, and the degree of local field change within the abrupt change zone is used as the basis for thickness determination. The thickness of the new material layer is set to a smaller value for the local location with a higher degree of field change, and a larger value for the local location with a lower degree of field change. The actual thickness of each new material layer is determined one by one according to this fixed determination rule.

[0051] Each newly laid material layer and the original media on both sides of the interface are connected by relying on the existing mesh nodes of the model to achieve seamless structural connection by sharing the same set of mesh nodes at the boundary positions of adjacent media structures. This completely eliminates structural gaps and interface discontinuities between media layers. After the media fusion work is completed, a model with continuous structure and complete integrity is formed. This model is the intermediate field model with optimized material layout. The intermediate field model with optimized geometric parameters and the intermediate field model with optimized material layout are spliced ​​and fully fused together in strict accordance with the original three-dimensional spatial topology, component assembly positions and global mesh system of the reference field model. After the structure, parameters and mesh of the two intermediate models are unified and integrated, the final complete global model is the optimized field model.

[0052] Repeated multiphysics coupling simulations were performed on the optimized field model. The output shows the electric field reconstruction distribution map of the optimized field model when the maximum electric field intensity is lower than the first threshold, including: The optimized field model is used as the current iteration field model. The current iteration field model is then subjected to a coupled simulation of the electromagnetic, thermal and fluid multiphysics fields to generate the current iteration coupled field distribution dataset. Extract the maximum electric field intensity value of the entire domain from the current iterative coupled field distribution dataset, and compare the maximum electric field intensity value with the first threshold; If the maximum electric field strength value is greater than or equal to the first threshold, the current iterative coupled field distribution dataset is used as the new initial coupled field distribution dataset, and the steps of generating the co-evolution parameter set and directional adjustment are re-executed to obtain the optimized field model for the next iteration. If the maximum electric field strength value is lower than the first threshold, the iteration stops, and the current iteration field model is output as the final reconstruction model. At the same time, electric field strength distribution data is extracted from the current iteration coupled field distribution dataset, and an electric field reconstruction distribution map is generated according to the geometric coordinate mapping of the final reconstruction model.

[0053] The optimized field model, after adjustments to both geometric parameters and material layout, is formally designated as the current iteration field model for this round of cyclic computation. Throughout the process, the unified and solidified set of boundary condition configuration templates, rated operating condition excitation source layout schemes, and multi-threaded parallel working mechanism for the simultaneous operation of four types of threads—electric field, magnetic field, thermal field, and fluid field—are used in the previous simulation work. An integrated multi-physics field coupling simulation of electric-magnetic-thermal-fluid fields is carried out. The simulation process strictly follows the established rules for field quantity interaction and transfer, continuously completes the calculation of each coupling iteration step, and determines the simulation termination node according to the preset convergence threshold. After the simulation process is completed, the four types of field quantity information generated in the entire model domain—electric field strength, magnetic induction intensity, temperature, and gas velocity—are summarized. All field quantity information is classified, sorted, and integrated according to a unified data format and spatial coordinate indexing rules. After the entire set of sorting work is completed, a complete and indexed dataset of the current iteration coupling field distribution is formed.

[0054] The algorithm iterates through each point record with unique three-dimensional spatial coordinates in the current iterative coupled field distribution dataset, reading the specific electric field strength values ​​corresponding to each gridded spatial point, and completely recording the field quantity information of all points in the entire domain. After the traversal and retrieval work is completed, the highest value is selected from all electric field strength values, which is the maximum electric field strength value of the entire domain. The first threshold previously determined in combination with switchgear insulation protection standards, factory test data, and safety margin requirements is used as a unified and fixed judgment benchmark for the entire domain. The extracted maximum electric field strength value of the entire domain is accurately compared and verified with this benchmark, and the comparison results are completely retained as the judgment basis for subsequent process execution.

[0055] When the comparison results confirm that the maximum electric field strength value of the entire domain meets the judgment condition of being greater than or equal to the first threshold, the data purpose attribute of the current iterative coupled field distribution dataset is re-labeled, and it is determined as the initial coupled field distribution dataset used in the new round of optimization process. Each step is carried out in strict accordance with the entire set of standardized operating procedures, including the complete execution of operations such as spatial discrete point screening and field strength distortion region division, topological morphology feature acquisition of each region, identification of symbiotic evolution seed points and joint influence domain delineation, and organization and generation of symbiotic evolution parameter set. Then, based on the generated parameter set, the geometric parameter orientation adjustment of the model electrode structure and the material layout optimization of the dielectric interface are completed in sequence. After the entire set of procedures is completed in accordance with the specifications, a brand-new optimized field model corresponding to this round of iteration process is generated.

[0056] When the comparison results confirm that the maximum electric field strength value of the entire domain meets the judgment condition of being lower than the first threshold, all simulation calculations, feature extraction, model adjustment and other work processes related to the iteration cycle are immediately stopped. The current iteration field domain model is officially recognized as the final reconstruction model. The model file classification, storage, version recording and path archiving are completed in accordance with the high-voltage equipment simulation model archiving management specifications. The original electric field strength distribution data covering the entire spatial area of ​​the model is completely extracted from the current iteration coupled field distribution dataset. Relying on the full-domain three-dimensional spatial geometric coordinate system built into the final reconstruction model, the electric field data and each grid point of the model are accurately matched point-to-point. The conversion and mapping of field quantity values ​​to visualization graphics are completed in strict accordance with the industry standards for electrical field map production. The full-domain electric field distribution state is completely restored. After all mapping work is completed, an electric field reconstruction distribution map with accurate data, complete outline and standardized display is generated.

[0057] Example 2: Figure 2 As shown, a switchgear electric field reconfiguration system based on field symbiosis simulation is used to implement the method in Embodiment 1, comprising the following modules connected in sequence: The multi-field simulation module is used to perform coupled simulation of multiple physics fields (electromagnetic, thermal, and fluid) on the reference field model of the target switchgear, and generate an initial coupled field distribution dataset. The topology parameter generation module is used to generate a set of co-evolution parameters based on the topology of the region where the electric field intensity value exceeds the first threshold in the initial coupled field distribution dataset. The model tuning module is used to make directional adjustments to the geometric parameters and material layout of the corresponding region in the benchmark field model based on the co-evolution parameter set, so as to obtain an optimized field model. The spectrum output module is used to repeatedly perform multi-physics coupling simulation on the optimized field model and output the electric field reconstruction distribution spectrum corresponding to the optimized field model when the maximum electric field intensity in the optimized field model is lower than the first threshold.

[0058] The implementation details of each module are the same as in Example 1.

[0059] Figure 3 A bar chart showing the multi-factor comprehensive calculation of the first threshold for electric field reconstruction. Determining the first threshold is the core decision-making process of the entire electric field reconstruction algorithm. Figure 3 The logical chain of threshold calculation was demonstrated through multi-factor weighted analysis. The system first collects the minimum insulation withstand strength values ​​of all insulating media (such as epoxy resin and air gaps) within the target switchgear and compares them with the maximum permissible operating field strength under the rated voltage level, taking the smaller of the two as the physical boundary benchmark. To further improve the engineering practicality of the reconfigured distribution, the "no partial discharge initiation field strength value" recorded during the factory withstand voltage test of this type of switchgear was also introduced as a real-time verification reference.

[0060] The final first threshold was calculated by weighting the aforementioned physical benchmarks and experimental data and multiplying it by a safety margin factor less than 1. This calculation model not only considers the intrinsic limits of the material but also takes into account the safety margin caused by fluctuations in the operating environment. As can be clearly seen in the comparison of the bar charts, the calculated first threshold is slightly lower than the minimum insulation strength, forming a robust insulation safety barrier. The threshold definition method using multi-source data fusion in this embodiment ensures that the model after electric field reconstruction not only meets the standards at the simulation level but also maintains long-term reliability under actual electrical operating conditions.

[0061] Figure 4 The graph shows the effect of directional adjustment of electrode surface geometry parameters and curvature smoothing. During the model optimization stage based on the evolution parameter set, the geometric correction of the electrode surface demonstrates the specific application of differential geometry in engineering design. Figure 4 The system demonstrates a "smooth evolution" process for electrode sharp corners and protruding regions. It extracts a set of geometric features to be optimized from the co-evolution parameter set and reconstructs the shape by performing a normal offset algorithm on the mesh nodes.

[0062] For sharp corner regions, the algorithm drives the mesh nodes to perform a small incremental offset outward along the normal of the electrode surface to increase the local radius of curvature; while for convex regions, a radial smoothing strategy centered on the vertex is adopted, which reduces the height value of local nodes to achieve a smooth connection with the surrounding continuous surface. Figure 4 The red dashed line represents the drastic curvature fluctuations before optimization, while the green solid line shows the smooth curvature transition after adjustment. The directional adjustment mechanism in this embodiment is not a global, blind change, but rather strictly constrained within the joint influence domain defined by the symbiotic evolution parameter set. By refitting the continuous electrode surface curvature, the system minimizes the electric field concentration effect caused by geometric abrupt changes without altering the main function of the components.

[0063] Figure 5 To optimize the convergence path of the iterative process of the field model, a convergence path of the optimized field model after multiple multiphysics simulations is shown. Each adjusted intermediate field model is considered a new iteration subject and re-enters the electro-magnetic-thermal-fluid coupled simulation thread for full-scale extrapolation. The system monitors the maximum electric field intensity value across the entire domain in real time and dynamically compares it with a first threshold. If the maximum field intensity still reaches or exceeds the threshold, the system will recalculate the co-evolution parameters based on the currently generated coupled field dataset, triggering a new round of geometry and material adjustments. Figure 5The black broken line with marked points clearly records the steady decrease of the maximum electric field strength as the number of iterations increases. The closed-loop logic of simulation, evaluation, adjustment, and re-simulation in this embodiment ensures the determinism of the optimization direction. When the maximum electric field strength successfully drops below the first threshold into the "electric field reconstruction target zone," the iteration automatically stops, thus avoiding over-design and ensuring the optimality of the reconstruction result under physical boundary constraints.

[0064] Figure 6 The system reconstructs the global electric field intensity distribution map of the reconstructed switchgear. As the final output, the electric field reconstruction distribution map is a visual representation of the high-quality reconstruction work. This map uses high-precision cloud mapping technology to show the electric field energy distribution of the final reconstructed model across the entire domain. The system extracts the converged current iteration coupled field distribution dataset and aligns it with the geometric coordinate system of the final model with high precision.

[0065] Figure 6 The equipotential lines displayed are extremely uniform, and the high-density red field strength clusters no longer appear at the electrode edges and dielectric interfaces. The smooth color transition signifies the homogenization of the potential gradient, directly demonstrating the synergistic effectiveness of the preceding geometric smoothing and material gradient adjustment. This map not only provides a quantitative reading of the global field strength but also offers an intuitive topological representation, providing engineers with a basis for verifying the reconstruction effect and evaluating the insulation margin of equipment. In terms of spatial accuracy, the mapping algorithm employs trilinear interpolation technology, ensuring that the distribution details of the electric field can be accurately reproduced even at extremely fine grid cells, achieving a high-quality conversion from discrete data to a continuous distribution map.

[0066] Example 3: A switchgear electric field reconstruction device based on field symbiosis simulation, comprising: One or more processors; Memory, used to store one or more computer programs; When one or more programs are executed by one or more processors, the one or more processors execute the method in Example 1.

[0067] Example 4: A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method in Example 1.

[0068] Finally, it should be noted that the above 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for reconstructing the electric field of a switchgear based on field symbiosis simulation, characterized in that the steps are as follows: include: For the reference field model of the target switchgear, perform coupled simulation of multiple physics fields including electromagnetism, heat and current to generate an initial coupled field distribution dataset; Based on the topological features of regions where the electric field intensity exceeds a first threshold in the initial coupled field distribution dataset, a set of co-evolution parameters is generated, including: Traverse the initial coupled field distribution dataset, filter out all spatial discrete points with electric field strength values ​​greater than a preset first threshold, and connect adjacent spatial discrete points into one or more continuous field strength distortion regions; Extract the topological features of each field strength distortion region; Spatial superposition analysis of the curvature change profile and extension direction in the topological morphology features is performed to identify the coincidence point between the abrupt curvature change on the electrode surface and the abnormal attenuation of the normal field strength at the dielectric interface, and the coincidence point is marked as the co-evolution seed point. Based on the seed point of co-evolution, a preset buffer distance is extended outward along the edge of the projection shape to generate a joint influence domain. All topological feature data sets within the joint influence domain are stored as a co-evolution parameter set. Based on the co-evolution parameter set, the geometric parameters and material layout of the corresponding region in the benchmark field model are adjusted in a directional manner to obtain the optimized field model; The multiphysics coupling simulation is repeatedly performed on the optimized field model, and the electric field reconstruction distribution map of the optimized field model is output when the maximum electric field intensity in the optimized field model is lower than the first threshold.

2. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 1, characterized in that, The specific reference field model is as follows: Obtain the initial three-dimensional structural model of the target switchgear. The initial three-dimensional structural model includes the three-phase main bus, circuit breaker poles, contact boxes, current transformers, grounding switches, and metal enclosure. The geometric dimensions of each component, the relative positions between each component, and the material properties of each component in the initial three-dimensional structural model are set as variables that can be changed independently to obtain the reference field model.

3. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 2, characterized in that, Generate an initial coupled field distribution dataset, including: Preset boundary conditions and excitation sources are applied to the reference field model; Simultaneously start the electric field simulation thread, magnetic field simulation thread, thermal field simulation thread, and fluid field simulation thread; In each coupling iteration step, the temperature distribution obtained by the thermal field simulation thread is fed back to the electric field simulation thread and the magnetic field simulation thread to update the conductivity parameters of each component and the magnetic permeability parameters of the ferromagnetic component. Simultaneously, the gas velocity distribution obtained by the fluid field simulation thread is fed back to the thermal field simulation thread to update the convective heat transfer coefficient. When the maximum relative rate of change of the electric field intensity distribution between two adjacent iterations is lower than the preset convergence threshold, the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution and gas velocity distribution are stored together as the initial coupled field distribution dataset.

4. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 3, characterized in that, After storing the converged electric field intensity distribution, magnetic induction intensity distribution, temperature distribution, and gas velocity distribution together as the initial coupled field distribution dataset, the following is also included: The electric field intensity sequence along the central axis of the three-phase main bus, the magnetic induction intensity sequence along the inner wall of the metal enclosed shell, and the temperature sequence on the upper surface of the circuit breaker pole were extracted from the initial coupled field distribution dataset. Determine whether the gradient between two adjacent points in the electric field intensity sequence exceeds the preset electric field distortion threshold. If so, mark the area between the two adjacent points as a potential partial discharge risk area. Determine whether the highest value of the temperature sequence exceeds the preset thermal stability threshold. If so, mark the corresponding position of the circuit breaker pole as a thermal fault candidate area. The initial coupled field distribution dataset is considered valid only if the electric field intensity sequence does not have a gradient exceeding the electric field distortion threshold and the highest value of the temperature sequence is below the thermal stability threshold.

5. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 1, characterized in that, The preset first threshold is as follows: Obtain the minimum insulation withstand strength value of all insulating media in the target switchgear, as well as the maximum allowable operating field strength value corresponding to the rated voltage level of the target switchgear; Compare the minimum insulation withstand strength value with the maximum permissible working field strength value, and take the smaller of the two as the benchmark reference value; Obtain the partial discharge initiation field strength value recorded in the factory withstand voltage test of the target switchgear, and then multiply the weighted average of the partial discharge initiation field strength value and the benchmark reference value by the safety margin coefficient to generate the preset first threshold.

6. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 1, characterized in that, When the optimized field model is obtained, an intermediate field model is first generated, including: Extract all geometric feature sets marked as to be smoothed from the co-evolution parameter set. The geometric feature set includes the coordinate positions and curvature change contours of sharp corner regions and convex regions with a curvature radius of less than a preset curvature threshold on the electrode surface. For sharp corner regions, the corresponding electrode surface mesh nodes are found in the reference field model, and the mesh nodes are offset outward along the normal of the electrode surface by an incremental amount. For the protruding region, find the corresponding protruding vertex in the reference field model, and expand a circular region around the protruding vertex. Gradually reduce the height value of all grid nodes in the circular region to be flush with the surrounding electrode surface. The adjusted mesh nodes are refitted into a continuous electrode surface to generate an intermediate field model with optimized geometric parameters.

7. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 6, characterized in that, Based on the co-evolution parameter set, the geometric parameters and material layout of the corresponding regions in the baseline field model are adjusted in a targeted manner to obtain an optimized field model, including: Extract all interface feature sets marked as transition layers to be added from the symbiotic evolution parameter set; In the reference field model, locate the medium interface corresponding to the interface feature set, and insert new material layers layer by layer from one side of the medium to the other side along the normal direction of the medium interface. The dielectric constant of the new material layer is set to gradually transition from the dielectric constant value of the first side medium to the dielectric constant value of the second side medium, and the thickness of each new material layer is inversely proportional to the local gradient value of the electric field gradient abrupt change band. The inserted new material layer is fused with the original medium material at common nodes to generate an intermediate field model with optimized material layout. Then, the intermediate field model with optimized geometric parameters is merged with the intermediate field model with optimized material layout to obtain an optimized field model.

8. The switchgear electric field reconstruction method based on field symbiosis simulation as described in claim 1, characterized in that, Repeated multiphysics coupling simulations were performed on the optimized field model. The output shows the electric field reconstruction distribution map of the optimized field model when the maximum electric field intensity is lower than the first threshold, including: The optimized field model is used as the current iteration field model. The current iteration field model is then subjected to a coupled simulation of the electromagnetic, thermal and fluid multiphysics fields to generate the current iteration coupled field distribution dataset. Extract the maximum electric field intensity value of the entire domain from the current iterative coupled field distribution dataset, and compare the maximum electric field intensity value with the first threshold; If the maximum electric field strength value is greater than or equal to the first threshold, the current iterative coupled field distribution dataset is used as the new initial coupled field distribution dataset, and the steps of generating the co-evolution parameter set and directional adjustment are re-executed to obtain the optimized field model for the next iteration. If the maximum electric field strength value is lower than the first threshold, the iteration stops, and the current iteration field model is output as the final reconstruction model. At the same time, electric field strength distribution data is extracted from the current iteration coupled field distribution dataset, and an electric field reconstruction distribution map is generated according to the geometric coordinate mapping of the final reconstruction model.

9. A switchgear electric field reconfiguration system based on field symbiosis simulation, used to implement the method described in any one of claims 1 to 8, characterized in that, include: The multi-field simulation module is used to perform coupled simulation of multiple physics fields (electromagnetic, thermal, and fluid) on the reference field model of the target switchgear, and generate an initial coupled field distribution dataset. The topology parameter generation module is used to generate a set of co-evolution parameters based on the topology of the region where the electric field intensity value exceeds the first threshold in the initial coupled field distribution dataset. The model tuning module is used to make directional adjustments to the geometric parameters and material layout of the corresponding region in the benchmark field model based on the co-evolution parameter set, so as to obtain an optimized field model. The spectrum output module is used to repeatedly perform multi-physics coupling simulation on the optimized field model and output the electric field reconstruction distribution spectrum corresponding to the optimized field model when the maximum electric field intensity in the optimized field model is lower than the first threshold.

Images