Vacuum interrupter insulation structure optimization method, system, storage medium and device

Abstract

The application relates to the technical field of vacuum arc-extinguishing chamber insulation structure, and discloses a vacuum arc-extinguishing chamber insulation structure optimization method, which comprises the following steps: a two-dimensional axisymmetric electrostatic field parameterized geometric model is established in finite element simulation software, and design variables are defined; optimization is set, and constraint conditions of the design variables are preset; a whale optimization algorithm is adopted, the number of whales is set according to the dimension of the design variables, and the position vector of each whale represents the value of a group of design variables; for each whale individual, the position vector is automatically assigned to the parameterized geometric model, finite element electrostatic field simulation is triggered once, the global maximum electric field strength is extracted as the fitness value of the individual, the position vector with the minimum fitness value is taken as the optimal position vector, the position vectors of all whale individuals are updated, the parameter combination of the design variables corresponding to the global optimal position vector is obtained, and the optimization design scheme is taken as the parameter combination, so that the blank in the aspects of systematicness, automation and global optimization capability is filled up.

Description

Technical Field

[0001] This invention relates to the field of vacuum interrupter insulation structure technology, and in particular to a method, system, storage medium and device for optimizing the insulation structure of a vacuum interrupter. Background Technology

[0002] Vacuum circuit breakers are key devices in power systems for realizing circuit breaking, closing, and protection functions, with the vacuum interrupter being its core component. The uniformity of the electric field distribution and the magnitude of the maximum electric field strength inside the interrupter directly affect the insulation performance and operational reliability of the equipment. Optimizing the electric field distribution within the interrupter and reducing local electric field concentration are of great significance for improving the insulation strength of the circuit breaker, reducing the risk of breakdown, extending its service life, and ensuring the safe and stable operation of the power grid.

[0003] Currently, insulation optimization methods for vacuum interrupters mainly focus on analyzing the impact of single or a few structural parameters on the electrostatic field distribution through finite element method (FEM) simulations. For example, the contact gap, the chamfer radius of the contact edges, the radius and shape of the main shield, and the relative positional relationship between the conductive rod and the shield have all been proven to be key factors affecting the electric field strength. Studies generally show that appropriately increasing the contact gap and chamfer radius can effectively reduce the electric field concentration at the contact edges; while optimizing the structure and position of the main shield can significantly improve the overall uniformity of the electric field distribution. These studies provide valuable qualitative guidance and some quantitative references for the engineering design of interrupters.

[0004] However, existing methods still have significant limitations. First, most studies employ univariate analysis or orthogonal experimental design, i.e., fixing other parameters and changing only one or a few to observe changes in the electric field. While intuitive, this approach ignores the complex couplings and interactions that may exist between structural parameters, making it difficult to obtain a truly globally optimal solution. Second, the optimization process heavily relies on engineers' experience and repeated trial-and-error processes of "simulation-adjustment-resimulation," resulting in low efficiency, long design cycles, and optimization results that are often not optimal, or even locally optimal. Third, as vacuum circuit breakers develop towards high voltage, large capacity, and miniaturization, the internal structure of the arc-extinguishing chamber is becoming increasingly complex, and the electric field environment is becoming more severe, placing higher demands on insulation design. Traditional methods are proving inadequate when facing multidimensional, nonlinear, and strongly coupled optimization problems. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter, thereby filling the gaps in existing technologies regarding systematic, automated, and global optimization capabilities.

[0006] The first aspect of this invention provides a method for optimizing the insulation structure of a vacuum interrupter, comprising the following steps: Taking the vacuum interrupter as the optimization object, a two-dimensional axisymmetric electrostatic field parameterized geometric model of it was established in the finite element simulation software, and several key geometric parameters affecting the electric field distribution were defined as design variables. The optimization objective is set to minimize the maximum electric field intensity inside the vacuum interrupter, while pre-setting constraints on the design variables. The whale optimization algorithm is adopted. The number of whales is set according to the dimension of the design variables. Within the preset range of design variable values, an initial population composed of multiple individual whales is randomly generated. The position vector of each whale represents a set of design variable values. For each individual whale, its position vector is automatically assigned to the parametric geometric model, and a finite element electrostatic field simulation is triggered to obtain the electric field distribution. The maximum electric field intensity in the global domain is extracted as the fitness value of the individual. The position vector with the smallest fitness value is taken as the optimal position vector. The position vectors of all individual whales are updated until the preset convergence condition is met. The parameter combination of design variables corresponding to the globally optimal position vector is obtained as the final insulation structure optimization design scheme.

[0007] Optional key geometric design variables include the following parameters: contact gap, contact edge chamfer radius, main shield radius, distance between the stationary main shield and the conductive rod, and distance between the stationary main shield and the end shield.

[0008] Optionally, the optimization objective is to minimize the maximum electric field strength throughout the arc-extinguishing chamber under the condition that the rated working voltage is applied to the stationary end and the moving end is grounded. The maximum electric field strength shall not exceed 80% of the allowable value of the material. The constraints include: the contact opening distance is in the range of 20mm to 25mm, the contact edge chamfer radius is in the range of 0.5mm to 3mm, the main shield radius is in the range of 70mm to 75mm, the distance between the stationary end main shield and the conductive rod is in the range of 7mm to 12mm, and the distance between the stationary end main shield and the end shield is in the range of 33mm to 53mm.

[0009] Optional, fitness value Determined by the following formula: , in, This represents the maximum electric field strength value. For the first i The amount of violation of a constraint. For the first i The penalty coefficient for each constraint violation is set to 250.

[0010] Optional, C i Determined based on the type of inequality in the constraint conditions, including: For design variables exceeding the boundary constraints, the violation value is taken as the absolute value of the portion exceeding the boundary. For the allowable value constraint on electric field strength, the violation is the portion of the actual electric field strength that exceeds the allowable value.

[0011] Optionally, updating the whale's location includes the following steps: Obtain the system parameter A in the whale optimization algorithm, and generate random numbers P∈[0,1]; When P < 0.5, if |A| < 1, then update the position according to the prey encirclement strategy; if |A| ≥ 1, then update the position according to the random search strategy. When P≥0.5, update the position according to the bubble net attack strategy; Perform boundary checks on the updated position to ensure it is within the preset value range of the design variables.

[0012] Optionally, triggering a finite element electrostatic field simulation includes the following steps: The whale's position vector is written into the corresponding variable of the parametric geometric model through a script interface, thereby enabling automatic updates of the model geometry. Automatically invoke and execute finite element simulation calculations of electrostatic fields; The post-processing program automatically extracts the global maximum electric field intensity value from the simulation results; The program automatically detects whether the whale's position vector violates the constraints of the design variables.

[0013] A second aspect of the present invention provides a system for optimizing the insulation structure of a vacuum interrupter, the system comprising: The parametric modeling module is used to establish a two-dimensional axisymmetric electrostatic field parametric geometric model of a vacuum interrupter in finite element simulation software, and to define several key geometric parameters that affect the electric field distribution as design variables. The problem definition module, connected to the parametric modeling module, is used to set the optimization objective and constraints. The optimization objective is to minimize the maximum electric field intensity inside the arc extinguishing chamber. The whale optimization module is used to execute the whale optimization algorithm process. It includes: a population initialization unit, which randomly generates an initial whale population within the range of design variable values, where the position vector of each whale individual represents a set of design variable values; a fitness evaluation and simulation driving unit, which automatically assigns the position vectors of whale individuals to the parameterized model and triggers automated finite element simulation to calculate the fitness value; and a position update unit, which updates the position vectors of whale individuals in the population according to the strategy of the whale optimization algorithm. The convergence judgment unit is used to determine whether the optimization process meets the preset convergence conditions; The output module is used to output the combination of structural parameters corresponding to the globally optimal position vector after the algorithm converges, as the final insulation structure optimization design scheme.

[0014] A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter.

[0016] The technical solution provided by the embodiments of the present invention has the following advantages compared with the prior art: This invention provides a method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter. Addressing the shortcomings of existing vacuum interrupter insulation design methods, which rely on manual experience, single-parameter analysis, are inefficient, and struggle to achieve global optimum, this invention employs the whale optimization algorithm as its optimization engine. This algorithm can simultaneously handle multivariable, high-dimensional search spaces defined by multiple key geometric parameters. During the iteration process, the algorithm searches on a population basis, exploring multiple parameter combinations simultaneously and considering their synergistic effects and coupling relationships. Its ultimate goal is to find the parameter combination that optimizes the global objective (minimum maximum electric field strength), rather than the optimal value of a single parameter. This effectively overcomes the limitations of traditional single-variable or orthogonal experimental methods in complex coupled problems, and has a higher probability of obtaining a truly global or near-global optimal solution. An automated closed-loop optimization process driven by algorithm simulation is constructed. Seamlessly integrating parametric modeling, automatic parameter assignment, triggered simulation, fitness calculation, and position updates, the algorithm automates the entire simulation-adjustment-resimulation process after defining design variables, objectives, and constraints. This significantly reduces reliance on human experience and intervention, greatly improving optimization design efficiency and shortening product development cycles. Deeply coupling the whale optimization algorithm with finite element electric field simulation, it automatically and systematically searches for the optimal combination of key geometric parameters, fundamentally optimizing the electric field distribution inside the arc-extinguishing chamber, reducing the maximum electric field intensity, and thus significantly improving its insulation reliability. It efficiently and automatically searches for the optimal combination of structural parameters that minimizes the maximum electric field intensity and achieves the most uniform electric field distribution inside the arc-extinguishing chamber, guiding the development of new products and the improvement of existing products, significantly enhancing the insulation performance and market competitiveness of vacuum circuit breakers. Attached Figure Description

[0017] Figure 1 A flowchart of a method for optimizing the insulation structure of a vacuum interrupter provided in an embodiment of the present invention; Figure 2 The present invention provides an operational flowchart for an optimization method of the insulation structure of a vacuum interrupter. Detailed Implementation

[0018] The following detailed description of a specific embodiment of the present invention is provided in conjunction with the accompanying drawings. However, it should be understood that the scope of protection of the present invention is not limited to the specific embodiment.

[0019] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the technical solution of this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0020] The present invention will be described below through several specific embodiments. To keep the following description of the embodiments clear and concise, detailed descriptions of known functions and components may be omitted. When any component of an embodiment of the present invention appears in more than one drawing, the component may be represented by the same reference numerals in each drawing.

[0021] like Figure 1 As shown, the first embodiment of the present invention provides a method for optimizing the insulation structure of a vacuum interrupter, including the following steps: Step 1: Taking the vacuum interrupter as the optimization object, establish its two-dimensional axisymmetric electrostatic field parameterized geometric model in the finite element simulation software, and define several key geometric parameters that affect the electric field distribution as design variables; Step 2: Set the optimization objective to minimize the maximum electric field intensity inside the vacuum interrupter, and preset the constraints of the design variables; Step 3: Employing the whale optimization algorithm, the number of whales is set according to the dimensions of the design variables. Within the preset range of design variable values, an initial population of multiple individual whales is randomly generated. The position vector of each whale represents a set of design variable values. For each individual whale, its position vector is automatically assigned to the parametric geometric model, triggering a finite element electrostatic field simulation to obtain the electric field distribution. The maximum electric field strength across the entire domain is extracted as the fitness value of that individual. The position vector with the smallest fitness value is taken as the optimal position vector (X*). The position vectors of all whale individuals are updated until the preset convergence condition is met, obtaining the parameter combination of design variables corresponding to the globally optimal position vector, which serves as the final insulation structure optimization design scheme. Specifically, this includes:

[0022] 3.1) Initialize the whale population: Based on the dimensions of the design variables (5) and the algorithm stability requirements, set the whale population size. N =30. Within the preset range of design variable values, an initial population of 30 whale individuals is randomly generated. The position vector of each whale individual represents a set of design variable values. (Fish population size) N The typical value is 30-50, and it is determined according to the number of design variables. In this embodiment, there are 5 variables, which is usually set to 5 to 10 times the number of variables to ensure the initial diversity of the population in the solution space. In this embodiment, 5 variables are selected. N =30. 3.2) Fitness assessment and automated simulation: For each individual whale in the population, its position vector is automatically assigned to the parameterized two-dimensional axisymmetric geometric model of step 1), and an automated finite element electrostatic field simulation is triggered. The simulation automatically calculates the electric field distribution under the set of structural parameters and extracts the global maximum electric field strength (Emax) as the fitness value of the individual.

[0023] 3.3) Update the current optimal position: Compare the fitness values ​​of all whale individuals to determine the current optimal whale position (X*), which represents the optimal solution in the current population.

[0024] 3.4) Updating Whale Location: According to the whale optimization algorithm, whales update their location using three strategies: encircling prey, bubble net attacks, and search-and-hunt. 3.5) Iterative Convergence Judgment: Repeat steps 3.2)-3.4), setting the convergence condition as follows: if the number of iterations reaches the preset maximum number of iterations (80), the algorithm is considered to have converged, and the iteration stops. Referring to relevant intelligent algorithm application research in the field of electrical equipment structure optimization, for multi-parameter optimization problems of similar complexity, a satisfactory solution can usually be obtained with a maximum number of iterations between 50 and 100. This invention comprehensively considers convergence reliability and computational efficiency, and sets the maximum number of iterations to 80. Therefore, the maximum number of iterations is selected as 80.

[0025] This invention provides an optimization method for the insulation structure of a vacuum interrupter. Addressing the shortcomings of existing vacuum interrupter insulation design methods, which rely on manual experience, single-parameter analysis, are inefficient, and struggle to achieve global optimum, this method employs a whale optimization algorithm as its optimization engine. This algorithm can simultaneously handle multivariable, high-dimensional search spaces defined by multiple key geometric parameters. During iteration, the algorithm searches on a population basis, exploring multiple parameter combinations simultaneously and considering their synergistic effects and coupling relationships. Its ultimate goal is to find the parameter combination that optimizes the global objective (minimum maximum electric field strength), rather than the optimal value of a single parameter. This effectively overcomes the limitations of traditional single-variable or orthogonal experimental methods in complex coupled problems, and has a higher probability of obtaining a truly global or near-global optimal solution. An automated closed-loop optimization process driven by algorithm simulation is constructed. Parametric modeling, automatic assignment, simulation triggering, fitness calculation, and position updating are seamlessly integrated. Only the design variables, objectives, and constraints need to be defined; the subsequent simulation-adjustment-resimulation process is entirely completed automatically by the algorithm, greatly reducing reliance on manual experience and human intervention, significantly improving optimization design efficiency, and shortening the product development cycle. By deeply coupling the whale optimization algorithm with finite element electric field simulation, the optimal combination of key geometric parameters is automatically and systematically searched to fundamentally optimize the electric field distribution inside the arc-extinguishing chamber, reduce the maximum electric field intensity, and thus significantly improve its insulation reliability. It efficiently and automatically searches for the best combination of structural parameters that minimizes the maximum electric field intensity and achieves the most uniform electric field distribution inside the arc-extinguishing chamber, thereby guiding the development of new products and the improvement of existing products, significantly enhancing the insulation performance and market competitiveness of vacuum circuit breakers.

[0026] Contact gap ( d ), contact edge chamfer radius ( r ), Main shield radius ( R It is indeed a conventional key geometric parameter affecting the electric field of a vacuum interrupter, and there is a lot of related research. Existing research may focus more on the size or position of a single shield, while less attention is paid to the systematic optimization of the relative positional relationship between the main shield at the stationary end and the adjacent conductor / shielding structure.

[0027] Based on the above problems, in this embodiment of the invention, the key geometric design variables include the following parameters: contact opening distance, contact edge chamfer radius, main shield radius, distance between the stationary main shield and the conductive rod, and distance between the stationary main shield and the end shield.

[0028] The distance between the stationary main shield and the conductive rod l 1 The distance between the main shield and the end shield at the static end. l 2 Incorporating it into the optimization system means more comprehensive control over the electric field distribution in the static end region. Optimization l1 It can improve the electric field between the main shield and the high-voltage conductor, and optimize l 2 It can regulate the electric field between the main shield and the end grounding shield, and the combination of the two can more precisely manage the electric field gradient of the entire static end insulation system.

[0029] Optionally, the optimization objective is to minimize the maximum electric field strength throughout the entire arc-extinguishing chamber under the condition of applying rated operating voltage to the stationary end and grounding the moving end. The maximum electric field strength must not exceed 80% of the allowable value of the material. Simultaneously, the optimization process must ensure that the uniformity of the electric field distribution meets engineering requirements. After optimization, the maximum electric field strength of key components such as the edge of the arc-extinguishing chamber shield and the outer shell must not exceed 80% of the allowable value of the material. Furthermore, to ensure the engineering practicality and safety of the optimized scheme, the following constraints are set: all design variables must be within a reasonable mechanical structure and manufacturing process range. Specifically, the constraints include: contact gap, the range of which is determined by the breaking current capacity, insulation recovery characteristics, and overall mechanical structure dimensions, and is between 20mm and 25mm. The chamfer radius of the contact edge is limited by the thickness of the contact plate itself and machining capabilities; to ensure its mechanical strength, the range is determined to be between 0.5mm and 3mm. The radius of the main shield is limited by the overall outer diameter of the arc-extinguishing chamber and its assembly relationship with other internal components. Considering the inner diameter of the arc-extinguishing chamber shell and the safe distance between it and the contacts and the arc-extinguishing chamber shell, its value range is determined to be 70mm to 75mm. The distance between the stationary end main shield and the conductive rod must ensure the insulation strength between the conductive rod and the main shield, and consider the thermal expansion margin, with a value range of 7mm-12mm. The distance between the stationary end main shield and the end shield must ensure the controllable electric field between the main shield and the end shield, and meet the overall axial dimension limit, with a value range of 33mm-53mm. Minimizing the maximum electric field strength Emax is the optimization objective, which is the direction the algorithm strives for, that is, searching for a set of parameters that makes the simulated Emax value as low as possible; while Emax ≤ 80% of the allowable value is an independent constraint, which is a safety upper limit that must be met. The relationship between the two is: the optimization algorithm must find the lowest possible Emax value under the premise of satisfying the constraint Emax ≤ 80% of the allowable value (and all other constraints). The final minimized result must have an Emax value that is less than or equal to the 80% threshold, but the specific value is determined by the whale optimization algorithm search in this embodiment of the invention.

[0030] This constraint stipulates that the maximum electric field strength must not exceed 80% of the material's allowable value. Specifically, in the model, this constraint applies to: After the finite element simulation is completed, the maximum value (Emax) is extracted from the global electric field distribution of the entire arc-extinguishing chamber model. Then, it is checked whether this maximum value is ≤ (80% of the material's allowable electric field strength). If a violation occurs, a corresponding violation value Ci = max(0, Emax - 0.8 * E_allow) is generated, multiplied by a penalty coefficient λ, and added to the fitness value F. This causes the fitness of individual whales in this scheme to decrease, resulting in their elimination by the algorithm.

[0031] The performance of the optimization algorithm largely depends on the proper construction of the fitness function. The fitness function is used to quantitatively evaluate the quality of each individual whale. In this embodiment, the fitness function is defined as a penalty function, and the fitness value... Determined by the following formula:

[0032] , in, This represents the maximum electric field strength value. For the first i The amount of violation of a constraint. For the first i The penalty coefficient for each constraint violation is set to 250. This is to effectively drive the search away from infeasible regions. It should be set to a positive number much larger than the typical value of the objective function (Emax). In this embodiment, it is determined as follows: First, based on empirical design, a typical Emax value range is estimated, approximately 20-25 kV / mm. Then, the penalty coefficient is... The value is uniformly set to 10 to 100 times the upper limit of this typical value. λ i =250. This setting ensures that any penalty for constraint violation ( Significantly alters fitness value This guides the algorithm to prioritize satisfying constraints.

[0033] Optional, C i The violation is determined based on the type of inequality in the constraint conditions, including: for design variable out-of-bounds constraints, the violation is measured as the absolute value of the portion exceeding the boundary; for allowable field strength constraints, the violation is measured as the portion of the actual field strength exceeding the allowable value.

[0034] for example: For contact opening distance d Must meet 20mm≤ d ≤25 mm, the violation consists of two parts: =max(0,d−25) and =max(0,20−d).

[0035] refer to Figure 2 Updating the whale's location involves the following steps: Calculate parameter a and system parameters , And the probability of judgment P.

[0036] In the formula, a As the number of iterations increases, the iterations linearly decrease from 2 to 0, thus controlling the balance between exploration and development. r A random number in the range [0, 1] For a random coefficient, Its main function is to introduce randomness to control the distance or influence weight between an individual whale and the target (the current optimal solution or a random individual) when updating its position. This is the system vector, controlling the direction and distance the whale moves.

[0037] Obtain the system parameter A in the whale optimization algorithm, and generate random numbers P∈[0,1]; When P < 0.5, if |A| < 1, then update the position according to the prey encirclement strategy: In the formula, To determine the whale's location next; This is the position of the current optimal solution; This represents the current distance between the whale and its prey. The location of the whale.

[0038] If |A|≥1, then update the position according to the random search strategy: , , In the formula, This represents the position of a random whale in the current population. This represents the distance between the current whale and the random solution.

[0039] When P ≥ 0.5, update the position according to the bubble web attack strategy: , , In the formula, This represents the distance between the current whale position and the current optimal whale position. This is the helical shape constant (usually set to 1); lA random number in [0, 1]; It is a spiral equation.

[0040] Perform boundary checks on the updated positions to ensure they are within the preset range of the design variables. After the position update is complete, calculate the fitness of each whale and compare it with the previously retained optimal whale position. If the new optimal position is better, replace the whale with the new one.

[0041] Specifically, triggering a finite element electrostatic field simulation includes the following steps: The whale's position vector, i.e., a set of [ d , r , R , l 1 , l 2 The parameters are written into the corresponding variables of the parametric geometric model through the script interface (using Python scripts to call ANSYS's MAPDL library) to achieve automatic updates of the model geometry; Automatically invoke and execute finite element simulation calculations of electrostatic fields; The post-processing program automatically extracts the global maximum electric field intensity value from the simulation results, specifically including the following steps: 1. The finite element solver (ANSYS's MAPDL library) is automatically started via batch commands in the operating system or control statements within a script, and the model file with updated parameters is loaded to perform electrostatic field calculations. This process requires no manual intervention and is driven cyclically by the optimization main program.

[0042] 2. Invocation method: Simulation platform: ANSYS MAPDL was used to establish a parametric two-dimensional axisymmetric electrostatic field model of the vacuum interrupter, and key geometric dimensions were defined as APDL variables.

[0043] Parameter passing: The optimized main program (Python script) combines the generated parameters and dynamically generates an executable model file by modifying the variable values ​​in the APDL script template.

[0044] Automatic solution: The main program calls the ANSYS solver in the background through system commands (Python's subprocess module), executes the updated APDL script, and completes the electrostatic field calculation.

[0045] Result Extraction: After the solution is completed, the main program automatically reads the result file output by ANSYS. By parsing the result file, the electric field intensity of all nodes in the global domain is extracted and its maximum value is calculated, thus obtaining Emax.

[0046] Constraint detection: At the same time, the field strength values ​​of preset monitoring points (such as the inner surface of the ceramic shell and the edge of the shield) are read from the result file, compared with the constraint threshold, and the constraint violation amount Ci is automatically calculated.

[0047] The program automatically detects whether the whale's position vector violates the constraints of the design variables.

[0048] The method for optimizing the insulation structure of a vacuum interrupter provided by this invention further includes step 4: outputting and verifying the optimal design scheme. After the algorithm converges, it outputs the combination of design parameters corresponding to the globally optimal individual whale, which is the optimal insulation structure design scheme. Detailed drawings to guide production can be generated based on this set of parameters. Independent finite element simulation verification and comparison were conducted: To objectively verify the optimization effect of this invention, independent finite element simulation comparison verification was performed, with the specific steps as follows:

[0049] 1. Determine the benchmark: Select a set of structural parameters based on experience design that are widely used in the current project as benchmark scheme 1. The specific parameters are as follows: d =22 mm, r =1.5 mm, R =72.5 mm, l 10 =9.5 mm, l 2 =43 mm.

[0050] 2. Establishing Verification Models: In the finite element software, two two-dimensional axisymmetric electrostatic field models of the vacuum interrupter were independently established, strictly following the parameters of the empirical scheme 1 and the optimized scheme output by this invention. Except for geometric dimensions, all other settings (material properties, rated voltage 31.5kV, grounding boundary, mesh generation strategy and accuracy) of the two models remained completely identical.

[0051] 3. Simulation and Data Extraction: Solve the two models separately, and then extract the following key data through post-processing: the maximum electric field intensity value over the entire domain. Emax Electric field intensity distribution on the edge of the contact and the end of the main shield.

[0052] Effect Analysis: If the optimized scheme reduces the maximum electric field strength by η = [(Emax_empirical - Emax_optimized) / Emax_empirical] × 100% ≥ 15%, then the method of this invention is considered to improve the electric field distribution and can systematically and quantitatively obtain a design scheme with better insulation performance. Compared to traditional empirical design schemes, the optimized scheme obtained using the method of this invention can effectively reduce the maximum electric field strength inside the arc-extinguishing chamber by more than 15% while meeting all engineering constraints, and significantly improve the uniformity of the electric field distribution. This provides a direct and quantitative design basis for improving the insulation performance and operational reliability of vacuum circuit breakers.

[0053] The second part of the embodiments of the present invention provides a vacuum interrupter insulation structure optimization system, the system comprising: The parametric modeling module is used to establish a two-dimensional axisymmetric electrostatic field parametric geometric model of a vacuum interrupter in finite element simulation software, and to define several key geometric parameters that affect the electric field distribution as design variables. The problem definition module, connected to the parametric modeling module, is used to set the optimization objective and constraints. The optimization objective is to minimize the maximum electric field intensity inside the arc extinguishing chamber. The whale optimization module is used to execute the whale optimization algorithm process. It includes: a population initialization unit, which randomly generates an initial whale population within the range of design variable values, where the position vector of each whale individual represents a set of design variable values; a fitness evaluation and simulation driving unit, which automatically assigns the position vectors of whale individuals to the parameterized model and triggers automated finite element simulation to calculate the fitness value; and a position update unit, which updates the position vectors of whale individuals in the population according to the strategy of the whale optimization algorithm. The convergence judgment unit is used to determine whether the optimization process meets the preset convergence conditions; The output module is used to output the combination of structural parameters corresponding to the globally optimal position vector after the algorithm converges, as the final insulation structure optimization design scheme.

[0054] The third embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter.

[0055] The fourth part of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter.

[0056] like Figure 2As shown, the implementation steps for insulation optimization design of the arc-extinguishing chamber of a 31.5kV vacuum circuit breaker in this embodiment include: 1) Determining the Optimization Design Object and Parametric Modeling: In this embodiment, the arc-extinguishing chamber of a 31.5kV vacuum circuit breaker is taken as the optimization object. A two-dimensional axisymmetric electrostatic field parametric model is established in the finite element simulation software, and the following key insulation structure dimensions are set as design variables: contact opening distance (…). d ), contact edge chamfer radius ( r ), Main shield radius ( R ), the distance between the stationary end main shield and the conductive rod ( l 1 ) and the distance between the stationary main shield and the end shield ( l 2 );

[0057] 2) Define the optimization objective and constraints: The optimization objective is set as: minimizing the maximum electric field strength inside the arc-extinguishing chamber under the rated operating voltage (31.5kV). The following engineering constraints are also set: contact distance... d Range: 20mm~25mm, contact edge chamfer radius r Range: 0.5mm~3mm, radius of main shield R Range: 70mm~75mm, spacing l 1 Range: 7mm~12mm, spacing l 2 Range: 33mm~53mm;

[0058] 3) Implement the whale optimization algorithm to perform automated optimization iterations and finally output the optimal insulation structure design scheme.

[0059] In this embodiment, the optimization design object and parametric modeling in step 1) mainly focus on structural optimization of the concentrated electric field region inside the vacuum interrupter. Specifically, the goal is to reduce the maximum electric field intensity and homogenize the electric field distribution, selecting the key geometric parameters that have the most significant impact on the electric field as design variables. In the finite element software, a model is built using parametric scripts to ensure that each design variable can be directly called and modified by the algorithm.

[0060] In this embodiment, step 2) defines the optimization objective and constraints based on the vacuum interrupter design specifications, material properties, and process feasibility, establishing a complete mathematical model for the optimization problem. The optimization objective is defined as minimizing the maximum electric field strength (Emax) occurring throughout the interrupter under rated operating voltage. Simultaneously, to ensure the engineering practicality of the design, strict constraints are set: all geometric parameters must be within feasible manufacturing and assembly ranges; the electric field strength at critical insulating components (such as the ceramic shell) must not exceed the allowable field strength of its material, and sufficient safety margin must be maintained; the optimized structure should not lead to the emergence of new or more severe electric field concentration points.

[0061] Through the automated optimization process described above, the whale optimization algorithm can efficiently search within a complex design space composed of five key structural parameters, effectively balancing global exploration and local exploitation capabilities, and avoiding getting trapped in local optima. Ultimately, the algorithm outputs the combination of structural parameters corresponding to the globally optimal whale individual.

[0062] The above inventions are merely a few specific embodiments of the present invention. However, the embodiments of the present invention are not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for optimizing the insulation structure of a vacuum interrupter, characterized in that, Includes the following steps: Taking the vacuum interrupter as the optimization object, a two-dimensional axisymmetric electrostatic field parameterized geometric model of it was established in the finite element simulation software, and several key geometric parameters affecting the electric field distribution were defined as design variables. The optimization objective is set to minimize the maximum electric field intensity inside the vacuum interrupter, while pre-setting constraints on the design variables. The whale optimization algorithm is adopted. The number of whales is set according to the dimension of the design variables. Within the preset range of design variable values, an initial population composed of multiple individual whales is randomly generated. The position vector of each whale represents a set of design variable values. For each individual whale, its position vector is automatically assigned to the parametric geometric model, triggering a finite element electrostatic field simulation to obtain the electric field distribution. The maximum electric field intensity in the global domain is extracted as the fitness value of the individual. The position vector with the smallest fitness value is taken as the optimal position vector. The position vectors of all whale individuals are updated until the preset convergence condition is met, and the parameter combination of the design variables corresponding to the globally optimal position vector is obtained as the final insulation structure optimization design scheme.

2. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 1, characterized in that, The key geometric design variables include the following parameters: contact opening distance, contact edge chamfer radius, main shield radius, distance between the stationary main shield and the conductive rod, and distance between the stationary main shield and the end shield.

3. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 2, characterized in that, The optimization objective is to minimize the maximum electric field strength throughout the arc-extinguishing chamber under the condition that the rated working voltage is applied to the stationary end and the moving end is grounded. The maximum electric field strength shall not exceed 80% of the allowable value of the material. The constraints include: the contact opening distance is in the range of 20mm to 25mm; the chamfer radius of the contact edge is in the range of 0.5mm to 3mm; the radius of the main shield is in the range of 70mm to 75mm; the distance between the stationary end main shield and the conductive rod is in the range of 7mm to 12mm; and the distance between the stationary end main shield and the end shield is in the range of 33mm to 53mm.

4. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 1, characterized in that, The fitness value Determined by the following formula: ， in, This represents the maximum electric field strength value. For the first i The amount of violation of a constraint. For the first i The penalty coefficient for each constraint violation is set to 250.

5. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 4, characterized in that, The C i Determined based on the type of inequality in the constraint conditions, including: For design variables exceeding the boundary constraints, the violation value is taken as the absolute value of the portion exceeding the boundary. For the allowable value constraint on electric field strength, the violation is the portion of the actual electric field strength that exceeds the allowable value.

6. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 1, characterized in that, The process of updating the whale's location includes the following steps: Obtain the system parameter A in the whale optimization algorithm, and generate random numbers P∈[0,1]; When P < 0.5, if |A| < 1, then update the position according to the prey encirclement strategy; if |A| ≥ 1, then update the position according to the random search strategy. When P≥0.5, update the position according to the bubble net attack strategy; Perform boundary checks on the updated position to ensure it is within the preset value range of the design variables.

7. The method for optimizing the insulation structure of a vacuum interrupter as described in claim 1, characterized in that, The process of triggering a finite element electrostatic field simulation includes the following steps: The whale's position vector is written into the corresponding variable of the parametric geometric model through a script interface, thereby enabling automatic updates of the model geometry. Automatically invoke and execute finite element simulation calculations of electrostatic fields; The post-processing program automatically extracts the global maximum electric field intensity value from the simulation results; The program automatically detects whether the whale's position vector violates the constraints of the design variables.

8. A vacuum interrupter insulation structure optimization system, characterized in that, The system includes: The parametric modeling module is used to establish a two-dimensional axisymmetric electrostatic field parametric geometric model of a vacuum interrupter in finite element simulation software, and to define several key geometric parameters that affect the electric field distribution as design variables. The problem definition module, connected to the parametric modeling module, is used to set the optimization objective and constraints, wherein the optimization objective is to minimize the maximum electric field intensity inside the arc extinguishing chamber. The whale optimization module is used to execute the whale optimization algorithm process. It includes: a population initialization unit, which randomly generates an initial whale population within the range of design variable values, where the position vector of each whale individual represents a set of design variable values; a fitness evaluation and simulation driving unit, which automatically assigns the position vectors of whale individuals to the parameterized model and triggers automated finite element simulation to calculate the fitness value; and a position update unit, which updates the position vectors of whale individuals in the population according to the strategy of the whale optimization algorithm. The convergence judgment unit is used to determine whether the optimization process meets the preset convergence conditions; The output module is used to output the combination of structural parameters corresponding to the globally optimal position vector after the algorithm converges, as the final insulation structure optimization design scheme.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the method, system, storage medium, and device for optimizing the insulation structure of a vacuum interrupter as described in any one of claims 1 to 7.

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