A composite material actuator winding layer sequence optimization method and system based on a multi-material parameter coupling model

Abstract

The application discloses a composite material actuator winding layer sequence optimization method and system based on a multi-material parameter coupling model, and the method comprises the following steps: obtaining material parameters and working condition data of a composite material actuator; establishing a multi-material parameter coupling model based on the material parameters and the working condition data; defining a variable space and constraint conditions of the multi-material parameter coupling model; based on a predetermined objective function, substituting the defined variable space into the multi-material parameter coupling model for iterative calculation, adjusting the layer parameters to meet the constraint conditions, and outputting an initial optimal layer sequence; performing a test on the initial optimal layer sequence, correcting the material parameters of the multi-material parameter coupling model based on the test result when the test result cannot meet the test requirement, substituting the corrected material parameters into the multi-material parameter coupling model to adjust the layer sequence, and performing a test on the adjusted layer sequence until the layer sequence meets the test requirement.

Description

Technical Field

[0001] This invention relates to the fields of aerospace and engineering equipment technology, and more specifically, to a method and system for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. Background Technology

[0002] In the aerospace and engineering equipment fields, lightweighting of hydraulic systems is an important development direction. For example, reducing the weight of hydraulic systems in aircraft can save fuel, enhance maneuverability, and extend range; in engineering machinery, using lightweight hydraulic cylinders can reduce overturning moments and expand the operating radius; and in hydraulically driven robots, using lightweight hydraulic cylinders can improve dynamic response and endurance. Carbon fiber reinforced resin matrix composites (CFRP), due to their excellent specific strength and environmental adaptability, have become an ideal material for achieving lightweighting of hydraulic systems. Using CFRP to manufacture hydraulic actuators can significantly improve the level of lightweighting and reduce energy consumption.

[0003] However, the field of composite hydraulic actuators is still in its early stages and faces many technical bottlenecks. For example, the all-composite cylinder presents significant technical challenges in terms of inner wall wear resistance and reliable connection with metal end caps, as well as in sealing reliability, friction and wear, and dynamic response. The design and control of fiber winding molding process parameters are crucial for the manufacturing of composite cylinders, and issues such as winding angle optimization, non-geodetic fiber placement, and consistent curing quality have not yet been fully resolved.

[0004] The main challenge in optimizing the winding and stacking sequence of composite material actuators is to achieve lightweighting while meeting all performance requirements. The core objective is to find the optimal winding and stacking sequence to minimize the actuator's weight while simultaneously satisfying technical requirements such as pressure resistance and fatigue life.

[0005] Existing technologies have several drawbacks: First, traditional empirical methods rely on engineers' experience to determine the stacking sequence, lacking scientific basis and making it difficult to guarantee the performance and lightweight requirements of the actuator cylinder. Furthermore, different engineers have different experiences, leading to significant differences in results. Second, single-material parameter optimization methods consider only one material parameter, ignoring material interactions and operating conditions, potentially resulting in results that do not meet actual usage requirements. Third, purely numerical simulation methods rely solely on numerical calculations without combining them with actual experimental verification and correction, leading to deviations between the model and reality and inaccurate optimization results. Fourth, trial-and-error methods involve continuously manufacturing samples for testing, which is costly, time-consuming, and inefficient.

[0006] Therefore, there is an urgent need to further utilize this method to solve the problem of lightweighting composite material actuators while meeting performance requirements. This invention was created to meet this practical need. Summary of the Invention

[0007] The present invention provides a method and system for optimizing the winding and stacking sequence of composite material actuators based on a multi-material parameter coupling model, in order to solve the problem of how to optimize the winding and stacking sequence through a multi-material parameter coupling model.

[0008] To address the aforementioned problems, this invention provides a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. The method includes: Obtain material parameters and operating condition data for composite material actuators; Based on the material parameters and the working condition data, a multi-material parameter coupling model is established; Define the variable space and constraints of the multi-material parameter coupling model; Based on the predetermined objective function, the defined variable space is substituted into the multi-material parameter coupling model for iterative calculation. By adjusting the stacking parameters to meet the constraints, the initial optimal stacking order is output. The initial optimal stacking sequence is tested. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are modified based on the test results. The modified material parameters are then substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements.

[0009] Preferably, the material parameters include the tensile strength and modulus of the fiber, the shear strength and curing shrinkage of the resin matrix, and the bond strength at the fiber-resin interface. The operating data includes the working pressure, fatigue load, and temperature range of the actuator cylinder; The formula for calculating the tensile strength of a fiber is: Where A is the cross-sectional area of ​​the fiber. This represents the maximum breaking load of the fiber. The formula for calculating the modulus of a fiber is: in, This represents the stress increment of the fiber. This represents the strain increment of the fiber; The formula for calculating the shear strength of the resin matrix is: in, To apply shear force, The shear area; The formula for calculating the curing shrinkage rate of the resin matrix is: in, This represents the initial volume of the resin matrix. This represents the final volume of the resin matrix. The formula for calculating the bond strength at the fiber-resin interface is: Where d is the measured fiber diameter and L is the embedding length. For deadhesion force; The formula for calculating the working pressure of the actuator cylinder is: in, For stress range, For the cycle number, This represents the total number of cycles.

[0010] Preferably, establishing a multi-material parameter coupling model based on the material parameters and the operating condition data includes: The material parameters include: longitudinal modulus, transverse modulus, Poisson's ratio, and tensile strength of the fiber; elastic modulus, shear modulus, and yield strength of the resin; and critical strain energy release rate and maximum normal stress of the resin interface. The material parameters are input into the material library of the finite element software to characterize the material behavior of the fiber, resin, and interface. Define the operating parameters of the actuator, apply the internal pressure load to the wall of the laminated structure, and convert the fatigue load spectrum containing stress amplitude and cycle number into time history load steps. A geometric model of the stacked cylinder of the actuator was established using finite element software. Eight-node hexahedral elements were used to simulate the fiber layer and resin layer respectively, and zero-thickness cohesive elements were used to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length. The internal pressure load is applied to the inner surface of the laminated cylinder by fixing the end of the actuator cylinder as a boundary condition. And set up an incremental loading scheme; Solve the static equilibrium equations in and: in, For stress amplitude, It is a volume force vector. For stress tensor, The stiffness tensor or elasticity matrix of the material. For strain tensor, For the displacement gradient tensor, It is the transpose of the displacement gradient tensor; Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer: When the failure index equals 1, the pressure value is recorded as the burst pressure. For fatigue life prediction, sinusoidal cyclic loading is applied to simulate pressure fluctuations, and the maximum and minimum stresses of the laminated structure are extracted to calculate the stress amplitude. ; Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The number of fatigue life cycles is output in real time; among which, These are material constants related to the fatigue properties of materials. In the first i The actual number of cycles applied at the stress level. In the first i The fatigue life or total number of cycles before failure corresponding to the stress level; The material parameters and working condition parameters are coupled to achieve automated iterative calculation in the stacked cylindrical geometric model and output the results; the output results of the finite element model are compared with experimental data to ensure that the error is less than 5%.

[0011] Preferably, defining the variable space and constraints of the multi-material parameter coupling model includes: The variable space is defined as a multidimensional discrete or continuous space containing a stacked angular sequence: in, The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The position of the corresponding angle value in the sequence; The variable space is parameterized using vectors. As an optimization input; the spatial definition includes quantization processing: angle Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms; For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. Influence on stiffness matrix components: in, and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; Total equivalent thickness Angle-weighted average: in, It is a single-layer thickness; The defined constraints include: pressure resistance constraints, fatigue cycle constraints, total equivalent thickness constraints, weight limit constraints, and dimensional tolerance constraints. Set the pressure resistance requirement for the actuator, internal pressure This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in The radius of the actuator cylinder; Pressure resistance constraint requirements , Considering the allowable stress of the material and a safety factor Therefore , Yield strength; Transform the pressure resistance constraint into a variable space inequality: The fatigue cycle constraint is defined based on the SN curve model, given the pressure fluctuation range. Stress amplitude: Define the SN relationship as The S-N relationship describes the fatigue life of a material. N f With the applied stress amplitude The power-law relationship between them is expressed mathematically as follows: ,in A and B It is the fatigue constant of the material; the required fatigue life is... : in, The minimum fatigue life or target fatigue life threshold required by the design; Substituting the stress values, we get: in: Total equivalent thickness constraint: Calculate the total weight using weight limit constraints: in, For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: in, This is the maximum allowable weight in the design of the actuator cylinder structure; Dimensional tolerance constraints target diameter Actual diameter ,Require , The upper limit of tolerance; the dimensional tolerance constraint is converted to:

[0012] Preferably, the step of iteratively calculating the multi-material parameter coupling model by substituting the defined variable space into the predetermined objective function, adjusting the stacking parameters to satisfy the constraints, and outputting the initial optimal stacking order includes: The objective function is to minimize the weight of the actuator cylinder. An optimization algorithm is used to iteratively calculate the stacking order using a multi-material coupling model. If the constraints are not met, the stacking angle or order is adjusted. This process is repeated until an initial optimal stacking order that satisfies all constraints is obtained. The weight calculation of the actuator cylinder is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in Where A is the material density and A is the cross-sectional area of ​​the actuator cylinder. It is the thickness of the i-th layer; Constraints include maximum stress limits, and the maximum stress is output by the multi-material parameter coupling model. The constraint function is defined as: in, To allow for a stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, select the gradient-based optimization method, and set the initial stack angle. and order Random or experience-based generation; define step size parameter. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time. Substitute the parameters into the multi-material parameter coupling model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. and stress distribution; The multi-material parameter coupling model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violations: like If the constraint is satisfied, the iteration terminates, and the output is... and As the initial optimal stacking order; If not satisfied Adjust the stacking angle or order; Calculate the gradient of the objective function and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers; Iterate until convergence or N is reached; set k = k + 1, and repeat the performance calculation and tuning steps; the termination condition is... If k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization.

[0013] Preferably, the step of testing the initial optimal stacking sequence, and when the test results do not meet the test requirements, correcting the material parameters of the multi-material parameter coupling model based on the test results, substituting the corrected material parameters into the multi-material parameter coupling model to adjust the stacking sequence, and testing the adjusted stacking sequence until the stacking sequence meets the test requirements, includes: A prototype was fabricated according to the initial optimal stacking sequence, and pressure, burst, and fatigue tests were conducted. Based on the test results, the material parameters of the multi-material parameter coupling model were corrected, and the stacking sequence was re-optimized until the test results met all test requirements, including: Based on the initial design ply angle sequence and ply thickness Prototypes are prepared using prepreg or dry fiber preforming processes, and curing process parameters are controlled, including temperature. ,pressure ,time The sample geometry follows a preset standard; the environmental temperature and humidity conditions are recorded during the preparation process. , and material batch information; Perform the pressure resistance test sequentially: constant internal pressure To stabilize, burst test: at a constant rate Pressure testing to failure, and axial or circumferential fatigue testing: Stress ratio: frequency Number of loops ; Synchronous acquisition of key response data: compressive deformation Explosion pressure Fatigue life and strain field distribution Record failure modes, including matrix cracking, delamination, fiber breakage, and location coordinates. ; Based on the experimental data, the material constitutive parameters are inverted, and the experimental response residual is defined as follows: in, For the number of data points; For the first Stress data values ​​obtained from experimental observations; The corresponding first-order material constitutive model calculated based on the current material constitutive model. Predicted stress values ​​at each point; This refers to the sampling number or index of the test data points; Initial parameters for the coupled finite element model: in, and These are the initial values ​​for the longitudinal and transverse elastic moduli. This is the initial value of the shear modulus. This is the initial value of Poisson's ratio; Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in This is the sensitivity matrix; in, The damping factor, For parameter increment vectors; The radius of the actuator cylinder; The first calculated by the model i Partial derivative of each stress value; For the first j Partial derivatives of constitutive parameters of a material; Using the corrected material parameters as input, an optimization model for the laminate is established. Objective function: Minimize weight The constraints include: burst pressure. Fatigue life Interlaminar shear stress ; in, This is the minimum burst pressure required by the design. This represents the minimum fatigue life required by the design. The yield strength of the matrix material; The optimal seeding sequence can be solved using genetic algorithms or sequential quadratic programming. Interlaminar stress constraints are calculated using classical laminate theory: in, For transverse shear force, The total thickness; the iterative process continues until all test results meet the tolerance: in, The burst pressure value was measured in the experiment; The burst pressure value required by the design specifications.

[0014] Based on another aspect of the present invention, the present invention provides a composite material actuator winding stacking sequence optimization system based on a multi-material parameter coupling model, the system comprising: The acquisition unit is used to acquire material parameters and operating condition data of the composite material actuator. A model building unit is used to build a multi-material parameter coupling model based on the material parameters and the working condition data. Define the unit, which is used to define the variable space and constraints of the multi-material parameter coupling model; The output unit is used to perform iterative calculations by substituting the defined variable space into the multi-material parameter coupling model based on a predetermined objective function, adjusting the stacking parameters to meet the constraints, and outputting the initial optimal stacking order. The result unit is used to test the initial optimal stacking sequence. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are modified based on the test results, and the modified material parameters are substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements.

[0015] This invention provides a method and system for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. The method includes: acquiring material parameters and operating condition data of the composite material actuator; establishing a multi-material parameter coupling model based on the material parameters and operating condition data; defining the variable space and constraints of the multi-material parameter coupling model; iteratively calculating the defined variable space into the multi-material parameter coupling model based on a predetermined objective function, adjusting the stacking parameters to meet the constraints, and outputting an initial optimal stacking sequence; conducting experiments on the initial optimal stacking sequence; when the experimental results do not meet the experimental requirements, correcting the material parameters of the multi-material parameter coupling model based on the experimental results, and substituting the corrected material parameters into the multi-material parameter coupling model to adjust the stacking sequence, and conducting experiments on the adjusted stacking sequence until the stacking sequence meets the experimental requirements. This invention couples multiple material parameters and operating condition parameters, constructs a model, defines variable space and constraints, performs iterative calculations with the lightest weight as the objective function, and combines experimental parameter correction to finally determine the optimal stacking sequence. The technical solution of this invention first collects multiple material parameters and operating condition data, then constructs a multi-material parameter coupled model, defines the variable space and constraints, iteratively calculates using an optimization algorithm, and finally corrects the results through experiments. The highlight is that by comprehensively considering multiple material parameters and operating condition parameters and continuously correcting them through experiments, the optimal stacking sequence can be found more accurately. Attached Figure Description

[0016] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures: Figure 1 This is a flowchart of a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model according to a preferred embodiment of the present invention. Figure 2 A flowchart illustrating a preferred embodiment of the present invention for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model; and Figure 3 This is a structural diagram of a composite material actuator winding stacking sequence optimization system based on a multi-material parameter coupling model according to a preferred embodiment of the present invention. Detailed Implementation

[0017] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0018] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0019] Figure 1 This is a flowchart of a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model according to a preferred embodiment of the present invention.

[0020] To address the issue of the winding and stacking sequence in composite material actuators, this invention constructs a multi-material parameter coupling model. By comprehensively considering the interrelationships and influences among various material parameters, the winding and stacking sequence is optimized. This invention helps to overcome the bottlenecks in the manufacturing process of composite material hydraulic actuators, improve the performance and quality of actuators, meet the demand for lightweight hydraulic actuators in aerospace, engineering machinery, and other fields, and promote the development of related industries.

[0021] This invention solves the problems of traditional methods, such as considering only one factor and lacking experimental verification. Compared with traditional empirical methods, it is more scientific and accurate; compared with single material parameter optimization methods, it comprehensively considers multiple factors; compared with simple numerical simulation methods, it combines experiments to correct the model; compared with trial and error methods, it greatly reduces costs and time.

[0022] This invention provides a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. This method can significantly reduce the weight of the actuators, improve the performance and efficiency of aviation hydraulic systems, save fuel, enhance maneuverability, and extend range. In engineering machinery, it can reduce overturning moment and expand the operating radius; in hydraulically driven robots, it can significantly improve dynamic response and endurance. The value of this invention lies in overcoming the bottlenecks in the winding process of composite material hydraulic actuators, and its significance lies in promoting weight reduction in aviation hydraulic systems. In real-world scenarios, it can be widely applied in aerospace, engineering machinery, robotics, and other fields.

[0023] like Figure 1 As shown, this invention provides a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. The method includes: Step 101: Obtain the material parameters and operating condition data of the composite material actuator; Preferably, the material parameters include the tensile strength and modulus of the fiber, the shear strength and curing shrinkage of the resin matrix, and the bond strength at the fiber-resin interface. Operating data includes the working pressure, fatigue load, and temperature range of the actuator cylinder; The formula for calculating the tensile strength of a fiber is: Where A is the cross-sectional area of ​​the fiber. This represents the maximum breaking load of the fiber. The formula for calculating the modulus of a fiber is: in, This represents the stress increment of the fiber. This represents the strain increment of the fiber; The formula for calculating the shear strength of the resin matrix is: in, To apply shear force, The shear area; The formula for calculating the curing shrinkage rate of the resin matrix is: in, This represents the initial volume of the resin matrix. This represents the final volume of the resin matrix. The formula for calculating the bond strength at the fiber-resin interface is: Where d is the measured fiber diameter and L is the embedding length. For deadhesion force; The formula for calculating the working pressure of the actuator cylinder is: in, For stress range, For the cycle number, This represents the total number of cycles.

[0024] This invention collects multiple material parameters and operating condition data of composite material actuators, including the tensile strength and modulus of carbon fibers, the shear strength and curing shrinkage of the resin matrix, the bonding strength of the fiber-resin interface, and the working pressure, fatigue load, and temperature range of the actuator.

[0025] This invention employs ASTM D3039 standard for carbon fiber tensile testing. A universal testing machine is used to load a standard specimen at a constant displacement rate, and the load-displacement curve is recorded simultaneously. The maximum breaking load is then derived through a data acquisition system. And the cross-sectional area A. The tensile strength is calculated as follows: Modulus evaluation is based on the stress-strain relationship in the linear elastic region, and the slope is selected for calculation: ,in It is the stress increment. It is the strain increment, and the curve is fitted using the least squares method to reduce the error.

[0026] The resin matrix shear strength test was conducted according to ASTM D5379 Iosipescu method. V-notch specimens were prepared, and shear force was applied in a biaxial loading fixture. Record the failure load; shear area. Calibration by geometric dimensions, formula Calculate shear strength. Curing shrinkage is measured using a thermomechanical analyzer (TMA) to monitor volume changes during curing: initial volume... With final volume Dividing the difference by the initial value yields the volume shrinkage rate. The influence of thermal history is corrected by combining DSC data.

[0027] The fiber-resin interfacial bond strength was evaluated using a single fiber pull-out test. Fibers were embedded in the resin matrix, and an axial force was applied until detachment occurred; the detachment force was then recorded. Interfacial shear strength formula Where d is the measured fiber diameter and L is the embedding length, calibrated by a microscope. The test is repeated three times and the average value is taken to eliminate variation.

[0028] Actuator operating condition data collection is based on sensors and design documents. Real-time recording of working pressure utilizes a piezoelectric pressure sensor, and an integrated data acquisition card stores peak pressure. The fatigue load spectrum is extracted from accelerated testing or historical operating data and converted into equivalent stress amplitude. in, It is the stress range. It is a repeating number. This is the total number of cycles. The temperature range is recorded by arranging a thermocouple array on the surface of the actuator, and the minimum and maximum temperatures are recorded. and Samples are taken every 10 seconds to ensure coverage of the entire operating cycle. All data are aggregated into a database for outlier removal and unit calibration.

[0029] Step 102: Based on material parameters and working condition data, establish a multi-material parameter coupling model; Preferably, a multi-material parameter coupling model is established based on material parameters and operating condition data, including: Material parameters include: longitudinal modulus, transverse modulus, Poisson's ratio, and tensile strength of the fiber; elastic modulus, shear modulus, and yield strength of the resin; and critical strain energy release rate and maximum normal stress at the resin interface. The material parameters are input into the material library of the finite element software to characterize the material behavior of the fiber, resin, and interface. Define the operating parameters of the actuator, apply the internal pressure load to the wall of the laminated structure, and convert the fatigue load spectrum containing stress amplitude and cycle number into time history load steps. A geometric model of the stacked cylinder of the actuator was established using finite element software. Eight-node hexahedral elements were used to simulate the fiber layer and resin layer respectively, and zero-thickness cohesive elements were used to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length. An internal pressure load is applied to the inner surface of the laminated cylinder, with the end of the fixed actuator cylinder serving as the boundary condition. And set up an incremental loading scheme; Solve the static equilibrium equations in and: in, For stress amplitude, It is a volume force vector. For stress tensor, The stiffness tensor or elasticity matrix of the material. For strain tensor, For the displacement gradient tensor, It is the transpose of the displacement gradient tensor; Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer: When the failure index equals 1, the pressure value is recorded as the burst pressure. For fatigue life prediction, sinusoidal cyclic loading is applied to simulate pressure fluctuations, and the maximum and minimum stresses of the laminated structure are extracted to calculate the stress amplitude. ; Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The number of fatigue life cycles is output in real time; among which, These are material constants related to the fatigue properties of materials. In the first i The actual number of cycles applied at the stress level. In the first i The fatigue life or total number of cycles before failure corresponding to the stress level; Material parameters and operating condition parameters are coupled to achieve automated iterative calculations in the geometric model of a stacked cylinder and output the results. The output results of the finite element model are compared with experimental data to ensure that the error is less than 5%.

[0030] This invention couples the material parameters of fibers, resins, and interfaces with the internal pressure and fatigue parameters of the actuator cylinder, and uses the finite element method to construct a multi-material parameter coupled model that can predict the stress distribution, burst pressure, and fatigue life of the laminated structure. The specific implementation method of this step is as follows: Collect detailed parameters of fibers, resins, and interface materials, including the longitudinal modulus of the fibers. lateral modulus Poisson's ratio and tensile strength The elastic modulus of the resin shear modulus and yield strength and interface parameters such as critical strain energy release rate and maximum normal stress These parameters are input into the finite element software through a material library to ensure that the behavior of anisotropic materials is accurately characterized. The operating parameters of the actuator cylinder, including internal pressure, are defined. As a uniformly distributed load applied to the wall, the fatigue load spectrum includes stress amplitude. and number of loops The load needs to be converted into a time history load step. A multilayer cylindrical geometry model was built using commercial finite element software such as Abaqus. The mesh was generated using eight-node hexahedral elements to simulate the fiber layer and resin layer, and zero-thickness cohesive elements to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length to capture local stress concentrations.

[0031] Apply boundary conditions to fix the end of the actuator cylinder and apply a pressure load. On the internal surface, an incremental loading scheme is defined. The static equilibrium equations are solved. in and: Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer. When the index equals 1, the pressure value is recorded as the burst pressure.

[0032] For fatigue life prediction, a sinusoidal cyclic load is applied to simulate pressure fluctuations, and the maximum and minimum stress amplitudes are extracted for calculation. Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The model outputs the number of fatigue life cycles in real time. All parameters are coupled within the model for automated iterative calculation, and the output includes a von Mises stress distribution contour map, critical burst pressure value, and fatigue life curve. The model is validated by comparing it with experimental data to ensure the error is less than 5%.

[0033] Step 103: Define the variable space and constraints of the multi-material parameter coupling model; Preferably, the variable space and constraints of the multi-material parameter coupling model are defined, including: Define the variable space as a multidimensional discrete or continuous space containing stacked angular sequences: in, The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The position of the corresponding angle value in the sequence; The variable space is parameterized using vectors. As an optimization input; the spatial definition includes quantization processing: angle Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms; For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. Influence on stiffness matrix components: in, and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; Total equivalent thickness Angle-weighted average: in, It is a single-layer thickness; The defined constraints include: pressure resistance constraints, fatigue cycle constraints, total equivalent thickness constraints, weight limit constraints, and dimensional tolerance constraints. Set the pressure resistance requirement for the actuator, internal pressure This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in The radius of the actuator cylinder; Pressure resistance constraint requirements , Considering the allowable stress of the material and a safety factor Therefore , Yield strength; Transform the pressure resistance constraint into a variable space inequality: The fatigue cycle constraint is defined based on the SN curve model, given the pressure fluctuation range. Stress amplitude: Define the SN relationship as The S-N relationship describes the fatigue life of a material. N f With the applied stress amplitude The power-law relationship between them is expressed mathematically as follows: ,in A and B It is the fatigue constant of the material; the required fatigue life is... : in, The minimum fatigue life or target fatigue life threshold required by the design; Substituting the stress values, we get: in: Total equivalent thickness constraint: Calculate the total weight using weight limit constraints: in, For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: in, This is the maximum allowable weight in the design of the actuator cylinder structure; Dimensional tolerance constraints target diameter Actual diameter ,Require , The upper limit of tolerance; the dimensional tolerance constraint is converted to:

[0034] This invention defines a variable space for the winding stacking sequence, encompassing stacking angles, number of layers, and sequential combinations. It also sets constraints, including pressure resistance requirements, fatigue cycles, weight limits, and dimensional tolerances for the actuator. The specific implementation method of this step is as follows: The variable space is defined as a multidimensional discrete or continuous space containing stacked angular sequences: Each of them The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The corresponding angle value's position in the sequence. The variable space needs to be parameterized using vectors. As optimization input, computational feasibility and constraint verification are ensured. Spatial definition includes quantization processing: angles. Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms.

[0035] For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. (Angle) Influencing the components of the stiffness matrix, for example: in and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; total equivalent thickness Based on angle-weighted average This represents the thickness of a single layer. This model is used for subsequent constraint calculations and requires input of material parameters such as typical values ​​for carbon fiber and epoxy resin. , .

[0036] The constraint setting first addresses the pressure resistance requirements of the actuator. Internal pressure. This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in Radius of the actuator cylinder; pressure resistance requirements , Considering the allowable stress of the material and a safety factor Therefore , Let the yield strength be the constraint. This constraint is transformed into a variable space inequality: This needs to be verified during optimization.

[0037] The fatigue cycle constraint is based on the SN curve model. Given a pressure fluctuation range... Stress amplitude: SN relationship is defined as , and Let be the material fatigue constant; and be the required fatigue life. Therefore: Substituting the stress values, we get: in: Therefore, the constraint is: Calculate the total weight using weight limit constraints: For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: Dimensional tolerance constraints target diameter Actual diameter ,Require , This is the upper limit of the tolerance; this constraint is transformed into: All constraints are integrated into the optimization framework, and feasible solutions in the variable space are obtained through numerical methods such as sequential quadratic programming.

[0038] Step 104: Based on the predetermined objective function, substitute the defined variable space into the multi-material parameter coupling model for iterative calculation, adjust the stacking parameters to meet the constraints, and output the initial optimal stacking order; Preferably, based on a predetermined objective function, the defined variable space is substituted into the multi-material parameter coupling model for iterative calculation. By adjusting the stacking parameters to satisfy the constraints, the initial optimal stacking sequence is output, including: The objective function is to minimize the weight of the actuator cylinder. An optimization algorithm is used to iteratively calculate the stacking order using a multi-material coupling model. If the constraints are not met, the stacking angle or order is adjusted. This process is repeated until an initial optimal stacking order that satisfies all constraints is obtained. The weight calculation of the actuator cylinder is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in Where A is the material density and A is the cross-sectional area of ​​the actuator cylinder. It is the thickness of the i-th layer; Constraints include maximum stress limits, and the maximum stress is output by the multi-material parameter coupling model. The constraint function is defined as: in, To allow for a stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, select the gradient-based optimization method, and set the initial stack angle. and order Random or experience-based generation; define step size parameter. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time. Substitute the parameters into the multi-material parameter coupling model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. and stress distribution; The multi-material parameter coupling model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violations: like If the constraint is satisfied, the iteration terminates, and the output is... and As the initial optimal stacking order; If not satisfied Adjust the stacking angle or order; Calculate the gradient of the objective function and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers; Iterate until convergence or N is reached; set k = k + 1, and repeat the performance calculation and tuning steps; the termination condition is... If k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization.

[0039] (4) Using the lightest actuator weight as the objective function, the performance of the stacking sequence is iteratively calculated by substituting the optimization algorithm into the coupled model. If the constraints are not met, the stacking angle or sequence is adjusted, and the process is repeated until an initial stacking sequence that satisfies all constraints is obtained. The specific implementation method of this step is as follows: Define the optimization objective function and constraints. The objective function needs to minimize the weight of the actuator cylinder, and the weight calculation is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in A is the material density, and A is the cross-sectional area of ​​the actuator cylinder. This is the thickness of the i-th layer. Constraints include a maximum stress limit to ensure structural safety; the coupled model outputs the maximum stress. The constraint function is defined as: To set the allowable stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, selecting a gradient-based optimization method such as Sequential Quadratic Programming (SQP). Set the initial stack angle. and order Random or experience-based generation; define step size parameter. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time.

[0040] Substitute the values ​​into the coupled model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. And stress distribution. The model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violation: Check if the constraints are satisfied. If If the constraint is satisfied, the iteration terminates, and the output is... and As the initial stacking order. If not satisfied. Adjust the stacking angle or order. Gradient calculation is used for angle adjustment: calculate the gradient of the objective function. and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers.

[0041] Iterate until convergence or N is reached. Set k = k + 1 and repeat the performance calculation and tuning steps; the termination condition is... If k > N, or k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization. The final output satisfies all constraints. and s.

[0042] Step 105: Conduct experiments on the initial optimal stacking sequence. If the experimental results do not meet the experimental requirements, modify the material parameters of the multi-material parameter coupling model based on the experimental results, and substitute the modified material parameters into the multi-material parameter coupling model to adjust the stacking sequence. Then, conduct experiments on the adjusted stacking sequence until the stacking sequence meets the experimental requirements.

[0043] Preferably, the initial optimal stacking sequence is tested. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are corrected based on the test results. The corrected material parameters are then substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements, including: A prototype was fabricated according to the initial optimal stacking sequence, and pressure, burst, and fatigue tests were conducted. Based on the test results, the material parameters of the multi-material parameter coupling model were corrected, and the stacking sequence was re-optimized until the test results met all test requirements, including: Based on the initial design ply angle sequence and ply thickness Prototypes are prepared using prepreg or dry fiber preforming processes, and curing process parameters are controlled, including temperature. ,pressure ,time The sample geometry follows a preset standard; the environmental temperature and humidity conditions are recorded during the preparation process. , and material batch information; Perform the pressure resistance test sequentially: constant internal pressure To stabilize, burst test: at a constant rate Pressure testing to failure, and axial or circumferential fatigue testing: Stress ratio: frequency Number of loops ; Synchronous acquisition of key response data: compressive deformation Explosion pressure Fatigue life and strain field distribution Record failure modes, including matrix cracking, delamination, fiber breakage, and location coordinates. ; Based on the experimental data, the material constitutive parameters are inverted, and the experimental response residual is defined as follows: in, For the number of data points; For the first Stress data values ​​obtained from experimental observations; The corresponding first-order material constitutive model calculated based on the current material constitutive model. Predicted stress values ​​at each point; This is the sampling number or index of the test data points (values ​​range from 1 to m); Initial parameters for the coupled finite element model: in, and These are the initial values ​​for the longitudinal and transverse elastic moduli. This is the initial value of the shear modulus. This is the initial value of Poisson's ratio; Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in This is the sensitivity matrix; in, The damping factor, For parameter increment vectors; The radius of the actuator cylinder; The first calculated by the model i Partial derivative of each stress value; For the first j The partial derivative (or change) of a material constitutive parameter. Using the corrected material parameters as input, an optimization model for the laminate is established. Objective function: Minimize weight The constraints include: burst pressure. Fatigue life Interlaminar shear stress ; in, This is the minimum burst pressure required by the design (or the specified burst pressure value). This is the minimum fatigue life required by the design (or the specified burst pressure value). The yield strength of the matrix material; The optimal seeding sequence can be solved using genetic algorithms or sequential quadratic programming. Interlaminar stress constraints are calculated using classical laminate theory: in, For transverse shear force, The total thickness; the iterative process continues until all test results meet the tolerance: in, The burst pressure value was measured in the experiment; The burst pressure value required by the design specifications.

[0044] This invention involves fabricating specimens or prototypes according to the initial layering sequence, conducting pressure resistance, burst, and fatigue tests, and revising the material parameters of the coupled model based on the test results. The layering sequence is then re-optimized until the test results meet all technical requirements. The specific implementation method of this step is as follows: Based on the initial design ply angle sequence and ply thickness Standard samples or small prototypes are prepared using prepreg or dry fiber preforming processes. Strict control of curing process parameters (temperature) is essential. ,pressure ,time To ensure good interlayer bonding and complete resin curing, the specimen geometry strictly adheres to standards such as ASTM D3039 (tensile) and ASTM D3410 (compression). Ambient temperature and humidity conditions must be recorded during the preparation process. , (and material batch information.)

[0045] This invention sequentially performs a pressure resistance test (constant internal pressure) To stabilize), blasting test (at a constant rate) (Pressure to failure) and axial or circumferential fatigue tests (stress ratio: frequency Number of loops Synchronously collect key response data: compressive deformation. Explosion pressure Fatigue life and strain field distribution Record the failure mode (matrix cracking, delamination, fiber fracture) and its location coordinates. .

[0046] Material constitutive parameters are inverted based on experimental data. Experimental response residuals are defined as follows: in The number of data points. Input initial parameters for the coupled finite element model (e.g., Abaqus / Standard): Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in Sensitivity matrix: The damping factor, For parameter increment vectors.

[0047] This invention uses modified material parameters As input, a laminate optimization model is established. The objective function is to minimize the weight. The constraints include: burst pressure. Fatigue life Interlaminar shear stress The optimal seeding sequence is solved using a genetic algorithm or Sequence Quadratic Programming (SQP). Interlaminar stress constraints are calculated using classical laminate theory (CLT): in For transverse shear force, This represents the total thickness. The iterative process continues until all test results meet the tolerance. This invention discloses a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model. The method includes the following steps: (1) collecting multi-material parameters and working condition data of the composite material actuator, including the tensile strength and modulus of carbon fiber, the shear strength and curing shrinkage of the resin matrix, the bonding strength of the fiber-resin interface, and the working pressure, fatigue load, and temperature range of the actuator. (2) coupling the material parameters of the fiber, resin, and interface with the working condition parameters such as the internal pressure and fatigue of the actuator, and using the finite element method to construct a multi-material parameter coupling model that can predict the stress distribution, burst pressure, and fatigue life of the stacked structure. (3) defining the variable space of the winding stacking sequence, covering the stacking angle, number of layers, and sequence combination, and setting constraints, including the pressure resistance requirements, fatigue cycles, weight limits, and dimensional tolerances of the actuator. (4) using the lightest actuator weight as the objective function, using the optimization algorithm to iteratively calculate the performance of the stacking sequence by substituting it into the coupling model. If the constraints are not met, the stacking angle or sequence is adjusted, and the process is repeated until an initial stacking sequence that satisfies all constraints is obtained. (5) Prepare test specimens or prototypes according to the initial stacking sequence, and conduct pressure resistance, burst, and fatigue tests. Based on the test results, correct the material parameters of the coupled model and re-optimize the stacking sequence until the test results meet all technical requirements. For example... Figure 2 As shown.

[0048] This invention is applied to hydraulic systems in the aerospace and engineering equipment fields, thereby achieving lightweight hydraulic systems, improving aircraft performance and efficiency, reducing overturning moments in engineering machinery, and enhancing the dynamic response and endurance of hydraulically driven robots. This invention utilizes a composite material actuator winding and stacking sequence optimization method based on a multi-material parameter coupling model. This method optimizes the winding and stacking sequence of composite material actuators, solving bottleneck problems in winding processes, sealing technologies, and composite-metal connection structures for composite hydraulic actuators. This results in higher-performance composite material actuators for controlling operations such as opening and closing aircraft doors. This invention has wide applications in aerospace, engineering machinery, and robotics.

[0049] Figure 3 This is a flowchart of a method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model according to a preferred embodiment of the present invention.

[0050] like Figure 3 As shown, this invention provides a composite material actuator winding stacking sequence optimization system based on a multi-material parameter coupling model. The system includes: Acquisition unit 301 is used to acquire material parameters and working condition data of composite material actuator cylinder; Preferably, the material parameters include the tensile strength and modulus of the fiber, the shear strength and curing shrinkage of the resin matrix, and the bond strength at the fiber-resin interface. Operating data includes the working pressure, fatigue load, and temperature range of the actuator cylinder; The formula for calculating the tensile strength of a fiber is: Where A is the cross-sectional area of ​​the fiber. This represents the maximum breaking load of the fiber. The formula for calculating the modulus of a fiber is: in, This represents the stress increment of the fiber. This represents the strain increment of the fiber; The formula for calculating the shear strength of the resin matrix is: in, To apply shear force, The shear area; The formula for calculating the curing shrinkage rate of the resin matrix is: in, This represents the initial volume of the resin matrix. This represents the final volume of the resin matrix. The formula for calculating the bond strength at the fiber-resin interface is: Where d is the measured fiber diameter and L is the embedding length. For deadhesion force; The formula for calculating the working pressure of the actuator cylinder is: in, For stress range, For the cycle number, This represents the total number of cycles.

[0051] Element 302 is established to build a multi-material parameter coupling model based on material parameters and working condition data; Preferably, unit 302 is used to establish a multi-material parameter coupling model based on material parameters and working condition data, including: Material parameters include: longitudinal modulus, transverse modulus, Poisson's ratio, and tensile strength of the fiber; elastic modulus, shear modulus, and yield strength of the resin; and critical strain energy release rate and maximum normal stress at the resin interface. The material parameters are input into the material library of the finite element software to characterize the material behavior of the fiber, resin, and interface. Define the operating parameters of the actuator, apply the internal pressure load to the wall of the laminated structure, and convert the fatigue load spectrum containing stress amplitude and cycle number into time history load steps. A geometric model of the stacked cylinder of the actuator was established using finite element software. Eight-node hexahedral elements were used to simulate the fiber layer and resin layer respectively, and zero-thickness cohesive elements were used to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length. An internal pressure load is applied to the inner surface of the laminated cylinder, with the end of the fixed actuator cylinder serving as the boundary condition. And set up an incremental loading scheme; Solve the static equilibrium equations in and: in, For stress amplitude, It is a volume force vector. For stress tensor, The stiffness tensor or elasticity matrix of the material. For strain tensor, For the displacement gradient tensor, It is the transpose of the displacement gradient tensor; Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer: When the failure index equals 1, the pressure value is recorded as the burst pressure. For fatigue life prediction, sinusoidal cyclic loading is applied to simulate pressure fluctuations, and the maximum and minimum stresses of the laminated structure are extracted to calculate the stress amplitude. ; Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The number of fatigue life cycles is output in real time; among which, These are material constants related to the fatigue properties of materials. In the first i The actual number of cycles applied at the stress level. In the first i The fatigue life or total number of cycles before failure corresponding to the stress level; By coupling material parameters with operating parameters, automation is achieved within the geometric model of a stacked cylinder. Iterative calculations are performed, and the results are output. The output results of the finite element model are compared with the experimental data to ensure that the error is less than 5%.

[0052] Define element 303 to define the variable space and constraints of the multi-material parameter coupling model; Preferably, the definition unit 303 is used to define the variable space and constraints of the multi-material parameter coupling model, including: Define the variable space as a multidimensional discrete or continuous space containing stacked angular sequences: in, The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The position of the corresponding angle value in the sequence; The variable space is parameterized using vectors. As an optimization input; the spatial definition includes quantization processing: angle Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms; For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. Influence on stiffness matrix components: in, and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; Total equivalent thickness Angle-weighted average: in, It is a single-layer thickness; The defined constraints include: pressure resistance constraints, fatigue cycle constraints, total equivalent thickness constraints, weight limit constraints, and dimensional tolerance constraints. Set the pressure resistance requirement for the actuator, internal pressure This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in The radius of the actuator cylinder; Pressure resistance constraint requirements , Considering the allowable stress of the material and a safety factor Therefore , Yield strength; Transform the pressure resistance constraint into a variable space inequality: The fatigue cycle constraint is defined based on the SN curve model, given the pressure fluctuation range. Stress amplitude: Define the SN relationship as The S-N relationship describes the fatigue life of a material. N f With the applied stress amplitude The power-law relationship between them is expressed mathematically as follows: ,in A and B It is the fatigue constant of the material; the required fatigue life is... : in, The minimum fatigue life or target fatigue life threshold required by the design; Substituting the stress values, we get: in: Total equivalent thickness constraint: Calculate the total weight using weight limit constraints: in, For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: in, The weight of the structure (represented by density) ,length L nominal diameter D and total thickness Decision), and the constraints are , This indicates the maximum allowable weight (or maximum mass) limit in the design of this actuator cylinder structure. Dimensional tolerance constraint target diameter. Actual diameter ,Require , The upper limit of tolerance; the dimensional tolerance constraint is converted to:

[0053] Output unit 304 is used to perform iterative calculations by substituting the defined variable space into the multi-material parameter coupling model based on a predetermined objective function, adjusting the stacking parameters to meet the constraint conditions, and outputting the initial optimal stacking sequence. Preferably, the output unit 304 is used to perform iterative calculations based on a predetermined objective function, substituting the defined variable space into a multi-material parameter coupling model, adjusting the stacking parameters to meet the constraints, and outputting the initial optimal stacking sequence, including: The objective function is to minimize the weight of the actuator cylinder. An optimization algorithm is used to iteratively calculate the stacking order using a multi-material coupling model. If the constraints are not met, the stacking angle or order is adjusted. This process is repeated until an initial optimal stacking order that satisfies all constraints is obtained. The weight calculation of the actuator cylinder is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in Where A is the material density and A is the cross-sectional area of ​​the actuator cylinder. It is the thickness of the i-th layer; Constraints include maximum stress limits, and the maximum stress is output by the multi-material parameter coupling model. The constraint function is defined as: in, To allow for a stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, select the gradient-based optimization method, and set the initial stack angle. and order Random or experience-based generation; define step size parameter. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time. Substitute the parameters into the multi-material parameter coupling model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. and stress distribution; The multi-material parameter coupling model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violations: like If the constraint is satisfied, the iteration terminates, and the output is... and As the initial optimal stacking order; If not satisfied Adjust the stacking angle or order; Calculate the gradient of the objective function and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers; Iterate until convergence or N is reached; set k = k + 1, and repeat the performance calculation and tuning steps; the termination condition is... If k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization.

[0054] The result unit 305 is used to test the initial optimal stacking sequence. When the test results cannot meet the test requirements, the material parameters of the multi-material parameter coupling model are corrected based on the test results. The corrected material parameters are then substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements.

[0055] Preferably, the result unit 305 is used to test the initial optimal stacking sequence. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are corrected based on the test results, and the corrected material parameters are substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements, including: A prototype was fabricated according to the initial optimal stacking sequence, and pressure, burst, and fatigue tests were conducted. Based on the test results, the material parameters of the multi-material parameter coupling model were corrected, and the stacking sequence was re-optimized until the test results met all test requirements, including: Based on the initial design ply angle sequence and ply thickness Prototypes are prepared using prepreg or dry fiber preforming processes, and curing process parameters are controlled, including temperature. ,pressure ,time The sample geometry follows a preset standard; the environmental temperature and humidity conditions are recorded during the preparation process. , and material batch information; Perform the pressure resistance test sequentially: constant internal pressure To stabilize, burst test: at a constant rate Pressure testing to failure, and axial or circumferential fatigue testing: Stress ratio: frequency Number of loops ; Synchronous acquisition of key response data: compressive deformation Explosion pressure Fatigue life and strain field distribution Record failure modes, including matrix cracking, delamination, fiber breakage, and location coordinates. ; Based on the experimental data, the material constitutive parameters are inverted, and the experimental response residual is defined as follows: in, Indicates the first k Stress data values ​​obtained from experimental observations (i.e., experimental measurements); This indicates the corresponding first-order material constitutive model calculated based on the current material constitutive model. k The predicted stress value at each point (i.e., the model calculated value); The sampling number or index of the test data point (value range from 1 to...) m ).

[0056] Initial parameters for the coupled finite element model: in, and These are the initial values ​​for the longitudinal and transverse elastic moduli. This is the initial value of the shear modulus. This is the initial value of Poisson's ratio; Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in This is the sensitivity matrix; in, The damping factor, For parameter increment vectors; The radius of the actuator cylinder; The first calculated by the model i Partial derivative of each stress value; For the first j The partial derivative (or change) of a material constitutive parameter. Using the corrected material parameters as input, an optimization model for the laminate is established. Objective function: Minimize weight The constraints include: burst pressure. Fatigue life Interlaminar shear stress ; in, This is the minimum burst pressure required by the design (or the specified burst pressure value). This is the minimum fatigue life required by the design (or the fatigue life specification value). It represents the yield strength of the matrix material.

[0057] The optimal seeding sequence can be solved using genetic algorithms or sequential quadratic programming. Interlaminar stress constraints are calculated using classical laminate theory: in, For transverse shear force, The total thickness; the iterative process continues until all test results meet the tolerance: in, The burst pressure value (or failure pressure test value) is obtained from the test. The burst pressure value (or target failure pressure value) required by the design specifications.

[0058] The preferred embodiment of the present invention provides a composite material actuator winding stacking sequence optimization system based on a multi-material parameter coupling model, which corresponds to the preferred embodiment of the present invention provides a composite material actuator winding stacking sequence optimization method based on a multi-material parameter coupling model. These will not be described in detail here.

[0059] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0060] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0061] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0062] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0063] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0064] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0065] The invention has been described with reference to a few embodiments. However, as will be known to those skilled in the art, and as defined in the appended claims, other embodiments besides those disclosed above fall equivalently within the scope of the invention.

[0066] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless otherwise expressly defined herein. All references to “a / / the [device, component, etc.]” ​​are openly interpreted as at least one instance of the device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein are not necessarily to be performed in the exact order disclosed, unless explicitly stated otherwise.

Claims

1. A method for optimizing the winding stacking sequence of composite material actuators based on a multi-material parameter coupling model, the method comprising: Obtain material parameters and operating condition data for composite material actuators; Based on the material parameters and the working condition data, a multi-material parameter coupling model is established; Define the variable space and constraints of the multi-material parameter coupling model; Based on the predetermined objective function, the defined variable space is substituted into the multi-material parameter coupling model for iterative calculation. By adjusting the stacking parameters to meet the constraints, the initial optimal stacking order is output. The initial optimal stacking sequence is tested. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are modified based on the test results. The modified material parameters are then substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements.

2. The method according to claim 1, wherein the material parameters include the tensile strength and modulus of the fiber, the shear strength and curing shrinkage of the resin matrix, and the bonding strength of the fiber-resin interface; The operating data includes the working pressure, fatigue load, and temperature range of the actuator cylinder; The formula for calculating the tensile strength of a fiber is: in, A is the cross-sectional area of ​​the fiber. This represents the maximum breaking load of the fiber. The formula for calculating the modulus of a fiber is: in, This represents the stress increment of the fiber. This represents the strain increment of the fiber; The formula for calculating the shear strength of the resin matrix is: in, To apply shear force, The shear area; The formula for calculating the curing shrinkage rate of the resin matrix is: in, This represents the initial volume of the resin matrix. This represents the final volume of the resin matrix. The formula for calculating the bond strength at the fiber-resin interface is: Where d is the measured fiber diameter and L is the embedding length. For de-adhesion; The formula for calculating the working pressure of the actuator cylinder is: in, For stress range, For the cycle number, This represents the total number of cycles.

3. The method according to claim 1, wherein establishing a multi-material parameter coupling model based on the material parameters and the working condition data includes: The material parameters include: longitudinal modulus, transverse modulus, Poisson's ratio, and tensile strength of the fiber; elastic modulus, shear modulus, and yield strength of the resin; and critical strain energy release rate and maximum normal stress of the resin interface. The material parameters are input into the material library of the finite element software to characterize the material behavior of the fiber, resin, and interface. Define the operating parameters of the actuator, apply the internal pressure load to the wall of the laminated structure, and convert the fatigue load spectrum containing stress amplitude and cycle number into time history load steps. A geometric model of the stacked cylinder of the actuator was established using finite element software. Eight-node hexahedral elements were used to simulate the fiber layer and resin layer respectively, and zero-thickness cohesive elements were used to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length. The internal pressure load is applied to the inner surface of the laminated cylinder by fixing the end of the actuator cylinder as a boundary condition. And set up an incremental loading scheme; Solve the static equilibrium equations in and: in, The stress amplitude, It is a volume force vector. For stress tensor, The stiffness tensor or elasticity matrix of the material. For strain tensor, Let be the displacement gradient tensor. It is the transpose of the displacement gradient tensor; Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer: When the failure index equals 1, the pressure value is recorded as the burst pressure. For fatigue life prediction, sinusoidal cyclic loading is applied to simulate pressure fluctuations, and the maximum and minimum stresses of the laminated structure are extracted to calculate the stress amplitude. ; Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The number of fatigue life cycles is output in real time; among which, These are material constants related to the fatigue properties of materials. In the first i The actual number of cycles applied at the stress level. In the first i The fatigue life or total number of cycles before failure corresponding to the stress level; The material parameters and working condition parameters are coupled to achieve automated iterative calculation in the stacked cylindrical geometric model and output the results; the output results of the finite element model are compared with experimental data to ensure that the error is less than 5%.

4. The method according to claim 1, wherein defining the variable space and constraints of the multi-material parameter coupling model includes: The variable space is defined as a multidimensional discrete or continuous space containing a stacked angular sequence: in, The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The position of the corresponding angle value in the sequence; The variable space is parameterized using vectors. As an optimization input; the spatial definition includes quantization processing: angle Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms; For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. Influence on stiffness matrix components: in, and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; Total equivalent thickness Angle-weighted average: in, Single-layer thickness; The defined constraints include: pressure resistance constraints, fatigue cycle constraints, total equivalent thickness constraints, weight limit constraints, and dimensional tolerance constraints. Set the pressure resistance requirement for the actuator, internal pressure This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in The radius of the actuator cylinder; Pressure resistance constraint requirements , Considering the allowable stress of the material and a safety factor Therefore , Yield strength; Transform the pressure resistance constraint into a variable space inequality: The fatigue cycle constraint is defined based on the SN curve model, given the pressure fluctuation range. Stress amplitude: Define the SN relationship as The S-N relationship describes the fatigue life of a material. N f With the applied stress amplitude The power-law relationship between them is expressed mathematically as follows: ,in A and B It is the fatigue constant of the material; the required fatigue life is... : in, This refers to the minimum fatigue life or target fatigue life threshold required by the design. Substituting the stress values, we get: in: Total equivalent thickness constraint: Calculate the total weight using weight limit constraints: in, For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: in, This is the maximum allowable weight in the design of the actuator cylinder structure; Dimensional tolerance constraints target diameter Actual diameter ,Require , The upper limit of tolerance; the dimensional tolerance constraint is converted to: 。 5. The method according to claim 1, wherein the step of substituting the defined variable space into the multi-material parameter coupling model for iterative calculation based on a predetermined objective function, adjusting the stacking parameters to satisfy the constraint conditions, and outputting the initial optimal stacking order includes: The objective function is to minimize the weight of the actuator cylinder. An optimization algorithm is used to iteratively calculate the stacking order using a multi-material coupling model. If the constraints are not met, the stacking angle or order is adjusted. This process is repeated until an initial optimal stacking order that satisfies all constraints is obtained. The weight calculation of the actuator cylinder is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in A is the material density, and A is the cross-sectional area of ​​the actuator cylinder. It is the thickness of the i-th layer; Constraints include maximum stress limits, and the maximum stress is output by the multi-material parameter coupling model. The constraint function is defined as: in, To allow for a stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, select the gradient-based optimization method, and set the initial stack angle. and order Generated randomly or based on experience; define step size parameters. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time. Substitute the parameters into the multi-material parameter coupling model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. and stress distribution; The multi-material parameter coupling model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violations: like If the constraint is satisfied, the iteration terminates, and the output is... and As the initial optimal stacking order; If not satisfied Adjust the stacking angle or order; Calculate the gradient of the objective function and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers; Iterate until convergence or N is reached; set k = k + 1, and repeat the performance calculation and tuning steps; the termination condition is... If k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization.

6. The method according to claim 1, wherein the initial optimal stacking sequence is tested, and when the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are modified based on the test results, and the modified material parameters are substituted into the multi-material parameter coupling model to adjust the stacking sequence, and the adjusted stacking sequence is tested until the stacking sequence meets the test requirements, comprising: A prototype was fabricated according to the initial optimal stacking sequence, and pressure, burst, and fatigue tests were conducted. Based on the test results, the material parameters of the multi-material parameter coupling model were corrected, and the stacking sequence was re-optimized until the test results met all test requirements, including: Based on the initial design ply angle sequence and ply thickness Prototypes are prepared using prepreg or dry fiber preforming processes, and curing process parameters are controlled, including temperature. ,pressure ,time The sample geometry follows a preset standard; the environmental temperature and humidity conditions are recorded during the preparation process. , and material batch information; Perform the pressure resistance test sequentially: constant internal pressure To stabilize, burst test: at a constant rate Pressure testing to failure, and axial or circumferential fatigue testing: Stress ratio: frequency Number of loops ; Synchronous acquisition of key response data: compressive deformation Explosion pressure Fatigue life and strain field distribution Record failure modes, including matrix cracking, delamination, fiber breakage, and location coordinates. ; Based on the experimental data, the material constitutive parameters are inverted, and the experimental response residual is defined as follows: in, For the number of data points; For the first Stress data values ​​obtained from experimental observations; The corresponding first part calculated based on the current material constitutive model Predicted stress values ​​at each point; This refers to the sampling number or index of the test data points; Initial parameters for the coupled finite element model: in, and These are the initial values ​​for the longitudinal and transverse elastic moduli. This is the initial value of the shear modulus. This is the initial value of Poisson's ratio; Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in This is the sensitivity matrix; in, The damping factor, For parameter increment vectors; The radius of the actuator cylinder; The first calculated by the model i Partial derivative of each stress value; For the first j Partial derivatives of constitutive parameters of a material; Using the corrected material parameters as input, an optimization model for the laminate is established. Objective function: Minimize weight The constraints include: burst pressure. Fatigue life Interlaminar shear stress ; in, This is the minimum burst pressure required by the design. This represents the minimum fatigue life required by the design. The yield strength of the matrix material; The optimal seeding sequence can be solved using genetic algorithms or sequential quadratic programming. Interlaminar stress constraints are calculated using classical laminate theory: in, For transverse shear force, The total thickness; the iterative process continues until all test results meet the tolerance: in, The burst pressure value was measured in the experiment; The burst pressure value required by the design specifications.

7. A composite material actuator winding stacking sequence optimization system based on a multi-material parameter coupling model, the system comprising: The acquisition unit is used to acquire material parameters and operating condition data of the composite material actuator. A model building unit is used to build a multi-material parameter coupling model based on the material parameters and the working condition data. Define the unit, which is used to define the variable space and constraints of the multi-material parameter coupling model; The output unit is used to perform iterative calculations by substituting the defined variable space into the multi-material parameter coupling model based on a predetermined objective function, adjusting the stacking parameters to meet the constraint conditions, and outputting the initial optimal stacking order. The result unit is used to test the initial optimal stacking sequence. When the test results do not meet the test requirements, the material parameters of the multi-material parameter coupling model are modified based on the test results, and the modified material parameters are substituted into the multi-material parameter coupling model to adjust the stacking sequence. The adjusted stacking sequence is then tested until the stacking sequence meets the test requirements.

8. The system according to claim 7, wherein the material parameters include the tensile strength and modulus of the fiber, the shear strength and curing shrinkage of the resin matrix, and the bond strength at the fiber-resin interface; The operating data includes the working pressure, fatigue load, and temperature range of the actuator cylinder; The formula for calculating the tensile strength of a fiber is: in, A is the cross-sectional area of ​​the fiber. This represents the maximum breaking load of the fiber. The formula for calculating the modulus of a fiber is: in, This represents the stress increment of the fiber. This represents the strain increment of the fiber; The formula for calculating the shear strength of the resin matrix is: in, To apply shear force, The shear area; The formula for calculating the curing shrinkage rate of the resin matrix is: in, This represents the initial volume of the resin matrix. This represents the final volume of the resin matrix. The formula for calculating the bond strength at the fiber-resin interface is: Where d is the measured fiber diameter and L is the embedding length. For de-adhesion; The formula for calculating the working pressure of the actuator cylinder is: in, For stress range, For the cycle number, This represents the total number of cycles.

9. The system according to claim 7, wherein the establishing unit is configured to establish a multi-material parameter coupling model based on the material parameters and the working condition data, comprising: The material parameters include: longitudinal modulus, transverse modulus, Poisson's ratio, and tensile strength of the fiber; elastic modulus, shear modulus, and yield strength of the resin; and critical strain energy release rate and maximum normal stress of the resin interface. The material parameters are input into the material library of the finite element software to characterize the material behavior of the fiber, resin, and interface. Define the operating parameters of the actuator, apply the internal pressure load to the wall of the laminated structure, and convert the fatigue load spectrum containing stress amplitude and cycle number into time history load steps. A geometric model of the stacked cylinder of the actuator was established using finite element software. Eight-node hexahedral elements were used to simulate the fiber layer and resin layer respectively, and zero-thickness cohesive elements were used to simulate the interface. The mesh size was optimized to 0.5 mm based on the feature length. The internal pressure load is applied to the inner surface of the laminated cylinder by fixing the end of the actuator cylinder as a boundary condition. And set up an incremental loading scheme; Solve the static equilibrium equations in and: in, The stress amplitude, It is a volume force vector. For stress tensor, The stiffness tensor or elasticity matrix of the material. For strain tensor, Let be the displacement gradient tensor. It is the transpose of the displacement gradient tensor; Calculate the stress field Based on the stress results, the burst pressure was predicted, and the Tsai-Hill failure criterion was used to assess the failure of each layer: When the failure index equals 1, the pressure value is recorded as the burst pressure. For fatigue life prediction, sinusoidal cyclic loading is applied to simulate pressure fluctuations, and the maximum and minimum stresses of the laminated structure are extracted to calculate the stress amplitude. ; Based on the material SN curve model Combined with Miner's cumulative damage rule Assess the damage, when The number of fatigue life cycles is output in real time; among which, These are material constants related to the fatigue properties of materials. In the first i The actual number of cycles applied at the stress level. In the first i The fatigue life or total number of cycles before failure corresponding to the stress level; The material parameters and working condition parameters are coupled to achieve automated iterative calculation in the stacked cylindrical geometric model and output the results; the output results of the finite element model are compared with experimental data to ensure that the error is less than 5%.

10. The system according to claim 7, wherein the defining unit is used to define the variable space and constraints of the multi-material parameter coupling model, including: The variable space is defined as a multidimensional discrete or continuous space containing a stacked angular sequence: in, The fiber winding angle of the i-th layer is represented by a value in the interval [0, 1]. Or predefined discrete sets such as Number of layers For integer variables, constrained to the minimum number of layers. and maximum number of layers Between, for example Sequential combinations are achieved through sequence indexing. Indicates angular arrangement, where The position of the corresponding angle value in the sequence; The variable space is parameterized using vectors. As an optimization input; the spatial definition includes quantization processing: angle Discretization with a step size of 5°, number of layers Fixed range to reduce search dimensions, order Candidate combinations are generated using enumeration or permutation algorithms; For modeling the stacked angles, the equivalent mechanical properties are calculated using classical lamination theory. Influence on stiffness matrix components: in, and For longitudinal and transverse elastic moduli, Shear modulus Poisson's ratio; Total equivalent thickness Angle-weighted average: in, Single-layer thickness; The defined constraints include: pressure resistance constraints, fatigue cycle constraints, total equivalent thickness constraints, weight limit constraints, and dimensional tolerance constraints. Set the pressure resistance requirement for the actuator, internal pressure This leads to the maximum circumferential stress. Based on the thin-walled pressure vessel model: ,in The radius of the actuator cylinder; Pressure resistance constraint requirements , Considering the allowable stress of the material and a safety factor Therefore , Yield strength; Transform the pressure resistance constraint into a variable space inequality: The fatigue cycle constraint is defined based on the SN curve model, given the pressure fluctuation range. Stress amplitude: Define the SN relationship as The S-N relationship describes the fatigue life of a material. N f With the applied stress amplitude The power-law relationship between them is expressed mathematically as follows: ,in A and B It is the fatigue constant of the material; the required fatigue life is... : in, The minimum fatigue life or target fatigue life threshold required by the design; Substituting the stress values, we get: in: Total equivalent thickness constraint: Calculate the total weight using weight limit constraints: in, For material density, The length of the actuator cylinder For nominal diameter, Total thickness; constraints Therefore: in, The maximum allowable weight in the actuator cylinder structure design; Dimensional tolerance constraints target diameter Actual diameter ,Require , The upper limit of tolerance; the dimensional tolerance constraint is converted to: 。 11. The system according to claim 7, wherein the output unit is configured to perform iterative calculations based on a predetermined objective function, substituting a defined variable space into the multi-material parameter coupling model, adjusting the stacking parameters to satisfy the constraint conditions, and outputting an initial optimal stacking order, comprising: The objective function is to minimize the weight of the actuator cylinder. An optimization algorithm is used to iteratively calculate the stacking order using a multi-material coupling model. If the constraints are not met, the stacking angle or order is adjusted. This process is repeated until an initial optimal stacking order that satisfies all constraints is obtained. The weight calculation of the actuator cylinder is based on the properties and geometric parameters of the laminated material. Assume the laminate consists of n layers, and the angle vector of each layer is: Let the sequential index be s, and the weight function be expressed as: ,in A is the material density, and A is the cross-sectional area of ​​the actuator cylinder. It is the thickness of the i-th layer; Constraints include maximum stress limits, and the maximum stress is output by the multi-material parameter coupling model. The constraint function is defined as: in, To allow for a stress threshold, the optimization problem is formulated as follows: Initialize the optimization algorithm parameters, select the gradient-based optimization method, and set the initial stack angle. and order Generated randomly or based on experience; define step size parameters. and convergence tolerance The iteration counter k is set to 0, and the maximum number of iterations N limits the computation time. Substitute the parameters into the multi-material parameter coupling model to calculate the current performance. In iteration step k, ... and Input the mechanical model of the laminate and calculate its weight. and stress distribution; The multi-material parameter coupling model is based on classical laminated theory, and stress calculation involves the stiffness matrix. : ,in It is the strain vector, solved through finite element analysis. Assess the amount of constraint violations: like If the constraint is satisfied, the iteration terminates, and the output is... and As the initial optimal stacking order; If not satisfied Adjust the stacking angle or order; Calculate the gradient of the objective function and constrained gradient Updated perspective: If the gradient is ineffective, then randomly perturb the order. For example, swapping the positions between layers; Iterate until convergence or N is reached; set k = k + 1, and repeat the performance calculation and tuning steps; the termination condition is... If k > N, and convergence is still not achieved, reinitialize the parameters and restart the optimization.

12. The system according to claim 7, wherein the result unit is configured to test the initial optimal stacking sequence, and when the test results do not meet the test requirements, to modify the material parameters of the multi-material parameter coupling model based on the test results, and to substitute the modified material parameters into the multi-material parameter coupling model to adjust the stacking sequence, and to test the adjusted stacking sequence until the stacking sequence meets the test requirements, comprising: A prototype was fabricated according to the initial optimal stacking sequence, and pressure, burst, and fatigue tests were conducted. Based on the test results, the material parameters of the multi-material parameter coupling model were corrected, and the stacking sequence was re-optimized until the test results met all test requirements, including: Based on the initial design ply angle sequence and ply thickness Prototypes are prepared using prepreg or dry fiber preforming processes, and curing process parameters are controlled, including temperature. ,pressure ,time The sample geometry follows a preset standard; the environmental temperature and humidity conditions are recorded during the preparation process. , and material batch information; Perform the pressure resistance test sequentially: constant internal pressure To stabilize, burst test: at a constant rate Pressure testing to failure, and axial or circumferential fatigue testing: Stress ratio: frequency Number of loops ; Synchronous acquisition of key response data: compressive deformation Explosion pressure Fatigue life and strain field distribution Record failure modes, including matrix cracking, delamination, fiber breakage, and location coordinates. ; Based on the experimental data, the material constitutive parameters are inverted, and the experimental response residual is defined as follows: in, For the number of data points; For the first Stress data values ​​obtained from experimental observations; The corresponding first part calculated based on the current material constitutive model Predicted stress values ​​at each point; This refers to the sampling number or index of the test data points; Initial parameters for the coupled finite element model: in, and These are the initial values ​​for the longitudinal and transverse elastic moduli. This is the initial value of the shear modulus. This is the initial value of Poisson's ratio; Calculate theoretical stress The Levenberg-Marquardt algorithm is used to iteratively update the parameters: in This is the sensitivity matrix; in, The damping factor, For parameter increment vectors; The radius of the actuator cylinder; The first calculated by the model i Partial derivative of each stress value; For the first j Partial derivatives of constitutive parameters of a material; Using the corrected material parameters as input, an optimization model for the laminate is established. Objective function: Minimize weight The constraints include: burst pressure. Fatigue life Interlaminar shear stress ; in, This is the minimum burst pressure required by the design. This represents the minimum fatigue life required by the design. The yield strength of the matrix material; The optimal seeding sequence can be solved using genetic algorithms or sequential quadratic programming. Interlaminar stress constraints are calculated using classical laminate theory: in, For transverse shear force, The total thickness; the iterative process continues until all test results meet the tolerance: in, The burst pressure value was measured in the experiment; The burst pressure value required by the design specifications.

Images