Spring contact finger structure design method and system based on dung beetle optimization algorithm

Abstract

The invention belongs to but not limited to the technical field of gas insulation, and particularly relates to a spring contact finger structure design method and system based on a dung beetle optimization algorithm, and the method comprises the steps: obtaining a three-dimensional structure model of a to-be-optimized spring contact finger, and the three-dimensional structure model comprises geometric parameters of a spring contact finger body, a conductor domain and a spring contact seat; boundary conditions are applied to the spring contact finger body, the conductor domain and the spring contact seat structure, and the contact temperature rise of the contact finger is solved through an electric-thermal coupling model; setting the diameter of a spring wire of the spring contact finger, the intermediate diameter of the spring, the number of turns of the spring, the inclination angle of a single-turn spring and the angle of a V-shaped groove of the contact seat as d, phi, n, alpha and beta, and respectively changing structural parameters for multiple times to carry out electrothermal coupling analysis on the spring contact finger to obtain a contact temperature rise data set; based on a dung beetle optimization algorithm, optimizing the spring contact finger structure by setting a decision variable and an optimization target, wherein the optimization target is that the contact temperature rise of the spring contact finger is minimum; and outputting the optimal structure parameters of the spring contact finger.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the field of gas insulation technology, and in particular relates to a spring contact finger structure design method and system based on a dung beetle optimization algorithm. Background Art

[0002] With the continuous expansion of power transmission levels and scales, heating failures caused by poor contact of the finger structure are very common, affecting the safe and stable operation of the power grid. The working environment of the spring finger structure is affected by multiple environmental loads. When there is docking deflection and internal defects in the equipment, the spring finger will be affected, resulting in partial contact failure, thus causing serious heating failures. Therefore, it is of great significance to explore the influencing parameters of the spring finger heating failure and optimize the finger structure to improve the operating stability of the GIL equipment.

[0003] Existing research has rarely optimized the overall structure and parameters of the GIL spring contact finger, and the relationship between the spring contact finger structural parameters and the contact temperature rise is incomplete. Therefore, it is urgent to analyze the spring contact finger structural parameters, optimize the structural design, improve the surface temperature distribution of the spring contact finger structure, and increase the safety margin during operation.

[0004] In view of the above analysis, the technical problems that urgently need to be solved in the prior art are: the existing research has done little design optimization on the overall structure and parameters of the GIL spring contact fingers, and the influence relationship between the spring contact finger structural parameters and the contact temperature rise is incomplete. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a spring contact finger structure design method and system based on the dung beetle optimization algorithm, which is used to solve the problem of thermal failure caused by high temperature rise in the contact part of the existing spring contact finger structure and improve its structural stability.

[0006] The present invention is implemented in this way: a spring contact finger structure design method based on a dung beetle optimization algorithm, comprising:

[0007] Step 1, obtaining a three-dimensional structural model of the spring contact finger to be optimized, wherein the three-dimensional structural model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat;

[0008] Step 2, applying boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculating the contact temperature rise of the contact finger through an electric-thermal coupling model;

[0009] Step 3, setting the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, respectively, changing the structural parameters multiple times to perform electrothermal coupling analysis on the spring contact finger, and obtaining a contact temperature rise data set;

[0010] Step 4: Based on the dung beetle optimization algorithm, the spring contact finger structure is optimized by setting decision variables and optimization targets, and the optimization target is to minimize the contact temperature rise of the spring contact finger;

[0011] Step 5: Output the optimal structural parameters of the spring contact finger.

[0012] Further, in step 1, in step 1, the spring contact finger model to be optimized is a three-dimensional axisymmetric model;

[0013] Further, in step 2, in the boundary conditions of the model, the current is the rated operating current, the voltage at the bottom of the contact seat is zero, and the contact method is controlled by a penalty function;

[0014] Furthermore, in step 3, the following formula is used as the contact temperature rise target fitness function to minimize the error between the optimal structural dimension value calculated by the model and the actual value:

[0015]

[0016] Where, f(d, Ф, n, α, β, x) represents the optimization objective function of the spring contact finger model, x is the solution vector of the contact temperature rise, M is the number of tests, and δ is the objective function;

[0017] Furthermore, in step 4, the algorithm optimizes the decision variables of the spring contact finger spring wire diameter d, the spring middle diameter Ф, the number of spring coils n, the single-coil spring inclination angle α and the contact seat V-groove angle β, and the obtained data set is studied and trained to establish an online optimization model;

[0018] Further, in step 4:

[0019] Step 4.1: Set the DBO algorithm parameters, including the dung beetle population (POP), algorithm dimension (dim), and maximum number of iterations (Tmax).

[0020] Step 4.2: Initialize the population according to each structural parameter. Each structural parameter is randomly generated according to the DBO algorithm.

[0021] Step 4.3, calculate the fitness of each dung beetle in the population, evaluate the fitness value of the dung beetles in the population, and find the position of the dung beetle with the lowest temperature rise of the spring antenna.

[0022] Step 4.4, perform population iteration to determine whether the population size meets the set conditions. If it meets the conditions, update the position of the dung beetle according to the corresponding update strategy. If the local optimal value generated by this generation is better than the global optimal value, replace it. When the maximum number of iterations is reached, save the result.

[0023] Step 4.5, repeat the above operation until the termination condition is met, and output the historical optimal solution as the optimal parameter of the spring contact finger structure model.

[0024] Another object of the present invention is to provide a spring contact finger structure optimization system based on a dung beetle optimization algorithm for realizing the spring contact finger structure design method based on a dung beetle optimization algorithm, comprising:

[0025] A three-dimensional structure model acquisition module, used to acquire a three-dimensional structure model of the spring contact finger to be optimized, wherein the three-dimensional structure model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat;

[0026] A contact finger contact temperature rise calculation module, used to apply boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculate the contact finger contact temperature rise through an electric-thermal coupling model;

[0027] The contact temperature rise data set acquisition module is used to set the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, and perform electrothermal coupling analysis on the spring contact finger by changing the structural parameters multiple times to obtain the contact temperature rise data set;

[0028] The spring contact finger structure optimization module optimizes the spring contact finger structure by setting decision variables and optimization objectives based on the dung beetle optimization algorithm. The optimization objective is to minimize the contact temperature rise of the spring contact finger.

[0029] The optimal structural parameter output module is used to output the optimal structural parameters of the spring contact finger.

[0030] Another object of the present invention is to provide a computer device, the computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the spring contact finger structure design method based on the dung beetle optimization algorithm.

[0031] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the spring contact finger structure design method based on the dung beetle optimization algorithm.

[0032] Another object of the present invention is to provide an information data processing terminal, which includes the spring contact finger structure optimization system based on the dung beetle optimization algorithm.

[0033] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0034] First, the method of the present invention calculates the contact temperature rise data set of the spring contact finger by changing the spring contact finger structural parameters for multiple times, performs online optimization on the spring contact finger structure based on the dung beetle optimization method, extracts the influence weight of each structural parameter on the electrothermal performance of the spring contact finger, and uses the root mean square error method as the target optimization function to minimize the error between the obtained optimal structural dimension value of the spring contact finger structure and the actual value, thereby realizing online, efficient and accurate structural optimization of the spring contact finger structure and outputting the optimal structural dimension.

[0035] Second, the technical problem solved by the technical solution of the present invention.

[0036] 1) The optimization process is highly complex:

[0037] The existing technology needs to process a large amount of calculations during the optimization process of the spring contact finger structure. It is difficult for traditional methods to find the optimal solution within a reasonable time, and the calculation complexity is high.

[0038] 2) Difficulty in analyzing the electro-thermal coupling effect:

[0039] In the design of spring contacts, accurate analysis of the electro-thermal coupling effect is difficult, and conventional methods cannot effectively deal with the complex coupling relationship of multiple variables, resulting in low design accuracy.

[0040] 3) Lack of efficient optimization algorithms:

[0041] Traditional optimization methods are inefficient under multi-variable and multi-constraint conditions, lack algorithms that can quickly converge and find the global optimal solution, and the optimization results are often unsatisfactory.

[0042] Significant technological advancements:

[0043] 1) Improve optimization efficiency:

[0044] The present invention adopts the Dung Beetle Optimization Algorithm (DBO) and utilizes its efficient search and global optimization capabilities to greatly improve the optimization efficiency. The Dung Beetle Optimization Algorithm can quickly find the optimal solution in a complex multi-dimensional space and significantly shorten the optimization time.

[0045] 2) Accurate analysis of electrical-thermal coupling effects:

[0046] By establishing an electro-thermal coupling model and applying reasonable boundary conditions, an accurate analysis of the contact temperature rise of the spring contact finger is achieved. This model can accurately simulate the mutual influence of current and temperature changes, improving the accuracy and reliability of the design.

[0047] 3) Multivariable complex optimization capabilities:

[0048] By conducting electro-thermal coupling analysis on various structural parameters such as the spring wire diameter, spring middle diameter, number of spring coils, single-turn spring inclination angle and contact seat V-groove angle of the spring contact finger, and using the dung beetle optimization algorithm for optimization, the optimization problem of complex coupling relationships of multiple variables was solved, and comprehensive and detailed parameter optimization was achieved.

[0049] 4) Guarantee of global optimal solution:

[0050] The dung beetle optimization algorithm has a powerful global search capability, which can avoid falling into the dilemma of local optimal solutions and ensure the global optimal solution is found. This significantly improves the reliability and performance of the design, making the optimization results more feasible in practical applications.

[0051] 5) Simplify complex calculations:

[0052] By reasonably setting the fitness function and optimization target, the complex calculation process is simplified, making the optimization process more intuitive and easy to implement. This provides a more convenient operation method for engineering applications and improves the efficiency of engineering design.

[0053] The present invention innovatively combines the dung beetle optimization algorithm and the electro-thermal coupling model, effectively solving the problems of high optimization complexity, difficult electro-thermal coupling effect analysis, and lack of efficient optimization algorithms in the prior art. It significantly improves the optimization efficiency and design accuracy, ensures the global optimal solution, simplifies complex calculations, and promotes the advancement of spring contact finger structure design technology, which has important application value and practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of a spring contact finger structure design method based on a dung beetle optimization algorithm provided in an embodiment of the present invention;

[0055] Figure 2 It is a structural diagram of a spring finger structure optimization system based on a dung beetle optimization algorithm provided by an embodiment of the present invention;

[0056] Figure 3 is a flow chart of an embodiment of a spring contact finger structure design method based on a dung beetle optimization algorithm provided in an embodiment of the present invention;

[0057] Figure 4 1 is a schematic diagram comparing the temperature field cloud diagrams of the 550kV GIL spring contact fingers before and after optimization provided by an embodiment of the present invention; wherein, (a) is before optimization, and (b) is after optimization. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0059] Example 1: High reliability connector design

[0060] In aerospace and military equipment, the reliability and performance of connectors are crucial. As a key component in the connector, the design quality of the spring contact finger directly affects the contact performance and service life of the connector.

[0061] 1) System initialization:

[0062] A three-dimensional structural model of the connector spring contact finger to be optimized is obtained, including geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat.

[0063] 2) Electrical-thermal coupling analysis:

[0064] Boundary conditions are imposed on the spring contact finger structure, and the contact temperature rise of the contact finger is calculated through the electric-thermal coupling model to ensure stability in high current and high temperature environments.

[0065] 3) Parameter optimization:

[0066] The spring wire diameter, spring middle diameter, number of spring coils, single-coil spring inclination angle and contact seat V-groove angle of the spring contact finger are set as optimization variables. By changing these structural parameters multiple times, an electro-thermal coupling analysis is performed to obtain the contact temperature rise data set.

[0067] Based on the dung beetle optimization algorithm, the decision variables and optimization objectives are set, and the optimization objective is to minimize the contact temperature rise of the spring contact finger.

[0068] 4) Optimize result output:

[0069] The optimal structural parameters of the optimized spring contact fingers are output and applied to the manufacture and testing of actual connectors.

[0070] #Industry application advantages:

[0071] - Improve the reliability and life of the connector: The optimized spring contacts can remain stable in high current and high temperature environments, reducing the failure rate.

[0072] -Improved contact performance: Optimized design ensures the connector has lower contact resistance and higher conductivity.

[0073] Example 2: Electric vehicle charging interface design

[0074] In the charging interface of electric vehicles (EVs), spring contacts are important conductive components, and their design affects charging efficiency and safety. Optimizing the spring contact structure to reduce contact resistance and improve thermal stability is the key to improving the performance of charging interfaces.

[0075] 1) System initialization:

[0076] Obtain the three-dimensional structural model of the electric vehicle charging interface to be optimized, including the geometric parameters of the spring contact finger body, conductor domain and spring contact seat.

[0077] 2) Electrical-thermal coupling analysis:

[0078] Boundary conditions are imposed on the spring contact finger structure, and the contact temperature rise of the contact finger is calculated through the electric-thermal coupling model to ensure thermal stability during high current charging.

[0079] 3) Parameter optimization:

[0080] The spring wire diameter, spring middle diameter, number of spring coils, single-coil spring inclination angle and contact seat V-groove angle of the spring contact finger are set as optimization variables. By changing these structural parameters multiple times, an electro-thermal coupling analysis is performed to obtain the contact temperature rise data set.

[0081] Based on the dung beetle optimization algorithm, the decision variables and optimization objectives are set, and the optimization objective is to minimize the contact temperature rise of the spring contact finger.

[0082] 4) Optimize result output:

[0083] The optimal structural parameters of the optimized spring contact fingers are output and applied to the manufacturing and testing of actual charging interfaces.

[0084] #Industry application advantages:

[0085] -Improve charging efficiency: The optimized spring contact fingers can significantly reduce contact resistance and improve power transmission efficiency.

[0086] - Enhanced safety: Through optimized design, the potential safety hazards caused by overheating during charging are reduced, ensuring the stability and safety of the charging process.

[0087] By applying the spring contact finger structure design method based on the dung beetle optimization algorithm, significant technological progress can be achieved in the fields of aerospace, military equipment and electric vehicle charging interfaces. The optimized spring contact finger structure has important application value in improving reliability, performance and safety.

[0088] like Figure 1 As shown, the spring finger structure design method based on the dung beetle optimization algorithm includes:

[0089] Step 1, obtaining a three-dimensional structural model of the spring contact finger to be optimized, wherein the three-dimensional structural model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat;

[0090] Step 2, applying boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculating the contact temperature rise of the contact finger through an electric-thermal coupling model;

[0091] Step 3, setting the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, respectively, changing the structural parameters multiple times to perform electrothermal coupling analysis on the spring contact finger, and obtaining a contact temperature rise data set;

[0092] Step 4: Based on the dung beetle optimization algorithm, the spring contact finger structure is optimized by setting decision variables and optimization targets, and the optimization target is to minimize the contact temperature rise of the spring contact finger;

[0093] Step 5: Output the optimal structural parameters of the spring contact finger.

[0094] In step 1, in step 1, the spring contact finger model to be optimized is a three-dimensional axisymmetric model;

[0095] In step 2, in the boundary conditions of the model, the current is the rated operating current, the voltage at the bottom of the contact seat is zero, and the contact method selects the penalty function for control;

[0096] In step 3, the following formula is used as the contact temperature rise target fitness function to minimize the error between the optimal structural dimension value calculated by the model and the actual value:

[0097]

[0098] Where, f(d, Ф, n, α, β, x) represents the optimization objective function of the spring contact finger model, x is the solution vector of the contact temperature rise, M is the number of tests, and δ is the objective function;

[0099] In step 4, the algorithm optimizes the decision variables of the spring contact finger spring wire diameter d, the spring middle diameter Ф, the number of spring coils n, the single-coil spring inclination angle α and the contact seat V-groove angle β, and the obtained data set is learned and trained to establish an online optimization model;

[0100] In step 4:

[0101] Step 4.1: Set the DBO algorithm parameters, including the dung beetle population (POP), algorithm dimension (dim), and maximum number of iterations (Tmax).

[0102] Step 4.2: Initialize the population according to each structural parameter. Each structural parameter is randomly generated according to the DBO algorithm.

[0103] Step 4.3, calculate the fitness of each dung beetle in the population, evaluate the fitness value of the dung beetles in the population, and find the position of the dung beetle with the lowest temperature rise of the spring antenna.

[0104] Step 4.4, perform population iteration to determine whether the population size meets the set conditions. If it meets the conditions, update the position of the dung beetle according to the corresponding update strategy. If the local optimal value generated by this generation is better than the global optimal value, replace it. When the maximum number of iterations is reached, save the result.

[0105] Step 4.5, repeat the above operation until the termination condition is met, and output the historical optimal solution as the optimal parameter of the spring contact finger structure model.

[0106] like Figure 2 As shown, the spring finger structure optimization system based on the dung beetle optimization algorithm includes:

[0107] A three-dimensional structure model acquisition module, used to acquire a three-dimensional structure model of the spring contact finger to be optimized, wherein the three-dimensional structure model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat;

[0108] A contact finger contact temperature rise calculation module, used to apply boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculate the contact finger contact temperature rise through an electric-thermal coupling model;

[0109] The contact temperature rise data set acquisition module is used to set the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, and perform electrothermal coupling analysis on the spring contact finger by changing the structural parameters multiple times to obtain the contact temperature rise data set;

[0110] The spring contact finger structure optimization module optimizes the spring contact finger structure by setting decision variables and optimization objectives based on the dung beetle optimization algorithm. The optimization objective is to minimize the contact temperature rise of the spring contact finger.

[0111] The optimal structural parameter output module is used to output the optimal structural parameters of the spring contact finger.

[0112] Example 1

[0113] See also Figure 3 The present invention provides a spring contact finger structure design method based on a dung beetle optimization algorithm, comprising the following steps:

[0114] Step 101, obtaining a three-dimensional structural model of the spring contact finger to be optimized, wherein the three-dimensional structural model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat, the spring contact finger model is modeled using a three-dimensional parameter equation, the conductor and the spring contact seat are made of aluminum alloy, and the spring contact finger model is made of copper;

[0115] Step 102, applying boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, calculating the contact temperature rise of the contact finger through the electric-thermal coupling model, setting the current to the rated operating current of 5500A, setting the bottom voltage of the spring contact seat to 0, and selecting the penalty function for contact method control;

[0116] Step 103, setting the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the single-coil spring inclination angle and the contact seat V-groove angle to d, Φ, n, α and β, respectively, changing the structural parameters multiple times to perform electrothermal coupling analysis on the spring contact finger, the control variables are d, Φ, n, α and β, and the upper and lower limits are shown in Table 1, and the contact temperature rise data set is obtained;

[0117] Table 1 Upper and lower limits of each control variable

[0118] variable Upper limit Lower limit d 1mm 2mm Ф 133mm 134mm n 97 laps 147 laps α 30° 60° β 120° 150°

[0119] Step 104: Based on the dung beetle optimization algorithm, the spring contact finger structure is optimized by setting decision variables and optimization targets. The optimization target is to minimize the contact temperature rise of the spring contact finger. The algorithm optimization decision variables are the spring wire diameter d of the spring contact finger, the spring middle diameter Ф, the number of spring coils n, the single-coil spring inclination angle α and the contact seat V-groove angle β. The obtained data set is studied and trained, an online optimization model is established, and the root mean square error function is calculated as the target fitness function, so that the error between the optimal structural size value obtained by optimization and the actual value is minimized:

[0120]

[0121] Among them, f(d, Ф, n, α, β, x) represents the optimization objective function of the spring contact finger model, x is the solution vector of contact temperature rise, M is the number of tests, and δ is the objective function.

[0122] Set the DBO algorithm parameters, including the number of dung beetle populations (POP=100), algorithm dimension (dim=5), and maximum number of iterations (Tmax=100); initialize the population according to each structural parameter, and each structural parameter is randomly generated according to the DBO algorithm; calculate the root mean square error of each dung beetle in the population as the target fitness function, evaluate the fitness value of the dung beetles in the population, and find the dung beetle position with the lowest temperature rise of the spring finger; perform population iteration to determine whether the population size meets the set conditions. If it meets the conditions, update the dung beetle position according to the corresponding update strategy. If the local optimal value generated by this generation is better than the global optimal value, replace it. If the maximum number of iterations is reached, save the result.

[0123] Step 105, repeat the above operation until the termination condition is met, and output the optimal structural parameters of the spring contact finger. Input the output optimal structural parameters into the reconstructed spring contact finger model, import it into the electrothermal coupling analysis model for calculation, obtain the surface temperature distribution cloud map of the optimized spring contact finger structure, and compare the contact temperature rise values ​​of the spring contact finger structure before and after optimization. Before and after optimization, the temperature field cloud map is as follows: Figure 4 The contact temperature rise of the spring contact finger surface at the rated operating current is shown in Table 2.

[0124] Table 2 Spring contact surface temperature rise at rated operating current

[0125] Before optimization(K) After optimization (K) Maximum temperature of spring contact finger 341.965 341.309 Maximum contact temperature rise of spring contact finger 48.3 47.5

[0126] In one embodiment, the optimization method comprises the following steps:

[0127] Step 1, obtaining a three-dimensional structural model of the spring contact finger to be optimized, wherein the three-dimensional structural model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat;

[0128] Step 2, applying boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculating the contact temperature rise of the contact finger through an electric-thermal coupling model;

[0129] Step 3, setting the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, respectively, changing the structural parameters multiple times to perform electrothermal coupling analysis on the spring contact finger, and obtaining a contact temperature rise data set;

[0130] Step 4: Based on the dung beetle optimization algorithm, the spring contact finger structure is optimized by setting decision variables and optimization targets, and the optimization target is to minimize the contact temperature rise of the spring contact finger;

[0131] Step 5, outputting the optimal structural parameters of the spring contact finger;

[0132] Further, in step 1, in step 1, the spring contact finger model to be optimized is a three-dimensional axisymmetric model;

[0133] Furthermore, in step 2, in the boundary conditions of the model, the current is the rated operating current, the voltage at the bottom of the contact seat is zero, and the contact method selects the penalty function for control;

[0134] Furthermore, in step 3, the following formula is used as the contact temperature rise target fitness function to minimize the error between the optimal structural dimension value calculated by the model and the actual value:

[0135]

[0136] Where, f(d, Ф, n, α, β, x) represents the optimization objective function of the spring contact finger model, x is the solution vector of the contact temperature rise, M is the number of tests, and δ is the objective function;

[0137] Furthermore, in step 4, the algorithm optimizes the decision variables of the spring contact finger spring wire diameter d, the spring middle diameter Ф, the number of spring coils n, the single-coil spring inclination angle α and the contact seat V-groove angle β, and the obtained data set is studied and trained to establish an online optimization model;

[0138] Furthermore, in step 4:

[0139] Step 4.1: Set the DBO algorithm parameters, including the dung beetle population (POP), algorithm dimension (dim), and maximum number of iterations (Tmax).

[0140] Step 4.2: Initialize the population according to each structural parameter. Each structural parameter is randomly generated according to the DBO algorithm.

[0141] Step 4.3, calculate the fitness of each dung beetle in the population, evaluate the fitness value of the dung beetles in the population, and find the position of the dung beetle with the lowest temperature rise of the spring antenna.

[0142] Step 4.4, perform population iteration to determine whether the population size meets the set conditions. If it meets the conditions, update the position of the dung beetle according to the corresponding update strategy. If the local optimal value generated by this generation is better than the global optimal value, replace it. When the maximum number of iterations is reached, save the result.

[0143] Step 4.5, repeat the above operation until the termination condition is met, and output the historical optimal solution as the optimal parameter of the spring contact finger structure model.

[0144] An application embodiment of the present invention provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of a spring contact finger structure design method based on a dung beetle optimization algorithm.

[0145] The application embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of a spring contact finger structure design method based on a dung beetle optimization algorithm.

[0146] The application embodiment of the present invention provides an information data processing terminal, which includes a spring contact finger structure optimization system based on a dung beetle optimization algorithm.

[0147] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0148] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A spring finger structure design method based on dung beetle optimization algorithm, characterized in that: include: Step 1, obtaining a three-dimensional structural model of the spring contact finger to be optimized, wherein the three-dimensional structural model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat; Step 2, applying boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculating the contact temperature rise of the contact finger through an electric-thermal coupling model; Step 3, setting the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, respectively, changing the structural parameters multiple times to perform electrothermal coupling analysis on the spring contact finger, and obtaining a contact temperature rise data set; Step 4: Based on the dung beetle optimization algorithm, the spring contact finger structure is optimized by setting decision variables and optimization targets, and the optimization target is to minimize the contact temperature rise of the spring contact finger; Step 5: Output the optimal structural parameters of the spring contact finger.

2. The spring contact finger structure design method based on the dung beetle optimization algorithm according to claim 1, characterized in that: In step 1, the spring contact finger model to be optimized is a three-dimensional axisymmetric model.

3. The spring contact finger structure design method based on the dung beetle optimization algorithm according to claim 1, characterized in that: In step 2, in the boundary conditions of the model, the current is the rated operating current, the voltage at the bottom of the contact seat is zero, and the contact method selects the penalty function for control.

4. The spring contact finger structure design method based on the dung beetle optimization algorithm according to claim 1, characterized in that: In step 3, the following formula is used as the contact temperature rise target fitness function to minimize the error between the optimal structural dimension value calculated by the model and the actual value: Among them, f(d, Ф, n, α, β, x) represents the optimization objective function of the spring contact finger model, x is the solution vector of contact temperature rise, M is the number of tests, and δ is the objective function.

5. The spring contact finger structure design method based on the dung beetle optimization algorithm according to claim 1, characterized in that: In step 4, the algorithm optimizes the decision variables of the spring contact finger spring wire diameter d, the spring center diameter Ф, the number of spring coils n, the single-coil spring inclination angle α and the contact seat V-groove angle β. The obtained data set is studied and trained to establish an online optimization model.

6. The spring contact finger structure design method based on the dung beetle optimization algorithm according to claim 1, characterized in that: In step 4: Step 4.1, set the DBO algorithm parameters, including the dung beetle population (POP), algorithm dimension (dim), and maximum number of iterations (Tmax); Step 4.2: Initialize the population according to each structural parameter, and each structural parameter is randomly generated according to the DBO algorithm. Step 4.3, calculating the fitness of each dung beetle in the population, evaluating the fitness value of the dung beetles in the population, and finding the position of the dung beetle with the lowest temperature rise of the spring antenna; Step 4.4, perform population iteration to determine whether the population size meets the set conditions. If it meets the conditions, update the position of the dung beetle according to the corresponding update strategy. If the local optimal value generated by this generation is better than the global optimal value, replace it. When the maximum number of iterations is reached, save the result. Step 4.5, repeat the above operation until the termination condition is met, and output the historical optimal solution as the optimal parameter of the spring contact finger structure model.

7. A spring finger structure optimization system based on a dung beetle optimization algorithm for implementing the spring finger structure design method based on a dung beetle optimization algorithm as claimed in any one of claims 1 to 6, characterized in that: include: A three-dimensional structure model acquisition module, used to acquire a three-dimensional structure model of the spring contact finger to be optimized, wherein the three-dimensional structure model includes geometric parameters of the spring contact finger body, the conductor domain and the spring contact seat; A contact finger contact temperature rise calculation module, used to apply boundary conditions to the spring contact finger body, the conductor domain and the spring contact seat structure, and calculate the contact finger contact temperature rise through an electric-thermal coupling model; The contact temperature rise data set acquisition module is used to set the spring wire diameter of the spring contact finger, the spring middle diameter, the number of spring coils, the inclination angle of the single coil spring and the V-groove angle of the contact seat to d, Ф, n, α and β, and perform electrothermal coupling analysis on the spring contact finger by changing the structural parameters multiple times to obtain the contact temperature rise data set; The spring contact finger structure optimization module optimizes the spring contact finger structure by setting decision variables and optimization objectives based on the dung beetle optimization algorithm. The optimization objective is to minimize the contact temperature rise of the spring contact finger. The optimal structural parameter output module is used to output the optimal structural parameters of the spring contact finger.

8. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the spring contact finger structure design method based on the dung beetle optimization algorithm as claimed in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the spring contact finger structure design method based on the dung beetle optimization algorithm as claimed in any one of claims 1 to 6.

10. An information data processing terminal, comprising the spring contact finger structure optimization system based on the dung beetle optimization algorithm according to claim 7.

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