Frame repair method and system based on multi-damage coupling quantification and dynamic formation
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA AIRPLANT STRENGTH RES INST
- Filing Date
- 2026-07-03
- Publication Date
- 2026-08-04
AI Technical Summary
[0008]针对现有技术中的上述不足，本发明提供的一种基于多损伤耦合量化与动态编队的框板修理方法及系统，解决了现有技术中修理方案设计依赖人工经验、效率低下且难以实现全局优化的问题
[0050]In terms of intelligent decision-making and optimization, existing technologies only automate the modeling process, while repair solutions still require manual specification or rely on simple rules. This invention, however, introduces a damage severity scoring mechanism, stress influence factor analysis methods, and a hierarchical dynamic formation optimization algorithm to achieve fully automated decision-making and collaborative optimization from intelligent damage identification to repair solution generation. This improvement significantly reduces reliance on expert experience and substantially enhances the scientific rigor and consistency of repair solutions.
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Figure CN122508928A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of strength testing and damage detection technology, specifically to a frame plate repair method and system based on multi-damage coupling quantization and dynamic formation. Background Technology
[0002] Aircraft frame structures (such as wing spars, ribs, and fuselage bulkheads) are the main load-bearing components. During long-term service, they are prone to multiple damages due to fatigue or accidental impacts, such as cracks around holes and impact damage. To ensure flight safety, timely and effective repairs are essential.
[0003] Traditional frame-plate structure repair design relies heavily on engineers' experience, resulting in cumbersome processes and low standardization. It typically requires manual damage identification, selection of reinforcement types and sizes based on experience, manual placement of fasteners, and subsequent finite element analysis verification. This method has significant drawbacks: 1. It is difficult to scientifically assess the interactions between damages, easily leading to conservative (over-strengthening) or insufficient repair solutions; 2. Manual placement makes it difficult to achieve optimal fastener distribution, potentially leaving new stress concentration points; 3. The entire design cycle is long, inefficient, and makes it difficult to achieve lightweight optimization of the repair solution.
[0004] With the development of digital maintenance technology, parametric modeling methods have been introduced to improve modeling efficiency. However, existing parametric methods mainly focus on the rapid generation of geometric models, and there are still gaps in intelligent damage assessment and automatic selection and optimization of repair solutions.
[0005] For the problem of mechanical connection repair, existing technical solutions approach the issue from four levels: traditional experience, parametric modeling, rule-driven, and independent optimization, but all of them have significant limitations.
[0006] In the design and optimization of mechanical connection repair schemes, mainstream methods include traditional experience-based design methods, basic parametric modeling methods, rule-based automated repair systems, and independent optimization methods. Traditional experience-based design methods rely on engineers manually selecting reinforcement models and determining fastener layouts based on manuals and experience, and then completing the design through finite element verification. The entire process requires repeated trial and error. Basic parametric modeling methods use scripts such as Python to drive CAD / CAE software such as CATIA and ABAQUS to achieve parametric generation and automatic finite element analysis of frame structure geometry. Although it can automate fixed processes, the selection of reinforcements and fastener layouts in the repair scheme still need to be predefined and input manually. Rule-based automated repair systems can achieve preliminary automatic selection of reinforcements by setting simple rules, but their rules are rigid, unable to handle complex situations, and lack optimization capabilities. Independent optimization methods are only used in individual research attempts, applying artificial bee colony algorithms to a single aspect of the repair scheme (such as fastener layout optimization), failing to organically combine reinforcement size optimization with fastener layout optimization.
[0007] In summary, the existing solutions have failed to form a complete mechanical connection repair design and optimization system, and have many shortcomings in terms of intelligence level, multi-damage handling capability, lightweight optimization effect and fastener layout. Summary of the Invention
[0008] To address the aforementioned shortcomings in the prior art, this invention provides a frame plate repair method and system based on multi-damage coupling quantization and dynamic formation, which solves the problems of existing repair scheme design relying on manual experience, low efficiency, and difficulty in achieving global optimization.
[0009] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: a frame plate repair method based on multi-damage coupling quantization and dynamic formation, comprising the following steps:
[0010] S1: For the wing frame structure, perform parametric modeling of the frame structure and damage, and score the severity of the damage to determine the repair priority;
[0011] S2: Divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and number of reinforcements;
[0012] S3: Based on a hierarchical dynamic formation optimization algorithm, a two-level collaborative optimization is performed on the size of the reinforcing member, the number of fasteners and their arrangement.
[0013] S4: Through the finite element software script interface, parametric modeling, analysis calculation and result extraction are realized, driving optimization iteration and outputting the optimal repair solution.
[0014] Further, step S1 includes the following sub-steps:
[0015] S11: Receive the basic parameters of the frame plate structure input by the user, including length, width, thickness, number of ribs, rib coordinates and included angle parameters, and generate the shell unit frame plate geometric model after fault tolerance verification;
[0016] S12: Receive the number, type, location and size parameters of damage input by the user, verify whether the damage is within the effective area and does not overlap, and set crack-stopping holes for the cracks;
[0017] S13: Calculate the damage severity index and output a damage repair priority list in descending order.
[0018] Furthermore, the severity index of the injury The calculation formula is:
[0019]
[0020] in, For damage type weighting coefficients, For damage characterization size, This is the critical size for damage tolerance. For position penalty weights, These represent the distances from the damage to the nearest existing fastener hole, the edge of the structure, and other damage, respectively.
[0021] Furthermore, step S2 includes the following sub-steps:
[0022] S21: The frame plate skin is divided into multiple repair areas by using the frame plate stiffeners, and the intersection of the stiffeners is set as the positioning anchor point of the reinforcement;
[0023] S22: Calculate the interaction influence factor between any two damages, and determine the damage coupling strength and repair mode based on the magnitude of the interaction influence factor;
[0024] S23: Based on the damage severity score and the multi-damage interaction influence factor, all damages are divided into different damages or damage groups, and the reinforcement configuration and quantity are automatically recommended.
[0025] Furthermore, the method for determining whether two damages share the same reinforcing member based on their interaction influence factors is as follows:
[0026]
[0027]
[0028] in, The interaction amplification factor is calculated when two damages are separated by ribs in different frames. ,otherwise, ; For the first The first injury and the first The angle of the damage, The shortest distance between damages For the first Damage length, For the first Damage length, The diameter of the fastener used for repair.
[0029] Furthermore, the determination of damage coupling strength and repair mode based on the magnitude of interaction influence factors specifically includes:
[0030] when ≤0 indicates a weak interaction between the two damages, requiring independent repair using two reinforcing components;
[0031] when >0 indicates a strong interaction between the two damages, requiring a single reinforcement to cover the entire damaged area.
[0032] Furthermore, step S3 includes the following sub-steps:
[0033] S31: Determine the initial stiffener design area based on the geometric center of the damage or damage group. The optimization problem is defined as: under the premise of satisfying strength, stiffness and process constraints, solve for the optimal stiffener length, width, number of fasteners and their coordinate array, with the optimization objective being to minimize the stiffener mass and maximize the structural safety margin.
[0034] S32: Define individual codes, each individual being a triple containing the length, width, and fastener coordinates of the reinforcement, and randomly generate the initial population;
[0035] S33: Perform a two-level optimization iteration and dynamically adjust the inertia weight of the particle swarm optimization based on the current aggregation degree of the formation;
[0036] In the two-level optimization, the upper-level optimization uses an adaptive differential evolution algorithm to perform crossover and mutation operations on the length and width of the reinforcement, and introduces dynamic splitting and dynamic fusion operations; the lower-level optimization treats the fastener coordinate array of each individual as a particle swarm, and the position update of each fastener follows the standard particle swarm optimization rules, and is additionally guided by three biomimetic forces: pheromone attraction, formation repulsion and boundary constraint.
[0037] S34: In each generation of optimization, the parameterized finite element analysis model is called to calculate the fitness value of each new individual, and the fitness ranking and selection operations are performed on the parent and child individuals.
[0038] S35: Repeat steps S33-S34 until the maximum number of iterations or fitness value converges, output the optimal individual, and decode to obtain the optimal reinforcement size and fastener layout scheme.
[0039] Furthermore, the dynamic splitting operation is specifically as follows: for the parent individual, if the equivalent stress at a certain fastener position is higher than the set value and the density of fasteners around it is lower than the upper limit, then the fastener is split into two, and the new position is slightly adjusted near its original position.
[0040] The dynamic fusion operation is as follows: if the Euclidean distance between two fasteners is less than 1.5 times the hole diameter, and the stress directions of their respective units are similar, then the two fasteners are merged into one, and the new position is the weighted center of the two.
[0041] Furthermore, the fitness value The calculation formula is:
[0042]
[0043] in, These are the weighting coefficients. To enhance the quality of reinforcing components and fasteners, For the maximum equivalent stress at the fastener hole edge and damaged edge, Let be the penalty function.
[0044] A frame plate repair system based on multi-damage coupling quantization and dynamic formation includes:
[0045] The parametric modeling and intelligent damage assessment module is used to perform parametric modeling of frame and plate structures and damage, and to score the severity of damage to determine repair priorities.
[0046] The reinforcement adaptive optimization module is used to divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and quantity of reinforcements.
[0047] The hierarchical dynamic formation optimization design module is used to perform two-level collaborative optimization of the size of the reinforcement, the number of fasteners and their arrangement based on the hierarchical dynamic formation optimization algorithm.
[0048] The finite element analysis automation module is used to achieve parametric modeling, analysis calculation and result extraction through the finite element software script interface, drive optimization iteration and output the optimal repair solution.
[0049] The beneficial effects of this invention are:
[0050] In terms of intelligent decision-making and optimization, existing technologies only automate the modeling process, while repair solutions still require manual specification or rely on simple rules. This invention, however, introduces a damage severity scoring mechanism, stress influence factor analysis methods, and a hierarchical dynamic formation optimization algorithm to achieve fully automated decision-making and collaborative optimization from intelligent damage identification to repair solution generation. This improvement significantly reduces reliance on expert experience and substantially enhances the scientific rigor and consistency of repair solutions.
[0051] Regarding multi-damage handling capabilities, existing technologies treat multiple damages as independent entities and process them separately, without considering the mutual influence between damages. This invention, however, intelligently recommends using clustered reinforcement components for overall repair by calculating damage severity and interaction factors. This effectively avoids under-repair or localized overload problems caused by ignoring damage interactions, significantly improving the reliability and safety of multi-damage repair scenarios.
[0052] In terms of lightweighting and force transmission path optimization, existing technologies typically use fixed shapes and sizes for reinforcements, chosen empirically, resulting in a disconnect between fastener layout and reinforcement shape. This invention employs a hierarchical dynamic formation optimization (HDFO) algorithm to collaboratively optimize reinforcement dimensions and fastener layout, essentially optimizing the load transfer path. The fastener formation behavior naturally creates an efficient force flow network, adaptively determining the reinforcement dimensions. This optimization achieves reinforcement weight reduction under the same strength requirements, and results in more uniform load transfer, fundamentally reducing the risk of secondary damage and contributing to overall aircraft weight reduction.
[0053] Regarding the selection of reinforcement components and adaptive fastener layout, existing technologies arrange fasteners according to uniform distribution or simple rules, which is difficult to adapt to complex stress field distributions. The HDFO algorithm of this invention supports variable-dimensional optimization, allowing the number of fasteners to be dynamically split and merged based on stress field information, and the layout guided by multiple forces, automatically meeting complex process constraints. This characteristic adaptively enables a scientific layout of fasteners, placing more where needed and fewer where less important, effectively reducing the maximum stress at the hole edge and improving the fatigue life of the repair area.
[0054] In summary, this invention deeply integrates biomimetic swarm intelligence optimization algorithms with traditional structural repair processes, providing a novel, efficient, and adaptive multi-damage repair solution for frame and plate structures, which has advanced technology and broad engineering application prospects. Attached Figure Description
[0055] Figure 1 This is a flowchart of the frame plate repair method based on multi-damage coupling quantization and dynamic formation according to the present invention.
[0056] Figure 2 This is a schematic diagram of the frame plate structure and damage model.
[0057] Figure 3 Flowchart of the hierarchical dynamic formation optimization algorithm.
[0058] Among them, 1. skin; 2. the first vertical rib; 3. the... One vertical rib; 4. The first 5. The first horizontal reinforcing bar; 6. The angle of the first reinforcing bar. 7. Crack damage; 8. Hole damage. Detailed Implementation
[0059] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0060] Example 1, as Figure 1 As shown, a frame plate repair method based on multi-damage coupling quantization and dynamic formation includes the following steps:
[0061] S1: For the wing frame structure, perform parametric modeling of the frame structure and damage, and score the severity of the damage to determine the repair priority;
[0062] S1 includes the following steps:
[0063] S11: Receives basic structural parameters of the frame plate from user input, including length. ,width ,thickness Number of reinforcing bars (number of horizontal reinforcing bars) Number of vertical reinforcing bars ), stiffener coordinates (Y coordinate) X coordinate and included angle (30°~90°) parameters, after fault tolerance verification, generate the shell unit frame plate geometric model;
[0064] In this embodiment, considering the geometric features of the wing frame structure, it is simplified into a shell unit frame model containing multiple ribs. This model consists of a skin and multiple crisscrossing ribs, forming a typical mesh-like structure, such as... Figure 2 As shown, the figure includes skin 1, the first vertical rib 2, and the... 3rd vertical rib 4. First horizontal reinforcing bar; 5. Angle of the first reinforcing bar. 6. Crack damage 7. Hole damage 8.
[0065] S12: Number of damages received from user input ,type (e.g., impact dents, cracks, holes), location and dimensions Parameters are used to verify whether the damage is within the effective area and does not overlap, and crack arrest holes are set for the cracks.
[0066] S13: Calculate the damage severity index and output a damage repair priority list in descending order.
[0067] The severity index of the injury The calculation formula is:
[0068]
[0069] in, The damage type weighting coefficient (example: 0.5 for impact dent, 0.8 for puncture, and 1.0 for crack). The dimensions are used to characterize the damage (length for cracks, area for impact damage). This is the critical size for damage tolerance. The location penalty weight is applied; a larger value is assigned if the damage is located on a main load-bearing reinforcement bar or in a high-stress area. These represent the distances from the damage to the nearest existing fastener hole, the edge of the structure, and other damage, respectively.
[0070] This formula comprehensively considers damage type weighting coefficients, damage characterization dimensions, damage tolerance critical dimensions, location penalty weights, and the distance from the damage to the nearest existing fastener hole, structural edge, and other damage. The system output is based on... A damage list sorted in descending order to guide repair priorities.
[0071] S2: Divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and number of reinforcements;
[0072] S2 includes the following steps:
[0073] S21: Divide the frame plate skin into multiple repair areas (rectangular or quadrilateral areas) using frame plate stiffeners, and set the intersection of the stiffeners as anchor points for reinforcement positioning;
[0074] S22: Calculate the interaction influence factor between any two damages, and determine the damage coupling strength and repair mode based on the magnitude of the interaction influence factor;
[0075] The interaction factor of any two damages The method for determining whether the same reinforcement component should be shared is as follows:
[0076]
[0077]
[0078] in, The interaction amplification factor is calculated when two damages are separated by ribs in different frames. ,otherwise, ; For the first The first injury and the first The angle of the damage, The shortest distance between damages For the first Damage length, For the first Damage length, The diameter of the fastener used for repair.
[0079] The determination of damage coupling strength and repair mode based on the magnitude of interaction influence factors specifically includes:
[0080] when ≤0 indicates a weak interaction between the two damages, requiring independent repair using two reinforcing components;
[0081] when >0 indicates a strong interaction between the two damages, requiring a single reinforcement to cover the entire damaged area.
[0082] S23: For each damage or damage group, find the anchor point closest to its geometric center. Based on the damage severity score and the multi-damage interaction influence factor, all damages are divided into different damages or damage groups, and the reinforcement configuration and quantity are automatically recommended.
[0083] S3: Based on a hierarchical dynamic formation optimization algorithm, a two-level collaborative optimization is performed on the size of the reinforcing member, the number of fasteners, and their arrangement. The flowchart of the hierarchical dynamic formation optimization algorithm is shown below. Figure 3 As shown;
[0084] S3 includes the following steps:
[0085] S31: Determine the initial stiffener design region based on the geometric center of the damage or damage group. The optimization problem is defined as: under the premise of satisfying strength, stiffness, and process constraints, find the optimal stiffener length. ,width Number of fasteners and its coordinate array The optimization objective is to minimize the mass of the reinforcing components and maximize the structural safety margin.
[0086] S32: Define individual codes, for each individual A triple containing the length, width, and fastener coordinates of the reinforcement. ,in It is a dynamic array with a length of The population is variable and the initial population is generated randomly.
[0087] In this embodiment, a certain number of individuals are randomly generated, and each individual's... Generated randomly within a reasonable range. The minimum value is determined based on the damage size, and the maximum value is determined by the length and width of the reinforcement. The value is a random integer within this range. The coordinates in the data are outside the damaged elliptical region. The distribution within the region follows a random distribution.
[0088] S33: Perform a two-level optimization iteration and dynamically adjust the inertial weight of the particle swarm optimization according to the current clustering degree. When the clustering degree is high, the weight is reduced to strengthen the local search, and vice versa to strengthen the global exploration, thus obtaining new offspring individuals.
[0089] In the two-level optimization, the upper-level optimization uses the adaptive differential evolution algorithm (SaDE) to perform crossover and mutation operations on the length and width of the reinforcement, and introduces dynamic splitting and dynamic fusion operations; the lower-level optimization treats the fastener coordinate array of each individual as a particle swarm, and the position update of each fastener follows the standard particle swarm optimization rules (inertia, individual historical optimum, global optimum), and is additionally guided by three biomimetic forces: pheromone attraction, formation repulsion, and boundary constraint.
[0090] Among these, pheromone attraction: moves towards the gradient direction of the high stress / high strain energy region in the current finite element analysis. Cluster repulsion: follows Reynolds' separation rule to prevent excessive proximity to other fasteners. Boundary constraint: ensures that fasteners do not exceed the reinforcement boundary and meet the edge distance requirements.
[0091] The dynamic splitting operation is as follows: For the parent individual, if the equivalent stress at a certain fastener position is higher than the set value and the density of fasteners around it is lower than the upper limit, then the fastener is split into two, and the new position is slightly adjusted near its original position.
[0092] The dynamic fusion operation is as follows: if the Euclidean distance between two fasteners is less than 1.5 times the hole diameter, and the stress directions of their respective units are similar, then the two fasteners are merged into one, and the new position is the weighted center of the two.
[0093] S34: In each generation of optimization, the parameterized finite element analysis model is called to calculate the fitness value of each new individual, and the fitness ranking and selection operations are performed on the parent and child individuals.
[0094] The fitness value The calculation formula is:
[0095]
[0096] in, These are the weighting coefficients. To enhance the quality of reinforcing components and fasteners, For the maximum equivalent stress at the fastener hole edge and damaged edge, Let be the penalty function.
[0097] S35: Repeat steps S33-S34 until the maximum number of iterations is reached or the fitness value converges, output the optimal individual, and decode to obtain the optimal reinforcement size. Fastener layout scheme .
[0098] S4: Through the finite element software script interface, parametric modeling, analysis calculation and result extraction are realized, driving optimization iteration and outputting the optimal repair solution.
[0099] Step S4 specifically includes:
[0100] S41: Create a txt file to store the frame plate repair structure parameters obtained from S1 and S2, as well as user-defined material and mesh parameters. This includes frame plate structure parameters: length, width, height, thickness, number of horizontal ribs, number of vertical ribs, included angle, y-coordinate of each horizontal rib, x-coordinate of each vertical rib, length, original fastener hole positions, original hole diameters, number of damages, damage type, and damage location; reinforcement parameters: number of reinforcements, reinforcement positions, reinforcement configuration, reinforcement dimensions, fastener diameter, and fastener positions on each face of the reinforcement; material property parameters for each component, boundary conditions, loads, mesh size, and refined mesh size.
[0101] S42: Write ABAQUS Python script interface code to read all parameters in the txt file, perform parametric modeling analysis, extract the maximum stress in the area of interest of each component, and substitute it into step S34 to calculate the fitness for optimization.
[0102] Through the above systematic steps, this invention realizes an integrated automated process from damage assessment and intelligent generation of repair plans to optimization design, improving the design efficiency and global optimality of aircraft frame structure damage repair.
[0103] Example 2: A frame plate repair system based on multi-damage coupling quantization and dynamic formation, comprising:
[0104] The parametric modeling and intelligent damage assessment module is used to perform parametric modeling of frame and plate structures and damage, and to score the severity of damage to determine repair priorities.
[0105] The reinforcement adaptive optimization module is used to divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and quantity of reinforcements.
[0106] The hierarchical dynamic formation optimization design module is used to perform two-level collaborative optimization of the size of the reinforcement, the number of fasteners and their arrangement based on the hierarchical dynamic formation optimization algorithm.
[0107] The finite element analysis automation module is used to achieve parametric modeling, analysis calculation and result extraction through the finite element software script interface, drive optimization iteration and output the optimal repair solution.
[0108] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the invention.
Claims
1. A frame plate repair method based on multi-damage coupling quantization and dynamic formation, characterized in that, Includes the following steps: S1: For the wing frame structure, perform parametric modeling of the frame structure and damage, and score the severity of the damage to determine the repair priority; S2: Divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and number of reinforcements; S3: Based on a hierarchical dynamic formation optimization algorithm, a two-level collaborative optimization is performed on the size of the reinforcing member, the number of fasteners and their arrangement. S4: Through the finite element software script interface, parametric modeling, analysis calculation and result extraction are realized, driving optimization iteration and outputting the optimal repair solution.
2. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 1, characterized in that, S1 includes the following steps: S11: Receive the basic parameters of the frame plate structure input by the user, including length, width, thickness, number of ribs, rib coordinates and included angle parameters, and generate the shell unit frame plate geometric model after fault tolerance verification; S12: Receive the number, type, location and size parameters of damage input by the user, verify whether the damage is within the effective area and does not overlap, and set crack-stopping holes at both ends of the crack. S13: Calculate the damage severity index and output a damage repair priority list in descending order.
3. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 2, characterized in that, The severity index of the injury The calculation formula is: ； in, For damage type weighting coefficients, For damage characterization size, This is the critical size for damage tolerance. For position penalty weights, These represent the distances from the damage to the nearest existing fastener hole, the edge of the structure, and other damage, respectively.
4. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 1, characterized in that, S2 includes the following steps: S21: The frame plate skin is divided into multiple repair areas by using the frame plate stiffeners, and the intersection of the stiffeners is set as the positioning anchor point of the reinforcement; S22: Calculate the interaction influence factor between any two damages, and determine the damage coupling strength and repair mode based on the magnitude of the interaction influence factor; S23: Based on the damage severity score and the multi-damage interaction influence factor, all damages are divided into different damages or damage groups, and the reinforcement configuration and quantity are automatically recommended.
5. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 4, characterized in that, The method for determining whether two damages share the same reinforcement component is as follows: ； ； in, The interaction amplification factor is calculated when two damages are separated by ribs in different frames. ,otherwise, ; For the first The first injury and the first The angle of the damage, The shortest distance between damages For the first Damage length, For the first Damage length, The diameter of the fastener used for repair.
6. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 5, characterized in that, The determination of damage coupling strength and repair mode based on the magnitude of interaction influence factors specifically includes: when ≤0 indicates a weak interaction between the two damages, requiring independent repair using two reinforcing components; when >0 indicates a strong interaction between the two damages, requiring a single reinforcement to cover the entire damaged area.
7. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 1, characterized in that, S3 includes the following steps: S31: Determine the initial stiffener design area based on the geometric center of the damage or damage group. The optimization problem is defined as: under the premise of satisfying strength, stiffness and process constraints, solve for the optimal stiffener length, width, number of fasteners and their coordinate array, with the optimization objective being to minimize the stiffener mass and maximize the structural safety margin. S32: Define individual codes, each individual being a triple containing the length, width, and fastener coordinates of the reinforcement, and randomly generate the initial population; S33: Perform a two-level optimization iteration and dynamically adjust the inertia weight of the particle swarm optimization based on the current aggregation degree of the formation; In the two-level optimization, the upper-level optimization uses an adaptive differential evolution algorithm to perform crossover and mutation operations on the length and width of the reinforcement, and introduces dynamic splitting and dynamic fusion operations; the lower-level optimization treats the fastener coordinate array of each individual as a particle swarm, and the position update of each fastener follows the standard particle swarm optimization rules, and is additionally guided by three biomimetic forces: pheromone attraction, formation repulsion and boundary constraint. S34: In each generation of optimization, the parameterized finite element analysis model is called to calculate the fitness value of each new individual, and the fitness ranking and selection operations are performed on the parent and child individuals. S35: Repeat steps S33-S34 until the maximum number of iterations or fitness value converges, output the optimal individual, and decode to obtain the optimal reinforcement size and fastener layout scheme.
8. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 7, characterized in that, The dynamic splitting operation is as follows: for the parent individual, if the equivalent stress at a certain fastener position is higher than the set value and the density of fasteners around it is lower than the upper limit, then the fastener is split into two, and the new position is slightly adjusted near its original position. The dynamic fusion operation is as follows: if the Euclidean distance between two fasteners is less than 1.5 times the hole diameter, and the stress directions of their respective units are similar, then the two fasteners are merged into one, and the new position is the weighted center of the two.
9. The frame plate repair method based on multi-damage coupling quantization and dynamic formation according to claim 7, characterized in that, The fitness value The calculation formula is: ； in, These are the weighting coefficients. To enhance the quality of reinforcing components and fasteners, For the maximum equivalent stress at the fastener hole edge and damaged edge, Let be the penalty function.
10. A system for a frame plate repair method based on multi-damage coupling quantization and dynamic formation as described in any one of claims 1-9, characterized in that, include: The parametric modeling and intelligent damage assessment module is used to perform parametric modeling of frame and plate structures and damage, and to score the severity of damage to determine repair priorities. The reinforcement adaptive optimization module is used to divide the repair area, analyze the interaction of multiple damages, and adaptively determine the configuration and quantity of reinforcements. The hierarchical dynamic formation optimization design module is used to perform two-level collaborative optimization of the size of the reinforcement, the number of fasteners and their arrangement based on the hierarchical dynamic formation optimization algorithm. The finite element analysis automation module is used to achieve parametric modeling, analysis calculation and result extraction through the finite element software script interface, drive optimization iteration and output the optimal repair solution.