Structure optimization method and device of basin-type insulator, terminal equipment and storage medium

Abstract

The invention discloses a structure optimization method and device for a basin-type insulator, terminal equipment and a storage medium. A plurality of coordinate points with the same abscissa are selected from a basin body concave surface and a basin body convex surface of a parameterized finite element model of the basin-type insulator as target coordinate points; then, according to the overall maximum field intensity, the concave surface maximum field intensity, the convex surface maximum field intensity, the first difference value and the second difference value of the basin-type insulator, an objective function is constructed, according to the ordinate of the target coordinate point, a plurality of initial celestial bodies are randomly constructed, and according to the objective function and the initial celestial bodies, a Kepler algorithm is adopted to carry out iterative updating operation on the initial celestial bodies, and the initial celestial bodies are obtained. And when the number of iterations of the iteration updating operation reaches a preset iteration number threshold value, obtaining a target celestial body, and finally generating a target structure parameter of the basin-type insulator according to the target celestial body. Therefore, the defect that a current structure optimization method is prone to falling into local optimum is overcome, and the practicability of a basin-type insulator structure optimization scheme is guaranteed.

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 of a pot-type insulator. Background Art

[0002] Gas-insulated metal-enclosed switchgear (GIS) has the advantages of small footprint, compact structure, strong environmental adaptability, and long maintenance cycle, and is widely used in EHV and UHV substations. At present, miniaturized GIS equipment has the advantages of reducing material consumption, insulating gas usage, and manufacturing costs, and has become the main development direction. Miniaturization development has higher requirements for the design of the internal insulation structure of GIS. Among them, the basin insulator, as one of the important components of the internal insulation structure of GIS, supports electrical components such as conductors, circuit breakers, and grounding electrodes. It is also necessary to provide high-strength electrical insulation and provide effective insulation between the conductive part and the housing or other electrical components of the equipment to prevent current leakage or electrical breakdown. Therefore, the rationality of its structural design will directly affect the overall insulation performance of GIS. If the structural design is unreasonable, its insulation margin will be reduced, it will be more sensitive to electric field distortion, and the risk of insulation failure will increase. Therefore, optimizing the structure of the basin insulator is a must to achieve GIS miniaturization.

[0003] In the traditional optimization of basin insulator structure, the optimization goal is to minimize the internal electric field strength and the distribution of the electric field along the surface of the insulator, reduce the discharge risk by reducing the electric field strength, and improve the insulation performance of the insulator. Genetic algorithms and particle swarm algorithms are mostly used in the field of basin insulator structure optimization, but these two types of algorithms have certain limitations. When performing multi-parameter optimization, there are problems such as easy to fall into local optimality and slow convergence speed, which causes this method to ignore 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, device, terminal equipment and storage medium for a pot-type insulator, which effectively overcome the defect that the current structural optimization method is prone to fall into local optimum and ensure the practicality of the structural optimization scheme for the pot-type insulator.

[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 a pot body concave structure and a pot body convex structure of the pot-type insulator;

[0007] Selecting 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;

[0008] Constructing an objective function according to the overall maximum field strength of the pot 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;

[0009] According to the ordinate of the target coordinate point, a number of initial celestial bodies are randomly constructed, and according to the target function and the initial celestial body, the Kepler algorithm is used to perform an iterative update operation on the initial celestial body, and when the number of iterations of the iterative update operation reaches a preset iteration number threshold, a target celestial body is generated;

[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 by using an interpolation function to generate the target structural parameters of the pot-type insulator.

[0011] Furthermore, constructing an objective function according to the overall maximum field strength of the pot 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] Determine, according to the electrical performance parameters, the overall maximum field strength constraint value of the pot insulator, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value between the concave maximum field strength and the concave minimum field strength, and the second difference constraint value between the convex maximum field strength and the convex minimum field strength;

[0014] Determine, according to 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, 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;

[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 number of initial celestial bodies according to the ordinate of the target coordinate point, and performing an iterative update operation on the initial celestial body using the Kepler algorithm according to the target function and the initial celestial body, 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 initialize the initial position of the initial celestial body; wherein the position is the ordinate of a number of the target coordinate points;

[0021] Calculating the 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 the target celestial body is output;

[0023] The iterative update operation includes:

[0024] Acquire 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] According to the law of universal gravitation and a preset gravitational coefficient, the gravitational force between each celestial body to be optimized and the central celestial body is calculated, and the speed of each celestial body to be optimized is determined according to the gravitational force;

[0026] According to the gravity, speed, and preset orbital perturbation mechanism of each celestial body to be optimized, the orbit of each celestial body to be optimized is perturbed to allow the celestial body to be optimized to be globally explored, and then the position to be evaluated of each celestial body to be optimized after the orbital perturbation is determined;

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

[0028] Determine the optimization 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 determine the target fitness value of each celestial body to be optimized at the optimization position;

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

[0030] Determine whether the current number of iterations is not less than the iteration number threshold;

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

[0032] 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 the target celestial body is used as the position required for 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 required for the next round of iterative update operation.

[0033] Furthermore, the randomly initializing the initial position of the initial celestial body includes:

[0034] Obtaining structural parameters of the pot-type insulator;

[0035] According to the structural parameters, determining the range of ordinate values ​​of each target coordinate point;

[0036] 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.

[0037] Another embodiment of the present invention provides a structure optimization device for a pot-type insulator, comprising:

[0038] A model acquisition module, used to acquire 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 a pot body concave structure and a pot body convex structure of the pot-type insulator;

[0039] A coordinate point determination module, 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;

[0040] An objective function construction module is used to construct an objective function according to the overall maximum field strength of the pot 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;

[0041] A structure optimization module, used for 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 body using the Kepler algorithm according to the target function and the initial celestial body, and generating 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 by using an interpolation function to generate the target structural parameters of the pot-type insulator.

[0043] Furthermore, constructing an objective function according to the overall maximum field strength of the pot 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] Determine, according to the electrical performance parameters, the overall maximum field strength constraint value of the pot insulator, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value between the concave maximum field strength and the concave minimum field strength, and the second difference constraint value between the convex maximum field strength and the convex minimum field strength;

[0046] Determine, according to 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, 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;

[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, and 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 running, the device where the storage medium is located is controlled to execute a structural optimization method for a pot-type 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 of a basin insulator. The method selects a plurality of coordinate points with the same horizontal coordinates from a basin concave surface and a basin 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 longitudinal coordinate of the target coordinate point, a plurality of initial celestial bodies are randomly constructed, and according to the target function and the initial celestial body, a Kepler algorithm is used to perform an iterative update operation on the initial celestial body. When the number of iterations of the iterative update operation reaches a preset threshold of the number of iterations, the target celestial body is obtained, and finally, according to the target celestial body, the longitudinal coordinate of the target coordinate point is updated, and then the parameterized finite element model is optimized by an interpolation function 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 fall into the local optimum. Secondly, while performing structural optimization, the present invention pays attention to the distribution of the electric field of the basin insulator after optimization according to the electric field distribution on the concave surface and the convex surface of the basin of the basin insulator, so as to avoid the insulation performance failure caused by the 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 It is a flow chart of a method for structural optimization of a pot-type insulator provided in one embodiment of the present invention.

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

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

[0058] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are 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 creative work 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 technicians in the technical field 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" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0060] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0061] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood 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 the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after 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 clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the 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 an 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 pot body concave structure and a pot body convex structure of the pot-type insulator;

[0067] In a preferred embodiment of the present invention, a pre-constructed parametric finite element model of a pot-type insulator is obtained. It can be understood that the finite element model (Finite Element Model, referred to as FEM) is a numerical analysis method, a mathematical model for solving practical engineering problems. It divides a continuum into a finite number of discrete units, and obtains the behavior of the entire continuum by mathematically describing and solving these units. Parameterization refers to the introduction of some important parameters in the model in the form of variables, so that the geometric shape of the model can 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 body of the parameterized finite element model as target coordinate points;

[0069] In a preferred embodiment of the present invention, Figure 3 As shown, 5 coordinates are selected from the concave and convex surfaces of the basin insulator for optimization to determine the optimization range of its size. Specifically, 5 key points in the concave and convex surface curve of the basin are selected to determine their horizontal coordinates. 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), (198, j1);

[0070] Furthermore, the value range of the vertical axis is:

[0071]

[0072] S3, constructing an objective function according to the overall maximum field strength of the pot 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;

[0073] Preferably, constructing the objective function according to the overall maximum field strength of the pot 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 comprises:

[0074] S31, obtaining a preset overall maximum field strength constraint value of the pot-type 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;

[0075] S32, 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, respectively, 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;

[0076] S33. Construct the objective function 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.

[0077] Preferably, the objective function is:

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

[0079] 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.

[0080] In a preferred embodiment of the present invention, the constraints of the electrical performance of the pot insulator are selected from the maximum field strength E1(x), the maximum field strength along the concave surface E2(x), the maximum field strength along the convex surface E3(x), the difference between the maximum and minimum field strength along the concave surface E4(x), and the difference between the maximum and minimum 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 according to the ordinate of the target coordinate point, and using the Kepler algorithm to iteratively update the initial celestial bodies 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;

[0086] Preferably, the step of 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 body using the Kepler algorithm according to the target function and the initial celestial body, 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 initializing the initial position of the initial celestial body; wherein the position is the ordinate of a number of the target coordinate points;

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

[0089] S411, obtaining structural parameters of the pot-type insulator;

[0090] S412, determining the range of ordinate values ​​of each target coordinate point according to the structural parameters;

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

[0092] S42, according to the initial fitness value and the initial central celestial body, using the Kepler algorithm, repeatedly performing an iterative update operation on the initial celestial body until the number of iterations is not less than the iteration number threshold, and outputting the target celestial body;

[0093] S43, according to the objective function value and the initial central celestial body, using the Kepler algorithm, 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, 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 speed of each celestial body to be optimized according to the gravitational force;

[0097] S433, performing orbital perturbation on each celestial body to be optimized according to the gravity, velocity, and preset orbital perturbation mechanism of each celestial body to be optimized, so as to perform 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;

[0098] S434, calculating the 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 the optimization 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 optimization position;

[0100] S436, taking the celestial body to be optimized with the largest target fitness value as the target celestial body;

[0101] S437, determining 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 speed, gravitational constant, celestial body mass and celestial body position are initialized; a random value is taken from the range of ordinate values ​​in step S2, and the initial position of the initial celestial body is initialized according to the random value. It can be understood that the initialization of the Kepler algorithm is the same as other algorithms, and each initial celestial body will be placed at a random position on the orbit.

[0105] Secondly, we first calculate the effect of Kepler's gravity, and according to the law of universal gravitation, we get the gravity and speed of each celestial body; it can be understood that the speed of a celestial body is affected by the gravity of the central celestial body. When a celestial body approaches the central celestial body, its speed will increase, and when it moves farther away, its speed will decrease. If a celestial body is close to the central celestial body, then the gravity of the central celestial body will be quite strong, and the celestial body will try to increase its speed to avoid being pulled towards the central celestial body. However, if a celestial body moves away from the central celestial body, then its speed will slow down because the gravity of the central celestial body is weak.

[0106] Then the orbital perturbation is calculated, and the position of the celestial body is updated after the orbital perturbation; it can be understood that in the solar system, most celestial bodies rotate counterclockwise around the sun, and they all rotate around their own axes. However, there are also some celestial bodies that rotate clockwise around the sun. The Kepler algorithm uses this behavior to escape the local optimal area, that is, by using the flag F to change the search direction so that it can accurately scan the search space. After that, a global exploration is carried out, and a selection mechanism is introduced to update the position of celestial bodies at different stages, as follows:

[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 speed of the celestial body; ρ, U, r represent parameters; according to the optimal solution, the speed, gravity, position and mass of the celestial body are updated, and the global optimal position is retained. It can be understood that the celestial bodies rotate around the central celestial body in their respective elliptical orbits. During the rotation, the celestial bodies approach the central celestial body in a certain period of time and then move away from the central celestial body. The Kepler algorithm simulates this behavior through two main phases: exploration and exploitation phases. Explore the celestial bodies far away from the central celestial body to find new solutions, while using the solutions close to the central celestial body more accurately because it looks for new places near the optimal solution. When the celestial body is far away from the central celestial body, the speed of the celestial body will represent the exploration operator. However, this speed is affected by the gravity of the central celestial body, which helps the current celestial body to slightly exploit the area near the optimal solution. At the same time, when the celestial body approaches the central celestial body, its speed increases sharply, allowing it 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 speed is used to avoid the local optimum, 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] As the iteration proceeds, the gravity gradually decays, making the speed and position update amplitude of the celestial body smaller, and the simulated celestial body gradually tends to be stable, and finally reaches the convergence condition, that is, the maximum number of iterations is reached, the iteration ends, and the optimal solution (target celestial body) is output.

[0110] S5. According to the target celestial body, the ordinate of the target coordinate point is updated, and then the parameterized finite element model is optimized by using an interpolation function to generate target structural parameters of the pot-type insulator.

[0111] In a preferred embodiment of the present invention, the ordinate of the target coordinate point in the parameterized finite element model is updated according to the target celestial body, and the concave and convex surface shape structure of the basin is obtained using an interpolation function, thereby achieving structural optimization of the basin insulator and achieving global and uniform electric field distribution.

[0112] The present embodiment provides a structural optimization method for a pot-type insulator, by selecting a number of 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 constructing a target function according to 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, and randomly constructing a number of initial celestial bodies according to the vertical coordinate of the target coordinate point, and using the Kepler algorithm to iteratively update the initial celestial body according to the target function and the initial celestial body, when the number of iterations of the iterative update operation reaches a preset iteration number threshold, the target celestial body is obtained, and finally, according to the target celestial body, the vertical coordinate of the target coordinate point is updated, 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 fall into the local optimum. Secondly, while performing structural optimization, the present invention pays attention to the distribution of the electric field of the basin insulator after optimization according to the electric field distribution on the concave surface and the convex surface of the basin of the basin insulator, so as to avoid the insulation performance failure caused by the 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 an embodiment of the present invention, comprising:

[0114] A model acquisition module, used to acquire 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 a pot body concave structure and a pot body convex structure of the pot-type insulator;

[0115] A coordinate point determination module, 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 according to the overall maximum field strength of the pot 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, used for 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 body using the Kepler algorithm according to the target function and the initial celestial body, and generating 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 by using an interpolation function to generate the target structural parameters of the pot-type insulator.

[0119] Preferably, constructing the objective function according to the overall maximum field strength of the pot 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 comprises:

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

[0121] Determine, according to the electrical performance parameters, the overall maximum field strength constraint value of the pot insulator, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value between the concave maximum field strength and the concave minimum field strength, and the second difference constraint value between the convex maximum field strength and the convex minimum field strength;

[0122] Determine, according to 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, 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;

[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 schematic, 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 on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying 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 may understand and implement it without paying any creative effort.

[0128] Those skilled in the art can 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, 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 above embodiments is implemented.

[0130] The terminal device may be a computing device such as a desktop computer, a notebook, 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, and uses various interfaces and lines to connect various parts of the entire terminal device.

[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 according to 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 devices.

[0133] Another preferred embodiment of the present invention provides a storage medium, the storage medium is a computer-readable storage medium, the computer program is stored in the computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, 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, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0134] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle 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 a pot body concave structure and a pot body convex structure of the pot-type insulator; Selecting 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; Constructing an objective function according to the overall maximum field strength of the pot 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 ordinate of the target coordinate point, a number of initial celestial bodies are randomly constructed, and according to the target function and the initial celestial body, the Kepler algorithm is used to perform an iterative update operation on the initial celestial body, and when the number of iterations of the iterative update operation reaches a preset iteration number threshold, a target celestial body is generated; According to the target celestial body, the ordinate of the target coordinate point is updated, and then the parameterized finite element model is optimized by using an interpolation function to generate the target structural parameters of the pot-type insulator.

2. A method for optimizing the structure of a pot-type insulator according to claim 1, characterized in that: The objective function is constructed according to the overall maximum field strength of the pot 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, including: Obtaining a preset overall maximum field strength constraint value of the pot-type 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, according to 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, 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; 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.

3. A method for optimizing the structure of a pot-type insulator according to claim 2, characterized in that: The objective function is: F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x); 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.

4. A method for optimizing the structure of a pot-type insulator according to claim 3, characterized in that: The method randomly constructs a plurality of initial celestial bodies according to the ordinate of the target coordinate point, and performs an iterative update operation on the initial celestial body using the Kepler algorithm according to the target function and the initial celestial body, and generates a target celestial body when the number of iterations of the iterative update operation reaches a preset iteration number threshold, including: Randomly initialize the initial position of the initial celestial body; wherein the position is the ordinate of a number of the target coordinate points; Calculating the 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 the target celestial body is output; The iterative update operation includes: Acquire 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; According to the law of universal gravitation and a preset gravitational coefficient, the gravitational force between each celestial body to be optimized and the central celestial body is calculated, and the speed of each celestial body to be optimized is determined according to the gravitational force; According to the gravity, speed, and preset orbital perturbation mechanism of each celestial body to be optimized, the orbit of each celestial body to be optimized is perturbed to allow the celestial body to be optimized to be globally explored, and then the position to be evaluated of each celestial body to be optimized after the orbital perturbation is determined; Calculating, according to the objective function, a second fitness value of each of the celestial bodies to be optimized at the position to be evaluated; Determine the optimization 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 determine the target fitness value of each celestial body to be optimized at the optimization 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 number of iterations 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.

5. A method for optimizing the structure of a pot-type insulator according to claim 4, characterized in that: The randomly initializing the initial position of the initial celestial body comprises: Obtaining structural parameters of the pot-type insulator; According to the structural parameters, determining the range of ordinate values ​​of each target coordinate point; 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.

6. A structural optimization device for a pot-type insulator, characterized in that: include: A model acquisition module, used to acquire 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 a pot body concave structure and a pot body convex structure of the pot-type insulator; A coordinate point determination module, 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 is used to construct an objective function according to the overall maximum field strength of the pot 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; A structure optimization module, used for 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 body using the Kepler algorithm according to the target function and the initial celestial body, and generating 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 by using an interpolation function to generate the target structural parameters of the pot-type insulator.

7. A structure optimization device for a pot-type insulator according to claim 6, characterized in that: The objective function is constructed according to the overall maximum field strength of the pot 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, including: Obtaining electrical performance parameters of the pot-type insulator; Determine, according to the electrical performance parameters, the overall maximum field strength constraint value of the pot insulator, the concave maximum field strength constraint value, the convex maximum field strength constraint value, the first difference constraint value between the concave maximum field strength and the concave minimum field strength, and the second difference constraint value between the convex maximum field strength and the convex minimum field strength; Determine, according to 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, 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; 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.

8. The structure optimization device for a pot-type insulator according to claim 7, characterized in that: The objective function is: F(x)=ω1E1(x) 2 +ω2E2(x) 3 / 2 +ω3E3(x) 3 / 2 +ω4E4(x)+ω5E5(x); 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.

9. A terminal device, characterized in that: The invention 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, a method for optimizing the structure of a pot-type insulator as claimed in any one of claims 1 to 5 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, 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 5.

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