Particle swarm algorithm-based composite material patching and repairing stress optimization method and system

Abstract

The invention belongs to the technical field of composite material damage repair, and particularly discloses a composite material patching repair stress optimization method based on a particle swarm optimization algorithm, and the method comprises the following steps: constructing a composite material laminated plate non-uniform stepped patching repair three-dimensional model, and carrying out the analogue simulation through a finite element analysis method, stress distribution and deformation conditions under the actual load are obtained; according to the stress distribution and the deformation condition under the actual load, a composite laminated plate non-uniform stepped patching repair optimization model is constructed; and carrying out iterative solution on the composite material laminated plate non-uniform stepped patching repair optimization model by adopting a particle swarm optimization algorithm, outputting an optimal repair scheme, and realizing minimum optimization of the composite material patching repair maximum stress. The method solves the problems that a traditional uniform patching repair design method neglects the non-uniform characteristic of a damaged area, certain limitation exists in the aspect of stress distribution optimization, and the optimal repair effect is difficult to achieve.

Description

Technical Field

[0001] The present invention belongs to the technical field of composite material damage repair, and in particular relates to a composite material patching repair stress optimization method and system based on a particle swarm algorithm. Background Art

[0002] Advanced composite materials have been widely used in the aviation field due to their superior material, physical properties and designability. The amount of advanced composite materials used has, to a certain extent, become one of the important criteria for measuring the economy, functionality and advancement of large passenger aircraft and advanced fighter aircraft. In particular, in recent years, advanced composite materials have been widely used in the primary and secondary load-bearing structures of domestic large commercial passenger aircraft and large military transport aircraft.

[0003] However, the environmental complexity and challenges faced by materials during service have increased significantly. For example, runway debris splashing, bird strike risks, and accidental tool drops during maintenance operations can significantly reduce the strength and performance of composite structures. Some typical impact damage can cause splitting, scratches, pits, and penetration damage to the composite fuselage structure. Damage repair and service life extension of composite materials have become research hotspots. At the same time, the design of aviation composite structures is developing towards integration and co-curing, and the integration and large-scale trends of composite structures have also posed challenges to damage repair.

[0004] As an effective method for repairing composite material damage, the design optimization of the stepped patching repair technology is of great significance for improving the repair effect and material performance. Among the composite material repair methods, there are two main technical means: mechanical connection repair (usually riveting) and adhesive repair. Mechanical connection repair can usually transmit a larger load, it performs well in terms of anti-peeling performance, and allows disassembly and reassembly. This method is basically not affected by the external environment, and there is no residual stress generated during gluing. Usually, when repairing thicker skins, mechanical connection repair methods are used. However, mechanical connection also has many disadvantages. It requires opening holes around the damaged part, which forms a stress concentration area and cuts off the continuity of the original fiber; the weight gain of the structure is also more obvious. In addition, metal fasteners will undergo galvanic corrosion and fatigue resistance will also decrease. These have limited the further application and development of mechanical connection repair in the field of composite material repair. The adhesive repair technology has excellent properties such as good connection efficiency and smooth surface of the repaired component, so it is widely used in the aviation field as one of the most common repair methods. Adhesive repair mainly includes patching and patching. The patching method refers to the process of directly repairing the surface of the repaired structural part by gluing after removing the damaged part of the structure; while the digging method is to dig out the damaged and defective parts first, and then fill the original place with new materials by gluing. Composite material digging and patching technology has the advantages of being able to restore the aerodynamic shape of the structure, generating small repair stress, basically no eccentric load and small weight increase. Especially for structural parts that need to ensure high stealth performance, it has become the mainstream repair technology for composite materials.

[0005] Existing research has made significant progress in composite material repair, but there are still some key issues to be resolved. First, the traditional patching repair design method has certain limitations in optimizing stress distribution, especially under complex load conditions, it is difficult to achieve the best repair effect. Second, most of the existing repair methods are based on uniform step design, ignoring the uneven characteristics of the damaged area, resulting in stress concentration and reduced fatigue life in the repaired structure in practical applications. Summary of the invention

[0006] The purpose of the present invention is to solve the problem that traditional repair methods have limitations in geometric design and cannot achieve accurate optimization of maximum stress. A composite material patching repair stress optimization method and system based on particle swarm algorithm are proposed.

[0007] The technical solution of the present invention is as follows: In the first aspect, a stress optimization method for composite material repair based on particle swarm algorithm comprises the following steps: S1. Construct a three-dimensional model of non-uniform step patching and repair of composite laminates, and use finite element analysis to simulate and obtain the stress distribution and deformation under actual load; S2. According to the stress distribution and deformation under actual load, an optimization model for the repair of non-uniform step-cutting of composite laminates is established; S3. The particle swarm optimization algorithm is used to iteratively solve the optimization model of non-uniform step patching repair of composite laminates, output the best repair plan, and achieve the optimization of minimizing the maximum stress of patching repair of composite materials.

[0008] The beneficial effects of the present invention are: The present invention constructs an optimization model for the non-uniform step patching and repair of composite material laminates according to the stress distribution and deformation under actual load, and iteratively solves the optimization model for the non-uniform step patching and repair of composite material laminates by introducing a particle swarm optimization algorithm, thereby achieving accurate optimization of the maximum stress and efficient repair of composite material damage.

[0009] Preferably, the expression formula of the non-uniform step patching and repair optimization model of the composite laminate in step S2 is:

[0010] in, represents the optimization objective function; Indicates The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates The equivalent stress value of the non-uniform patching repair optimization model of composite laminates in the possible repair schemes; It represents the maximum equivalent stress value among all possible repair solutions; Indicates all possible repair solutions; Indicates the volume of the non-uniform stepped excavation repair patch; It represents the limiting volume of the non-uniform stepped excavation repair patch; Indicates The repair patch of the possible repair solution The volume of the ply layup; It represents the total number of plies of the composite laminate; Subject to Indicates constraints; min represents the minimization objective function.

[0011] The beneficial effects of the above preferred solution are: Taking the volume constraint as a constraint condition ensures that the amount of repair material used does not exceed the predetermined volume limit. When the repair scheme represented by the particle exceeds the volume constraint, the scheme will be deemed invalid and excluded from the search range in subsequent iterations (its value is assigned to infinity), which effectively limits the amount of repair material used and ensures the practicality of the optimization results.

[0012] Preferably, the Equivalent stress value of the optimization model for non-uniform patching repair of composite laminates with possible repair schemes The calculation formula is:

[0013] in, , and Respectively represent The principal stresses in three directions of the composite laminate repaired by the possible repair schemes, , and Respectively represent The composite laminates repaired by the possible repair solutions are , and Shear stress in the direction normal to the plane.

[0014] Preferably, the step S3 specifically includes the following sub-steps: S31. Initialize the design variable patching parameters and the population parameters of the particle swarm; wherein the design variable patching parameters include the particle position; the population parameters of the particle swarm include the inertia weight and the particle speed; the particles represent possible repair solutions; S32. Calculate the objective function of the optimization model for the repair of non-uniform step-cutting of composite laminates; S33. Taking the objective function as a multi-dimensional search space, and calculating the updated inertia weight in the search space; S34. Based on the updated inertia weight, calculate the updated particle velocity and particle position; S35. Determine whether the preset maximum number of iterations has been reached. If so, the process ends and the best repair plan is output to achieve the optimization of minimizing the maximum stress of the composite material patching repair; if not, update and return to step S32.

[0015] Preferably, the updated inertia weight in step S33 The calculation formula is:

[0016] in, represents the initial inertia weight; Indicates the weight when the iteration reaches the maximum number of iteration steps; Indicates the maximum number of iteration steps; Indicates the current iteration step number.

[0017] Preferably, the calculation formula of the updated particle velocity in step S34 is:

[0018] in, Represents the updated particle velocity; Represents the particle velocity before updating, i.e. The repair patch of the possible repair solution The volume of the ply layup; and represents the acceleration factor, Represents a random number between 0 and 1; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; represents the individual historical optimal value; Represents the global historical optimal value; Represents the updated inertia weight.

[0019] Preferably, the calculation formula for the updated particle position in step S34 is:

[0020] in, Represents the updated particle position; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates the updated particle velocity.

[0021] The beneficial effects of the above preferred solution are: Through the above optimization scheme, the particle swarm optimization algorithm is introduced to efficiently optimize the repair parameters. By iteratively updating the position and speed of particles, the optimal solution is gradually approached, the weight coefficient is dynamically adjusted, and the global search and local search capabilities are balanced, which improves the algorithm convergence speed and solution quality.

[0022] In a second aspect, a composite material patching and repair stress optimization system based on a particle swarm algorithm is provided. The system includes a processor, and the processor is used to execute the composite material patching and repair stress optimization method based on a particle swarm algorithm as described in the first aspect.

[0023] In a third aspect, a computer-readable storage medium stores computer instructions. In response to a computer reading the computer instructions in the storage medium, the computer executes the composite material patching repair stress optimization method based on particle swarm algorithm as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The figure shows a flow chart of a composite material patching and repair stress optimization method based on a particle swarm algorithm provided in Example 1 of the present invention.

[0025] Figure 2 Shown is a schematic diagram of a three-dimensional model for non-uniform step patching and repair of a composite laminate provided in Example 1 of the present invention.

[0026] Figure 3 It is a schematic diagram of the repair parameters of the non-uniform stepped composite material provided in Example 1 of the present invention.

[0027] Figure 4 The figure shows the geometry, boundary conditions and load schematic diagram of the laminated plate example with four fiber layers provided in Example 3 of the present invention.

[0028] Figure 5 Shown is a stress cloud diagram of a four-layer fiber ply laminate under uniform step repair provided in Example 3 of the present invention.

[0029] Figure 6 Shown is a stress cloud diagram of a four-layer fiber ply laminate under non-uniform step repair provided in Example 3 of the present invention.

[0030] Figure 7 Shown is an iteration history diagram of the objective function of a laminate calculation example with four fiber layers provided in Example 3 of the present invention.

[0031] Figure 8 The figure shows the geometry, boundary conditions and load schematic diagram of the eight-layer fiber ply laminate example provided in Example 3 of the present invention.

[0032] Fig. 9 Shown is a stress cloud diagram of an eight-layer fiber ply laminate under uniform step repair provided in Example 3 of the present invention.

[0033] Fig.10 Shown is a stress cloud diagram of an eight-layer fiber ply laminate under non-uniform step repair provided in Example 3 of the present invention.

[0034] Fig.11 Shown is an iteration history diagram of the objective function of the eight-layer fiber ply laminate example provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0035] Now, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the accompanying drawings are only exemplary and are intended to explain the principles and spirit of the present invention, rather than to limit the scope of the present invention.

[0036] Embodiment 1: like Figure 1As shown, a composite material patching repair stress optimization method based on particle swarm algorithm includes the following steps: S1. Construct a three-dimensional model of non-uniform step patching and repair of composite laminates, such as Figure 2 and Figure 3 As shown, the finite element analysis method is used for simulation to obtain the stress distribution and deformation under the actual load; S2. According to the stress distribution and deformation under actual load, an optimization model for the repair of non-uniform step-cutting of composite laminates is established; S3. The particle swarm optimization algorithm is used to iteratively solve the optimization model of non-uniform step patching repair of composite laminates, output the best repair plan, and achieve the optimization of minimizing the maximum stress of patching repair of composite materials.

[0037] In the particle swarm algorithm, the problem to be solved, that is, the objective function of the optimization model of non-uniform step patching and repair of composite laminates, is regarded as a multidimensional search space. Each "particle" represents a potential solution, that is, a possible repair plan. The particle position indicates the position of the solution in the search space, and the particle velocity indicates the moving direction and speed of the solution in the search space. The particle updates its own speed and position according to the individual historical optimal value and the global historical optimal value, so as to continuously approach the optimal solution, that is, the best repair plan, and realize the optimization of minimizing the maximum stress of patching and repair of composite materials.

[0038] In this embodiment, the expression formula of the non-uniform step patching and repair optimization model of the composite laminate in step S2 is:

[0039] in, represents the optimization objective function; Indicates The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates The equivalent stress value of the non-uniform patching repair optimization model of composite laminates in the possible repair schemes; It represents the maximum equivalent stress value among all possible repair solutions; Indicates all possible repair solutions; Indicates the volume of the non-uniform stepped excavation repair patch; It represents the limiting volume of the non-uniform stepped excavation repair patch; Indicates The repair patch of the possible repair solution The volume of the ply layup; It represents the total number of plies of the composite laminate; Subject toIndicates constraints; min represents the minimization objective function.

[0040] In this embodiment, the Equivalent stress value of the optimization model for non-uniform patching repair of composite laminates with possible repair schemes The calculation formula is:

[0041] in, , and Respectively represent The principal stresses in three directions of the composite laminate repaired by the possible repair schemes, , and Respectively represent The composite laminates repaired by the possible repair solutions are , and Shear stress in the direction normal to the plane.

[0042] In this embodiment, step S3 specifically includes the following sub-steps: S31. Initialize the design variable patching parameters and the population parameters of the particle swarm; wherein the design variable patching parameters include the particle position; the population parameters of the particle swarm include the inertia weight and the particle speed; the particles represent possible repair solutions; S32. Calculate the objective function of the optimization model for the repair of non-uniform step-cutting of composite laminates; S33. Taking the objective function as a multi-dimensional search space, and calculating the updated inertia weight in the search space; S34. Based on the updated inertia weight, calculate the updated particle velocity and particle position; S35. Determine whether the preset maximum number of iterations has been reached. If so, the process ends and the best repair plan is output to achieve the optimization of minimizing the maximum stress of the composite material patching repair; if not, update and return to step S32.

[0043] In this embodiment, the inertia weight It is dynamic and adopts a linear decreasing weight strategy. The inertia weight after updating in step S33 is The calculation formula is:

[0044] in, represents the initial inertia weight; Indicates the weight when the iteration reaches the maximum number of iteration steps; Indicates the maximum number of iteration steps; Indicates the current iteration step number.

[0045] In this embodiment, the calculation formula of the updated particle velocity in step S34 is:

[0046] in, Represents the updated particle velocity; Represents the particle velocity before updating, i.e. The repair patch of the possible repair solution The volume of the ply layup; and represents the acceleration factor, Represents a random number between 0 and 1; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; represents the individual historical optimal value; Represents the global historical optimal value; Represents the updated inertia weight.

[0047] In this embodiment, the calculation formula of the updated particle position in step S34 is:

[0048] in, Represents the updated particle position; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates the updated particle velocity.

[0049] Embodiment 2: A composite material patching and repair stress optimization system based on a particle swarm algorithm is used to configure and execute the composite material patching and repair stress optimization method based on a particle swarm algorithm in Example 1.

[0050] In this embodiment, the system can be an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. The processor executes the program to implement part or all of the steps of the composite material patching repair stress optimization method based on particle swarm algorithm as described in Example 1.

[0051] In this embodiment, the electronic device may include: a processor, a memory, a bus and a communication interface. The processor, the communication interface and the memory are connected via a bus. The memory stores a computer program that can be run on the processor. When the processor runs the computer program, it executes part or all of the steps of the composite material patching and repair stress optimization method based on the particle swarm algorithm provided in the aforementioned embodiment 1 of the present application.

[0052] The system in the embodiment of the present invention can also be a computer-readable storage medium, which stores a computer program. When the computer program is executed, some or all steps of the composite material patching and repair stress optimization method based on particle swarm algorithm as described in Example 1 are implemented.

[0053] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0054] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0055] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0056] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0057] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0058] Embodiment 3: On the basis of Example 1, the composite material patching and repair stress optimization method based on particle swarm algorithm proposed in the present invention is used to carry out patching and repair optimization experiments on four-layer fiber ply panels and eight-layer fiber ply panels to verify the technical effect of the present invention.

[0059] In this embodiment, for a four-layer fiber ply board, Figure 4 As shown in the figure, the composite plate is 160mm long, 160mm wide, 1.6mm thick, and contains a damaged area with a radius of 14mm in the center; the left end is fixed and the right end is subjected to a displacement of 2mm. It is found through the stress cloud map that Figure 5As shown in the figure, the stress of the uniform step repair calculation model is mainly concentrated at the junction of the patch and the parent material and in the direction perpendicular to the load. The maximum stress occurs in the adhesive layer, and the stress value of the patch is generally small. The stress distribution of the parent material is uneven, and the stress is mainly concentrated on the parent material at the upper and lower parts where the patch and the parent material intersect. Figure 6 As shown in the figure, the calculation results of the optimized non-uniform step repair show that the maximum stress decreases by 22.97%, the stress level tends to be average, and the stress transfer path is more reasonable than that before optimization. Figure 7 It can be obtained that the objective function has approached the optimal solution in the fourth optimization, indicating that the composite material repair stress optimization method based on particle swarm algorithm proposed in the present invention performs well in terms of convergence speed and solution quality.

[0060] In this embodiment, for an eight-layer fiber ply board, Figure 8 As shown in the figure, the length of the composite plate is 160mm, the width is 160mm, the thickness is 1.6mm, and the center contains a damaged area with a radius of 13mm; the left end is fixed and the right end is subjected to a displacement of 2mm. The fiber laying angle is [0°, ±45°, 90°]s. It is found through the stress cloud map that Fig. 9 As shown in the figure, the stress of the uniform step repair calculation model is mainly concentrated at the junction of the patch and the base material, the stress distribution is mainly concentrated in the bonding area and the horizontal direction of the base material, the maximum stress occurs in the adhesive layer area, and the stress is mainly concentrated on the base material at the upper and lower parts where the patch and the base material intersect. Fig.10 As shown in the figure, the calculation results of the optimized non-uniform step repair show that the maximum stress decreases by 16.61%, the stress level tends to be average, and the stress transfer path is more reasonable than that before optimization. Fig.11 It can be obtained that the optimal solution of the target result area is obtained at the 22nd iteration, which once again proves the effectiveness of the stress optimization method for composite material patching repair based on particle swarm algorithm proposed in the present invention.

[0061] By optimizing the patch repair of four-layer fiber plywood and eight-layer fiber plywood examples, the maximum equivalent stress of the patch in the uniform step-type patch repair model and the optimized model is compared as shown in Table 1.

[0062] Table 1 Optimization results of different layer numbers and layer angles

[0063] The optimal result of the maximum equivalent stress optimization of the four-layer fiber ply laminate under the non-uniform step state is 153.3Mpa, and the maximum equivalent stress decreases by 22.92%; for the eight-layer fiber ply laminate, the optimal result is 404.0Mpa, and the maximum equivalent stress decreases by 16.30%; the new calculation file generated by the optimized design variables is substituted back into the finite element analysis software to calculate the results of 153.340Mpa and 404.635Mpa respectively, as shown in Fig.10 As shown, it is almost the same as the optimization model, which verifies the effectiveness of the composite material patching repair stress optimization method based on particle swarm algorithm proposed in the present invention.

[0064] The experimental results show that compared with the traditional uniform patching repair method, the composite material patching repair stress optimization method based on particle swarm algorithm proposed in the present invention can significantly reduce the maximum stress in the repair area, showing great potential in composite material damage repair in the aerospace field. This achievement not only provides a new strategy for composite material damage repair, but also realizes the automatic search and optimization of repair schemes through the combination of parameterized models and finite element analysis, greatly improving the repair efficiency and reducing costs. Especially for those cases with complex stress distribution and irregular damage shapes, this method can still effectively find the optimal repair plan, further confirming its broad application prospects in practice. In summary, this study not only improves the performance of composite structures, provides important guarantees for safe operation in the aerospace field, but also provides valuable references for the further development and application of composite material repair technology.

[0065] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A composite material patching repair stress optimization method based on particle swarm algorithm, characterized in that: The method comprises the following steps: S1. Construct a three-dimensional model of non-uniform step patching and repair of composite laminates, and use finite element analysis to simulate and obtain the stress distribution and deformation under actual load; S2. According to the stress distribution and deformation under actual load, an optimization model for the repair of non-uniform step-cutting of composite laminates is established; S3. The particle swarm optimization algorithm is used to iteratively solve the optimization model of non-uniform step patching repair of composite laminates, output the best repair plan, and achieve the optimization of minimizing the maximum stress of patching repair of composite materials.

2. The composite material repair stress optimization method based on particle swarm algorithm according to claim 1 is characterized in that: The expression formula of the non-uniform step patching and repair optimization model of the composite laminate in step S2 is: in, represents the optimization objective function; Indicates The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates The equivalent stress value of the non-uniform patching repair optimization model of composite laminates in the possible repair schemes; It represents the maximum equivalent stress value among all possible repair solutions; Indicates all possible repair solutions; Indicates the volume of the non-uniform stepped excavation repair patch; It represents the limiting volume of the non-uniform stepped excavation repair patch; Indicates The repair patch of the possible repair solution The volume of the ply layup; It represents the total number of plies of the composite laminate; Subject to Indicates constraints; min represents the minimization objective function.

3. The composite material repair stress optimization method based on particle swarm algorithm according to claim 2 is characterized in that: The said Equivalent stress value of the optimization model for non-uniform patching repair of composite laminates with possible repair schemes The calculation formula is: in, , and Respectively represent The principal stresses in three directions of the composite laminate repaired by the possible repair schemes, , and Respectively represent The composite laminates repaired by the possible repair solutions are , and Shear stress in the direction normal to the plane.

4. The composite material repair stress optimization method based on particle swarm algorithm according to claim 1 is characterized in that: The step S3 specifically includes the following sub-steps: S31. Initialize the design variable patching parameters and the population parameters of the particle swarm; wherein the design variable patching parameters include the particle position; the population parameters of the particle swarm include the inertia weight and the particle speed; the particles represent possible repair solutions; S32. Calculate the objective function of the optimization model for the repair of non-uniform step-cutting of composite laminates; S33. Taking the objective function as a multi-dimensional search space, and calculating the updated inertia weight in the search space; S34. Based on the updated inertia weight, calculate the updated particle velocity and particle position; S35. Determine whether the preset maximum number of iterations has been reached. If so, the process ends and the best repair plan is output to achieve the optimization of minimizing the maximum stress of the composite material patching repair; if not, update and return to step S32.

5. The composite material repair stress optimization method based on particle swarm algorithm according to claim 4 is characterized in that: The inertia weight after updating in step S33 The calculation formula is: in, represents the initial inertia weight; Indicates the weight when the iteration reaches the maximum number of iteration steps; Indicates the maximum number of iteration steps; Indicates the current iteration step number.

6. The composite material repair stress optimization method based on particle swarm algorithm according to claim 4 is characterized in that: The calculation formula of the updated particle velocity in step S34 is: in, Represents the updated particle velocity; Represents the particle velocity before updating, i.e. The repair patch of the possible repair solution The volume of the ply layup; and represents the acceleration factor, Represents a random number between 0 and 1; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; represents the individual historical optimal value; Represents the global historical optimal value; Represents the updated inertia weight.

7. The composite material repair stress optimization method based on particle swarm algorithm according to claim 4 is characterized in that: The calculation formula for the updated particle position in step S34 is: in, Represents the updated particle position; Represents the particle position before the update, i.e. The repair patch of the possible repair solution The difference parameters between the layer stacking and the next layer; Indicates the updated particle velocity.

8. A composite material patching and repair stress optimization system based on particle swarm algorithm, characterized in that: The method comprises a processor, wherein the processor is used to execute the composite material patching repair stress optimization method based on particle swarm algorithm according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. In response to the computer reading the computer instructions in the storage medium, the computer executes the composite material patching repair stress optimization method based on particle swarm algorithm as described in any one of claims 1 to 7.

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