A high-precision material property parameter identification and optimization method based on skeleton

Abstract

The application belongs to the field of material parameter optimization, and particularly relates to a high-precision material characteristic parameter identification and optimization method based on a skeleton, which comprises the following steps: S1: obtaining an initial value of a parameter based on a skeleton biomechanical test; S2: establishing a basic finite element model according to the skeleton biomechanical test, and optimizing the parameter at a local level to obtain an optimized value of the parameter; and S3: establishing a whole bone level finite element model, and optimizing the parameter at a global level to obtain final material characteristic parameters of the skeleton. The method solves the problems of low accuracy and high cost of high-precision material characteristic parameter optimization of the skeleton.

Description

Technical Field

[0001] This invention belongs to the field of material parameter optimization, and in particular relates to a high-precision material property parameter identification and optimization method based on skeleton. Background Technology

[0002] Compared to dummy models, human models possess anatomical structures and biomaterial properties that more closely resemble the human body, resulting in higher biofidelity. They can more accurately simulate human injuries and are increasingly becoming important tools for injury mechanism research in industries such as automotive safety, aerospace, and healthcare. Within human models, the constitutive parameters of the skeleton have a crucial impact on the model's kinematic and mechanical responses, and are key to determining the model's accuracy.

[0003] Currently, methods for identifying constitutive material parameters of skeleton include mathematical analysis based on biomechanical experiments of skeleton. However, skeleton is a complex composite material, and data obtained from limited experimental samples cannot fully represent the real behavior of the entire skeletal system. Furthermore, conducting biomechanical experiments requires expensive technology and equipment, resulting in low parameter accuracy and high cost. Alternatively, numerical simulation calculations can be performed using specific samples to seek the optimal material constitutive parameters by adjusting the parameters. This process of gradually adjusting parameters requires very deep prior experience and theoretical knowledge, carries specific risks, and can lead to inaccuracies in parameter inverse calculation. Summary of the Invention

[0004] This invention provides a method for high-precision material property parameter identification and optimization based on skeleton, which solves the problems of low accuracy and high cost in optimizing high-precision material property parameters of skeleton.

[0005] The basic solution provided by this invention is a high-precision material property parameter identification and optimization method based on skeleton, which specifically includes the following steps: S1: Initial values ​​of parameters are obtained based on skeletal biomechanical tests. These initial values ​​include the initial values ​​of elastic modulus, yield stress, tangent modulus, and effective plastic strain in the elastic stage. S2: Based on the skeletal biomechanical experiments, a basic finite element model is established. The root mean square error of the biomechanical experiment curve and the simulation curve is used as the objective function to optimize the elastic modulus, yield stress, and tangent modulus. At the same time, the effective plastic strain is optimized using the displacement difference at the moment of bone fracture in the biomechanical experiment and simulation as the objective function. S3: Establish an osteopathic finite element model. Statistical analysis is performed on the elastic modulus, yield stress, tangent modulus, and effective plastic strain preliminarily optimized in S2. The analysis results are used as the variable space. The similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, are set as objective functions for multi-objective parameter optimization. The optimized elastic modulus, yield stress, tangent modulus, and effective plastic strain are output as the final bone material property parameters.

[0006] The principles and advantages of this invention are as follows: 1. This invention optimizes data obtained from skeletal biomechanical experiments using both a basic finite element model and an osteopathic finite element model. The basic finite element model optimizes bone material properties at a local level, while the osteopathic finite element model optimizes bone material properties globally based on the parameters output from the basic finite element model. This multi-objective optimization outputs the optimized elastic modulus, yield stress, tangent modulus, and effective plastic strain as bone material properties. This method achieves high-precision, multi-dimensional optimization of bone constitutive material parameters, obtaining highly accurate constitutive parameters that reflect the true mechanical response of the bone at both the global and local levels. Compared to existing methods that optimize parameters through mathematical analysis, this method offers higher accuracy and lower cost, obtaining relatively accurate material properties without requiring expensive technology or equipment. Compared to existing parameter optimization methods that rely solely on numerical simulation, this method does not depend on prior experience, resulting in higher stability in parameter identification and optimization.

[0007] 2. When optimizing the material property parameters of bones at the local level, this invention first identifies the material parameters in the elastic stage, namely elastic modulus, yield stress and tangent modulus, and then identifies the material parameters in the plastic stage, namely effective plastic strain. This ensures the accuracy of the parameter inverse calculation process and avoids overfitting of material curves.

[0008] 3. When optimizing the material property parameters of bones at both the local and global levels, this invention uses the displacement difference at the moment of bone fracture in biomechanical tests and simulations as the objective function, which can ensure the accuracy of the mechanical response and failure response of bone materials at the osteotomy level.

[0009] Preferably, in step S1, the step of obtaining the initial value of the parameter is as follows: S1-1) Convert the force-displacement curves of all biomechanical test specimens into stress-strain curves, and determine the ultimate stress and ultimate strain values ​​of the materials; S1-2) Divide the stress-strain curve into curve segments according to the ultimate stress and ultimate strain values ​​of the material, fit each curve segment, select the curve segment with the closest fit degree to 1, and define the slope of the curve segment as the initial value of the elastic modulus. S1-3) Set the bias curve, and define the stress corresponding to the intersection of the bias curve and the stress-strain curve as the initial value of the yield stress, and the strain corresponding to the intersection as the initial value of the yield strain. S1-4) Calculate the initial value of tangent modulus and the initial value of effective plastic strain based on the initial value of elastic modulus.

[0010] Using mathematical models and formulas, initial values ​​can be provided for the optimization process based on biomechanical experiments. This helps ensure that the subsequent parameter optimization algorithm starts searching for the optimal solution from a relatively ideal position, increasing the possibility of finding the global optimum while reducing unnecessary waste of computational resources. At the same time, the selection of initial values ​​based on mathematical formulas helps to enhance the stability and reliability of the final optimization results. Reliable initial values ​​can ensure that the obtained optimization parameters are closer to the actual situation, thereby enhancing the stability and reliability of the results.

[0011] More preferably, in steps S1-4), the initial value of the tangent modulus is calculated using the following formula:

[0012] In the formula, The initial value of the tangent modulus. This is the initial value of the elastic modulus; The formula for calculating the initial value of effective plastic strain is as follows:

[0013] In the formula, For the initial value of effective plastic strain, This is the ultimate strain value. This represents the initial value of the yield strain.

[0014] Calculating the initial values ​​of parameters using a clear relation can simplify the entire calculation process and reduce reliance on complex experimental data.

[0015] Preferably, step S2 includes: S2-1) Establish the basic finite element model; S2-2) Optimize the elastic modulus, yield stress and tangent modulus, determine the variable space of each optimization parameter according to the initial value, and determine the root mean square error of the biomechanical test curve and simulation curve as the objective function; S2-3) Import the elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test into the basic finite element model in sequence until the root mean square error of the biomechanical test curve and the simulation curve meets the optimization objective. Output the optimization variables that meet the optimization objective and define them as the optimized values ​​of elastic modulus, yield stress and tangent modulus, respectively. S2-4) Optimize the effective plastic strain, determine the variable space of the effective plastic strain based on the initial value of the effective plastic strain, and determine the displacement difference at the moment of bone fracture in biomechanical experiments and simulations as the objective function; S2-5) Import the effective plastic strain obtained from the bone biomechanical test into the basic finite element model until the displacement difference at the bone fracture moment in the biomechanical test and simulation meets the optimization objective. Output the optimization variable that meets the optimization objective and define it as the effective plastic strain optimization value.

[0016] When optimizing material property parameters at the local level, the optimization is completed in two stages. In the first stage, the optimization focuses on the elastic modulus, yield stress, and tangent modulus. The variable space is determined based on the initial values ​​of each parameter, and the root mean square error between the biomechanical experimental curve and the simulation curve is used as the objective function. Experimental data is imported into the basic finite element model and continuously adjusted until the preset optimization objective is met, ultimately obtaining accurate material parameters for the elastic stage (optimized values ​​for elastic modulus, yield stress, and tangent modulus). This process ensures the accuracy and reliability of the model under small deformation conditions, laying a solid foundation for subsequent analysis. The second stage focuses on identifying the key parameter of the plastic stage—effective plastic strain. The variable space is determined based on the initial value of the effective plastic strain, and the displacement difference at the moment of bone fracture in biomechanical experiments and simulations is used as the objective function for optimization. Iterative adjustments are made until the optimization objective is achieved, and the optimized value of the effective plastic strain is output. This method enables the model to more accurately capture the behavioral characteristics of bone materials during large deformation or failure stages, thereby improving the overall realism of the simulation.

[0017] This phased optimization method accurately identifies key material parameters at different stages of mechanical behavior while effectively preventing overfitting during the stress-strain curve fitting process. This strategy not only ensures high accuracy in the parameter inverse calculation process but also enhances the model's simplicity and generalization ability, making it more suitable for practical engineering applications and scientific research.

[0018] More preferably, in step S2-2), when optimizing the elastic modulus, yield stress, and tangent modulus, the variable space is the elastic modulus. , Yield stress , Tangent modulus , ,in, This is the initial value of the elastic modulus. The initial value of the yield stress. The initial value is the tangent modulus; in steps S2-4), when optimizing the effective plastic strain, the variable space is the effective plastic strain. , ,in, This represents the initial value of the effective plastic strain.

[0019] Determining the variable space of optimization variables based on the initial values ​​of the parameters provides a more reasonable and reliable optimization range for the optimization process, reducing the risk of overfitting. Appropriate variable space settings can help avoid the model from overfitting to a specific dataset; it also avoids blindly searching within the entire possible parameter space, thereby greatly improving optimization efficiency. Using their unique initial values ​​to set the variable space allows for more precise and personalized adjustments for each sample, resulting in optimization results that are more in line with the actual situation.

[0020] More preferably, step S3 includes: S3-1) Establish an osteopathic finite element model; S3-2) Optimize the elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the variable space of each optimization parameter based on the optimized values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, as the objective function. S3-3) The elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test are sequentially imported into the osteopathic finite element model until the optimization objective is met. The optimization variables that meet the optimization objective are output and defined as the optimal values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain, respectively.

[0021] By utilizing the key parameters such as elastic modulus, yield stress, tangent modulus, and effective plastic strain optimized in step S2, and combining them with biomechanical experimental data, a more accurate osteopathic-level finite element model is established, ensuring the accuracy and reliability of the model's initial state. Based on the osteopathic-level model, comprehensive parameter optimization is performed to improve the model's performance at a macroscopic level. By simultaneously adjusting multiple key parameters, the mechanical response of the bone under different loading conditions can be captured more comprehensively, thereby improving the overall performance of the model. The similarity score between biomechanical experimental curves and simulation curves, as well as the displacement difference at the moment of bone fracture in actual and simulated conditions, are used as dual objective functions to achieve more comprehensive and accurate optimization. Attached Figure Description

[0022] Figure 1 This is a flowchart of the present invention; Figure 2 This is a flowchart of step 2 of the present invention; Figure 3 This is a flowchart of step 3 of the present invention. Detailed Implementation

[0023] The following detailed description illustrates the specific implementation method: The specific implementation process is as follows: (See details) Figures 1 to 3 A high-precision material property parameter identification and optimization method based on skeleton, specifically including the following steps: S1: Initial values ​​of parameters are obtained based on skeletal biomechanical experiments, including the initial value of the elastic modulus in the elastic phase. Initial value of yield stress Initial value of tangent modulus and initial value of effective plastic strain ; In step S1, the steps for obtaining the initial values ​​of the parameters are as follows: S1-1) Convert the force-displacement curves of all biomechanical test specimens into stress-strain curves and determine the ultimate stress value of the material. Ultimate strain value ; Stress transformation formula:

[0024] In the formula, The applied force is obtained by the force sensor during the three-point bend test. The distance between the two support points in the three-point bend test. The width of the sample. The height of the sample; Strain conversion formula:

[0025] In the formula, The displacement of the loading point is obtained by the displacement sensor in the three-point bend test. The distance between the two support points in the three-point bend test. This represents the height of the sample.

[0026] The highest point on the stress-strain curve is the material failure point, and the stress value corresponding to this failure point is the ultimate stress value. The corresponding strain value is the ultimate strain value. ; In this embodiment, 573 three-point bending tests were conducted on femoral specimens with a diameter of 12mm × 2mm × 0.5mm, resulting in 573 test curves. The ultimate stress and ultimate strain values ​​of each curve were then extracted.

[0027] S1-2) Divide the stress-strain curve into curve segments according to the ultimate stress and ultimate strain values ​​of the material, fit each curve segment, select the curve segment with the closest fit degree to 1, and define the slope of the curve segment as the initial value of the elastic modulus. In this embodiment, the stress-strain curve is divided into 15 segments with a window width of 30% of the ultimate stress value and a step size of 5% of the ultimate stress value; The function performs a univariate linear regression fit on each curve segment; outputs the intercept and regression coefficients from the regression model via commands; and uses the coefficient of determination to measure the goodness of fit, selecting the fitted curve segment with the coefficient of determination closest to 1, and taking the slope of this curve segment as the initial value of the elastic modulus. ; S1-3) Set an offset curve, and define the stress corresponding to the intersection of the offset curve and the stress-strain curve as the initial value of the yield stress. The strain corresponding to the intersection point is defined as the initial value of the yield strain. ; The curve segment selected in S1-2) is defined as the zero strain point at its intersection with the horizontal axis (strain axis), i.e., the origin of the stress-strain curve coordinate system is shifted to this point; the selected curve segment is offset by 0.0069%, and the offset curve is defined as the offset curve; the stress corresponding to the intersection of the offset curve and the stress-strain curve is defined as the initial yield stress. The corresponding strain is defined as the initial value of the yield strain. .

[0028] The expression for the bias curve is as follows:

[0029] In the formula, For the bias curve, This is the initial value of the elastic modulus. This is the fitted curve segment.

[0030] S1-4) Calculate the initial value of the tangent modulus and the initial value of the effective plastic strain based on the initial value of the elastic modulus; in step S1-4), the formula for calculating the initial value of the tangent modulus is as follows:

[0031] In the formula, The initial value of the tangent modulus. This is the initial value of the elastic modulus; The formula for calculating the initial value of effective plastic strain is as follows:

[0032] In the formula, For the initial value of effective plastic strain, This is the ultimate strain value. This represents the initial value of the yield strain.

[0033] In this embodiment, a total of 573 tests were conducted. Statistical analysis of the initial values ​​obtained from each test yielded an average initial value of 14.4 GPa for the overall elastic modulus, an average initial value of 92.67 MPa for the yield stress, an average initial value of 0.72 GPa for the tangent modulus, and an average initial value of 1.71% for the effective plastic strain.

[0034] S2: Based on the skeletal biomechanical experiments, a basic finite element model is established. The root mean square error of the biomechanical experiment curve and the simulation curve is used as the objective function to optimize the elastic modulus, yield stress, and tangent modulus. At the same time, the effective plastic strain is optimized using the displacement difference at the moment of bone fracture in the biomechanical experiment and simulation as the objective function. S2-1) Establish the basic finite element model; Measure the width at the middle and both ends of each sample. , , ) and thickness ( , , ), and the length of the sample ( The positions of the four middle nodes are determined by the width and thickness of the sample's center, and the positions of the eight nodes at both ends are determined by the width and thickness of the samples at both ends. The sample is then divided into two equal parts, left and right, from the middle; taking the right side as an example. and between, , The dimensional changes between the elements are interpolated using a linear function to achieve a smooth linear transition in the mesh, resulting in a mesh element division with 9 nodes in the thickness direction, 17 nodes in the width direction, and 97 nodes in the length direction. The construction of the sample on the left is similar, ultimately forming a 20-sided polyhedron model similar in size and shape to the actual sample. The sample uses... A bilinear elastoplastic material constitutive model (MAT_PIECEWISE_LINEAR_PLASTICITYA) is used. The support shafts at both ends of the specimen and the impact head in the middle are simulated as rigid walls, with a defined contact point and a friction coefficient of 0.05. Acceleration is applied to the impact head to simulate actual loading. The displacement of the impact head and the time history curves of its contact force with the specimen are output at the same sampling frequency as in the experiment, thus obtaining the force-displacement curves of the numerical simulation, ensuring that the boundary conditions and output results of the finite element model are consistent with the experimental results.

[0035] S2-2) Optimize the elastic modulus, yield stress and tangent modulus, determine the variable space of each optimization parameter according to the initial value, and determine the root mean square error of the biomechanical test curve and simulation curve as the objective function; In step S2-2), when optimizing the elastic modulus, yield stress, and tangent modulus, the variable space is the elastic modulus. , Yield stress , Tangent modulus , ,in, This is the initial value of the elastic modulus. The initial value of the yield stress. The initial value for the tangent modulus is used. In this step, the material failure range is not set, i.e., the effective plastic strain is not defined. The objective function expression in S2-2 is as follows:

[0036] In the formula, This represents the root mean square error of the biomechanical test curve and the simulation curve. These are the sampling point values ​​in the stress-strain curve during the simulation. These are the sampling point values ​​in the stress-strain curve during biomechanical testing. It represents the number of sampling points.

[0037] S2-3) Import the elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test into the basic finite element model in sequence until the root mean square error of the biomechanical test curve and the simulation curve meets the optimization objective. Output the optimization variables that meet the optimization objective and define them as the optimized values ​​of elastic modulus, yield stress and tangent modulus, respectively. Specifically, such as Figure 2 As shown, the i-th elastic modulus E, the i-th yield stress SIGY, and the i-th tangent modulus ETAN are imported into the basic finite element model, and simulation is performed using the DYNA main program; when the optimization objective is met... When this happens, the optimized value of the elastic modulus is output. Optimal yield stress value and tangent modulus optimization value If the condition is not met, then i = i + 1, and import new parameters until all parameters within the specified space are traversed.

[0038] In this embodiment, based on the initial values ​​obtained in step S1, simulations and benchmarking and optimization of the experimental curves were performed on 573 experiments in sequence to obtain optimized values ​​of material parameters corresponding to each experimental curve. Statistical analysis of the optimized values ​​obtained in step S2 revealed that the statistical average of the optimized elastic modulus was 12.06 Pa, the statistical average of the optimized yield stress was 78.13 MPa, the statistical average of the optimized effective plastic strain was 1.99%, and the statistical average of the optimized tangent modulus was 0.59 GPa.

[0039] S2-4) Optimize the effective plastic strain, determine the variable space of the effective plastic strain based on the initial value of the effective plastic strain, and determine the displacement difference at the moment of bone fracture in biomechanical experiments and simulations as the objective function; In steps S2-4), when optimizing the effective plastic strain, the variable space is the effective plastic strain. , ,in, The initial value of the effective plastic strain is used; during the optimization of the effective plastic strain, the elastic modulus, yield stress, and tangent modulus are the optimized values ​​of the elastic modulus output in step S2-3). Optimal yield stress value and tangent modulus optimization value That is, elastic modulus Yield stress Tangent modulus ; The objective function expression in S2-4 is as follows:

[0040] In the formula, This represents the displacement difference at the moment of bone fracture in biomechanical experiments and simulations. This represents the failure displacement at the moment of bone fracture in the simulation. This represents the failure displacement at the moment of bone fracture during a biomechanical test.

[0041] S2-5) Import the effective plastic strain obtained from the bone biomechanical test into the basic finite element model until the displacement difference at the bone fracture moment in the biomechanical test and simulation meets the optimization objective. Output the optimization variable that meets the optimization objective and define it as the effective plastic strain optimization value.

[0042] Specifically, such as Figure 2 As shown, the j-th effective plastic strain FS is imported into the basic finite element model and simulated using the DYNA main program. When the condition is met, the effective plastic strain that satisfies the optimization objective is output as the optimized value of the effective plastic strain. If the condition is not met, then j = j + 1, and import new parameters until all parameters within the specified space are traversed.

[0043] S3: Establish an osteopathic finite element model. Statistical analysis is performed on the elastic modulus, yield stress, tangent modulus, and effective plastic strain preliminarily optimized in S2. The analysis results are used as the variable space. The similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, are set as objective functions for multi-objective parameter optimization. The optimized elastic modulus, yield stress, tangent modulus, and effective plastic strain are output as the final bone material property parameters.

[0044] Step S3 includes: S3-1) Establish an osteopathic finite element model; Bones give The MAT_PIECEWISE_LINEAR_PLASTICITYA bilinear elastoplastic material constitutive model uses rigid walls to simulate the support axes at both ends of the skeleton and the impact head in the middle, defining the contact with the specimen and setting the friction coefficient to 0.1. BOUNDAR_SPC restricts the displacement at both ends of the skeleton, through BOUNDARY_PRESCRIBED_MOTION_RIGID(Vel) sets the loading speed of the impactor to be consistent with that of the osteopathic test. It outputs the time history curves of the impactor's displacement and its contact force with the specimen at the same sampling frequency as the test, thus obtaining the force-displacement curves for numerical simulation.

[0045] S3-2) Optimize the elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the variable space of each optimization parameter based on the optimized values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, as the objective function. When defining the variable space, the material constitutive parameters are obtained from biomechanical experiments and simulations in step S2. Statistical analysis is then performed to obtain the mean and standard deviation. The mean ± standard deviation is defined as the variable space, and the variable space = [mean - standard deviation, mean + standard deviation].

[0046] S3-3) The elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test are sequentially imported into the osteopathic finite element model until the optimization objective is met. The optimization variables that meet the optimization objective are output and defined as the optimal values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain, respectively.

[0047] Specifically, such as Figure 3As shown, the k-th elastic modulus E, k-th yield stress SIGY, k-th tangent modulus ETAN, and k-th effective plastic strain FS are imported into the osteopathic finite element model and simulated using the DYNA main program. If the optimization objective in S3-3) is satisfied, the optimized elastic modulus E, yield stress SIGY, tangent modulus ETAN, and effective plastic strain are output as the final value of the elastic modulus. final value of yield stress tangent modulus final value and the final value of effective plastic strain If the condition is not met, then k=k+1 is the input of other parameter values ​​in the variable space, and the process continues until all parameters in the variable space are traversed.

[0048] In this embodiment, the final value of the elastic modulus The final yield stress is 17.3 GPa. The final value of the tangent modulus is 89.6 MPa. The final effective plastic strain is 1.22 GPa. It is 1.4%.

[0049] The above are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A high-precision material property parameter identification and optimization method based on skeleton, characterized in that, Specifically, the following steps are included: S1: Initial values ​​of parameters are obtained based on skeletal biomechanical tests. These initial values ​​include the initial values ​​of elastic modulus, yield stress, tangent modulus, and effective plastic strain in the elastic stage. S2: Based on the skeletal biomechanical experiments, a basic finite element model is established. The root mean square error of the biomechanical experiment curve and the simulation curve is used as the objective function to optimize the elastic modulus, yield stress, and tangent modulus. At the same time, the effective plastic strain is optimized using the displacement difference at the moment of bone fracture in the biomechanical experiment and simulation as the objective function. S3: Establish an osteopathic finite element model. Statistical analysis is performed on the elastic modulus, yield stress, tangent modulus, and effective plastic strain preliminarily optimized in S2. The analysis results are used as the variable space. The similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, are set as objective functions for multi-objective parameter optimization. The optimized elastic modulus, yield stress, tangent modulus, and effective plastic strain are output as the final bone material property parameters.

2. The method for high-precision material property parameter identification and optimization based on skeleton according to claim 1, characterized in that: In step S1, the steps for obtaining the initial values ​​of the parameters are as follows: S1-1) Convert the force-displacement curves of all biomechanical test specimens into stress-strain curves, and determine the ultimate stress and ultimate strain values ​​of the materials; S1-2) Divide the stress-strain curve into curve segments according to the ultimate stress and ultimate strain values ​​of the material, fit each curve segment, select the curve segment with the closest fit degree to 1, and define the slope of the curve segment as the initial value of the elastic modulus. S1-3) Set the bias curve, and define the stress corresponding to the intersection of the bias curve and the stress-strain curve as the initial value of the yield stress, and the strain corresponding to the intersection as the initial value of the yield strain. S1-4) Calculate the initial value of tangent modulus and the initial value of effective plastic strain based on the initial value of elastic modulus.

3. The high-precision material property parameter identification and optimization method based on skeleton according to claim 2, characterized in that: In steps S1-4), the initial value of the tangent modulus is calculated using the following formula: In the formula, The initial value of the tangent modulus. This is the initial value of the elastic modulus; The formula for calculating the initial value of effective plastic strain is as follows: In the formula, The initial value of effective plastic strain, This is the ultimate strain value. This represents the initial value of the yield strain.

4. The method for high-precision material property parameter identification and optimization based on skeleton according to claim 1, characterized in that: Step S2 includes: S2-1) Establish the basic finite element model; S2-2) Optimize the elastic modulus, yield stress and tangent modulus, determine the variable space of each optimization parameter according to the initial value, and determine the root mean square error of the biomechanical test curve and simulation curve as the objective function; S2-3) Import the elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test into the basic finite element model in sequence until the root mean square error of the biomechanical test curve and the simulation curve meets the optimization objective. Output the optimization variables that meet the optimization objective and define them as the optimized values ​​of elastic modulus, yield stress and tangent modulus, respectively. S2-4) Optimize the effective plastic strain, determine the variable space of the effective plastic strain based on the initial value of the effective plastic strain, and determine the displacement difference at the moment of bone fracture in biomechanical experiments and simulations as the objective function; S2-5) Import the effective plastic strain obtained from the bone biomechanical test into the basic finite element model until the displacement difference at the bone fracture moment in the biomechanical test and simulation meets the optimization objective. Output the optimization variable that meets the optimization objective and define it as the effective plastic strain optimization value.

5. The high-precision material property parameter identification and optimization method based on skeleton according to claim 4, characterized in that: In step S2-2), when optimizing the elastic modulus, yield stress, and tangent modulus, the variable space is the elastic modulus. , Yield stress , Tangent modulus , ,in, This is the initial value of the elastic modulus. The initial value of the yield stress. The initial value is the tangent modulus; in steps S2-4), when optimizing the effective plastic strain, the variable space is the effective plastic strain. , ,in, This represents the initial value of the effective plastic strain.

6. The high-precision material property parameter identification and optimization method based on skeleton according to claim 4, characterized in that: Step S3 includes: S3-1) Establish an osteopathic finite element model; S3-2) Optimize the elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the variable space of each optimization parameter based on the optimized values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain. Determine the similarity score between the biomechanical test curve and the simulation curve, as well as the displacement difference at the moment of bone fracture in the biomechanical test and simulation, as the objective function. S3-3) The elastic modulus, yield stress and tangent modulus obtained from the bone biomechanical test are sequentially imported into the osteopathic finite element model until the optimization objective is met. The optimization variables that meet the optimization objective are output and defined as the optimal values ​​of elastic modulus, yield stress, tangent modulus and effective plastic strain, respectively.

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