Part collision stress testing method based on digital image correlation

Abstract

The invention relates to a part collision stress testing method based on digital image correlation, which comprises the following steps of: developing a post-processing comparison software module, acquiring a corresponding relation between sample surface speckle image deformation and tensile load through a testing machine, calibrating a stress-strain curve of a part material based on the relation, and calculating the part collision stress. Processing the curve to obtain different stress-strain curves; in the simulation software, collision simulation is carried out on the part to obtain a simulation result, and grids of the CAE simulation software are mapped into a post-processing comparison module, so that the simulation result is aligned with measured data based on the same grid division; in the test software, actual collision test is carried out on the part to obtain a speckle actual measurement result, and an actual measurement speckle pattern is segmented again; and based on a stress-strain curve, a simulation result and a speckle actual measurement result, substituting a relationship between speckle deformation and force into a part strain field to calculate a stress field, and realizing a part collision stress test through strain comparison and / or stress comparison.

Description

Technical Field

[0001] The present invention relates to the field of parts collision testing, and in particular to a parts collision stress testing method based on digital image correlation. Background Art

[0002] As the safety and reliability requirements for parts continue to increase in the automotive, aerospace and other fields, part collision testing and stress analysis are becoming increasingly important. Currently, Computer Aided Engineering (CAE) simulation technology and Digital Image Correlation (DIC) technology are widely used in the engineering field to analyze the mechanical behavior of parts during collisions.

[0003] In the field of CAE simulation, establishing material models and performing collision simulations are the primary methods for evaluating component performance. Digital image correlation (DIC), a non-contact, full-field measurement technique, has been widely used to measure deformation of materials and structures.

[0004] However, existing technologies still face the following challenges: First, CAE simulation software typically obtains strain and stress through material model transformation, rather than obtaining the actual material-level strain and stress field of a part during a collision through actual testing. This leads to discrepancies between actual collision results and simulation results. Second, although DIC technology can measure the three-dimensional deformation dimensions of parts, there has been no effective method for understanding the actual forces acting on parts during a collision. Third, the test results of materials and parts in CAE simulations are not closely linked, lacking an effective comparative analysis mechanism. Finally, existing methods lack accurate interpolation methods for the stress-strain relationship at different strain rates when the intervals between adjacent strain rates are large, affecting the accuracy of stress field calculations. These issues severely restrict the accuracy and reliability of part collision testing, necessitating an urgent need for a part collision stress testing method that effectively combines simulation and measured data. Summary of the Invention

[0005] In order to solve the problem in the prior art that CAE simulation software obtains strain and stress through material model conversion rather than obtaining the real material-level strain and stress field of the part in the collision through actual testing, resulting in deviation between the actual collision results and the simulation results, and to achieve the technical effect of first real-time testing of the part force and comparing and correcting it with the CAE simulation results, the present invention provides a part collision stress testing method based on digital image correlation.

[0006] The present invention solves its technical problems by adopting a technical solution: providing a part collision stress testing method based on digital image correlation, comprising the following steps: developing a post-processing comparison software module in digital image correlation testing software, obtaining a correspondence between the deformation of a sample surface speckle image and the tensile load using a material high strain rate tensile testing machine, calibrating the stress-strain curve of the part material based on the correspondence, and filtering and averaging the curve to obtain stress-strain curves corresponding to different strain rates; performing a collision simulation on the part based on a preset grid configuration in simulation software to obtain simulation results, and mapping the grid of the CAE simulation software to the post-processing comparison module so that the simulation results and measured data are aligned based on the same grid division; performing an actual collision test on the part in the digital image correlation testing software to obtain measured speckle results, and re-segmenting the measured speckle image according to the CAE grid division; based on the stress-strain curves corresponding to different strain rates and the aligned simulation results and measured speckle results, substituting the relationship between speckle deformation and force into the part strain field to calculate the stress field, and implementing part collision stress testing through strain comparison and / or stress comparison.

[0007] Preferably, the strain comparison process includes: extracting the three-dimensional coordinates and time-strain sequences of the simulated and measured grid nodes in a post-processing comparison module, screening the grid nodes in key areas by the maximum strain threshold, and outputting a time-strain curve comparison diagram thereof.

[0008] Furthermore, the stress comparison process includes: calculating the local strain rate of each grid node based on the measured strain field after CAE mesh segmentation, matching the stress-strain curve at the corresponding rate, and linearly interpolating the curve to the current strain rate to generate a node-level true stress field.

[0009] Furthermore, for curves where the interval between adjacent strain rates exceeds a preset value, the cubic spline interpolation method is used to solve the stress value corresponding to the intermediate strain rate.

[0010] Optionally, the true composite stress is solved using the following formula: The true composite stress is solved using the following formula: σm = √(σx2+σy2+τxy2)×α, where σm is the true composite stress of grid node m, σx, σy, and τxy represent the x, y, and shear direction stress components calculated based on the speckle deformation and force model, respectively, and α is the stress correction coefficient corresponding to the strain rate in the material calibration curve.

[0011] Preferably, the grid configuration includes a grid size defined in CAE software.

[0012] Furthermore, the speckle measurement results include three-dimensional deformation data of the part surface.

[0013] Furthermore, wavelet transform filtering is used to eliminate speckle image noise, and averaging is achieved by weighted averaging of a preset number of test data sets under the same strain.

[0014] The computer-readable storage medium of the present application stores a computer program thereon, and when the computer program is executed by a processor, the above-mentioned part collision stress testing method is implemented.

[0015] The computer device of the present application includes a storage module, a processor, and a computer program stored in the storage module and executable on the processor. When the processor executes the computer program, the above-mentioned part collision stress testing method is implemented.

[0016] The computer program product of the present application includes a computer program, which implements the above-mentioned part collision stress testing method when executed by a processor.

[0017] The beneficial effects of the present invention include: realizing for the first time a method for real-time testing of part forces, comparing the results with CAE simulations, and correcting the results, thus resolving the existing problem of being unable to measure the actual forces on parts during a collision; improving the accuracy of early simulations for part design, effectively reducing the number of physical collision tests for parts and entire vehicles, and lowering R&D costs; employing an optical method for the first time to measure the deformation of speckles at any two points on a standard material spline, obtaining the relationship between speckle deformation and force through the load of a tensile testing machine, and achieving true measurement of strain and stress fields at the material level; being able to measure the mechanical properties of tiny regions on a part, thereby improving testing accuracy; and being applicable to other testing environments where strain gauge calibration for mechanical property measurement is inadequate, thus expanding its scope of application. Compared with existing technologies, the present invention closely integrates CAE simulation with DIC technology, establishing a link between material testing and part testing, and achieving precise measurement and analysis of the actual forces on parts during a collision. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or other aspects and advantages of the present application will become clearer and easier to understand through the following description of various aspects in conjunction with the accompanying drawings, in which the same or similar elements are represented by the same reference numerals. In the drawings:

[0019] Figure 1 FIG. 4 is a schematic flow chart of a method 100 for testing part collision stress according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] The description of the following specific embodiments is merely exemplary in nature and is not intended to limit the disclosed technology or the application and use of the disclosed technology. In addition, there is no intention to be bound by any express or implied theory presented in the foregoing technical field, background technology or the following specific embodiments.

[0021] In the following detailed description of the embodiments, numerous specific details are set forth to provide a more thorough understanding of the disclosed technology. However, it will be apparent to one of ordinary skill in the art that the disclosed technology can be practiced without these specific details. In other instances, well-known features are not described in detail to avoid unnecessarily complicating the description.

[0022] Terms such as “comprise” and “include” indicate that in addition to the units and steps directly and clearly stated in the specification, the technical solution of the present application does not exclude the situation where it has other units and steps that are not directly or clearly stated.

[0023] Hereinafter, various exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings.

[0024] Now refer to Figure 1 , Figure 1 FIG. 4 is a schematic flow chart of a method 100 for testing part collision stress according to an embodiment of the present application.

[0025] like Figure 1 As shown, in step S1: a post-processing comparison software module is developed in the digital image correlation test software, and the correspondence between the deformation of the speckle image on the sample surface and the tensile load is obtained through a material high strain rate tensile testing machine. Based on this relationship, the stress-strain curve of the part material is calibrated, and the curve is filtered and averaged to obtain stress-strain curves corresponding to different strain rates.

[0026] Specifically, a dedicated post-processing and comparison software module was first developed using digital image correlation testing software. This module is primarily used to process and analyze data acquired from high-strain-rate tensile tests. During development, the module framework was constructed using the C++ programming language and integrated with an image processing algorithm library to ensure the module's ability to efficiently process large amounts of speckle image data.

[0027] Next, the parts are tested using a high strain rate tensile testing machine. The testing machine is equipped with a high-speed camera system, and the acquisition frequency of the camera system is set to 5000 frames /

[0028] Seconds to ensure that the transient response of the material during high-speed deformation can be captured. A black and white speckle pattern is sprayed on the surface of the sample, and the speckle diameter is controlled between 0.5-1.5mm to ensure the accuracy of speckle recognition.

[0029] During the tensile test, the testing machine stretched the specimen at different loading rates (0.001 / s, 0.01 / s, 0.1 / s, 1 / s, 10 / s, and 100 / s). Simultaneously, a high-speed camera system captured the deformation of the speckle pattern on the specimen surface in real time, and the tensile load sensor recorded the corresponding load data. Using a digital image correlation algorithm, the displacement and strain fields of each point in the speckle image sequence were calculated and correlated with the simultaneously recorded load data.

[0030] Based on the correspondence between the acquired speckle image deformation and the tensile load, the stress-strain curve of the part material is calibrated. During the calibration process, the load data is first converted into engineering stress, and the speckle deformation data is converted into engineering strain. Then, the true stress-true strain curve of the material is calculated according to the true stress-true strain conversion formula.

[0031] The obtained stress-strain curves were filtered, and the speckle image noise was eliminated using wavelet transform filtering. Specifically, the original stress-strain curves were decomposed into five layers using the db4 wavelet basis function. After removing the high-frequency noise components, the signal was reconstructed to obtain a smooth stress-strain curve.

[0032] Then, the filtered curve was averaged. For each strain rate condition, 5 sets of repeated tests were performed to obtain 5 stress-strain curves. The 5 stress values ​​under the same strain value were weighted averaged, and the weight was determined according to the discrete degree of each set of data. The smaller the discrete degree, the greater the weight. In this way, the standard stress-strain curves corresponding to each strain rate (0.001 / s, 0.01 / s, 0.1 / s, 1 / s, 10 / s, 100 / s) were obtained.

[0033] In step S2, in the simulation software, a collision simulation is performed on the part based on a preset grid configuration to obtain a simulation result, and the grid of the CAE simulation software is mapped to a post-processing comparison module so that the simulation result and the measured data are aligned based on the same grid division.

[0034] Specifically, a finite element model of the part was created in LS-DYNA simulation software. Mesh configuration parameters were set based on the part's geometric characteristics and expected crash conditions. The mesh size was set to 2 mm to balance computational accuracy and efficiency. In areas of expected stress concentration, the mesh size was locally refined to 0.5 mm to improve computational accuracy in these areas.

[0035] In the simulation model, set the part's material parameters, including density, elastic modulus, Poisson's ratio, and the stress-strain curves at different strain rates obtained in Step 1. Set the collision boundary conditions, including the collision velocity, collision angle, and constraints. Set the collision velocity to 10 m / s, the collision angle to 90 degrees, and a fixed constraint to the bottom of the part.

[0036] Run a collision simulation and obtain simulation results, including the displacement field, strain field, stress field, and energy absorption at each node of the part. The simulation calculation time step is set to 1e-6 seconds, and the total calculation time is 20 milliseconds to ensure that the collision process is fully captured.

[0037] The mesh information in the CAE simulation software is exported to a common format (such as STL or IGES) and then imported into the post-processing comparison module. In the post-processing comparison module, a mesh mapping algorithm is established to establish a spatial correspondence between the CAE mesh and the measured data collection points.

[0038] During the mesh mapping process, the node coordinates and cell topology of the CAE mesh are first determined. A spatial index structure (such as an octree or KD tree) is then established to accelerate spatial searches. For each acquisition point in the measured data, the nearest node or cell containing that point is found in the CAE mesh, and a mapping relationship is established. For measured points that are not on a mesh node, shape function interpolation is used to calculate the corresponding physical quantity.

[0039] In this way, the simulation results and measured data are aligned based on the same grid division, laying the foundation for subsequent comparative analysis.

[0040] In step S3, in the digital image correlation test software, an actual collision test is performed on the parts to obtain the actual speckle measurement results, and the measured speckle pattern is re-divided according to the CAE grid division.

[0041] Specifically, a crash test specimen is first prepared. A black and white speckle pattern is sprayed onto the surface of the part, with the speckle diameter controlled between 0.5 and 1.5 mm to ensure accurate speckle recognition. The speckle pattern covers critical areas of the part, particularly those expected to be stressed.

[0042] A collision test platform was constructed, including a collision device, a high-speed camera system, and a data acquisition system. The high-speed camera system consisted of two or more high-speed cameras, set to capture data at a rate of 10,000 frames per second and a resolution of 1024 × 1024 pixels, to ensure that transient deformation of parts during collisions could be captured. The cameras were arranged as a stereo vision system to obtain 3D deformation information of the part surface.

[0043] Before the collision test, the stereo vision system is calibrated to determine the camera's intrinsic parameters (focal length, principal point coordinates, distortion coefficient, etc.) and extrinsic parameters (relative position and attitude between cameras). The calibration process uses a standard calibration plate and calculates the camera parameters by capturing images of the plate at different positions and attitudes.

[0044] Actual collision tests were conducted, with the collision speed set to 10 m / s, consistent with the simulation conditions. A high-speed camera system recorded the deformation of the part surface speckle pattern during the collision in real time.

[0045] Digital image correlation testing software is used to process image sequences captured by a high-speed camera system. Using an image correlation algorithm, the displacement field of each point in the speckle pattern is calculated, and thus the strain field. Specific steps include image preprocessing (such as denoising and contrast enhancement), feature point matching, sub-pixel displacement calculation, and strain field calculation.

[0046] The measured speckle pattern was re-divided according to the CAE grid. First, the CAE grid information was imported into the digital image correlation testing software. Then, a correspondence between speckle image points and CAE grid nodes was established. For each CAE grid cell, all speckle image points falling within that cell were identified. The average displacement and strain of these points were calculated as the measured values ​​for that grid cell.

[0047] In this way, the measured speckle results consistent with the CAE grid are obtained, including the displacement field and strain field data of each grid node.

[0048] In step S4, based on the stress-strain curves corresponding to different strain rates and the aligned simulation results and speckle measurement results, the relationship between speckle deformation and force is substituted into the part strain field to calculate the stress field, and the part collision stress test is achieved through strain comparison and / or stress comparison.

[0049] Specifically, a strain comparison analysis is first performed. In the post-processing comparison module, the 3D coordinates and time-strain sequences of the simulated and measured mesh nodes are extracted. For each mesh node, the strain values ​​calculated from the simulation are compared with the measured values, and the difference between the two is calculated.

[0050] Set a maximum strain threshold (e.g., 5%) and select key area mesh nodes where the strain exceeds the threshold. For these key nodes, output a time-strain curve comparison chart to visually display the difference between the simulation results and the measured results.

[0051] Then, a stress comparison analysis is performed. Based on the measured strain field after CAE meshing, the local strain rate of each mesh node is calculated. The strain rate calculation formula is: strain rate = strain increment / time increment, where the strain increment is the strain difference between two adjacent time steps, and the time increment is the time step.

[0052] For each mesh node, based on its local strain rate, match the closest strain rate curve from the stress-strain curves corresponding to different strain rates obtained in step 1. If the strain rate of the node is exactly equal to a certain standard strain rate, the stress-strain curve corresponding to that strain rate is directly used; if the strain rate of the node falls between two standard strain rates, the stress value at that strain rate is calculated through linear interpolation.

[0053] For curves where the interval between adjacent strain rates exceeds a preset value (e.g., an order of magnitude), a cubic spline interpolation method is used to solve for the stress values ​​corresponding to the intermediate strain rates, resulting in a smoother interpolation result. Specifically, a cubic spline function is used to fit the relationship between strain rate and stress, and then the stress value corresponding to the target strain rate is calculated.

[0054] Based on the matched stress-strain curve and the measured strain field, the true stress field of each mesh node is calculated. The true composite stress is solved using the following formula:

[0055] σm=√(σx 2 +σy 2 +τxy 2 )×α

[0056] Where σm is the true composite stress at the grid node m, σx, σy, and τxy represent the stress components in the x, y, and shear directions calculated based on the speckle deformation and force model, respectively, and α is the stress correction coefficient corresponding to the strain rate in the material calibration curve.

[0057] The stress correction factor α is calculated based on the material's stress response at different strain rates and generally increases with increasing strain rate. For the material used in this example, the α value is 1.0 at a strain rate of 0.001 / s and 1.5 at a strain rate of 100 / s. α values ​​for intermediate strain rates are calculated using linear interpolation.

[0058] The calculated true stress field is compared with the simulated stress field to analyze the differences between the two. Comparison indicators include maximum stress difference, average stress difference, and stress distribution morphology difference.

[0059] Through comprehensive analysis of strain and stress comparisons, the accuracy of the simulation model is evaluated, and simulation parameters are optimized and adjusted to improve the accuracy of simulation predictions. Ultimately, accurate testing and evaluation of part collision stress is achieved.

[0060] In some embodiments, wavelet transform filtering is used to eliminate speckle image noise, and averaging is achieved by weighted averaging a preset number of test data sets at the same strain. Specifically, the original stress-strain curve is decomposed into five layers using the db4 wavelet basis function, and the signal is reconstructed after removing high-frequency noise components. For averaging, a weighted average is performed on the five test data sets at the same strain value, with the weight determined based on the degree of dispersion of each data set, with the smaller the degree of dispersion, the larger the weight.

[0061] Furthermore, in some embodiments, the speckle pattern measurement results include 3D deformation data on the part surface. The 3D coordinates of the part surface are acquired through a stereo vision system, and the 3D displacement field is calculated using a digital image correlation algorithm, yielding complete 3D deformation data. This 3D deformation data is crucial for accurately assessing the deformation behavior and stress distribution of a part during a collision.

[0062] In some embodiments, the mesh configuration includes a mesh size defined in the CAE software. The base mesh size is set to 2 mm, and the mesh size in key areas is refined to 0.5 mm to balance computational accuracy and efficiency. Hexahedral elements are selected as the mesh type to improve computational accuracy and stability.

[0063] In some other embodiments, the strain comparison process is further described in detail.

[0064] The strain comparison process includes: extracting the three-dimensional coordinates and time-strain sequences of the simulated and measured grid nodes in the post-processing comparison module, screening the grid nodes in the key areas by the maximum strain threshold, and outputting a comparison diagram of their time-strain curves.

[0065] Specifically, the aligned simulation and measured speckle patterns were first loaded into the post-processing comparison module. For each grid node, its three-dimensional coordinates (x, y, z) were extracted, along with the time-strain series data for the entire collision process. The time series was sampled at a 0.1 millisecond interval and lasted 20 milliseconds, covering the entire collision process.

[0066] For each mesh node, the principal strains (maximum, intermediate, and minimum) and the equivalent plastic strain are calculated. The principal strains are calculated based on the eigenvalue decomposition of the strain tensor, while the equivalent plastic strains are calculated based on the von Mises yield criterion.

[0067] The maximum strain threshold is set to 5%, and the mesh nodes whose maximum principal strain or equivalent plastic strain exceeds the threshold are screened out. These nodes are usually located in the key deformation area or stress concentration area of ​​the part.

[0068] For the selected key area mesh nodes, a time-strain curve comparison chart is generated. In this comparison chart, the x-axis represents time (unit: milliseconds) and the y-axis represents the strain value (dimensionless). Different colored curves represent the simulation results and the measured results respectively.

[0069] By analyzing the time-strain curve comparison chart, we can visually observe the differences between the simulation results and the measured results. We mainly focus on the following aspects: the difference in the magnitude of the strain peak, the difference in the time when the strain peak occurs, the difference in the strain change rate (slope), and the overall difference in the curve shape.

[0070] Based on the comparative analysis results, the accuracy of the simulation model can be evaluated, and simulation parameters such as material model parameters, contact parameters, boundary conditions, etc. can be adjusted in a targeted manner to improve the accuracy of simulation predictions.

[0071] In some other embodiments, the stress comparison process is further described in detail.

[0072] The stress comparison process includes: calculating the local strain rate of each mesh node based on the measured strain field after CAE mesh segmentation, matching the stress-strain curve at the corresponding rate, and linearly interpolating the curve to the current strain rate to generate the true stress field at the node level.

[0073] Specifically, first, based on the measured strain field after CAE mesh segmentation, the local strain rate of each mesh node during the collision is calculated. The strain rate calculation formula is:

[0074] Strain rate = Δε / Δt

[0075] Wherein, Δε is the strain increment between two adjacent time steps, and Δt is the time step (0.1 milliseconds in this embodiment).

[0076] For each grid node, according to its local strain rate, the closest strain rate curve is matched from the stress-strain curves corresponding to different pre-calibrated strain rates (0.001 / s, 0.01 / s, 0.1 / s, 1 / s, 10 / s, 100 / s).

[0077] If the strain rate of a node is exactly equal to a certain standard strain rate, the stress-strain curve corresponding to the strain rate is directly used; if the strain rate of a node falls between two standard strain rates, the stress value at the strain rate is calculated by linear interpolation. The linear interpolation formula is:

[0078]

[0079] in, Denote strain as ε and strain rate as The stress value at and Represents less than and greater than Two standard strain rates, and They represent strain ε and strain rate respectively. and Note that logarithmic interpolation is used here because the strain rate sensitivity of materials is usually logarithmic.

[0080] For curves where the interval between adjacent strain rates exceeds a preset value (e.g., an order of magnitude), cubic spline interpolation is used to determine the stress values ​​corresponding to the intermediate strain rates. This method ensures the smoothness and continuity of the interpolated curve, avoiding the discontinuity that may be caused by linear interpolation.

[0081] Based on the matched stress-strain curves and the measured strain field, the true stress field is calculated for each mesh node. For a plane stress state, the x-direction stress σx, the y-direction stress σy, and the shear stress τxy are calculated. For a three-dimensional stress state, the z-direction stress σz and the corresponding shear stress component are also calculated.

[0082] The true resultant stress is solved using the following formula:

[0083] σm=√(σx 2 +σy 2 +τxy 2 )×α

[0084] Where σm is the true composite stress at the grid node m, σx, σy, and τxy represent the stress components in the x, y, and shear directions calculated based on the speckle deformation and force model, respectively, and α is the stress correction coefficient corresponding to the strain rate in the material calibration curve.

[0085] The calculation of the stress correction factor α is based on the material's stress response characteristics at different strain rates. For the material used in this example, the α value is 1.0 at a strain rate of 0.001 / s and 1.5 at a strain rate of 100 / s. α values ​​for intermediate strain rates are calculated by linear interpolation.

[0086] After generating the true nodal-level stress field, it is compared with the stress field calculated by simulation. Comparison metrics include maximum stress difference, mean stress difference, and stress distribution pattern difference. This allows a comprehensive assessment of the simulation model's accuracy in predicting part collision stresses.

[0087] In some other embodiments, the process of using the cubic spline interpolation method to solve the stress value corresponding to the intermediate strain rate for the curve where the interval between adjacent strain rates exceeds the preset value is further described in detail.

[0088] Specifically, the strain rate interval is first set to a preset value of one order of magnitude (i.e., a 10-fold relationship). If the interval between two adjacent standard strain rates (e.g., 0.1 / s and 10 / s) exceeds the preset value, the cubic spline interpolation method is used to solve the stress value corresponding to the intermediate strain rate (e.g., 1 / s).

[0089] The basic idea of ​​cubic spline interpolation is to construct a smooth curve that passes through all given data points, with continuous first and second derivatives at each data point. The relationship between strain rate and stress typically exhibits a good linear relationship in a logarithmic coordinate system. Therefore, before performing cubic spline interpolation, the logarithm of the strain rate is first taken.

[0090] The specific steps are as follows:

[0091] First, the logarithm of the standard strain rate (0.001 / s, 0.01 / s, 0.1 / s, 1 / s, 10 / s, 100 / s) was taken to obtain the logarithmic strain rate sequence (-3, -2, -1, 0, 1, 2).

[0092] For each strain value ε, the corresponding stress values ​​at different standard strain rates are collected to form a data set Where i = 1, 2, ..., 6, corresponding to six standard strain rates.

[0093] Use these data points to construct a cubic spline function Make And the first-order derivative and second-order derivative of S at each internal node are continuous.

[0094] The construction of cubic spline functions involves solving a system of linear equations and determining the coefficients of each cubic polynomial. Specifically, for the interval The cubic polynomial Si(x) on , which has the form:

[0095]

[0096] Among them, ai, bi, ci, di are unknown coefficients. By applying the following conditions:

[0097] -

[0098] -

[0099] -

[0100] -

[0101] -Natural boundary conditions:

[0102] Solve to obtain all coefficients ai, bi, ci, and di.

[0103] For any given strain rate First determine its logarithm Which range does it fall into Then use the corresponding cubic polynomial Calculate stress values.

[0104] In this way, a smooth and continuous stress-strain rate relationship can be obtained in the entire strain rate range, especially for areas with large intervals between adjacent strain rates, which can provide more accurate interpolation results.

[0105] In some other embodiments, the process of solving the true composite stress is further described in detail.

[0106] The true resultant stress is solved using the following formula:

[0107] σm=√(σx 2 +σy 2 +τxy 2 )×α

[0108] Where σm is the true composite stress at the grid node m, σx, σy, and τxy represent the stress components in the x, y, and shear directions calculated based on the speckle deformation and force model, respectively, and α is the stress correction coefficient corresponding to the strain rate in the material calibration curve.

[0109] Specifically, the stress components of each mesh node are first calculated based on the measured strain field and the matched stress-strain curve. For the plane stress state, the x-direction stress σx, the y-direction stress σy, and the shear stress τxy are calculated.

[0110] The calculation of the x-direction stress σx is based on the x-direction strain εx and the constitutive relationship of the material:

[0111] σx=E×εx / (1-ν 2 )+E×ν×εy / (1-ν 2 )

[0112] Where E is the elastic modulus of the material, ν is Poisson's ratio, εx and εy are the strains in the x-direction and y-direction, respectively.

[0113] Similarly, the calculation formula for the stress σy in the y direction is:

[0114] σy=E×εy / (1-ν 2 )+E×ν×εx / (1-ν 2 )

[0115] The calculation formula of shear stress τxy is:

[0116] τxy=G×γxy

[0117] Where G is the shear modulus of the material and γxy is the shear strain.

[0118] For the plastic deformation region, the plastic behavior of the material needs to be considered. According to the von Mises yield criterion and flow law, combined with the measured equivalent plastic strain and the matching stress-strain curve, the stress components in the plastic state are calculated.

[0119] The calculation of the stress correction factor α is based on the stress response characteristics of the material at different strain rates. For the material used in this embodiment, the α value is 1.0 at a strain rate of 0.001 / s and 1.5 at a strain rate of 100 / s. The α values ​​at intermediate strain rates are calculated by linear interpolation. The linear interpolation formula is:

[0120]

[0121] in, The strain rate is The stress correction factor when and Represents less than and greater than Two standard strain rates, and The strain rates are and The stress correction factor at .

[0122] Substitute the calculated stress components σx, σy, and τxy into the true composite stress formula:

[0123] σm=√(σx 2 +σy 2 +τxy 2 )×α

[0124] Calculate the true composite stress σm at each mesh node. This composite stress reflects the comprehensive stress state at the node and can be used to evaluate the stress distribution and possible failure location of the part during the collision process.

[0125] By calculating the true composite stress distribution on the entire part surface, stress concentration areas and potential failure points can be identified, providing an important basis for structural optimization and safety assessment of the part.

[0126] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described part impact stress testing method of the present application. The computer-readable medium referred to in this application includes various types of computer storage media and can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the computer-readable medium can include RAM, ROM, EPROM, E2PROM, registers, hard disks, removable disks, CD-ROMs or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other temporary or non-temporary medium that can be used to carry or store desired program code units in the form of instructions or data structures and can be accessed by a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. As used herein, disks typically reproduce data magnetically, while discs use lasers to reproduce data optically. Combinations of the above should also be included within the scope of protection of computer-readable media. The exemplary storage medium is coupled to the processor so that the processor can read and write information from / to the storage medium. In an alternative embodiment, the storage medium can be integrated into the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal (eg, an in-vehicle system, an external diagnostic device).

[0127] The present application also provides a computer device, including a storage module, a processor, and a computer program stored on the storage module and executable on the processor. When the processor executes the computer program, the above-mentioned part collision stress testing method of the present application is implemented.

[0128] The present application also provides a computer program product, including a computer program, which implements the above-mentioned part collision stress testing method of the present application when executed by a processor.

[0129] The specific embodiments described above are intended only to more clearly illustrate the principles of the present invention, wherein the various components are clearly shown or described to make the principles of the present invention easier to understand. Those skilled in the art may readily make various modifications or variations to the present invention without departing from the scope of the present invention. It should be understood that such modifications or variations are intended to be within the scope of the present invention.

Claims

1. A method for testing part collision stress based on digital image correlation, characterized in that: The method comprises the following steps: A post-processing comparison software module was developed within the digital image correlation testing software. The correspondence between the deformation of the speckle image on the specimen surface and the tensile load was obtained using a high-strain-rate tensile testing machine. Based on this correspondence, the stress-strain curve of the part material was calibrated. The curve was then filtered and averaged to obtain stress-strain curves corresponding to different strain rates. In the simulation software, a collision simulation is performed on the part based on a preset grid configuration to obtain a simulation result, and the grid of the CAE simulation software is mapped to a post-processing comparison module so that the simulation result and the measured data are aligned based on the same grid division; In the digital image correlation test software, the actual collision test of the parts is carried out to obtain the actual speckle measurement results, and the measured speckle pattern is re-divided according to the CAE grid division; as well as Based on the stress-strain curves corresponding to different strain rates and the aligned simulation results and speckle measurement results, the relationship between speckle deformation and force is substituted into the part strain field to calculate the stress field. Through strain comparison and / or stress comparison, the part collision stress test is realized.

2. The method according to claim 1, characterized in that The strain comparison process includes: In the post-processing comparison module, the three-dimensional coordinates and time-strain sequences of the simulated and measured grid nodes are extracted, the grid nodes in the key areas are screened by the maximum strain threshold, and a comparison diagram of their time-strain curves is output.

3. The method according to claim 1, characterized in that The stress comparison process includes: Based on the measured strain field after CAE mesh segmentation, the local strain rate of each mesh node is calculated to match the stress-strain curve at the corresponding rate, and the curve is linearly interpolated to the current strain rate to generate the true stress field at the node level.

4. The method according to claim 3, characterized in that For curves where the interval between adjacent strain rates exceeds the preset value, the cubic spline interpolation method is used to solve the stress value corresponding to the intermediate strain rate.

5. The method according to claim 3, characterized in that The true composite stress is solved using the following formula: σm=√(σx2+σy2+τxy2)×α Where σm is the true composite stress at the grid node m, σx, σy, and τxy represent the stress components in the x, y, and shear directions calculated based on the speckle deformation and force model, respectively, and α is the stress correction coefficient corresponding to the strain rate in the material calibration curve.

6. The method according to claim 1, wherein The mesh configuration includes the mesh size defined in the CAE software.

7. The method according to claim 1, characterized in that The speckle measurement results include three-dimensional deformation data of the part surface.

8. The method according to claim 1, characterized in that Wavelet transform filtering is used to eliminate speckle image noise, and averaging is achieved by weighted averaging of a preset number of test data under the same strain.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

10. A computer device comprising a storage module, a processor, and a computer program stored in the storage module and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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