Antenna weight lightening optimization method and system and medium
By establishing a mathematical model in the antenna structure and setting multiple boundary conditions, and using genetic algorithms or neural network algorithms to optimize feature design variables, the problem of incomplete antenna weight optimization is solved, and lightweight design is achieved while satisfying multiple performance constraints.
Patent Information
- Application Number
- CN202511540393.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-27
- Publication Date
- 2026-02-06
AI Technical Summary
In the design of highly integrated antenna payloads, existing technologies have failed to effectively consider electrical, mechanical, and thermal performance in the weight optimization process, resulting in incomplete weight optimization or affecting functional indicators.
By establishing a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, setting multiple boundary condition constraints, and using genetic algorithms or neural network algorithms to optimize the characteristic design variables of the antenna structure, the lightest weight can be achieved while meeting the requirements of standing wave ratio, thermal performance, and mechanical performance.
It enables the rapid finding of the optimal weight value without affecting the antenna's functional specifications. The optimization results are thorough, widely adaptable, and suitable for engineering applications with complex boundary conditions.
Smart Images
Figure CN121480025A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electronic device structure integration technology, and in particular to a method, system and medium for optimizing antenna weight reduction. Background Technology
[0002] In antenna payload design with high integration and weight requirements, the structural support layer and functional circuit layer are often combined into a single component. In such antennas, the structure typically performs multiple functions within the system: meeting antenna specifications, providing mechanical load-bearing capacity, and ensuring thermal conductivity. The weight specifications of the antenna structure are interdependent with these specifications, posing a significant challenge to weight reduction. Often, weight optimization compromises other functional requirements of the antenna. Conversely, weight optimization may be incomplete in order to maintain the antenna structure's functionality.
[0003] Currently, the main methods for reducing the weight of such complex antenna payloads include material replacement, structural optimization design, or topology optimization design. The weight is reduced and then the structural functional requirements are met. However, the required indicators are not taken into account as optimization boundary conditions during the optimization process. The impact of electrical performance, mechanical performance, and heat transfer performance is not considered in a comprehensive manner during the weight reduction process, resulting in incomplete weight optimization or the weight optimization affecting the functional indicators. Summary of the Invention
[0004] To address the aforementioned issues, this invention proposes a method, system, and medium for optimizing antenna weight reduction. By using the functional indicators of the antenna structure as constraints for weight reduction, the invention ensures that the antenna weight is minimized while meeting the requirements for antenna standing wave ratio, thermal performance, and mechanical performance.
[0005] The technical solution adopted in this invention is as follows: A method for optimizing antenna weight reduction includes: Extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including thermal resistance, standing wave ratio, stiffness and weight; Based on the requirements of antenna load on the thermal resistance, standing wave ratio, and stiffness of the antenna structure, constraints are established, and an optimization model is established to minimize the weight of the antenna structure under these constraints. The design variable value that minimizes the weight of the antenna structure under constraints is found through optimization methods and then verified.
[0006] Furthermore, establishing a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the transmission thermal resistance between the antenna heat source mounting surface and the radiating plate mounting surface and the characteristic design variables.
[0007] in, For transmission thermal resistance, Design variables for features. This represents the functional relationship between transmission thermal resistance and characteristic design variables.
[0008] Furthermore, establishing a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the antenna standing wave performance and the characteristic design variables based on an empirical model of electromagnetic wave theory.
[0009] in, For antenna standing wave performance, Design variables for features. This represents the functional relationship between antenna standing wave performance and characteristic design variables.
[0010] Furthermore, establishing a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the antenna structure stiffness and the characteristic design variables.
[0011] in, For antenna structural stiffness, Design variables for features. This represents the functional relationship between the antenna structure stiffness and characteristic design variables.
[0012] Furthermore, the establishment of constraints based on the antenna load requirements for the antenna structure's thermal resistance, standing wave ratio, and stiffness includes:
[0013] in, For transmission thermal resistance, This is the thermal resistance threshold. For antenna standing wave performance, Standing wave threshold; For antenna structural stiffness, This is the stiffness threshold.
[0014] Furthermore, the establishment of the optimization model that minimizes the weight of the antenna structure under constraints includes:
[0015]
[0016] Constraints:
[0017] in, Design a set of variables for the features. Design variables for features; This refers to the weight of the antenna structure. This represents the functional relationship between the antenna structure weight and characteristic design variables.
[0018] Furthermore, the step of finding the feature design variable value that minimizes the weight of the antenna structure under constraints through optimization methods includes: using a genetic algorithm or a neural network algorithm to iteratively solve for the feature design variable value that satisfies the constraints.
[0019] A lightweight antenna optimization system includes: The mathematical model building module is configured to extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including thermal resistance, standing wave ratio, stiffness and weight. The optimization model building module is configured to establish constraints based on the antenna load requirements for the antenna structure's thermal resistance, standing wave ratio, and stiffness, and to establish an optimization model that minimizes the weight of the antenna structure under these constraints. The optimization solution module is configured to find the characteristic design variable values that minimize the weight of the antenna structure under constraints through optimization methods, and then verify them.
[0020] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described antenna weight reduction optimization method.
[0021] The beneficial effects of this invention are as follows: 1) This invention adopts an antenna weight reduction optimization method under multiple boundary condition constraints, which can quickly find the optimal value that meets the constraints, the optimization result is thorough, the optimization will not affect the system's performance requirements, and the optimization speed is fast.
[0022] 2) This invention has a wide range of applications. Other constraints can be added as needed, such as adding constraints on manufacturability. The optimization objective can also be changed as needed, such as minimizing thermal resistance.
[0023] 3) This invention is not a one-sided optimization, but a comprehensive optimization with multiple objectives and multiple design variables, which is particularly suitable for engineering applications with complex boundary conditions and many coupling and cross-linking. Attached Figure Description
[0024] Figure 1 This is a flowchart of an antenna weight reduction optimization method according to Embodiment 1 of the present invention.
[0025] Figure 2This is a schematic diagram of an antenna load structure according to Embodiment 1 of the present invention.
[0026] Figure 3 This is an exploded view of the antenna load according to Embodiment 1 of the present invention.
[0027] Figure 4 This is a schematic diagram of the characteristic design variables of an antenna structure according to Embodiment 1 of the present invention.
[0028] Figure 5 This is a comparison diagram of an antenna structure before and after optimization according to Embodiment 1 of the present invention.
[0029] Reference numerals: 1-Antenna radiating plate, 2-Antenna structure, 3-Antenna load functional unit. Detailed Implementation
[0030] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments are now described. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention; that is, the described embodiments are only a part of the embodiments of the invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.
[0031] Example 1 like Figure 1 As shown, this embodiment provides a method for optimizing antenna weight reduction, including: Extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure. The physical parameters of the antenna structure include thermal resistance, standing wave ratio, stiffness and weight. Based on the requirements of antenna load on the thermal resistance, standing wave ratio, and stiffness of the antenna structure, constraints are established, and an optimization model is established to minimize the weight of the antenna structure under these constraints. The design variable value that minimizes the weight of the antenna structure under constraints is found through optimization methods and then verified.
[0032] Specifically, we will use a 4-channel antenna load as an example for explanation. Figure 2 and Figure 3As shown, the antenna radiator is welded to the antenna structure, and the antenna load functional units are mounted on the antenna structure with screws. In this antenna load, the antenna structure has three functions: first, it serves as a reflecting cavity for the antenna radiator, requiring a certain standing wave ratio (SWR); second, it acts as the main load-bearing structure for the antenna load, requiring a certain level of rigidity; and third, it needs to effectively conduct the heat generated by the functional units to the radiator, thus requiring a certain thermal resistance. Under the premise of meeting the requirements for antenna SWR, rigidity, and thermal resistance, the antenna structure needs to be as lightweight as possible.
[0033] Preferably, the method for optimizing the antenna weight of the above-mentioned 4-channel antenna load includes: Step 1: Extract the characteristic design variables of the antenna structure, such as... Figure 4 As shown, the antenna structure has structural feature design variables such as d1, d2, d3, d4, d5, d6 and thickness h1. These design variables are also the objects that need to be optimized and solved in this embodiment.
[0034] Step two, establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including: Establish a mathematical model of the transmission thermal resistance and characteristic design variables between the antenna body heat source mounting surface and the radiating plate mounting surface:
[0035] in, For transmission thermal resistance, This represents the functional relationship between transmission thermal resistance and characteristic design variables.
[0036] Based on the empirical model of electromagnetic wave theory, a mathematical model is established for the antenna standing wave performance and characteristic design variables:
[0037] in, For antenna standing wave performance, This represents the functional relationship between antenna standing wave performance and characteristic design variables.
[0038] Establish a mathematical model for the antenna structure stiffness and characteristic design variables:
[0039] in, For antenna structural stiffness, This represents the functional relationship between the antenna structure stiffness and characteristic design variables.
[0040] Step 3: Establish a mathematical model for the optimization objective, antenna structure weight, and characteristic design variables:
[0041] in, This refers to the weight of the antenna structure. Functional relationship between antenna structure weight and characteristic design variables Step four: Based on the input requirements of the antenna load, the thermal resistance of the antenna structure must be less than [value missing]. Standing wave needs to be smaller than Stiffness is at least greater than Based on the aforementioned requirements, establish the following constraints:
[0042] in, This is the thermal resistance threshold. Standing wave threshold, This is the stiffness threshold.
[0043] Step 5: Establish an optimization model that minimizes the weight of the antenna structure under multiple constraints:
[0044]
[0045] Constraints:
[0046] Step 6: Use a genetic algorithm or neural network algorithm to iteratively find the feature design variable values that satisfy the constraints.
[0047] Step 7: Verify the results. Figure 5 The optimized antenna structure is 25% lighter than the original structure.
[0048] Example 2 This embodiment provides a lightweight antenna optimization system, including: The mathematical model building module is configured to extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including thermal resistance, standing wave ratio, stiffness and weight. The optimization model building module is configured to establish constraints based on the antenna load requirements for the antenna structure's thermal resistance, standing wave ratio, and stiffness, and to establish an optimization model that minimizes the weight of the antenna structure under these constraints. The optimization solution module is configured to find the characteristic design variable values that minimize the weight of the antenna structure under constraints through optimization methods, and then verify them.
[0049] Example 3 This embodiment is based on embodiment 1: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the antenna weight reduction optimization method of Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form. The storage medium includes any entity or device capable of carrying computer program code, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage medium does not include electrical carrier signals and telecommunication signals.
[0050] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.
[0051] It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
Claims
1. A method for optimizing antenna weight reduction, characterized in that, include: Extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including thermal resistance, standing wave ratio, stiffness and weight; Based on the requirements of antenna load on the thermal resistance, standing wave ratio, and stiffness of the antenna structure, constraints are established, and an optimization model is established to minimize the weight of the antenna structure under these constraints. The design variable value that minimizes the weight of the antenna structure under constraints is found through optimization methods and then verified.
2. The antenna weight reduction optimization method according to claim 1, characterized in that, The establishment of a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the transmission thermal resistance between the antenna body's heat source mounting surface and the radiating plate mounting surface and the characteristic design variables. in, For transmission thermal resistance, Design variables for features. This represents the functional relationship between transmission thermal resistance and characteristic design variables.
3. The antenna weight reduction optimization method according to claim 1, characterized in that, The establishment of a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the antenna standing wave performance and the characteristic design variables based on an empirical model of electromagnetic wave theory. in, For antenna standing wave performance, Design variables for features. This represents the functional relationship between antenna standing wave performance and characteristic design variables.
4. The antenna weight reduction optimization method according to claim 1, characterized in that, The establishment of a mathematical model between the characteristic design variables and the physical parameters of the antenna structure includes: establishing a mathematical model between the antenna structure stiffness and the characteristic design variables. in, For antenna structural stiffness, Design variables for features. This represents the functional relationship between the antenna structure stiffness and characteristic design variables.
5. The antenna weight reduction optimization method according to claim 1, characterized in that, The constraints established based on the antenna load requirements for the antenna structure's thermal resistance, standing wave ratio, and stiffness include: in, For transmission thermal resistance, This is the thermal resistance threshold. For antenna standing wave performance, Standing wave threshold; For antenna structural stiffness, This is the stiffness threshold.
6. The antenna weight reduction optimization method according to claim 5, characterized in that, The optimization model for minimizing the weight of the antenna structure under constraints includes: Constraints: in, Design a set of variables for the features. Design variables for features; This refers to the weight of the antenna structure. This represents the functional relationship between the antenna structure weight and characteristic design variables.
7. The antenna weight reduction optimization method according to claim 1, characterized in that, The method of finding the feature design variable value that minimizes the weight of the antenna structure under constraints through optimization includes: using a genetic algorithm or a neural network algorithm to iteratively solve for the feature design variable value that satisfies the constraints.
8. A lightweight antenna optimization system, characterized in that, include: The mathematical model building module is configured to extract the characteristic design variables of the antenna structure and establish a mathematical model between the characteristic design variables and the physical parameters of the antenna structure, including thermal resistance, standing wave ratio, stiffness and weight. The optimization model building module is configured to establish constraints based on the antenna load requirements for the antenna structure's thermal resistance, standing wave ratio, and stiffness, and to establish an optimization model that minimizes the weight of the antenna structure under these constraints. The optimization solution module is configured to find the characteristic design variable values that minimize the weight of the antenna structure under constraints through optimization methods, and then verify them.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the antenna weight reduction optimization method according to any one of claims 1-7.