A method and device for optimizing the structure of a pot insulator, a terminal device and a storage medium

Abstract

The application discloses a kind of structure optimization method, device, terminal equipment and storage medium of basin type insulator, by selecting the same number of coordinate points as target coordinate points from the basin body concave surface and basin body convex surface of the parameterized finite element model of basin type insulator, then according to the overall maximum field intensity of basin type insulator, concave surface maximum field intensity, convex surface maximum field intensity, first difference and second difference, construct objective function, according to the ordinate of target coordinate point, iteratively update operation is carried out to initial celestial body according to objective function and initial celestial body using Kepler algorithm, when the iteration number of iteration update operation reaches the preset iteration number threshold, obtain target celestial body, finally according to target celestial body, generate the target structure parameter of basin type insulator. Therefore, the present application overcomes the defect that the current structure optimization method is easy to fall into local optimum, and ensures the practicability of the structure optimization scheme of basin type insulator.

Description

Technical Field

[0001] The present invention relates to the technical field of insulation structure design of power equipment, and in particular to a structure optimization method, device, terminal equipment and storage medium for a basin-type insulator. Background Art

[0002] Gas-insulated metal-enclosed switchgear (GIS) boasts advantages such as a small footprint, compact structure, strong environmental adaptability, and long maintenance cycles, making it widely used in extra-high-voltage and ultra-high-voltage substations. Currently, miniaturization of GIS equipment has become a major development trend, offering advantages such as reduced material consumption, reduced insulating gas usage, and lower manufacturing costs. However, miniaturization places higher demands on the design of the GIS's internal insulation structure. As a key component of the GIS's internal insulation structure, the basin insulator supports electrical components such as conductors, circuit breakers, and grounding electrodes. It also requires high-strength electrical insulation, effectively insulating the conductive parts from the equipment's casing and other electrical components to prevent current leakage or electrical breakdown. Therefore, the rationality of its structural design directly impacts the overall insulation performance of the GIS. Improper structural design can reduce insulation margins, increase sensitivity to electric field distortion, and increase the risk of insulation failure. Therefore, optimizing the structure of the basin insulator is essential for achieving GIS miniaturization.

[0003] In traditional pot-type insulator structure optimization, the optimization goal is to minimize the internal electric field intensity and the distribution of the electric field along the surface of the insulator, reduce the discharge risk by reducing the electric field intensity, and improve the insulation performance of the insulator. Genetic algorithms and particle swarm algorithms are mostly used in the field of pot-type insulator structure optimization. However, these two types of algorithms have certain limitations. When performing multi-parameter optimization, there are problems such as easy falling into local optimality and slow convergence speed. As a result, this method ignores the globality and uniformity of the entire electric field distribution when optimizing the insulator structure. Summary of the Invention

[0004] The embodiments of the present invention provide a structural optimization method, apparatus, terminal device, and storage medium for a pot-type insulator, which effectively overcome the defect that current structural optimization methods are prone to falling into local optimality and ensure the practicality of the pot-type insulator structural optimization solution.

[0005] An embodiment of the present invention provides a method for optimizing the structure of a pot-type insulator, comprising:

[0006] Obtaining a parameterized finite element model of the pot-type insulator to be optimized; wherein the parameterized finite element model is a finite element model for the concave structure and convex structure of the pot-type insulator;

[0007] Selecting a plurality of coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the basin of the parameterized finite element model as target coordinate points;

[0008] Constructing an objective function based on the overall maximum field strength of the basin insulator, the maximum field strength on the concave surface, the maximum field strength on the convex surface, the first difference between the maximum field strength on the concave surface and the minimum field strength on the concave surface, and the second difference between the maximum field strength on the convex surface and the minimum field strength on the convex surface;

[0009] Randomly constructing a number of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the target function and the initial celestial bodies, and generating a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold;

[0010] According to the target celestial body, the ordinate of the target coordinate point is updated, and then the parameterized finite element model is optimized using an interpolation function to generate target structural parameters of the pot insulator.

[0011] Furthermore, constructing an objective function based on the overall maximum field strength of the basin insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface includes:

[0012] Obtaining electrical performance parameters of the pot-type insulator;

[0013] Determining, according to the electrical performance parameters, an overall maximum electric field strength constraint value of the basin insulator, a concave surface maximum electric field strength constraint value, a convex surface maximum electric field strength constraint value, a first difference constraint value between the concave surface maximum electric field strength and the concave surface minimum electric field strength, and a second difference constraint value between the convex surface maximum electric field strength and the convex surface minimum electric field strength;

[0014] Determining, according to the overall maximum field strength constraint value, the concave surface maximum field strength constraint value, the convex surface maximum field strength constraint value, the first difference constraint value, and the second difference constraint value, a first weight of the overall maximum field strength, a second weight of the concave surface maximum field strength, a third weight of the convex surface maximum field strength, a fourth weight of the first difference, and a fifth weight of the second difference;

[0015] The objective function is constructed according to the overall maximum field strength, the concave maximum field strength, the convex maximum field strength, the first difference, the second difference, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight.

[0016] Furthermore, the objective function is:

[0017] F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x);

[0018] Among them, F(x) is the objective function, ω1 is the first weight, E1(x) is the overall maximum field strength, ω2 is the first weight, E2(x) is the maximum field strength of the concave surface, ω3 is the third weight, E3(x) is the maximum field strength of the convex surface, ω4 is the fourth weight, E4(x) is the first difference, ω5 is the fifth weight, and E5(x) is the second difference.

[0019] Furthermore, the step of randomly constructing a plurality of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the target function and the initial celestial bodies, and generating a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold, includes:

[0020] Randomly initializing the initial position of the initial celestial body; wherein the position is the vertical coordinate of a number of the target coordinate points;

[0021] Calculating an initial fitness value of each of the initial celestial bodies according to the objective function and the initial position, and determining an initial central celestial body according to the initial fitness value;

[0022] According to the initial fitness value and the initial central celestial body, the Kepler algorithm is used to repeatedly perform an iterative update operation on the initial celestial body until the number of iterations is not less than the iteration number threshold, and then the target celestial body is output;

[0023] The iterative update operation includes:

[0024] Obtaining a central celestial body, several current celestial bodies to be optimized, a first fitness value of each celestial body to be optimized, and a position of each celestial body to be optimized; initially, the central celestial body is the initial central celestial body, the celestial body to be optimized is the initial celestial body, the position is the initial position, and the first fitness value is the initial fitness value;

[0025] Calculating the gravitational force between each celestial body to be optimized and the central celestial body according to the law of universal gravitation and a preset gravitational coefficient, and determining the velocity of each celestial body to be optimized according to the gravitational force;

[0026] Performing orbital perturbations on each celestial body to be optimized based on its gravity, velocity, and a preset orbital perturbation mechanism, so as to allow for global exploration of the celestial body to be optimized, and then determining the position to be evaluated of each celestial body to be optimized after the orbital perturbation;

[0027] Calculating a second fitness value of each of the celestial bodies to be optimized at the position to be evaluated according to the objective function;

[0028] According to the first fitness value and the second fitness value of each of the to-be-optimized celestial bodies, an optimized position of each of the to-be-optimized celestial bodies is determined, and a target fitness value of each of the to-be-optimized celestial bodies at the optimized position is determined;

[0029] The to-be-optimized celestial body with the maximum target fitness value is taken as a target celestial body;

[0030] It is judged whether the current iteration number is not less than the iteration number threshold value;

[0031] If yes, the target celestial body is output;

[0032] If no, the target celestial body is taken as a central celestial body required for a next round of iteration updating operation, the optimized position of the target celestial body is taken as a position required for the next round of iteration updating operation, and the target fitness value of each of the to-be-optimized celestial bodies at the optimized position is taken as a first fitness value required for the next round of iteration updating operation.

[0033] Further, the random initialization of the initial position of the initial celestial body comprises:

[0034] The structure parameters of the basin-type insulator are acquired;

[0035] According to the structure parameters, a longitudinal coordinate value range of each target coordinate point is determined;

[0036] A random value is taken in the longitudinal coordinate value range, and the initial position of the initial celestial body is initialized according to the random value.

[0037] Another embodiment of the application provides a structure optimization device of a basin-type insulator, comprising:

[0038] A model acquisition module is configured to acquire a parameterized finite element model of a to-be-optimized basin-type insulator; wherein the parameterized finite element model is a finite element model of a basin body concave surface structure and a basin body convex surface structure of the basin-type insulator;

[0039] A coordinate point determination module is configured to select a plurality of coordinate points with the same horizontal coordinate from the basin body concave surface and the basin body convex surface of the parameterized finite element model as target coordinate points;

[0040] A target function construction module is configured to construct a target function according to the overall maximum field strength of the basin-type insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, a first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and a second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface;

[0041] a structure optimization module, configured to randomly construct a number of initial celestial bodies according to the ordinate of the target coordinate point, and perform an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the objective function and the initial celestial bodies, and generate a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold;

[0042] The structure generation module is used to update the ordinate of the target coordinate point according to the target celestial body, and then optimize the parameterized finite element model using an interpolation function to generate the target structural parameters of the pot insulator.

[0043] Furthermore, constructing an objective function based on the overall maximum field strength of the basin insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface includes:

[0044] Obtaining electrical performance parameters of the pot-type insulator;

[0045] Determining, according to the electrical performance parameters, an overall maximum electric field strength constraint value of the basin insulator, a concave surface maximum electric field strength constraint value, a convex surface maximum electric field strength constraint value, a first difference constraint value between the concave surface maximum electric field strength and the concave surface minimum electric field strength, and a second difference constraint value between the convex surface maximum electric field strength and the convex surface minimum electric field strength;

[0046] Determining, according to the overall maximum field strength constraint value, the concave surface maximum field strength constraint value, the convex surface maximum field strength constraint value, the first difference constraint value, and the second difference constraint value, a first weight of the overall maximum field strength, a second weight of the concave surface maximum field strength, a third weight of the convex surface maximum field strength, a fourth weight of the first difference, and a fifth weight of the second difference;

[0047] The objective function is constructed according to the overall maximum field strength, the concave maximum field strength, the convex maximum field strength, the first difference, the second difference, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight.

[0048] Furthermore, the objective function is:

[0049] F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x);

[0050] Among them, F(x) is the objective function, ω1 is the first weight, E1(x) is the overall maximum field strength, ω2 is the first weight, E2(x) is the maximum field strength of the concave surface, ω3 is the third weight, E3(x) is the maximum field strength of the convex surface, ω4 is the fourth weight, E4(x) is the first difference, ω5 is the fifth weight, and E5(x) is the second difference.

[0051] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a structural optimization method for a pot-type insulator as described in any one of the embodiments is implemented.

[0052] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute a structural optimization method for a pot insulator as described in any one of the above embodiments.

[0053] The following beneficial effects are achieved by implementing the present invention:

[0054] The present invention discloses a structural optimization method, device, terminal equipment and storage medium for a basin insulator. The method selects several coordinate points with the same horizontal coordinates from the concave surface and the convex surface of a parameterized finite element model of the basin insulator as target coordinate points, and then constructs a target function according to the overall maximum field strength of the basin insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface. According to the vertical coordinate of the target coordinate point, several initial celestial bodies are randomly constructed, and the Kepler algorithm is used to iteratively update the initial celestial bodies according to the target function and the initial celestial bodies. When the number of iterations of the iterative update operation reaches a preset iteration number threshold, the target celestial body is obtained. Finally, the vertical coordinate of the target coordinate point is updated according to the target celestial body, and the interpolation function is then used to optimize the parameterized finite element model to generate the target structural parameters of the basin insulator. Therefore, the present invention utilizes the advantage of global optimization of the Kepler algorithm to overcome the defect that the current structural optimization method is prone to falling into local optimality. Secondly, while performing structural optimization, the present invention pays attention to the distribution of the electric field after the optimization of the basin insulator based on the electric field distribution on the concave surface and the convex surface of the basin body of the basin insulator, so as to avoid the situation where the insulation performance fails due to excessive concentration or excessive strength of the local field, so as to ensure the practicality of the structural optimization scheme of the basin insulator. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The present invention is a flowchart of a method for optimizing the structure of a pot-type insulator provided in one embodiment of the present invention.

[0056] Figure 2 The figure is a schematic structural diagram of a structure optimization device for a pot-type insulator provided by one embodiment of the present invention.

[0057] Figure 3 This is a schematic diagram of the target coordinate points of a pot-type insulator provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0060] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0061] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0062] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0063] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0064] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0065] See also Figure 1 , is a flow chart of a method for optimizing the structure of a pot-type insulator provided by one embodiment of the present invention, comprising:

[0066] S1. Obtaining a parameterized finite element model of a pot-type insulator to be optimized; wherein the parameterized finite element model is a finite element model of a concave structure and a convex structure of a pot-type insulator;

[0067] In a preferred embodiment of the present invention, a pre-built parametric finite element model of a pot insulator is obtained. It is understood that the finite element model (FEM) is a numerical analysis method used to solve practical engineering problems. It divides a continuum into a finite number of discrete units. By mathematically describing and solving these units, the behavior of the entire continuum is derived. Parameterization, on the other hand, involves introducing some important parameters in the model as variables, allowing the model's geometry to be flexibly adjusted and optimized by changing the values ​​of these parameters.

[0068] S2, selecting a number of coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the basin of the parameterized finite element model as target coordinate points;

[0069] In a preferred embodiment of the present invention, Figure 3 As shown in the figure, 5 coordinates are selected from each concave and convex surface of the basin insulator for optimization to determine the optimization range of its size. Specifically, 5 key points are selected from the concave and convex surface curves of the basin body and their horizontal coordinates are determined. The coordinates of the 10 key points are (91, a), (118, b), (145, c), (171, d), (198, e), (91, f), (118, g), (145, h1), (171, i1), and (198, j1).

[0070] Further, the ordinate value range is:

[0071]

[0072] S3, according to the overall maximum field strength of the basin type insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference value of the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference value of the maximum field strength of the convex surface and the minimum field strength of the convex surface, the target function is constructed;

[0073] Preferably, the target function is constructed according to the overall maximum field strength of the basin type insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference value of the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference value of the maximum field strength of the convex surface and the minimum field strength of the convex surface, including:

[0074] S31, the overall maximum field strength constraint value, the maximum field strength constraint value of the concave surface, the maximum field strength constraint value of the convex surface, the first difference value constraint value of the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference value constraint value of the maximum field strength of the convex surface and the minimum field strength of the convex surface of the basin type insulator are obtained;

[0075] S32, according to the overall maximum field strength constraint value, the maximum field strength constraint value of the concave surface, the maximum field strength constraint value of the convex surface, the first difference value constraint value, and the second difference value constraint value, respectively determine the first weight of the overall maximum field strength, the second weight of the maximum field strength of the concave surface, the third weight of the maximum field strength of the convex surface, the fourth weight of the first difference value, and the fifth weight of the second difference value;

[0076] S33, according to the overall maximum field strength, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference value, the second difference value, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight, the target function is constructed.

[0077] Preferably, the target function is:

[0078] F(x) = ω1E1(x) 2 + ω2E2(x) 3 / 2 + ω3E3(x) 3 / 2 + ω4E4(x) + ω5E5(x);

[0079] Wherein, F(x) is the target function, ω1 is the first weight, E1(x) is the overall maximum field strength, ω2 is the first weight, E2(x) is the maximum field strength of the concave surface, ω3 is the third weight, E3(x) is the maximum field strength of the convex surface, ω4 is the fourth weight, E4(x) is the first difference value, ω5 is the fifth weight, E5(x) is the second difference value.

[0080] In a preferred embodiment of the present invention, the constraints on the electrical performance of the pot insulator are selected from the maximum electric field strength E1(x), the maximum electric field strength along the concave surface E2(x), the maximum electric field strength along the convex surface E3(x), the difference between the maximum and minimum electric field strength along the concave surface E4(x), and the difference between the maximum and minimum electric field strength along the convex surface E5(x);

[0081] Among them, E1(x)≤E1(x)max, E2(x)≤E2(x)max, E3(x)≤E3(x)max, E4(x)≤E4(x)max, E5(x)≤E5(x)max.

[0082] In summary, the objective function of the pot insulator is:

[0083] F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x);

[0084] ω1=1 / E1(x) max ;ω2=1 / E2(x) max ;ω3=1 / E3(x) max ;ω4=1 / E4(x) max ;ω5=1 / E5(x) max ;

[0085] S4. Randomly constructing a number of initial celestial bodies based on the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm based on the target function and the initial celestial bodies. When the number of iterations of the iterative update operation reaches a preset iteration threshold, generating a target celestial body;

[0086] Preferably, the step of randomly constructing a plurality of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the target function and the initial celestial bodies, and generating a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold, comprises:

[0087] S41. Randomly initialize the initial position of the initial celestial body; wherein the position is the vertical coordinate of a number of the target coordinate points;

[0088] Preferably, the randomly initializing the initial position of the initial celestial body includes:

[0089] S411. Obtaining structural parameters of the pot-type insulator;

[0090] S412, determining the range of the vertical coordinate value of each target coordinate point according to the structural parameters;

[0091] S413: Take a random value within the range of the vertical coordinate, and initialize the initial position of the initial celestial body according to the random value.

[0092] S42: Based on the initial fitness value and the initial central celestial body, using the Kepler algorithm, repeatedly perform an iterative update operation on the initial celestial body until the number of iterations is not less than the iteration number threshold, and output a target celestial body;

[0093] S43, using the Kepler algorithm according to the objective function value and the initial central celestial body, repeatedly performing an iterative update operation on the celestial body until the number of iterations is not less than the iteration number threshold, and outputting the target celestial body;

[0094] The iterative update operation includes:

[0095] S431, obtaining a central celestial body, a number of current celestial bodies to be optimized, a first fitness value of each celestial body to be optimized, and a position of each celestial body to be optimized; initially, the central celestial body is the initial central celestial body, the celestial body to be optimized is the initial celestial body, the position is the initial position, and the first fitness value is the initial fitness value;

[0096] S432. Calculate the gravitational force between each celestial body to be optimized and the central celestial body according to the law of universal gravitation and a preset gravitational coefficient, and determine the velocity of each celestial body to be optimized according to the gravitational force;

[0097] S433: performing orbital perturbations on each celestial body to be optimized based on its gravity, velocity, and a preset orbital perturbation mechanism, so as to globally explore the celestial body to be optimized, and then determining a position to be evaluated for each celestial body to be optimized after the orbital perturbations;

[0098] S434. Calculating a second fitness value of each of the celestial bodies to be optimized at the position to be evaluated according to the objective function;

[0099] S435, determining an optimized position of each celestial body to be optimized according to the first fitness value and the second fitness value of each celestial body to be optimized, and determining a target fitness value of each celestial body to be optimized at the optimized position;

[0100] S436. The celestial body to be optimized with the largest target fitness value is selected as the target celestial body;

[0101] S437: Determine whether the current number of iterations is not less than the iteration number threshold;

[0102] S438: If yes, output the target celestial body;

[0103] S439. If not, the target celestial body is used as the central celestial body required for the next round of iterative update operation, the optimized position of each celestial body to be optimized is used as the position in the next round of iterative update operation, and the target fitness value of each celestial body to be optimized at the optimized position is used as the first fitness value in the next round of iterative update operation.

[0104] In a preferred embodiment of the present invention, the number of celestial bodies is set to 50, the maximum number of iterations is set to 100, the celestial body velocity, gravitational constant, celestial body mass, and celestial body position are initialized, and a random value is selected within the range of vertical coordinate values ​​in step S2, and the initial position of the initial celestial body is initialized based on the random value. It can be understood that the initialization of the Kepler algorithm is similar to that of other algorithms, and each initial celestial body is placed at a random position on the orbit.

[0105] Secondly, we first calculate the effect of Kepler's gravity. Based on the law of universal gravitation, we can derive the gravitational force and velocity of each celestial body. It's understandable that the velocity of a celestial body is affected by the gravity of the central celestial body. When an object approaches the central celestial body, its velocity increases, and when it moves further away, its velocity decreases. If a celestial body is close to the central celestial body, the central celestial body's gravity is quite strong, and the celestial body will try to increase its velocity to avoid being pulled towards the central celestial body. However, if an object moves away from the central celestial body, its velocity will slow down because the central celestial body's gravity is weak.

[0106] The orbital perturbation is then calculated, and the position of the celestial body is updated based on the orbital perturbation. It is understandable that in the solar system, most celestial bodies orbit the sun counterclockwise, rotating around their own axes. However, some celestial bodies orbit the sun clockwise. The Kepler algorithm exploits this behavior to escape local optima by using a flag, F, to change the search direction, enabling it to accurately scan the search space. A global exploration is then performed, introducing a selection mechanism to update the positions of celestial bodies at different stages, as shown in the following formula:

[0107]

[0108] Among them, ξ represents the adjustment parameter; X i (t) represents the position of the celestial body to be optimized; V i(t) represents the celestial body velocity; p, U, r represent parameters; according to the optimal solution, the velocity, gravity and position of the celestial body and the mass are updated, and the global optimal position is retained. It can be understood that the celestial bodies rotate around the central celestial body on respective elliptical orbits. In the process of rotation, the celestial bodies approach the central celestial body at a certain time, and then move away from the central celestial body. Kepler algorithm simulates this behavior through two main stages: exploration and development stages. The celestial bodies far away from the central celestial body are explored to find new solutions, while the solutions close to the central celestial body are used more accurately because it finds new places near the best solution. When the celestial bodies are far away from the central celestial body, the velocity of the celestial bodies will represent the exploration operator. However, this velocity is affected by the gravity of the central celestial body, which helps the current celestial body slightly exploit the area near the best solution. At the same time, when the celestial bodies approach the central celestial body, their velocity increases sharply, enabling them to escape the gravity of the central celestial body. In this case, if the best solution so far (called the central celestial body) is a local minimum, the velocity is used to avoid local optimality, and the gravity of the central celestial body is used to help the operator attack the best solution so far to find a better solution.

[0109] Further, with the progress of iteration, the gravity gradually decays, making the velocity and position of the celestial bodies update smaller, simulating that the celestial bodies gradually tend to be stable, and finally reach the convergence condition, that is, reach the maximum number of iterations, the iteration ends, and the optimal solution (target celestial body) is output.

[0110] S5, according to the target celestial body, updating the longitudinal coordinate of the target coordinate point, and then using an interpolation function to optimize the parameterized finite element model to generate the target structure parameter of the basin type insulator.

[0111] In a preferred embodiment of the present application, according to the target celestial body, the longitudinal coordinate of the target coordinate point in the parameterized finite element model is updated, and the concave-convex surface shape structure of the basin body is obtained by using an interpolation function, so as to realize the optimization of the basin type insulator structure, and further achieve the globality and uniformity of the electric field distribution.

[0112] This embodiment provides a structural optimization method for a pot-type insulator, which selects several coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the pot body of a parameterized finite element model of the pot-type insulator as target coordinate points, and then constructs a target function based on the overall maximum field strength of the pot-type insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface. According to the vertical coordinates of the target coordinate points, several initial celestial bodies are randomly constructed, and the Kepler algorithm is used to iteratively update the initial celestial bodies based on the target function and the initial celestial bodies. When the number of iterations of the iterative update operation reaches a preset iteration number threshold, the target celestial body is obtained. Finally, the vertical coordinate of the target coordinate point is updated based on the target celestial body, and then the interpolation function is used to optimize the parameterized finite element model to generate the target structural parameters of the pot-type insulator. Therefore, the present invention utilizes the advantage of global optimization of the Kepler algorithm to overcome the defect that the current structural optimization method is prone to falling into local optimality. Secondly, while performing structural optimization, the present invention pays attention to the distribution of the electric field after the optimization of the basin insulator based on the electric field distribution on the concave surface and the convex surface of the basin body of the basin insulator, so as to avoid the situation where the insulation performance fails due to excessive concentration or excessive strength of the local field, so as to ensure the practicality of the structural optimization scheme of the basin insulator.

[0113] See also Figure 2 , is a schematic structural diagram of a structure optimization device for a pot-type insulator provided by one embodiment of the present invention, comprising:

[0114] A model acquisition module is used to obtain a parameterized finite element model of the pot-type insulator to be optimized; wherein the parameterized finite element model is a finite element model of the concave structure and the convex structure of the pot body of the pot-type insulator;

[0115] A coordinate point determination module is used to select a number of coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the basin body of the parameterized finite element model as target coordinate points;

[0116] An objective function construction module is used to construct an objective function based on the overall maximum field strength of the basin insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface;

[0117] a structure optimization module, configured to randomly construct a number of initial celestial bodies according to the ordinate of the target coordinate point, and perform an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the objective function and the initial celestial bodies, and generate a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold;

[0118] The structure generation module is used to update the ordinate of the target coordinate point according to the target celestial body, and then optimize the parameterized finite element model using an interpolation function to generate the target structural parameters of the pot insulator.

[0119] Preferably, constructing the objective function according to the overall maximum field strength of the basin insulator, the maximum field strength of the concave surface, the maximum field strength of the convex surface, the first difference between the maximum field strength of the concave surface and the minimum field strength of the concave surface, and the second difference between the maximum field strength of the convex surface and the minimum field strength of the convex surface includes:

[0120] Obtaining electrical performance parameters of the pot-type insulator;

[0121] Determining, according to the electrical performance parameters, an overall maximum electric field strength constraint value of the basin insulator, a concave surface maximum electric field strength constraint value, a convex surface maximum electric field strength constraint value, a first difference constraint value between the concave surface maximum electric field strength and the concave surface minimum electric field strength, and a second difference constraint value between the convex surface maximum electric field strength and the convex surface minimum electric field strength;

[0122] Determining, according to the overall maximum field strength constraint value, the concave surface maximum field strength constraint value, the convex surface maximum field strength constraint value, the first difference constraint value, and the second difference constraint value, a first weight of the overall maximum field strength, a second weight of the concave surface maximum field strength, a third weight of the convex surface maximum field strength, a fourth weight of the first difference, and a fifth weight of the second difference;

[0123] The objective function is constructed according to the overall maximum field strength, the concave maximum field strength, the convex maximum field strength, the first difference, the second difference, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight.

[0124] Preferably, the objective function is:

[0125] F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x);

[0126] Among them, F(x) is the objective function, ω1 is the first weight, E1(x) is the overall maximum field strength, ω2 is the first weight, E2(x) is the maximum field strength of the concave surface, ω3 is the third weight, E3(x) is the maximum field strength of the convex surface, ω4 is the fourth weight, E4(x) is the first difference, ω5 is the fifth weight, and E5(x) is the second difference.

[0127] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0128] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0129] Another preferred embodiment of the present invention provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a structural optimization method for a pot-type insulator as described in any one of the above embodiments is implemented.

[0130] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0131] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0132] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created based on the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0133] Another preferred embodiment of the present invention provides a storage medium, which is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. The computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium.

[0134] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimizing the structure of a pot-type insulator, characterized in that: include: Obtaining a parameterized finite element model of the pot-type insulator to be optimized; wherein the parameterized finite element model is a finite element model for the concave structure and convex structure of the pot-type insulator; Selecting a plurality of coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the basin of the parameterized finite element model as target coordinate points; Obtaining a preset overall maximum field strength constraint value of the basin insulator, a concave maximum field strength constraint value, a convex maximum field strength constraint value, a first difference constraint value between the concave maximum field strength and the concave minimum field strength, and a second difference constraint value between the convex maximum field strength and the convex minimum field strength; determining a first weight of the overall maximum field strength, a second weight of the concave maximum field strength, a third weight of the convex maximum field strength, a fourth weight of the first difference, and a fifth weight of the second difference based on the overall maximum field strength constraint value, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value, and the second difference constraint value; constructing an objective function based on the overall maximum field strength, the concave maximum field strength, the convex maximum field strength, the first difference, the second difference, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight; Randomly constructing a number of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the target function and the initial celestial bodies, and generating a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold; According to the target celestial body, the ordinate of the target coordinate point is updated, and then the parameterized finite element model is optimized using an interpolation function to generate target structural parameters of the pot insulator.

2. The method for optimizing the structure of a pot-type insulator according to claim 1, wherein: The objective function is: ； in, is the objective function, is the first weight, is the overall maximum field strength, is the second weight, is the maximum field strength on the concave surface, is the third weight, is the maximum field strength on the convex surface, is the fourth weight, is the first difference, is the fifth weight, is the second difference.

3. The method for optimizing the structure of a pot-type insulator according to claim 2, wherein: The method comprises the following steps: randomly constructing a plurality of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the target function and the initial celestial bodies, and generating a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold. Randomly initializing the initial position of the initial celestial body; wherein the position is the vertical coordinate of a number of the target coordinate points; Calculating an initial fitness value of each of the initial celestial bodies according to the objective function and the initial position, and determining an initial central celestial body according to the initial fitness value; According to the initial fitness value and the initial central celestial body, the Kepler algorithm is used to repeatedly perform an iterative update operation on the initial celestial body until the number of iterations is not less than the iteration number threshold, and then the target celestial body is output; The iterative update operation includes: Obtaining a central celestial body, several current celestial bodies to be optimized, a first fitness value of each celestial body to be optimized, and a position of each celestial body to be optimized; initially, the central celestial body is the initial central celestial body, the celestial body to be optimized is the initial celestial body, the position is the initial position, and the first fitness value is the initial fitness value; Calculating the gravitational force between each celestial body to be optimized and the central celestial body according to the law of universal gravitation and a preset gravitational coefficient, and determining the velocity of each celestial body to be optimized according to the gravitational force; Performing orbital perturbations on each celestial body to be optimized based on its gravity, velocity, and a preset orbital perturbation mechanism, so as to allow for global exploration of the celestial body to be optimized, and then determining the position to be evaluated of each celestial body to be optimized after the orbital perturbation; Calculating a second fitness value of each of the celestial bodies to be optimized at the position to be evaluated according to the objective function; Determining the optimized position of each celestial body to be optimized according to the first fitness value and the second fitness value of each celestial body to be optimized, and determining the target fitness value of each celestial body to be optimized at the optimized position; The celestial body to be optimized with the largest target fitness value is taken as the target celestial body; Determine whether the current number of iterations is not less than the iteration number threshold; If yes, output the target celestial body; If not, the target celestial body is used as the central celestial body required for the next round of iterative update operation, the optimized position of each celestial body to be optimized is used as the position in the next round of iterative update operation, and the target fitness value of each celestial body to be optimized at the optimized position is used as the first fitness value in the next round of iterative update operation.

4. The method for optimizing the structure of a pot-type insulator according to claim 3, wherein: The randomly initializing the initial position of the initial celestial body comprises: Obtaining structural parameters of the pot-type insulator; Determine the range of ordinate values ​​of each target coordinate point according to the structural parameters; A random value is taken within the range of the vertical coordinate value, and the initial position of the initial celestial body is initialized according to the random value.

5. A structural optimization device for a pot-type insulator, characterized in that: include: A model acquisition module is used to obtain a parameterized finite element model of the pot-type insulator to be optimized; wherein the parameterized finite element model is a finite element model of the concave structure and the convex structure of the pot body of the pot-type insulator; A coordinate point determination module is used to select a number of coordinate points with the same horizontal coordinates from the concave surface and the convex surface of the basin body of the parameterized finite element model as target coordinate points; an objective function construction module, configured to obtain a preset overall maximum field strength constraint value of the basin insulator, a concave maximum field strength constraint value, a convex maximum field strength constraint value, a first difference constraint value between the concave maximum field strength and the concave minimum field strength, and a second difference constraint value between the convex maximum field strength and the convex minimum field strength; determine a first weight of the overall maximum field strength, a second weight of the concave maximum field strength, a third weight of the convex maximum field strength, a fourth weight of the first difference, and a fifth weight of the second difference based on the overall maximum field strength constraint value, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value, and the second difference constraint value; and construct an objective function based on the overall maximum field strength, the concave maximum field strength, the convex maximum field strength, the first difference, the second difference, the first weight, the second weight, the third weight, the fourth weight, and the fifth weight; a structure optimization module, configured to randomly construct a number of initial celestial bodies according to the ordinate of the target coordinate point, and perform an iterative update operation on the initial celestial bodies using the Kepler algorithm according to the objective function and the initial celestial bodies, and generate a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold; The structure generation module is used to update the ordinate of the target coordinate point according to the target celestial body, and then optimize the parameterized finite element model using an interpolation function to generate the target structural parameters of the pot insulator.

6. The structure optimization device for a pot-type insulator according to claim 5, characterized in that: The objective function is: ； in, is the objective function, is the first weight, is the overall maximum field strength, is the second weight, is the maximum field strength on the concave surface, is the third weight, is the maximum field strength on the convex surface, is the fourth weight, is the first difference, is the fifth weight, is the second difference.

7. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for optimizing the structure of a pot-type insulator according to any one of claims 1 to 4 is implemented.

8. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is run, the device where the storage medium is located is controlled to execute the method for optimizing the structure of a pot-type insulator according to any one of claims 1 to 4.

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