Material parameter identification method and system for 3D printing structure

Abstract

The invention relates to the technical field of material parameter identification, and provides a material parameter identification method and system for a 3D printing structure, and the method comprises the following steps: S1, obtaining a three-dimensional model of a to-be-detected structure; s2, giving initial material parameters to the three-dimensional model, and performing finite element modal analysis on the three-dimensional model to obtain a multi-order modal shape; s3, obtaining a structural vibration sensitive area on the three-dimensional model according to the multi-order modal shape; s4, enabling the structure vibration sensitive area to correspond to the to-be-detected structure, and forming a detection area. According to the material parameter identification method and system of the 3D printing structure, the vibration test result of the structure is combined with the finite element analysis result of the structure according to the modal superposition attribute of the structure vibration, the material parameters of the 3D printing structure are identified by adopting an optimization method, and the method and system are not influenced by the change of the material parameters of the 3D printing structure; and material parameter identification can be directly carried out on the structure after 3D printing forming.

Description

Technical Field

[0001] The present invention relates to the technical field of material parameter identification, and in particular to a material parameter identification method and system for a 3D printing structure. Background Art

[0002] 3D printing technology has become an important tool in the field of materials science and engineering, and is currently widely used in manufacturing, medical, aerospace and other fields. 3D printing technology can create various structures for scientific research. For the study of the dynamic characteristics of structural vibration, it is necessary to know the material parameters of the structure (Young's modulus and Poisson's ratio). For the ship's gate rudder structure created by 3D printing, in order to study the hydrodynamic performance of the gate rudder, it is very important to easily and quickly identify the material parameters of the gate rudder structure in experimental research and numerical simulation comparative research. At the same time, the simple, fast and correct identification of the material parameters of the 3D printed structure can help companies optimize product design, reduce waste and reduce production costs, which is of great significance for promoting innovation and sustainable development in the manufacturing industry.

[0003] However, traditional material identification methods cannot quickly, accurately, and efficiently identify 3D printing materials. Existing 3D printing material identification technologies usually require the use of advanced sensors, imaging equipment, and computing resources, which results in high costs for technology and equipment. In many application scenarios, the properties of 3D printing materials need to be identified in real time or at high throughput, but existing reverse identification methods are computationally intensive and time-consuming, and often cannot meet these requirements.

[0004] CN118278225A discloses a material vibration SN characteristic identification method based on structural vibration test. By carrying out structural vibration fatigue test of target structure, an experimental structural dynamics model is established, and the vibration test is simulated by the model to obtain the structural stress characteristics of fatigue risk parts, and the structural vibration life analysis is carried out based on the structural stress characteristics to obtain the structural vibration fatigue life. The vibration stress is simulated for each vibration level in different load levels to determine the material vibration SN characteristics. However, the existing 3D printing technology is mainly based on fused deposition molding. After the 3D printing material is melted and solidified, its material properties change greatly, resulting in its material parameters being far from the raw materials. Therefore, the above-mentioned material identification method is not suitable for 3D printing materials. Summary of the invention

[0005] In view of this, the present invention proposes a material parameter identification method and system for a 3D printed structure. According to the modal superposition property of structural vibration, the material parameters of the 3D printed structure are identified by combining the vibration test results of the structure with the finite element analysis results of the structure, and an optimized method is used. The method and system are not affected by changes in the material parameters of the 3D printed structure, and can directly identify the material parameters of the structure after 3D printing.

[0006] The technical solution of the present invention is achieved in this way:

[0007] In one aspect, the present invention provides a method for identifying material parameters of a 3D printed structure, comprising the following steps:

[0008] S1 obtains a three-dimensional model of the structure to be tested;

[0009] S2 assigns initial material parameters to the three-dimensional model and performs finite element modal analysis on it to obtain multi-order modal vibration shapes;

[0010] S3 obtains the structural vibration sensitive area on the three-dimensional model according to the multi-order mode vibration shapes;

[0011] S4 maps the structural vibration sensitive area to the structure to be tested to form a detection area;

[0012] S5 excites the surface of the structure to be tested and collects vibration response data formed in the test area;

[0013] S6 determines the target optimization value based on the vibration response data, and uses the initial material parameters as independent variables to adjust the initial material parameters through the finite element optimization algorithm to obtain the final material property parameters of the structure to be tested.

[0014] On the basis of the above technical solution, preferably, step S2 includes the following steps:

[0015] S21 assigns arbitrary initial value material parameters to the three-dimensional model;

[0016] S22 discretizes the three-dimensional model into a finite element mesh;

[0017] S23 obtains multi-order natural frequencies and corresponding mode vibration shapes of the structure to be tested according to the finite element mesh.

[0018] On the basis of the above technical solution, preferably, step S3 includes the following steps:

[0019] S31 forms vibration mode diagrams of each mode through multiple-order mode vibration modes;

[0020] S32 determines the high displacement area of ​​the three-dimensional model in each mode according to the vibration shape diagram of each mode;

[0021] S33 marks the common high displacement areas of the three-dimensional model in each mode to form the structural vibration sensitive area.

[0022] On the basis of the above technical solution, preferably, in step S6, determining the target optimization value according to the vibration response data comprises the following steps:

[0023] S61 processes the vibration response data to obtain a frequency spectrum;

[0024] S62 determines the natural modal frequencies of the multi-order modal vibration shapes according to the frequency spectrum and uses them as target optimization values.

[0025] On the basis of the above technical solution, preferably, before step S1, it also includes determining the actual density of the structure to be measured, and in step S2, the actual density of the structure to be measured is assigned to the three-dimensional model together with the initial material parameters.

[0026] On the basis of the above technical solution, preferably, the initial value material parameters include Young's modulus and Poisson's ratio.

[0027] Further preferably, in step S6, adjusting the initial material parameters by a finite element optimization algorithm to obtain the final material property parameters of the structure to be tested comprises the following steps:

[0028] S63 sets the objective function based on Young's modulus and Poisson's ratio;

[0029] S64 calculates the gradient of the objective function with respect to Young's modulus and Poisson's ratio;

[0030] S65 updates the parameter vector using the update rule of the gradient descent method;

[0031] S66 repeats steps S64-S65 until the objective function converges;

[0032] After the S67 objective function converges, the final material property parameters of the structure to be tested are obtained.

[0033] On the basis of the above technical solution, preferably, step S7 is further included, in which the final material property parameters are assigned to the three-dimensional model, and finite element modal analysis is performed, and the finite element modal analysis results are compared and verified with the vibration test results of the structure to be tested.

[0034] Further preferably, in step S7, the finite element modal analysis includes free modal analysis and constrained modal analysis.

[0035] On the other hand, the present invention provides a material parameter identification system for a 3D printed structure, comprising a processor, a strain gauge sensor and a data acquisition card, wherein the processor is embedded with the above-mentioned material parameter identification method for a 3D printed structure, the strain gauge sensor is used to be arranged on a detection area of ​​the structure to be tested to collect a vibration signal formed in the detection area, and the data acquisition card is used to convert the vibration signal collected by the strain gauge sensor into vibration response data and transmit it to the processor.

[0036] The material parameter identification method and system of the 3D printing structure of the present invention has the following beneficial effects compared with the prior art:

[0037] (1) Based on the modal superposition properties of structural vibration, the material parameters of the 3D printed structure are identified by combining the vibration test results of the structure with the finite element analysis results of the structure. The method is not affected by the changes in the material parameters of the 3D printed structure and can directly identify the material parameters of the structure after 3D printing. Compared with the existing technology, the method can quickly and efficiently identify the material parameters of the 3D printed structure with higher accuracy.

[0038] (2) Different from the traditional material identification method, the present invention first measures the density of the structure to be tested, and then uses the Young's modulus and Poisson's ratio as independent variables, and derives them according to the target optimization value by the optimization algorithm, thereby determining the Young's modulus and Poisson's ratio of the material parameters other than the density. The Young's modulus and Poisson's ratio are not affected by the changes in the 3D printing material parameters, and can directly identify the material parameters of the structure after 3D printing. In addition, the material parameter identification of the 3D printed structure is not limited to metal materials and non-metal materials, and has a very wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A schematic diagram of the steps of the material parameter identification method of the 3D printing structure of the present invention;

[0041] Figure 2 It is a structural schematic diagram of a door rudder scaled model with a geometric ratio of 1 / 4 in an embodiment of the material parameter identification method of a 3D printing structure of the present invention;

[0042] Figure 3 It is a schematic diagram of the finite element free modal analysis of the door-rudder structure in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0043] Figure 4 A schematic diagram of the installation position of the strain gauge sensor and the position and direction of the hammer excitation force in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0044] Figure 5 A graph showing changes in time signals and frequency spectrum signals obtained by a vibration test in a free state in an embodiment of a material parameter identification method for a 3D printing structure of the present invention;

[0045] Figure 6It is a response surface optimization process and a response surface schematic diagram in an embodiment of a material parameter identification method for a 3D printing structure of the present invention;

[0046] Figure 7 It is a schematic diagram of the modal comparison of the door rudder structure in the free state in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0047] Figure 8 It is a time signal and spectrum signal variation diagram obtained by vibration test under the condition of fixed constraint of the door rudder root in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0048] Fig. 9 It is a schematic diagram of the comparison of the portal rudder structure modes under the condition of the fixed constraint of the portal rudder root in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0049] Fig.10 It is a time signal and spectrum signal change diagram obtained by vibration test after the rudder blade is connected to the rudder shaft and fixed conditions are applied to the end of the rudder shaft in the embodiment of the material parameter identification method of the 3D printing structure of the present invention;

[0050] Fig.11 It is a schematic diagram of the comparison of the door rudder modes after the rudder blade is connected to the rudder shaft and fixed conditions are applied to the end of the rudder shaft in the embodiment of the material parameter identification method of the 3D printing structure of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] like Figure 1-11 As shown, the material parameter identification method of the 3D printed structure of the present invention, according to the modal superposition property of the structural vibration, combines the vibration test results of the structure with the finite element analysis results of the structure, adopts an optimized method to identify the material parameters of the 3D printed structure, and verifies the rationality and correctness of the method, which specifically includes steps S1-S7.

[0053] Before performing step S1, the density of the structure to be measured is also obtained. The density can be directly obtained by obtaining the volume through a model, and the weight can be obtained in the form of load-bearing, and then converted into its actual density.

[0054] Step S1: Obtain a three-dimensional model of the structure to be measured.

[0055] The three-dimensional model of the structure to be tested needs to be drawn before 3D printing. In this step, it is only necessary to import the three-dimensional model of the 3D printed structure. In addition, in order to perform subsequent testing and data collection on the physical structure to be tested, in this step, the structure to be tested needs to be produced by 3D printing, or the printed structure to be tested needs to be used for subsequent data collection.

[0056] Step S2: assigning initial material parameters to the three-dimensional model, and performing finite element modal analysis on it to obtain multi-order modal vibration shapes.

[0057] Before performing finite element optimization, the three-dimensional model needs to be initially set up and its modal vibration shape needs to be calculated. The density of the structure to be measured obtained before step S1 also needs to be used as a parameter of the three-dimensional model to perform finite element simulation for the subsequent optimization process, which specifically includes steps S21-S23.

[0058] Step S21: Assign arbitrary initial value material parameters to the three-dimensional model.

[0059] The initial material parameters include Young's modulus and Poisson's ratio. In this step, the initial Young's modulus and Poisson's ratio need to be set. The initial values ​​can be selected based on empirical data or estimated values. However, this parameter is a variable in subsequent steps, so it does not need to be set accurately, but only needs to be within a reasonable range.

[0060] Step S22: discretize the three-dimensional model into a finite element mesh.

[0061] Divide the three-dimensional model into finite element meshes. The accuracy of the mesh division will affect the accuracy of the calculation results. Then select the appropriate element type (such as tetrahedron or hexahedron) and mesh size to ensure the stability and efficiency of the calculation. In addition, after setting up, you also need to check the quality of the mesh to ensure that there are no elements that are too small or too large to avoid numerical instability. You can use mesh optimization tools (such as automatic mesh generation and correction) to improve the mesh quality.

[0062] Step S23: obtaining multi-order natural frequencies and corresponding mode shapes of the structure to be measured according to the finite element mesh.

[0063] Configure the finite element software for free modal analysis, set the analysis type to "modal analysis", determine the order of analysis, that is, the number of natural frequencies and modal vibration shapes required for calculation. After setting, perform finite element modal analysis to calculate the natural frequencies and corresponding modal vibration shapes of the model. Finally, extract the analysis results to obtain the natural frequencies and vibration shapes of each order mode.

[0064] Step S3: According to the multi-order mode shapes, the structural vibration sensitive area on the three-dimensional model is obtained.

[0065] This step mainly analyzes the vibration shape diagrams of each mode to identify and mark the vibration sensitive areas on the three-dimensional model. The vibration sensitive area is the part of the structure that has a large displacement during vibration and may experience large stress and deformation in actual use. It can be specifically divided into steps S31-S33.

[0066] Step S31: forming a vibration shape diagram of each mode through multiple-order mode vibration shapes.

[0067] First, it is necessary to extract the vibration mode data of each mode, that is, to extract the vibration mode data of each mode from the finite element modal analysis. These data are usually expressed in the form of node displacement, describing the vibration mode of the structure in different modes.

[0068] The extracted vibration mode data is converted into a graphical representation. The displacement distribution under different modes can be directly displayed using color maps or deformation maps. The vibration mode diagram can clearly show the vibration form of the structure under each mode, making it easier to identify high displacement areas.

[0069] Step S32: According to the vibration mode diagrams of each order mode, determine the high displacement area of ​​the three-dimensional model in each order mode.

[0070] The vibration mode diagram of each mode is analyzed to identify the areas with large vibration displacement. High displacement areas usually appear in the areas with darker colors or larger deformation amplitudes in the vibration mode diagram. In this step, the image segmentation model can be used to divide the vibration mode diagram according to the color blocks, or a threshold can be set to identify the high displacement area. For example, the first ten percent of the displacement in the vibration mode can be set, and then the high displacement area of ​​each mode can be extracted according to the threshold.

[0071] After obtaining the high displacement areas, mark the high displacement areas of each mode on the 3D model. You can use color or other marking methods to highlight these areas.

[0072] Step S33: marking the common high displacement areas of the three-dimensional model in each mode to form a structural vibration sensitive area.

[0073] Summarize the high displacement areas of all modes and identify the common high displacement areas that appear in multiple modes. The common high displacement areas usually indicate that the structure has significant vibration problems in multiple modes. Step S4: correspond the structural vibration sensitive area to the structure to be tested to form a detection area.

[0074] The goal of this step is to apply the structural vibration sensitive areas identified in step S3 to the actual structure to be tested to determine the areas that need to be focused on. These detection areas are determined based on the vibration analysis results and are usually the areas on the structure to be tested that vibrate most violently.

[0075] Specifically, the vibration sensitive area data obtained through modal analysis can be mapped to the actual structure to be tested. This can be done by comparing the high displacement area of ​​the modal vibration shape with the geometric model of the actual structure. Using the post-processing function of the finite element analysis software, or through the model comparison tool, the vibration sensitive area is marked on the drawing or 3D model of the actual structure to form the test area.

[0076] Step S5: Excite the surface of the structure to be tested and collect vibration response data formed in the test area.

[0077] First, select a suitable excitation source according to the needs. Excitation sources include vibration tables, impact hammers, exciters, etc. The excitation source should be able to generate sufficient vibration to ensure that the vibration response of the structure can be measured. The selection of the excitation source can be determined according to the size and shape of the actual structure, and the excitation source can also use special equipment.

[0078] After determining the excitation source, it is necessary to set the parameters of the excitation source, such as frequency range, excitation amplitude, etc. These parameters should be determined based on the previous modal analysis results to ensure that the main vibration modes of the structure to be tested are covered.

[0079] Select the specific location to apply the excitation. You can choose to excite in the key area of ​​the structure or a location close to the detection area to ensure that the vibration can be effectively transmitted to the detection area. In the detection area, a vibration sensor needs to be preset to collect the vibration signal in the detection area, such as accelerometers, displacement sensors, strain gauges, etc. According to the previously marked detection area location, the sensors are installed in these areas. Ensure that the arrangement of the sensors can fully cover the sensitive area and that the sensors are in good contact with the surface of the structure.

[0080] After the sensor is set up, the surface of the physical structure can be stimulated to generate vibration, and the sensor can collect vibration data in the detection area to form vibration response data.

[0081] Step S6: Determine the target optimization value according to the vibration response data, and use the initial material parameters as independent variables to adjust the initial material parameters through the finite element optimization algorithm to obtain the final material property parameters of the structure to be tested.

[0082] Taking the spectrum peak obtained from the vibration test as a reference and the material parameters of the structure to be tested as independent variables, the material parameters are adjusted through the finite element optimization algorithm. When the error between the natural frequency calculated by the finite element and the natural frequency obtained by the experiment is minimized, the property parameters of the material to be tested are determined.

[0083] In this step, there are two parts. The first part is to determine the target optimization value according to the vibration response data. The target optimization value is determined according to the actual experiment. The target optimization value is used as the target value to optimize and adjust the material parameters, specifically steps S61-S62. The second part is to adjust the initial material parameters through the finite element optimization algorithm to obtain the final material property parameters of the structure to be tested, that is, to iteratively adjust the initial material parameters according to the target to obtain the final material property parameters matching the target. In this embodiment, for the convenience of explanation, the gradient descent method is used to solve the final material property parameters, specifically steps S63-S67. In addition to the gradient descent method, genetic algorithms, particle swarm algorithms, etc. can also be used. These algorithms adjust the material parameters through iterative optimization so that the modal frequency calculated by the finite element is as consistent as possible with the experimental data.

[0084] Step S61: Process the vibration response data to obtain a frequency spectrum.

[0085] First, the collected vibration response data needs to be preprocessed by denoising, filtering, etc. to improve the data quality, and the time domain data is converted into frequency domain data using Fourier transform or fast Fourier transform (FFT) to obtain the spectrum of the vibration response. In this embodiment, it is preferred to use fast Fourier transform to obtain the spectrum.

[0086] Step S62: Determine the natural modal frequencies of the multi-order modal vibration shapes according to the frequency spectrum, and use them as target optimization values.

[0087] It should be noted that the peaks of the spectrum can be considered as the first few natural mode frequencies of the structure to be tested.

[0088] Therefore, the corresponding natural modal frequencies can be directly identified from the spectrum, and the extracted natural modal frequencies are used as target optimization values, which will be used in the subsequent optimization process to adjust the material parameters so that the simulation results match the actual vibration characteristics.

[0089] Step S63: setting the objective function according to Young's modulus and Poisson's ratio.

[0090] In this embodiment, the objective function is established by taking Young's modulus and Poisson's modulus as independent variables and the experimentally obtained modal frequency as the target value, wherein the experimentally obtained modal frequency is the above-mentioned target optimization value.

[0091] There are multiple modal frequencies Need to match, so the objective function f(x) is defined as:

[0092]

[0093] in, is the i-th order natural frequency obtained by finite element analysis, which is related to Young's modulus E and Poisson's ratio v. is the i-th order natural frequency obtained by experimental measurement, which is the target optimization value mentioned above, and n is the number of modes.

[0094] The goal is to adjust E and v so that the modal frequency of the finite element calculation is With experimental frequency Match as much as possible to minimize the objective function f(x).

[0095] Step S64: Calculate the gradient of the objective function with respect to Young's modulus and Poisson's ratio.

[0096] Gradient descent is an iterative optimization algorithm that calculates the gradient of the objective function, updates the parameters along the negative direction of the gradient (that is, the direction in which the objective function value decreases), and gradually approaches the optimal solution.

[0097] Before calculating its gradient, it is necessary to set the initial values ​​of Young's modulus E0 and Poisson's ratio v0, and set the learning rate α. The learning rate α is used to control the update amplitude of the parameters at each iteration.

[0098] Calculate the gradient of the objective function f(x) with respect to E and v, denoted as Then we have:

[0099]

[0100] Specifically, each component of the gradient represents the rate of change of the objective function with respect to the corresponding material parameter:

[0101]

[0102]

[0103] in, and is the modal frequency The sensitivities to Young's modulus and Poisson's ratio, respectively, can be obtained by finite element analysis.

[0104] Step S65: Update the parameter vector using the update rule of the gradient descent method.

[0105] Using the update rule of the gradient descent method, update the parameter vector:

[0106]

[0107] Among them, k is the iteration step index, which indicates the current iteration number, which starts from 0 and increases by 1 for each iteration. k is the variable value at the kth iteration, representing the parameter estimate of the current iteration, For xk The gradient vector of the objective function f.

[0108] Expanded representation is:

[0109]

[0110] Step S66: Repeat steps S64-S65 until the objective function converges.

[0111] Before this step, it is necessary to set a convergence threshold ∈. When the above steps are repeated until the change in the value of the objective function is less than the convergence threshold ∈, the objective function is considered to have converged.

[0112] Step S67: After the objective function converges, the final material property parameters of the structure to be tested are obtained.

[0113] After determining that the objective function has converged, the current Young's modulus and Poisson's ratio are output as the final material property parameters of the structure to be tested.

[0114] Step S7: assign the final material property parameters obtained to the three-dimensional model, perform finite element modal analysis, and compare and verify the finite element modal analysis results with the vibration test results of the structure to be tested.

[0115] The finite element modal analysis includes free modal analysis and constrained modal analysis.

[0116] In a specific embodiment, Figure 2 As shown in the figure, a 1 / 4 scale model of a portal rudder is produced by 3D printing technology. The portal rudder model is the port blade of the portal rudder system. The structure consists of three parts: a portal rudder, a connecting rod and a strain gauge sensor. The materials used are PET-CF15, steel and aluminum alloy. The recommended values ​​of material parameters are as follows:

[0117]

[0118] This embodiment uses the door rudder model prepared above to carry out material property identification by combining vibration testing with modal analysis. The method described is based on the following theory:

[0119] The density of the door rudder model is directly identified by experimental methods. Using the response surface optimization method, the material parameters that need to be identified are: Young's modulus and Poisson's ratio. The basic process of identification is:

[0120] (1) Finite element modal analysis of the door-rudder structure in the free state. The nominal material parameters of the material are used to analyze the vibration mode of the finite element modal of the door-rudder structure to understand the vibration state of the door-rudder structure and determine the installation position of the strain gauge.

[0121] (2) Vibration experiment of the door rudder model in a free state: a strain gauge is installed at the vibration position determined in process (1). The vibration measurement is obtained through the strain gauge, and the spectrum analysis of the vibration signal is performed to obtain its main vibration spectrum characteristics.

[0122] (3) Taking the main frequency of the experimental vibration as the target value and the Young's modulus and Poisson's ratio of the gate-rudder model as the design variables, the material parameters of the gate-rudder structure are identified through the response surface optimization program.

[0123] (4) Identification of the material parameters of the gate rudder structure. In order to verify the correctness of the identified parameters, vibration tests and finite element modal analysis were carried out on the gate rudder structure under constrained conditions. The modal frequencies obtained by the two methods were compared. The consistent results proved the correctness of the identified material parameters.

[0124] The door rudder structure used in the experiment is a 3D printed model, and the 3D printing material used is PET-CF15. After consulting the data, the nominal material parameters of PET-CF15 are shown in the following table. The density is 1366kg / m 3 , Young's modulus is 6178MPa, and Poisson's ratio is unknown. The mass of the door rudder structure in the experiment is weighed and its volume is calculated. The actual density of the door rudder model is 1160kg / m 3 This embodiment mainly identifies two material parameters of the door rudder structure, namely, Young's modulus and Poisson's ratio.

[0125] <![CDATA[Density (kg / m 3 )]]> Young's modulus (Pa) Poisson's ratio name 1366 6.178e9 none FEA 1160 6.178e9 0.3

[0126] According to the structure, size and material of the gate rudder model described above, the model geometry is constructed in ANSYS, and the finite element free modal analysis of a single rudder blade is performed. According to the 3D printed gate rudder three-dimensional model, mesh division is performed, the mesh size is 0.01m, tetrahedral solid elements are used, the number of elements is 4386, and the number of nodes is 8135. The initial material parameters used in the finite element analysis of the gate rudder structure are shown in the table above. After the modal analysis, the first four modes are taken, and their modal frequencies and vibration shapes are as follows Figure 3 shown.

[0127] Because the initial material parameter values ​​are used in the finite element modal analysis, the modal frequencies in the finite element modal analysis are ignored, and the modal vibration modes are mainly examined. The first and third order modal vibration modes are bending modes, and the second and fourth order modal vibration modes are torsional vibration modes. According to the vibration forms of the modal vibration modes, it can be observed that in the first and third order modal vibration modes, the position where the strain gauge is pasted has obvious displacement changes, while in the second and fourth order torsional vibration modes, the position where the strain gauge is located has no obvious displacement changes. When the gate rudder vibrates with such vibration modes, the strain gauge will not produce obvious deformation in these areas, and no voltage signal will be generated. Therefore, it can be assumed that the two frequencies in the free vibration experiment of the gate rudder structure correspond to the first and third order vibration modes of the gate rudder, respectively.

[0128] The sensor strain gauge is installed at the corresponding position of the vibration sensitive area of ​​the rudder blade structure to carry out vibration testing.

[0129] The vibration analysis of the door rudder structure in the free state is carried out. The door rudder is suspended with an elastic rope, and a hammer is used to stimulate the door rudder perpendicular to the surface of the door rudder structure to make it vibrate. The vibration signal is collected by a piezoelectric strain gauge. The installation position of the strain gauge and the position and direction of the hammer excitation force are as follows: Figure 4 shown.

[0130] A single rudder blade Figure 5 (Left) As shown. The time signal and spectrum signal obtained from the strain gauge are shown Figure 5 (right) Two different responses appear at 138 Hz and 355 Hz.

[0131] Based on the results of the previous finite element analysis and experimental analysis, it is assumed that the frequency of 138 Hz obtained in the free vibration experiment of the door-rudder structure corresponds to the first-order mode of the door-rudder structure, and 355 Hz corresponds to the third-order mode of the door-rudder structure.

[0132] The response surface method is used to identify the parameters of the gate rudder structure. There are three material parameters of the gate rudder structure: density, Young's modulus and Poisson's ratio. The density parameter has been determined, and only the Young's modulus and Poisson's ratio of the gate rudder structure need to be identified. When applying the response surface optimization method, it is necessary to determine the optimization parameters: input parameters and output parameters. In this example, Young's modulus and Poisson's ratio are set as input parameters, and the first and third order natural frequencies of the gate rudder structure are set as output parameters.

[0133] In this embodiment, for the convenience of explanation, the optimization algorithm in the simulation software is directly used to optimize the parameters. Specifically, the response surface optimization is divided into three processes, and the main parameters in each process are set as follows:

[0134] (1) In the "Design of Experiments" process, set the "Design of Experiments type" to "Central Composite Design", set the lower limit of the input variable Young's modulus to 1e9 Pa and the upper limit to 7e9 Pa; the lower limit of Poisson's ratio to 0.01 and the upper limit to 0.3;

[0135] (2) In the “Response Surface” process, set “Response Surface Type” to “Genetic Aggregation”;

[0136] (3) In the "Optimization" process, set the target of the optimization parameters. The target value of the first-order modal frequency is 138 Hz, and the constraint condition is to search between 135 Hz and 140 Hz; the target value of the third-order modal frequency is 355 Hz, and the constraint condition is to search between 350 Hz and 360 Hz. The response surface obtained is as follows: Figure 6 shown.

[0137] After the entire optimization process, the optimized material parameters are as follows: Figure 3 shown.

[0138] To verify Figure 3 The correctness of the optimized material parameters shown is analyzed through the following three cases.

[0139] Will Figure 3 The optimized material parameters of the door rudder structure are applied to the free modal analysis of the door rudder structure. The results are as follows: Figure 7 shown.

[0140] The ends of the door rudder structure are fixed, and the time history and spectrum of the strain gauge voltage signal under the excitation force are as follows: Figure 8 shown.

[0141] right Figure 8 The boundary conditions of the door rudder structure are shown in the figure. The finite element method is used to perform modal analysis on the door rudder under constraint conditions. The results are shown in Fig. 9 shown.

[0142] The door rudder structure is connected to the connecting rod by bolts, and the end of the connecting rod is fixed. The time history and spectrum of the voltage signal of the strain gauge under the action of the excitation force are as follows: Fig.10 shown.

[0143] for Fig.10 The structure shown in the figure is subjected to finite element modal analysis under constraint conditions. The bolt connection between the connecting rod and the door rudder is achieved by gluing the two components together. The results are shown in Fig.11 shown.

[0144] This embodiment combines vibration test and finite element model analysis, and uses response surface method to identify the material parameters of the 3D printed door rudder structure. The vibration test and finite element model analysis results under various working conditions are compared to confirm the correctness of the material parameters of the door rudder structure identified by the response surface method, further promoting the feasibility, reliability and accuracy of the present invention.

[0145] It should be noted that the finite element modal analysis mentioned in this embodiment is a mature technology, and the finite element optimization technology is also embedded in software such as ANSYS. Therefore, the material parameter identification method algorithm proposed in the present invention is highly efficient, consumes less time, and can quickly and efficiently identify the material parameters of the 3D printed structure.

[0146] The material parameter identification system of the 3D printed structure of the present invention comprises a processor, a strain gauge sensor and a data acquisition card, wherein the processor is embedded with the above-mentioned material parameter identification method of the 3D printed structure, the strain gauge sensor is used to be arranged on the detection area of ​​the structure to be tested to collect the vibration signal formed in the detection area, and the data acquisition card is used to convert the vibration signal collected by the strain gauge sensor into vibration response data and transmit it to the processor.

[0147] Finite element analysis software is also provided in the processor. The system also includes a digital oscilloscope, through which the vibration waveform on the structure to be tested is displayed in real time.

[0148] In this system, the sensor strain gauge needs to be installed at the corresponding position of the vibration sensitive area of ​​the structure to be measured, and the vibration response of the structure to be measured is obtained by external force knocking method. The vibration response is subjected to spectrum analysis to obtain the frequency value corresponding to the peak value on the spectrum curve. The sensor material is piezoelectric material, and the function of the sensor is to provide a voltage output signal.

[0149] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A material parameter identification method for a 3D printed structure, characterized in that: The following steps are involved: S1 obtains a three-dimensional model of the structure to be tested; S2 assigns initial material parameters to the three-dimensional model and performs finite element modal analysis on it to obtain multi-order modal vibration shapes; S3 obtains the structural vibration sensitive area on the three-dimensional model according to the multi-order mode vibration shapes; S4 maps the structural vibration sensitive area to the structure to be tested to form a detection area; S5 excites the surface of the structure to be tested and collects vibration response data formed in the test area; S6 determines the target optimization value based on the vibration response data, and uses the initial material parameters as independent variables to adjust the initial material parameters through the finite element optimization algorithm to obtain the final material property parameters of the structure to be tested.

2. The material parameter identification method of the 3D printing structure according to claim 1, characterized in that: The step S2 comprises the following steps: S21 assigns arbitrary initial value material parameters to the three-dimensional model; S22 discretizes the three-dimensional model into a finite element mesh; S23 obtains multi-order natural frequencies and corresponding mode vibration shapes of the structure to be tested according to the finite element mesh.

3. The material parameter identification method of a 3D printing structure according to claim 1, characterized in that: The step S3 comprises the following steps: S31 forms vibration mode diagrams of each mode through multiple-order mode vibration modes; S32 determines the high displacement area of ​​the three-dimensional model in each mode according to the vibration shape diagram of each mode; S33 marks the common high displacement areas of the three-dimensional model in each mode to form the structural vibration sensitive area.

4. The material parameter identification method of a 3D printing structure according to claim 1, characterized in that: In step S6, determining the target optimization value according to the vibration response data includes the following steps: S61 processes the vibration response data to obtain a frequency spectrum; S62 determines the natural modal frequencies of the multi-order modal vibration shapes according to the frequency spectrum and uses them as target optimization values.

5. The material parameter identification method of a 3D printing structure according to claim 1, characterized in that: Before step S1, the actual density of the structure to be measured is determined. In step S2, the actual density of the structure to be measured is assigned to the three-dimensional model together with the initial material parameters.

6. The material parameter identification method of a 3D printing structure according to claim 1, characterized in that: The initial value material parameters include Young's modulus and Poisson's ratio.

7. The material parameter identification method of a 3D printing structure according to claim 6, characterized in that: In step S6, the initial material parameters are adjusted by a finite element optimization algorithm to obtain the final material property parameters of the structure to be tested, including the following steps: S63 sets the objective function based on Young's modulus and Poisson's ratio; S64 calculates the gradient of the objective function with respect to Young's modulus and Poisson's ratio; S65 updates the parameter vector using the update rule of the gradient descent method; S66 repeats steps S64-S65 until the objective function converges; After the S67 objective function converges, the final material property parameters of the structure to be tested are obtained.

8. The material parameter identification method of a 3D printing structure according to claim 1, characterized in that: The method further includes step S7, assigning the obtained final material property parameters to the three-dimensional model, performing finite element modal analysis, and comparing and verifying the finite element modal analysis results with the vibration test results of the structure to be tested.

9. The material parameter identification method of a 3D printing structure according to claim 8, characterized in that: In step S7, the finite element modal analysis includes free modal analysis and constrained modal analysis.

10. A material parameter identification system for a 3D printed structure, characterized in that: It comprises a processor, a strain gauge sensor and a data acquisition card, wherein the processor is embedded with the material parameter identification method of the 3D printed structure according to any one of claims 1 to 9, the strain gauge sensor is used to be arranged on the detection area of ​​the structure to be tested to collect the vibration signal formed in the detection area, and the data acquisition card is used to convert the vibration signal collected by the strain gauge sensor into vibration response data and transmit it to the processor.

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