High-precision performance characterization method and device for large complex thin-wall die-casting component

Abstract

The invention discloses a high-precision performance characterization method and device for a large complex thin-wall die-casting component, and relates to the technical field of data processing, and the method comprises the steps: obtaining and preprocessing engineering stress-strain curve data; accurately identifying and confirming a yield point, a necking point and a fracture starting point; based on an identification result, carrying out segmentation processing on the engineering stress-strain curve; performing fine fitting on the segmented curve to form an epitaxial curve; the epitaxial curve is verified, and data continuity and consistency are ensured; complementing the data according to a verification result, and generating a complete material hardening performance characterization report; and applying the representation report to a virtual simulation environment for calibration and optimization.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and device for high-precision performance characterization of large and complex thin-walled die-cast components. Background Art

[0002] In the modern automobile manufacturing industry, the crashworthiness of a vehicle refers to the ability to protect the safety of the occupants by sacrificing certain structures (such as body parts) to absorb collision energy when the vehicle collides. Specifically, crashworthiness refers to the ability of a vehicle to absorb energy through its own deformation during a collision, reduce the force acting on the occupants, and ensure that the occupants' living space is not affected. This is an important indicator for protecting the occupants from injury and measuring their safety.

[0003] How to accurately characterize and predict the mechanical properties of materials under impact conditions has become an urgent problem to be solved. In the process of material performance characterization, engineers' experience accounts for too much. The use of high-precision parametric material hardening performance characterization methods can greatly reduce labor costs and technical personnel's experience level. Summary of the invention

[0004] The purpose of this application is to provide a high-precision performance characterization method and device for large, complex, thin-walled die-cast components.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a high-precision performance characterization method for large, complex, thin-walled die-cast components, comprising: Acquire and preprocess engineering stress-strain curve data; Accurately identify and confirm the yield point, necking point and fracture initiation point; Based on the identification results, the engineering stress-strain curve is processed in sections; Finely fit the segmented curve to form an extension curve; Verify the extension curve to ensure data continuity and consistency; Complete the data based on the verification results and generate a complete material hardening performance characterization report; Use characterization reports in a virtual simulation environment for calibration and optimization.

[0006] Optionally, the step of acquiring and preprocessing engineering stress-strain curve data includes: Directly obtain original engineering stress-strain curve data from experimental testing equipment, and use a filter to smooth the data; Identify and extract valid data segments including yield point, necking point and fracture initiation point.

[0007] Optionally, the step of accurately identifying and confirming the yield point, the necking point and the fracture starting point includes: Calculate the first-order derivative of stress with respect to strain and smooth the first-order derivative through a filter; The second-order derivative is calculated based on the smoothed first-order derivative, and the yield point is confirmed by finding the first negative point after the maximum value of the second-order derivative; Determine the highest point of the stress-strain curve as the necking point; Based on the physical properties of the material and experimental conditions, the fracture starting point is comprehensively judged and confirmed.

[0008] Optionally, the step of performing segmented processing on the engineering stress-strain curve based on the recognition result includes: The engineering stress-strain curve is divided into multiple intervals according to the positions of the yield point, necking point and fracture initiation point; For each interval, the segmentation points are automatically determined according to the curvature change, ensuring that the segmented curve can accurately reflect the hardening performance changes of the material; Make necessary adjustments to the segmentation points to ensure the rationality of the segmentation and the continuity of the data.

[0009] Optionally, the step of performing fine fitting on the segmented curve to form an extension curve includes: Using a preset fitting algorithm to fit the segmented curve, the fitting algorithm at least includes: polynomial fitting or spline fitting; During the fitting process, the fitting parameters are dynamically adjusted according to the curvature and change trend of the curve to ensure that the fitting curve can smoothly transition and accurately reflect the hardening performance of the material; The fitting results were verified to ensure the consistency between the fitting curve and the original data.

[0010] Optionally, the step of verifying the epitaxial curve to ensure data continuity and consistency includes: Check whether the extension curve has a smooth transition at the segment connection to ensure data continuity; Compare the epitaxial curves with the original experimental data to verify their consistency; In the case of existing deviations, the fitting parameters or segmentation points are adjusted until the preset validation criteria are met.

[0011] Optionally, the step of completing the data according to the verification result to generate a complete material hardening performance characterization report includes: After the fracture initiation point, data completion is performed based on the trend of the extension curve to cover a wider range of data; Verify the completed data to ensure its continuity and consistency; The pre-processed engineering stress-strain curve data, the key characteristic point information identified and confirmed, the epitaxial curve after segmented fitting and the completed data are sorted and summarized to form a complete material hardening performance characterization report containing detailed analysis process and results.

[0012] In a second aspect, the present application provides a high-precision performance characterization device for large, complex, thin-walled die-cast components, comprising: An acquisition module is used to acquire and preprocess engineering stress-strain curve data; Identification module, used to accurately identify and confirm the yield point, necking point and fracture initiation point; A processing module, used for segmenting the engineering stress-strain curve based on the identification result; Finely fit the segmented curve to form an extension curve; Verify the extension curve to ensure data continuity and consistency; Complete the data based on the verification results and generate a complete material hardening performance characterization report; Use characterization reports in a virtual simulation environment for calibration and optimization.

[0013] Optionally, the acquisition module is further used to: Directly obtain original engineering stress-strain curve data from experimental testing equipment, and use a filter to smooth the data; Identify and extract valid data segments including yield point, necking point and fracture initiation point.

[0014] Optionally, the identification module is further used to: Calculate the first-order derivative of stress with respect to strain and smooth the first-order derivative through a filter; The second-order derivative is calculated based on the smoothed first-order derivative, and the yield point is confirmed by finding the first negative point after the maximum value of the second-order derivative; Determine the highest point of the stress-strain curve as the necking point; Based on the physical properties of the material and experimental conditions, the fracture starting point is comprehensively judged and confirmed.

[0015] Optionally, the processing module is further used to: The engineering stress-strain curve is divided into multiple intervals according to the positions of the yield point, necking point and fracture initiation point; For each interval, the segmentation points are automatically determined according to the curvature change, ensuring that the segmented curve can accurately reflect the hardening performance changes of the material; Make necessary adjustments to the segmentation points to ensure the rationality of the segmentation and the continuity of the data.

[0016] Optionally, the processing module is further used to: Using a preset fitting algorithm to fit the segmented curve, the fitting algorithm at least includes: polynomial fitting or spline fitting; During the fitting process, the fitting parameters are dynamically adjusted according to the curvature and change trend of the curve to ensure that the fitting curve can smoothly transition and accurately reflect the hardening performance of the material; The fitting results were verified to ensure the consistency between the fitting curve and the original data.

[0017] Optionally, the processing module is further used to: Check whether the extension curve has a smooth transition at the segment connection to ensure data continuity; Compare the epitaxial curves with the original experimental data to verify their consistency; In the case of existing deviations, the fitting parameters or segmentation points are adjusted until the preset validation criteria are met.

[0018] Optionally, the processing module is further used to: After the fracture initiation point, data completion is performed based on the trend of the extension curve to cover a wider range of data; Verify the completed data to ensure its continuity and consistency; The pre-processed engineering stress-strain curve data, the key characteristic point information identified and confirmed, the epitaxial curve after segmented fitting and the completed data are sorted and summarized to form a complete material hardening performance characterization report containing detailed analysis process and results.

[0019] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for high-precision performance characterization of large, complex, thin-walled die-cast components described in any one of the above.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described methods for high-precision performance characterization of large, complex, thin-walled die-cast components.

[0021] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods for high-precision performance characterization of large, complex, thin-walled die-cast components.

[0022] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a high-precision performance characterization method and device for large and complex thin-walled die-casting components. By acquiring and preprocessing engineering stress-strain curve data, the key performance points of the material are accurately identified, and then the engineering stress-strain curve is segmented based on these key points, and the segmented curve is finely fitted to form an epitaxial curve. On this basis, the epitaxial curve is further verified to ensure the continuity and consistency of the data, and then the data is supplemented according to the verification results to generate a complete material hardening performance characterization report. Finally, this characterization report is applied to a virtual simulation environment, and the simulation model is calibrated and optimized, which significantly improves the digital characterization accuracy of the material hardening performance. Through the accurate identification and segmented fitting of the engineering stress-strain curve, we can more accurately capture the hardening and softening behavior characteristics of the material, thereby improving the accuracy of the characterization results. At the same time, this high-precision characterization result is used to calibrate and optimize the virtual simulation model, so that the simulation results are closer to the actual experimental results, and the calibration efficiency of the simulation is significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A schematic diagram of a process for high-precision performance characterization of a large, complex, thin-walled die-cast component provided in one embodiment of the present application; Figure 2 A schematic diagram of functional modules of a high-precision performance characterization device for a large, complex, thin-walled die-cast component provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] like Figure 1 As shown, some embodiments of the present application provide a high-precision performance characterization method for a large, complex, thin-walled die-cast component. In the embodiments of the present application, the following steps 101 to 107 are included. Among them: Step 101: Acquire and preprocess engineering stress-strain curve data.

[0027] In the embodiment of the present application, first, the engineering stress-strain curve data of the material is obtained through experiments or existing databases. These data usually include stress values ​​and corresponding strain values. The acquired data may contain noise or unnecessary parts, so preprocessing is required. The specific steps include identifying and intercepting effective segments (such as removing the initial and final unstable parts of the curve), and using a filtering method (such as a Savitzky-Golay filter) to smooth the curve to reduce the impact of noise. Before filtering, it is necessary to first identify the yield point and the fracture starting point, and then intercept the effective segment.

[0028] Step 102, accurately identify and confirm the yield point, necking point and fracture starting point.

[0029] In the embodiments of the present application, the yield point is the point where the material transitions from elastic deformation to plastic deformation. For materials without obvious inflection points, a 0.2% offset is usually used as the yield point. The yield point can be identified by calculating the first-order derivative of stress with respect to strain, smoothing it with a Savitzky-Golay filter, and then finding the first negative value after the maximum value in the data after smoothing the second-order derivative. The necking point is the point where the material begins to show obvious necking during the stretching process, usually corresponding to the highest point of the curve. The necking point can be determined by calculating the true stress and true strain data after removing the elastic segment. The fracture initiation point is the point where the material is about to break, and it needs to be confirmed in the pre-processed curve based on the actual performance of the material.

[0030] Step 103: Based on the recognition result, the engineering stress-strain curve is processed in sections.

[0031] In the embodiment of the present application, the engineering stress-strain curve is segmented according to the identified key points (yield point, necking point, fracture initiation point, etc.). The purpose of segmentation is to more accurately describe the hardening and softening behavior of the material. The horizontal coordinate of the test point data is expanded to 50% of the effective true stress and true strain, and the number of segments and the position of each segment are automatically determined based on the input true stress-true strain data and its curvature.

[0032] The yield point can be determined by finding the first negative value after the maximum value in the smoothed second derivative data. This negative point marks the beginning of the transition from the elastic stage to the plastic stage of the stress-strain curve. Formula (1) is as follows: (1) True strain Calculation formula (2): (2) True stress Calculation formula (3): (3) in is the plastic strain, is the engineering stress.

[0033] Step 104, performing fine fitting on the segmented curve to form an extension curve.

[0034] In the embodiment of the present application, each segmented curve is fitted to form a continuous extension curve. During the fitting process, the smoothness and continuity of the curve need to be ensured. The automatic calibration algorithm based on slope control automatically adjusts the ordinate of the newly added test point until the slope between each test point and the previous test point meets a specific condition (0 or a negative value), ensuring that the curve correctly reflects the hardening and softening behavior of the material at the end point of each segment.

[0035] Step 105, verifying the epitaxial curve to ensure data continuity and consistency.

[0036] In the embodiment of the present application, the accuracy and reliability of the epitaxial curve are verified, including checking the continuity and consistency of the data and whether it conforms to the actual performance of the material. The verification can be performed by comparing the simulation results with the experimental results. By comparing the difference between the highest point simulation and the experimental results, the horizontal axis scaling factor is adjusted until the highest point simulation is consistent with the experiment.

[0037] Step 106, completing the data according to the verification results to generate a complete material hardening performance characterization report.

[0038] In the embodiment of the present application, the epitaxial curve is adjusted and optimized as necessary according to the verification results to generate a complete material hardening performance characterization report. The report should include information such as the material's engineering stress-strain curve, the identified key points, the segmented curve, the fitted epitaxial curve, and the verification results.

[0039] Step 107 , applying the characterization report to a virtual simulation environment for calibration and optimization.

[0040] In the embodiment of the present application, the generated material hardening performance characterization report is applied to the virtual simulation environment to calibrate and optimize the simulation model. By adjusting the simulation parameters and model settings, the simulation results are made closer to the actual experimental results, thereby improving the accuracy and reliability of the simulation. This can provide important technical support for subsequent material performance testing and vehicle structure design.

[0041] The embodiment of the present application obtains and pre-processes the engineering stress-strain curve data, accurately identifies the key performance points of the material, then performs segmented processing on the engineering stress-strain curve based on these key points, and performs fine fitting on the segmented curve to form an epitaxial curve. On this basis, the epitaxial curve is further verified to ensure the continuity and consistency of the data, and then the data is supplemented according to the verification results to generate a complete material hardening performance characterization report. Finally, this characterization report is applied to the virtual simulation environment, and the simulation model is calibrated and optimized, which significantly improves the digital characterization accuracy of the material hardening performance. Through the accurate identification and segmented fitting of the engineering stress-strain curve, we can more accurately capture the hardening and softening behavior characteristics of the material, thereby improving the accuracy of the characterization results. At the same time, this high-precision characterization result is used to calibrate and optimize the virtual simulation model, so that the simulation results are closer to the actual experimental results, and the calibration efficiency of the simulation is significantly improved.

[0042] Optionally, the step 101 includes: Step 1011, directly obtain original engineering stress-strain curve data from the experimental test equipment, and use a filter to smooth the data.

[0043] In the embodiment of the present application, during the test, the device will record the stress and strain changes of the material during the stress process to form the original engineering stress-strain curve data. These data are usually presented in the form of discrete points, including the corresponding relationship between stress and strain.

[0044] Since there may be factors such as noise and error in the experimental process, the raw data fluctuates greatly, which is not conducive to subsequent analysis. Therefore, it is necessary to use a filter to smooth the raw data. In the present invention, a Savitzky-Golay filter is used for smoothing. The filter smoothes the data by calculating the polynomial fitting value in the window around the data point, while retaining the characteristics and trends of the data. Through smoothing, the influence of noise and error on the data can be effectively reduced, and the accuracy and reliability of the data can be improved.

[0045] Step 1012, identifying and intercepting the valid data segment including the yield point, the necking point and the fracture starting point.

[0046] In the embodiment of the present application, the data after smoothing still contains a large number of data points, but not all data points are useful for subsequent analysis. Therefore, it is necessary to identify and intercept valid data segments containing key points. In the present invention, key points include yield points, necking points and fracture initiation points. These key points reflect the important mechanical properties of materials during stress. Automatically identifying these key points through algorithms and intercepting valid data segments containing these key points can provide a more accurate and reliable data basis for subsequent analysis.

[0047] Optionally, the step 102 includes: Step 1021, calculate the first-order derivative of stress with respect to strain, and smooth the first-order derivative through a filter.

[0048] In the present application embodiment, first, we use mathematical methods to process the stress-strain curve and calculate the first-order derivative of stress to strain. The purpose of this step is to capture the rate at which stress changes with strain, that is, the stiffness change of the material. Subsequently, we use a filter, such as a Savitzky-Golay filter, to smooth the calculated first-order derivative. The purpose of smoothing is to reduce noise and fluctuations in the data, so that the changing trend of the first-order derivative is clearer and more accurate.

[0049] Step 1022, calculating the second-order derivative based on the smoothed first-order derivative, and confirming the yield point by finding the first negative point after the maximum value of the second-order derivative.

[0050] In the embodiment of the present application, after obtaining the smoothed first-order derivative, we further calculate its second-order derivative. The second-order derivative reflects the speed of the stress change rate, that is, the rate of change of the material stiffness. By finding the first negative point after the maximum value of the second-order derivative, we can determine the yield point of the material. This is because the yield point is the critical point where the material changes from elastic deformation to plastic deformation. At this time, the stiffness of the material will change significantly, which is reflected in the second-order derivative as the first negative point after the maximum value.

[0051] Step 1023, determining the highest point of the stress-strain curve as the necking point.

[0052] In the embodiment of the present application, the necking point is the point corresponding to the cross-sectional shrinkage phenomenon caused by plastic deformation during the stretching process of the material. On the stress-strain curve, the necking point is usually shown as the highest point of the curve, that is, the point where the stress reaches the maximum value and the strain continues to increase. Therefore, we can determine the necking point by finding the highest point of the stress-strain curve.

[0053] Step 1024, comprehensively judge and confirm the fracture starting point based on the physical properties of the material and the experimental conditions.

[0054] In the embodiment of the present application, the fracture starting point is the point where cracks begin to appear in the material during the stretching process and may eventually lead to fracture. On the stress-strain curve, the fracture starting point may appear as a point where stress suddenly drops or strain increases sharply. However, due to the difference in the physical properties of the material and the experimental conditions, the performance of the fracture starting point may not be obvious or may change. Therefore, we need to make a comprehensive judgment based on the physical properties of the material (such as elastic modulus, yield strength, etc.) and experimental conditions (such as loading rate, ambient temperature, etc.), and confirm the position of the fracture starting point.

[0055] Optionally, the step 103 includes: Step 1031 , dividing the engineering stress-strain curve into a plurality of intervals according to the positions of the yield point, the necking point and the fracture starting point.

[0056] In the embodiment of the present application, first, we divide the entire curve into several intervals based on the positions of the yield point, necking point and fracture initiation point that have been identified and confirmed on the engineering stress-strain curve. These intervals represent the different mechanical properties exhibited by the material at different deformation stages. Before the yield point, the material is in the elastic deformation stage; between the yield point and the necking point, the material begins to enter the plastic deformation stage and exhibits hardening properties; after the necking point to the fracture initiation point, the hardening properties of the material may gradually weaken and tend to soften until it finally breaks. Through such a division, we can more clearly understand the performance changes of the material at different deformation stages.

[0057] Step 1032, for each interval, the segmentation points are automatically determined according to the curvature change, to ensure that the segmented curve can accurately reflect the hardening performance change of the material.

[0058] In an embodiment of the present application, after determining each interval, we further subdivide the curve within each interval. The purpose of this step is to more accurately capture the details of the changes in the hardening properties of the material. We use the curvature change of the curve as the basis for segmentation, and automatically determine the position of the segmentation point by calculating the curvature of each point and comparing it with a preset threshold. Areas with larger curvatures indicate that the hardening properties of the material change faster, so more segmentation points are needed to capture this change. Through such subdivision, we can ensure that the segmented curve can more accurately reflect the changes in the hardening properties of the material, and provide more valuable information for subsequent data processing and analysis.

[0059] Step 1033, make necessary adjustments to the segmentation points to ensure the rationality of the segmentation and the continuity of the data.

[0060] In an embodiment of the present application, after automatically determining the segmentation points, we also need to make necessary adjustments to the segmentation points. The purpose of this step is to ensure the rationality of the segmentation and the continuity of the data. We check whether each segmentation point is located near the inflection point or extreme point of the curve to ensure that the segmentation can accurately reflect the changing trend of the curve. At the same time, we also check whether the data between the segmentation points is continuous to avoid data breaks or jumps. If it is found that the segmentation points are unreasonable or the data is discontinuous, we will adjust the segmentation points until the requirements are met. Through such adjustments, we can ensure that the segmented curve can not only accurately reflect the changes in the hardening properties of the material, but also maintain the continuity and integrity of the data.

[0061] Optionally, the step 104 includes: Step 1041: Use a preset fitting algorithm to perform fitting processing on the segmented curve, and the fitting algorithm at least includes: polynomial fitting or spline fitting.

[0062] In the embodiment of the present application, after completing the segmentation of the engineering stress-strain curve, we then use a preset fitting algorithm to fit the segmented curve. These algorithms may include polynomial fitting or spline fitting, etc., which are commonly used curve fitting methods, and can select the most appropriate fitting method according to different data characteristics and requirements. Polynomial fitting is to approximate the original data points by constructing a polynomial function, while spline fitting is to smoothly connect a series of low-order polynomials (such as cubic splines) at the segmentation points to form an overall fitting curve.

[0063] Step 1042, during the fitting process, dynamically adjust the fitting parameters according to the curvature and change trend of the curve to ensure that the fitting curve can smoothly transition and accurately reflect the hardening performance of the material.

[0064] In the embodiments of the present application, the fitting process is not static, but needs to be dynamically adjusted according to the actual curvature and change trend of the curve. We pay close attention to the deviation between the fitting curve and the original data points, especially in the inflection points, extreme points and areas where the hardening performance changes significantly. By adjusting the parameters in the fitting algorithm, such as the order of the polynomial, the node position of the spline, etc., we can make the fitting curve closer to the original data while maintaining the smoothness and continuity of the curve. In this way, the fitting curve can not only accurately reflect the hardening performance of the material, but also achieve a smooth transition between different segments, avoiding the abruptness or fracture caused by segmented fitting.

[0065] Step 1043, verifying the fitting result to ensure the consistency between the fitting curve and the original data.

[0066] In the embodiments of the present application, we strictly verify the fitting results to ensure the consistency of the fitting curve with the original data. This step is crucial because it is directly related to the reliability and accuracy of the fitting results. We use a variety of verification methods, such as calculating the error between the fitting curve and the original data points, drawing residual graphs, etc., to comprehensively evaluate the fitting effect. If the verification results show that there is a significant deviation or inconsistency between the fitting curve and the original data, we will readjust the fitting parameters or select other fitting algorithms until a satisfactory fitting result is obtained. Through such a verification process, we can ensure that the fitting curve is not only mathematically close to the original data, but also physically able to accurately reflect the hardening properties of the material.

[0067] Optionally, the step 105 includes: Step 1051, check whether the extension curve has a smooth transition at the segment connection to ensure the continuity of the data.

[0068] In the embodiment of the present application, after completing the fitting process of each segmented curve and forming the overall extension curve, the first task is to check the smoothness of this curve at the segment connection. This is because segmented fitting may cause discontinuity or abruptness at the connection point, thereby affecting the overall continuity of the data and the accuracy of subsequent analysis. We carefully review each segment connection point and determine whether it has achieved a smooth transition by observing the changing trend and slope of the curve at these points. If any unevenness or breakage is found, we will record it and make it the focus of subsequent adjustments.

[0069] Step 1052, comparing the epitaxial curve with the original experimental data to verify their consistency.

[0070] In the present application example, we compare the extension curve with the original experimental data to verify the consistency between them. This step is the key to ensure the accuracy of the fitting result. We use a variety of methods to compare, including but not limited to calculating the error between the two, drawing a comparison chart, performing statistical analysis, etc. Through these methods, we can intuitively see whether the extension curve is consistent with the original data in terms of overall trend and key points, and whether there is a significant deviation.

[0071] Step 1053, in the case of existing deviations, the fitting parameters or segmentation points are adjusted until the preset verification criteria are met.

[0072] In the embodiment of the present application, if the extension curve is found to deviate from the original data during the comparison process, we will make adjustments immediately. The objects of adjustment may include parameters in the fitting algorithm, such as the order of the polynomial, the tension of the spline, etc., or the position of the segmentation point. The goal of the adjustment is to make the extension curve closer to the original data while maintaining the smoothness and continuity of the curve. We will adjust the relevant parameters or segmentation points in a targeted manner according to the size and distribution of the deviation, and re-fit and verify. This process will be repeated until the deviation between the extension curve and the original data meets the preset verification criteria. These standards may include statistical indicators such as the maximum error, mean error, standard deviation, and other specific standards set according to actual application requirements. Through such adjustments and optimizations, we can ensure that the final extension curve is both accurate and reliable, providing a solid foundation for subsequent material performance analysis and virtual simulation.

[0073] Optionally, the step 106 includes: Step 1061 , after the fracture starting point, data completion is performed based on the trend of the extension curve to cover a wider data range.

[0074] In the examples of the present application, after determining the fracture starting point, we noticed that the original engineering stress-strain curve data may not be available after this point due to experimental conditions or material fracture. In order to obtain a more complete and wider range of data, we perform data completion based on the trend of the fitted epitaxial curve. This step involves predicting and extending the behavior of the epitaxial curve after the fracture starting point, usually based on the existing trend of the curve, the physical properties of the material, and possible fracture mechanisms. The completed data should reflect the stress-strain behavior of the material after fracture as accurately as possible. Although this part of the data is based on predictions and assumptions, it is crucial to fully understand the hardening properties and fracture behavior of the material.

[0075] Step 1062, verify the completed data to ensure its continuity and consistency.

[0076] In the embodiments of the present application, after completing the data, we must conduct strict verification to ensure the continuity and consistency of the data. The verification of continuity mainly checks whether the completed data and the original data and the part of the extension curve before the fracture starting point can be smoothly connected without abruptness or fracture. The verification of consistency is to evaluate the rationality and accuracy of the completed data by comparing the completed data with the physical properties of the material, known experimental results, and possible fracture mechanisms. If the verification results show that there is a problem with the completed data, we will readjust the completion method or parameters until satisfactory results are obtained.

[0077] Step 1063, collating and summarizing the pre-processed engineering stress-strain curve data, the identified and confirmed key feature point information, the segmented fitting epitaxial curve and the completed data, to form a complete material hardening performance characterization report containing detailed analysis process and results.

[0078] In the examples of this application, we organize and summarize all the data obtained during the entire processing process, including the engineering stress-strain curve data after pretreatment, the key characteristic point information such as the yield point, necking point, and fracture starting point that are identified and confirmed, the epitaxial curve after segmented fitting, and the completed data. At the same time, we will also record the entire analysis process in detail, including the data processing method, the selection and parameter setting of the fitting algorithm, the identification and confirmation method of key characteristic points, the method of data completion and the verification results, etc. All of this information and data will be integrated into a complete material hardening performance characterization report, which will comprehensively and in detail display the hardening performance and fracture behavior of the material, and provide strong support for subsequent material research and development, design, and application.

[0079] Based on the same inventive concept, the embodiment of the present application also provides a large-scale complex thin-walled die-casting component high-precision performance characterization device for implementing the large-scale complex thin-walled die-casting component high-precision performance characterization method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more large-scale complex thin-walled die-casting component high-precision performance characterization device embodiments provided below can refer to the limitations of the large-scale complex thin-walled die-casting component high-precision performance characterization method above, and will not be repeated here.

[0080] In an exemplary embodiment, Figure 2 As shown, a high-precision performance characterization device 20 for large complex thin-walled die-casting components is provided, comprising: An acquisition module 201 is used to acquire and preprocess engineering stress-strain curve data; Identification module 202, used to accurately identify and confirm the yield point, necking point and fracture starting point; A processing module 203 is used to perform segment processing on the engineering stress-strain curve based on the recognition result; Finely fit the segmented curve to form an extension curve; Verify the extension curve to ensure data continuity and consistency; Complete the data based on the verification results and generate a complete material hardening performance characterization report; Use characterization reports in a virtual simulation environment for calibration and optimization.

[0081] Optionally, the acquisition module 201 is further used to: Directly obtain original engineering stress-strain curve data from experimental testing equipment, and use a filter to smooth the data; Identify and extract valid data segments including yield point, necking point and fracture initiation point.

[0082] Optionally, the identification module 202 is further configured to: Calculate the first-order derivative of stress with respect to strain and smooth the first-order derivative through a filter; The second-order derivative is calculated based on the smoothed first-order derivative, and the yield point is confirmed by finding the first negative point after the maximum value of the second-order derivative; Determine the highest point of the stress-strain curve as the necking point; Based on the physical properties of the material and experimental conditions, the fracture starting point is comprehensively judged and confirmed.

[0083] Optionally, the processing module 203 is further configured to: The engineering stress-strain curve is divided into multiple intervals according to the positions of the yield point, necking point and fracture initiation point; For each interval, the segmentation points are automatically determined according to the curvature change, ensuring that the segmented curve can accurately reflect the hardening performance changes of the material; Make necessary adjustments to the segmentation points to ensure the rationality of the segmentation and the continuity of the data.

[0084] Optionally, the processing module 203 is further configured to: Using a preset fitting algorithm to fit the segmented curve, the fitting algorithm at least includes: polynomial fitting or spline fitting; During the fitting process, the fitting parameters are dynamically adjusted according to the curvature and change trend of the curve to ensure that the fitting curve can smoothly transition and accurately reflect the hardening performance of the material; The fitting results were verified to ensure the consistency between the fitting curve and the original data.

[0085] Optionally, the processing module 203 is further configured to: Check whether the extension curve has a smooth transition at the segment connection to ensure data continuity; Compare the epitaxial curves with the original experimental data to verify their consistency; In the case of existing deviations, the fitting parameters or segmentation points are adjusted until the preset validation criteria are met.

[0086] Optionally, the processing module 203 is further configured to: After the fracture initiation point, data completion is performed based on the trend of the extension curve to cover a wider range of data; Verify the completed data to ensure its continuity and consistency; The pre-processed engineering stress-strain curve data, the key characteristic point information identified and confirmed, the epitaxial curve after segmented fitting and the completed data are sorted and summarized to form a complete material hardening performance characterization report containing detailed analysis process and results.

[0087] The embodiment of the present application obtains and pre-processes the engineering stress-strain curve data, accurately identifies the key performance points of the material, then performs segmented processing on the engineering stress-strain curve based on these key points, and performs fine fitting on the segmented curve to form an epitaxial curve. On this basis, the epitaxial curve is further verified to ensure the continuity and consistency of the data, and then the data is supplemented according to the verification results to generate a complete material hardening performance characterization report. Finally, this characterization report is applied to the virtual simulation environment, and the simulation model is calibrated and optimized, which significantly improves the digital characterization accuracy of the material hardening performance. Through the accurate identification and segmented fitting of the engineering stress-strain curve, we can more accurately capture the hardening and softening behavior characteristics of the material, thereby improving the accuracy of the characterization results. At the same time, this high-precision characterization result is used to calibrate and optimize the virtual simulation model, so that the simulation results are closer to the actual experimental results, and the calibration efficiency of the simulation is significantly improved.

[0088] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store high-precision performance characterization data of large and complex thin-walled die-casting components. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a high-precision performance characterization method for large and complex thin-walled die-casting components is implemented.

[0089] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0090] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0091] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0092] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0093] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0094] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0095] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0096] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0097] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A high-precision performance characterization method for large, complex, thin-walled die-cast components, characterized in that: The high-precision performance characterization method of the large-scale complex thin-walled die-casting component includes: Acquire and preprocess engineering stress-strain curve data; Accurately identify and confirm the yield point, necking point and fracture initiation point; Based on the identification results, the engineering stress-strain curve is processed in sections; Finely fit the segmented curve to form an extension curve; Verify the extension curve to ensure data continuity and consistency; Complete the data based on the verification results and generate a complete material hardening performance characterization report; Use characterization reports in a virtual simulation environment for calibration and optimization.

2. The high-precision performance characterization method for large, complex, thin-walled die-cast components according to claim 1 is characterized in that: The step of obtaining and preprocessing engineering stress-strain curve data includes: Directly obtain original engineering stress-strain curve data from experimental testing equipment, and use a filter to smooth the data; Identify and extract valid data segments including yield point, necking point and fracture initiation point.

3. The high-precision performance characterization method for large, complex, thin-walled die-casting components according to claim 1 is characterized in that: The steps of accurately identifying and confirming the yield point, the necking point and the fracture starting point include: Calculate the first-order derivative of stress with respect to strain and smooth the first-order derivative through a filter; The second-order derivative is calculated based on the smoothed first-order derivative, and the yield point is confirmed by finding the first negative point after the maximum value of the second-order derivative; Determine the highest point of the stress-strain curve as the necking point; Based on the physical properties of the material and experimental conditions, the fracture starting point is comprehensively judged and confirmed.

4. The high-precision performance characterization method for large, complex, thin-walled die-cast components according to claim 1, characterized in that: The step of segmenting the engineering stress-strain curve based on the identification result includes: The engineering stress-strain curve is divided into multiple intervals according to the positions of the yield point, necking point and fracture initiation point; For each interval, the segmentation points are automatically determined according to the curvature change, ensuring that the segmented curve can accurately reflect the hardening performance changes of the material; Make necessary adjustments to the segmentation points to ensure the rationality of the segmentation and the continuity of the data.

5. The high-precision performance characterization method for large-scale complex thin-walled die-casting components according to claim 1 is characterized in that: The step of finely fitting the segmented curve to form an extension curve includes: Using a preset fitting algorithm to fit the segmented curve, the fitting algorithm at least includes: polynomial fitting or spline fitting; During the fitting process, the fitting parameters are dynamically adjusted according to the curvature and change trend of the curve to ensure that the fitting curve can smoothly transition and accurately reflect the hardening performance of the material; The fitting results were verified to ensure the consistency between the fitting curve and the original data.

6. The high-precision performance characterization method for large, complex, thin-walled die-cast components according to claim 1, characterized in that: The step of verifying the epitaxial curve to ensure data continuity and consistency includes: Check whether the extension curve has a smooth transition at the segment connection to ensure data continuity; Compare the epitaxial curves with the original experimental data to verify their consistency; In the case of existing deviations, the fitting parameters or segmentation points are adjusted until the preset validation criteria are met.

7. The high-precision performance characterization method for large, complex, thin-walled die-cast components according to claim 1, characterized in that: The step of completing the data according to the verification results and generating a complete material hardening performance characterization report includes: After the fracture initiation point, data completion is performed based on the trend of the extension curve to cover a wider range of data; Verify the completed data to ensure its continuity and consistency; The pre-processed engineering stress-strain curve data, the key characteristic point information identified and confirmed, the epitaxial curve after segmented fitting and the completed data are sorted and summarized to form a complete material hardening performance characterization report containing detailed analysis process and results.

8. A high-precision performance characterization device for large, complex, thin-walled die-casting components, characterized in that: The high-precision performance characterization device for large-scale complex thin-walled die-casting components includes: An acquisition module is used to acquire and preprocess engineering stress-strain curve data; Identification module, used to accurately identify and confirm the yield point, necking point and fracture initiation point; A processing module, used for segmenting the engineering stress-strain curve based on the identification result; Finely fit the segmented curve to form an extension curve; Verify the extension curve to ensure data continuity and consistency; Complete the data based on the verification results and generate a complete material hardening performance characterization report; Use characterization reports in a virtual simulation environment for calibration and optimization.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for high-precision performance characterization of large, complex, thin-walled die-cast components as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for high-precision performance characterization of large-scale complex thin-walled die-cast components described in any one of claims 1-7 are implemented.

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