Test piece stress data processing method based on stress distribution mean value and related equipment thereof

Abstract

This invention provides a method and related equipment for processing specimen stress data based on the mean stress distribution, comprising: determining the mean stress distribution of a target specimen; constructing a dynamic response reconstruction model based on the mean stress distribution; constructing a stress distribution function of the target specimen using a preset optimization algorithm; substituting the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen; and testing and judging the applicability or failure risk of the target specimen under preset working conditions based on the target stress data. Through the above method steps, the actual stress state of the specimen under dynamic loading conditions can be analyzed, providing data for specimen performance evaluation and improving the accuracy and efficiency of specimen stress analysis.

Description

Technical Field

[0001] This invention relates to the field of dynamic mechanical property testing of solid materials, and in particular to a method, apparatus, electronic device and storage medium for processing specimen stress data based on the mean stress distribution. Background Technology

[0002] The split-type Hopkinson pressure bar is used to test strain rates of 10. 2 -10 4 s -1 Commonly used techniques for measuring the dynamic mechanical properties of materials in a wide range of applications. The SHPB (Split-Hopkinson-Pressure-Bar) test is based on the principle of one-dimensional elastic wave dynamics. It uses strain measurements on the SHPB elastic bar to obtain incident, reflected, and transmitted wave data. Existing data processing methods, such as two-wave and three-wave analysis, are typically used to calculate and reconstruct the stress, strain, and strain rate of the specimen. Based on the reconstructed stress-strain curve, the yield strength, compressive strength, and elastic modulus of the specimen material are determined.

[0003] Traditional SHPB (Strain-Restrain-Pulse Biometry) testing methods typically rely on single-point stress signals at the specimen ends for calculations, assuming a uniform stress distribution within the specimen to derive stress, strain, and strain rate. This approach fails to accurately reflect the internal stress state of the specimen under high-strain-rate impact conditions, especially given the temporal evolution and spatial distribution differences in stress propagation during impact. Relying solely on end-point data for overall stress estimation often introduces errors. Furthermore, existing methods typically lack a corresponding stress function model based on the actual internal stress distribution characteristics and a process for establishing a dynamic response reconstruction model through unified physical interpretation. This leads to discrepancies between the performance evaluation results obtained in the experiment and the dynamic mechanical properties of the specimen, making it difficult to accurately identify the specimen's suitability or potential failure risk under different operating conditions.

[0004] Therefore, the stress-strain curves of specimens obtained by existing specimen stress data processing methods based on the average stress of both ends or the stress of a single end have problems such as high reconstruction error and low data accuracy. Summary of the Invention

[0005] This invention provides a specimen stress data processing method based on the average stress distribution, which solves the problems of high reconstruction error and low data accuracy of specimen stress-strain curves obtained by existing specimen stress data processing methods based on the average stress values ​​of two end faces or the stress of a single end face.

[0006] Compared with existing technologies, the advantages of this invention are that it avoids the systematic errors introduced by traditional specimen stress data processing methods based on the average stress of both ends or the stress of a single end, when the equivalent conditions of the end faces are insufficient. It also improves the accuracy and stability of the overall stress state reconstruction of the specimen, ensuring consistent calculation basis for dynamic indicators such as stress, strain, and strain rate, and enhancing the accuracy of the specimen's stress-strain curve.

[0007] In a first aspect, the present invention provides a method for processing specimen stress data based on the mean stress distribution, the method comprising the following steps:

[0008] Determine the mean stress distribution of the target specimen;

[0009] Based on the mean stress distribution, a dynamic response reconstruction model is constructed;

[0010] The stress distribution function of the target specimen is constructed using a preset optimization algorithm;

[0011] The stress distribution function is substituted into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen.

[0012] Based on the target stress data, the applicability or failure risk of the target specimen under preset working conditions is tested and judged.

[0013] Optionally, determining the mean stress distribution of the target specimen includes:

[0014] The force response of the target specimen at a preset position is collected in real time to obtain the dynamic response data of the target specimen. The dynamic response data is used to describe the change in the end force of the target specimen.

[0015] Based on the dynamic response data, the internal stress distribution of the target specimen is calculated to obtain the average stress distribution.

[0016] Optionally, the dynamic response reconstruction model includes a stress reconstruction model, a strain reconstruction model, and a strain rate reconstruction model. The step of constructing the dynamic response reconstruction model based on the mean stress distribution includes:

[0017] Based on the mean stress distribution, target correlation parameters of the target specimen are determined, and the target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen.

[0018] Based on the target correlation parameters, the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model are constructed respectively.

[0019] Optionally, constructing the stress distribution function of the target specimen using a preset optimization algorithm includes:

[0020] Based on the dynamic response data of the target specimen and the mean stress distribution, an objective function is determined, which is used to characterize the internal stress distribution characteristics of the target specimen.

[0021] The objective function is solved using the preset optimization algorithm to obtain the stress distribution function.

[0022] Optionally, substituting the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen includes:

[0023] The stress distribution function is used as an input parameter to the dynamic response reconstruction model to calculate the stress response of the target specimen during dynamic loading, thereby obtaining stress response calculation data.

[0024] Based on the force response calculation data, the characteristics of the internal force of the target specimen changing with time and the characteristics of the force changing along the spatial position are extracted and processed to obtain time distribution characteristic data and spatial distribution characteristic data.

[0025] Based on the time distribution characteristic data and spatial distribution characteristic data, the overall stress state of the target specimen is analyzed to obtain the target stress data.

[0026] Optionally, the step of analyzing the overall stress state of the target specimen based on the time distribution characteristic data and spatial distribution characteristic data to obtain target stress data includes:

[0027] Based on the time distribution characteristic data, the first force characteristic data is determined, which is used to reflect the dynamic force change law of the target specimen;

[0028] Based on the spatial distribution characteristic data, second force characteristic data is determined, which is used to reflect the internal force distribution state of the target specimen.

[0029] The target stress data is obtained by correlating the first stress characteristic data and the second stress characteristic data. The target stress data is used to characterize the overall stress state of the target specimen.

[0030] Optionally, the step of testing and judging the suitability or failure risk of the target specimen under preset working conditions based on the target stress data includes:

[0031] Based on the target stress data, the dynamic stress-strain response curve of the target specimen is constructed;

[0032] Based on the dynamic stress-strain response curve, the mechanical performance data of the target specimen under the preset working conditions are determined. The mechanical performance data includes the stress threshold, structural limit, and deformation characteristics.

[0033] Based on the stress threshold, structural limit, and deformation characteristics of the target specimen under preset working conditions, the applicability or failure risk of the target specimen under the preset working conditions is tested and judged.

[0034] Secondly, the present invention also provides a specimen stress data processing device based on the average stress distribution value, the specimen stress data processing device based on the average stress distribution value includes:

[0035] The first acquisition module is used to determine the mean stress distribution of the target specimen;

[0036] The first construction module is used to construct a dynamic response reconstruction model based on the mean stress distribution.

[0037] The second construction module is used to construct the stress distribution function of the target specimen through a preset optimization algorithm;

[0038] The first determining module is used to substitute the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen.

[0039] The testing module is used to test and determine the suitability or failure risk of the target specimen under preset working conditions based on the target stress data.

[0040] Thirdly, the present invention provides an electronic 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 in the specimen stress data processing method based on the mean stress distribution provided by the present invention.

[0041] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in the specimen stress data processing method based on the mean stress distribution provided by the invention.

[0042] This invention determines the mean stress distribution of a target specimen; constructs a dynamic response reconstruction model based on the mean stress distribution; constructs a stress distribution function of the target specimen using a preset optimization algorithm; substitutes the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen; and tests and judges the applicability or failure risk of the target specimen under preset working conditions based on the target stress data.

[0043] Compared with the prior art, the beneficial effects of the present invention are that it can avoid the systematic errors introduced by the traditional specimen stress data processing method based on the average stress of both ends or the stress of a single end when the equivalent conditions of the end face are insufficient, and improve the accuracy and stability of the overall stress state reconstruction of the specimen, so that the dynamic indicators such as stress, strain and strain rate have a consistent calculation basis, and improve the accuracy of the stress-strain curve of the specimen. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart of a specimen stress data processing method based on the mean stress distribution provided in an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of an SHPB experimental apparatus provided in an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of a specimen stress data processing device based on the mean stress distribution provided in an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, Figure 1 This is a flowchart of a specimen stress data processing method based on the mean stress distribution provided by an embodiment of the present invention. The specimen stress data processing method based on the mean stress distribution includes the following steps:

[0051] 101. Determine the mean stress distribution of the target specimen.

[0052] In this embodiment of the invention, the above-mentioned specimen stress data processing method based on the mean stress distribution can be applied to a specimen stress data processing platform based on the mean stress distribution. The specimen stress data processing platform based on the mean stress distribution has functions such as stress data processing, stress data transmission and reception, and stress data memory storage, and can be built based on a server or server cluster. The server or server cluster can be an electronic device with stress data processing capabilities.

[0053] In this embodiment, the target specimen stress testing platform based on the average stress distribution can use strain gauges, fiber optic sensors, or dynamic response acquisition devices installed at the loading and support ends to detect the end stress wave signals of the target specimen during the SHPB impact loading process in real time, and convert the detected electrical signals into processable dynamic response data. Essentially, this involves collecting raw information about the stress state of the target specimen, which is the fundamental data source for subsequent calculations of the internal stress distribution and model construction. For example, when the target specimen is subjected to impact loading, the stress waveform changes at the loading end will form a signal curve in real time, containing key laws such as internal force propagation, stress peak changes, and elastoplastic deformation. This raw data is collected using the method described above.

[0054] The aforementioned target specimens refer to test samples whose impact response and mechanical properties are verified through SHPB dynamic testing. These can be metallic materials, rock materials, composite materials, engineering structural components, or other industrial materials requiring mechanical testing. During dynamic impact loading, stress propagation, stress wave superposition, and plastic yielding characteristics will occur within the target specimen, all of which can be identified and analyzed using the aforementioned target specimen stress testing platform based on the average stress distribution.

[0055] The aforementioned average stress distribution can be used to characterize the true internal stress state of the target specimen under dynamic impact. Specifically, the target specimen stress testing platform based on the average stress distribution can estimate the stress at different spatial locations inside the specimen through inversion analysis and internal stress distribution calculation, based on the collected dynamic response data at the specimen end. This ultimately yields a statistical equilibrium value of the internal stress across the entire domain. It should be noted that the aforementioned average stress distribution is not a single-point stress at the end face measurement point, nor is it a simple mathematical average. It is an average value of internal stress characteristics derived from wave propagation characteristics, boundary continuity, and the mechanical response relationship of the specimen, used as a unified dynamic calculation input.

[0056] It is understandable that the above-mentioned average stress distribution in this embodiment allows stress, strain and strain rate analysis to be performed under the same physical meaning, avoiding the problem of overall stress inversion deviation caused by traditional testing methods relying only on end data.

[0057] 102. Based on the mean stress distribution, construct a dynamic response reconstruction model.

[0058] In this embodiment of the invention, a mathematical model or describing function with engineering calculation significance can be established using the mean stress distribution. Specifically, the target specimen stress testing platform based on the mean stress distribution is reshaped through basic parameter combinations, variable correlations, and response relationships to form a model structure for further calculations. For example, after obtaining the mean stress distribution, the target specimen stress testing platform based on the mean stress distribution converts the stress characteristics of the target specimen into a set of input parameters that can be used for dynamic solution, and constructs a dynamic response reconstruction model for subsequent force field solution.

[0059] The aforementioned dynamic response reconstruction model can refer to a unified model structure capable of simultaneously outputting stress, strain, and strain rate, including but not limited to stress reconstruction models, strain reconstruction models, and strain rate reconstruction models. This dynamic response reconstruction model does not rely on the traditional three-wave method's averaging of stresses on both ends of the specimen, nor does it rely on the two-wave method's equivalent averaging of stresses on a single end and assuming equal stresses on both ends of the specimen. Instead, it establishes unified physical conditions through the distribution mean, thus providing a consistent calculation basis for the three types of dynamic indicators. For example, during impact loading, the aforementioned dynamic response reconstruction model can be used to obtain information such as the location of the maximum stress on the target specimen, the trend of deformation rate changes, and the stress differences in various internal regions, achieving extended reconstruction from external single-point signals to internal force field calculations.

[0060] 103. Construct the stress distribution function of the target specimen through a preset optimization algorithm.

[0061] In this embodiment of the invention, the above-mentioned preset optimization algorithm can be used as a calculation strategy for fitting the internal force distribution characteristics of the target specimen. The aim is to make the internal force distribution function satisfy the continuity of the specimen's force and the law of the real mechanical response by solving the objective function. This includes, but is not limited to, iterative optimization, variational fitting, minimum error convergence criterion, or other calculation strategies that can achieve distribution fitting.

[0062] For example, by optimizing the dynamic response and distribution mean at the end, an internal stress distribution function that best matches the stress state of the specimen can be generated, so that it can truly reflect the internal force transmission and strength change of the specimen during the impact process.

[0063] The stress distribution function mentioned above can be a functional expression or characteristic relationship obtained by solving the objective function through a preset optimization algorithm to describe the spatial distribution law of the internal force of the specimen. It is used to reflect the stress level, stress gradient change and stress peak position corresponding to different spatial positions of the target specimen during dynamic loading. It can be used as the input parameter in the subsequent dynamic response reconstruction model. For example, when the target specimen is subjected to a shock wave at one end, the internal stress will show a waveform change along the propagation direction. This waveform change can be described by the stress distribution function, thus providing a basis for the subsequent overall stress calculation.

[0064] 104. Substitute the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen.

[0065] In this embodiment of the invention, the target specimen stress testing platform based on the mean stress distribution can input the stress distribution function into the dynamic response reconstruction model. Based on the time history changes of the impact loading process, the internal stress response of the specimen is solved. Specifically, the solution process can include information such as the change of stress over time, stress propagation speed, waveform superposition, and the synergistic effect of internal model parameters, which are used to generate global response data of the dynamic stress state of the specimen.

[0066] For example, the calculation results of the above dynamic response reconstruction model can display information such as the time when the peak force of the target specimen occurs, the location of uneven internal force, and the force propagation trend.

[0067] In one possible embodiment, the target specimen stress testing platform based on the average stress distribution analyzes and extracts the internal stress of the specimen based on the calculated stress response results, and finally obtains a quantitative stress index that can truly reflect the overall dynamic stress state of the specimen, namely the target stress data.

[0068] The target stress data mentioned above comes from the results of global stress calculation and spatiotemporal characteristic analysis. It can characterize the load-bearing capacity of the specimen under a unified physical meaning. For example, the target stress data can be used to identify the true yield point, ultimate strength and softening trend of the specimen, so that the obtained strength evaluation results are closer to the true capacity of the specimen under impact conditions.

[0069] 105. Based on the target stress data, test and judge the applicability or failure risk of the target specimen under the preset working conditions.

[0070] In this embodiment of the invention, the aforementioned preset working condition can refer to the pre-set stress environment conditions of the specimen, including but not limited to impact strength, loading rate, strain rate level, temperature range, or other test scenario parameters. It is understood that the aforementioned preset working condition can be used to determine the stress analysis boundary of the target specimen, giving the evaluation of the target stress data a clear test object and target. For example, when a material is used in the protective structure of high-speed equipment and needs to ensure it does not fail under high strain rate conditions, the corresponding "preset working condition" can be set to a high-speed impact loading state to determine whether the material can meet the application requirements.

[0071] In one possible embodiment, the target specimen stress testing platform based on the average stress distribution can use target stress data, characteristic points of the stress-strain response curve, and dynamic performance indicators to determine whether the target specimen meets the stress bearing requirements under preset working conditions, or whether there is a risk of entering the failure boundary. For example, by analyzing the peak position, nonlinear change segment, and strength critical point of the curve corresponding to the target stress data, it can be determined whether the target specimen exhibits yielding, failure, or material softening behavior, thereby achieving a suitability assessment of the target specimen.

[0072] By employing the above methods and steps, a comprehensive reconstruction of the internal stress state of the specimen can be achieved based on real dynamic response data. Compared to traditional methods that rely solely on the assumption of single-point stress at the ends, this embodiment can accurately present the internal stress distribution of the specimen, obtain target stress data that reflects the true load-bearing capacity, and perform stress-strain characteristic analysis under a unified physical meaning, thereby improving the accuracy and reliability of specimen performance evaluation.

[0073] In this embodiment of the invention, the mean stress distribution of the target specimen is determined; a dynamic response reconstruction model is constructed based on the mean stress distribution; a stress distribution function of the target specimen is constructed using a preset optimization algorithm; the stress distribution function is substituted into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen; based on the target stress data, the applicability or failure risk of the target specimen under preset working conditions is tested and judged. Through the above method steps, the actual stress state of the specimen under dynamic loading conditions can be analyzed, providing data for specimen performance evaluation and improving the accuracy and efficiency of specimen stress analysis.

[0074] Optionally, in the step of determining the average stress distribution of the target specimen, the stress response of the target specimen at a preset position can be collected in real time to obtain dynamic response data of the target specimen. The dynamic response data is used to describe the end stress change of the target specimen. Based on the dynamic response data, the internal stress distribution of the target specimen is calculated and processed to obtain the average stress distribution.

[0075] In this embodiment of the invention, the aforementioned preset location may refer to a data acquisition point corresponding to the force transmission path at the end of the target specimen. This location is usually selected in the end face area where the specimen is connected and in contact with the incident rod or transmission rod, and is used to collect the force signal of the specimen during the dynamic impact loading process.

[0076] Specifically, the aforementioned preset positions can be determined based on the propagation law of the shock wave on the target specimen. Since the shock wave first enters from the end of the specimen and propagates inward, the end position can directly reflect the force change of the specimen at the moment of impact. By using these preset positions, the collected data can be ensured to have temporal integrity and representative impact response.

[0077] For example, in the SHPB test, the stress waveform at the end face of the target specimen is obtained by collecting data at the aforementioned preset location.

[0078] The aforementioned stress response refers to the characteristics of the stress wave signal generated by the target specimen under dynamic loading, including but not limited to information such as peak force, rise time morphology, waveform trend, and stress duration, used to reflect the actual stress state of the specimen under impact load. It is understood that the stress response is typically manifested through resistance strain signals generated at the specimen end face, changes in fiber optic photosensitive properties, or stress wave signals, reflecting the propagation characteristics and stress intensity changes after the shock wave enters the specimen. For example, when the specimen material has significant plasticity or impact absorption capacity, its stress response curve will exhibit characteristics such as a flat waveform and a reduced peak value.

[0079] In one possible embodiment, the target specimen stress testing platform based on the average stress distribution can continuously record the stress response signal at the end of the specimen at a high sampling frequency during the impact load test of the target specimen, ensuring that the collected data covers the complete process of shock wave generation, propagation, peak appearance, and energy attenuation. By acquiring data using this method, signal distortion or omission of key information, such as stress abrupt changes at the moment of impact and the location of wave peak formation, can be reduced, thereby ensuring the reliability of subsequent internal stress distribution calculations.

[0080] The dynamic response data acquired using the above methods can be used to describe the time-series signal data of stress changes at the ends of the specimen. It should be noted that this dynamic response data can be a continuous response curve that varies with time, reflecting the changes in the specimen's load-bearing capacity and the propagation of internal stress under impact loads. This includes, but is not limited to, characteristics such as peak stress, response duration, waveform structure, and rise edge morphology. It serves as a data source for solving the internal stress distribution of the specimen. For example, by performing time-domain structural analysis on the dynamic response data, it is possible to preliminarily determine whether the specimen exhibits yielding, an upper strength limit, or a softening trend.

[0081] The aforementioned internal force distribution refers to the stress changes at different spatial locations within the target specimen under dynamic impact loading. This means the shock wave propagates inward from the specimen's ends, and due to material properties, geometry, and energy attenuation, the peak stress and its variation at different points within the specimen will differ. By analyzing the dynamic response data and calculating the internal stress propagation characteristics, the magnitude and trend of the stress at different locations within the specimen can be obtained, thus forming the internal force distribution.

[0082] In another possible embodiment, the target specimen stress testing platform based on the average stress distribution can deduce the internal stress distribution of the specimen through the dynamic response data. Specifically, based on the shock wave propagation principle, the specimen wave impedance characteristics, and the stress conditions of the continuous medium, the end dynamic response can be used as the external input to solve or invert the stress values ​​at different spatial locations inside the target specimen to obtain the corresponding average stress distribution.

[0083] By using the above methods and steps, the inversion bias caused by the traditional end-face equivalence assumption can be avoided, and the accuracy of calculating the true load-bearing capacity of the specimen under dynamic loading conditions can be improved.

[0084] Optionally, the step of constructing a dynamic response reconstruction model based on the mean stress distribution may further include determining the target correlation parameters of the target specimen based on the mean stress distribution. The target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen. Based on the target correlation parameters, stress reconstruction models, strain reconstruction models, and strain rate reconstruction models are constructed respectively.

[0085] In this embodiment of the invention, the aforementioned target correlation parameter can refer to a characteristic parameter determined based on the average stress distribution of the target specimen, used to uniformly describe the stress change law of the specimen under dynamic loading conditions. It can be obtained by comprehensive quantification based on the changes in the internal stress state of the target specimen over time and space, including but not limited to stress characteristic values ​​reflecting the stress level of the specimen, correlation variables used to describe the trend of deformation rate changes, etc. For example, when the material exhibits high strength or obvious yield hysteresis under impact conditions, this state can be reflected by the target correlation parameter and then used for model construction.

[0086] The aforementioned dynamic stress state can refer to the actual stress change behavior of the target specimen during the impact loading process, including the stress growth process over time, the peak time, the propagation trend of internal stress waves, and the material strain response characteristics. For example, when the shock wave enters the interior of the specimen and causes the stress distribution to decay, the peak stress at different locations and the stages of stress change are key manifestations of the dynamic stress state.

[0087] In one possible embodiment, after obtaining the target associated parameters, the target specimen stress testing platform based on the mean stress distribution uses these parameters as a unified input basis to establish a model for solving the stress, strain, and strain rate response relationship of the specimen during dynamic loading.

[0088] For example, information such as stress-time history curves, deformation rate variation trends, and dynamic stress peak locations can be derived from target-related parameters to support the restoration of the specimen's true load-bearing state. This data can then be used to construct the aforementioned stress reconstruction model, strain reconstruction model, and strain rate reconstruction model.

[0089] More specifically, the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model mentioned above can be obtained through the following formulas:

[0090]

[0091] in, For stress reconstruction model, For strain reconstruction model, For the strain rate reconstruction model, it can be based on Figure 2 The schematic diagram of the SHPB experimental setup shown is used for explanation, and the formula is as follows: , For the target specimen in time, The stress and strain data at the location, that is, the target specimen at... The stress distribution function and strain distribution function at time t; The target specimen length is defined as follows: the cross-sectional position of the target specimen is measured from left end a to right end b. ; The wave resistance of the incident and transmission rods in the SHPB device; , , These represent the incident wave, reflected wave, and transmitted wave extracted from the incident rod and transmission rod during the experiment, respectively.

[0092] It should be noted that before testing, the elastic modulus, cross-sectional area, and wave resistance of the input and output rods were measured. Furthermore, the specimen length and cross-sectional area can be measured in advance using existing technology, and the specimen length and cross-sectional area are respectively... , Therefore, in this experiment, the incident wave generated by the impact of the hammer on the input rod propagates from left to right within the input rod. During this propagation, two strain signals are obtained by attaching strain gauges to the input and output rods respectively. Then, by using a reasonable design of the incident wave wavelength and the lengths of the input and output rods, the incident wave can be extracted from the two strain signals. Reflected waves Transmitted waves and the time it takes for the stress wave to pass through the specimen And based on the extracted data, the stress data of the specimen is calculated.

[0093] More specifically, the stress reconstruction model described above can be used to solve the distribution relationship of internal stress of a specimen during dynamic loading process with time and space using target associated parameters and the mean stress distribution. Through this stress reconstruction model, the true bearing pressure inside the specimen can be recovered, no longer limited to single-point values ​​at the end measuring points, and the overall stress level of the specimen can be presented in a dynamic form. For example, the stress reconstruction model can identify the peak stress points and stress propagation trends inside the specimen.

[0094] The strain reconstruction model described above can be used to determine the deformation characteristics of the specimen during the impact loading process based on the target correlation parameters, including the compression, tension or local plastic deformation state of the specimen material after being subjected to the shock wave, reflecting the stiffness characteristics and impact resistance of the specimen.

[0095] The strain rate reconstruction model described above can be used to determine the deformation rate variation law of the specimen during the impact process based on the target correlation parameters. Through the strain rate reconstruction model, the impact resistance performance of the specimen under high strain rate environment can be evaluated. For example, if the specimen exhibits different strain rate responses under the same impact intensity, it indicates that there are differences in the material toughness and impact energy absorption capacity. These characteristics can be recovered through the model.

[0096] By using the above methods and steps, the three dynamic indicators of stress, strain, and strain rate can be reconstructed simultaneously on the basis of unified correlation parameters. This avoids the accumulation of biases in traditional methods, improves the accuracy of specimen dynamic behavior evaluation, and provides a reliable basis for specimen impact strength analysis, performance limit identification, and engineering applicability judgment.

[0097] Optionally, in the step of constructing the stress distribution function of the target specimen through a preset optimization algorithm, the objective function is determined based on the dynamic response data and the mean stress distribution of the target specimen. The objective function is used to characterize the internal stress distribution characteristics of the target specimen. The objective function is then solved and calculated through the preset optimization algorithm to obtain the stress distribution function.

[0098] In this embodiment of the invention, the objective function can be a calculation expression or characteristic relationship that is constructed based on the dynamic response data of the specimen and the mean stress distribution to characterize the internal stress distribution law of the target specimen. Based on the dynamic response data collected in real time at the end of the specimen, by introducing the internal stress distribution mean information, the function can fit and associate the stress area inside the specimen that was not directly collected.

[0099] More specifically, when the specimen is subjected to a shock wave input, the waveform change of the end signal contains information about the internal stress propagation process. The objective function uses this information to transform features such as internal stress gradient, peak change location, and stress concentration section into solvable data relationships.

[0100] The aforementioned internal force distribution characteristics can refer to the force change state and force distribution law at different spatial locations of the target specimen during the impact load process, including but not limited to the magnitude of the peak force at each location, the attenuation or enhancement trend of the internal force, the force concentration area, wave propagation delay behavior, and differences in internal mechanical response. These characteristics can be derived and identified by combining dynamic response data with the overall force law of the specimen.

[0101] Understandably, the aforementioned internal stress distribution characteristics can indicate the actual stress differences experienced by different regions within the target specimen. For example, the region near the impact end typically experiences higher instantaneous stress, while the inner region may exhibit stress attenuation. By analyzing this characteristic, it is possible not only to reflect whether there are potential fracture risk points within the specimen, but also to identify whether the material possesses impact resistance characteristics or structural stiffness weaknesses.

[0102] In one possible embodiment, the target specimen stress testing platform based on the mean stress distribution performs iterative fitting optimization processing on the objective function according to the preset optimization algorithm to determine the stress distribution function that can truly characterize the internal force distribution relationship of the specimen.

[0103] Specifically, the aforementioned preset optimization algorithm can be obtained in the following way: First, set the target that the stress distribution function in the specimen should always maintain the minimum difference between the stress values ​​at its two ends and the test stress values ​​at the contact ends of the input rod and the output rod with the specimen, which can be obtained by optimizing the following formula. make:

[0104]

[0105] In the formula: In time The number of times the internal stress wave is transmitted and reflected back and forth in the specimen. The parameters at that moment are obtained from the above formula. , It is a dimensionless parameter constructed to make the formula in the preset optimization algorithm hold true. K represents a summation (or iteration) variable / index, which can start from the integer 0 and gradually increase to n. It is used to traverse each term in the summation expression to obtain the specimen's value. Stress distribution function of specimen at time ,as follows:

[0106]

[0107] In the formula: This represents the time it takes for the stress wave to pass through the specimen.

[0108] The obtained stress distribution function Substitute the incident waves extracted from the incident and transmission rods in the SHPB experiment into the above reconstruction model. Reflected waves Transmitted waves The data is used to determine the stress, strain, and strain rate of the specimen at the corresponding time. The stress-strain curve of the specimen is reconstructed from the stress and strain, and then the mechanical properties of the specimen material, such as yield strength, compressive strength, and elastic modulus, are determined.

[0109] By using the above methods and steps, based on the dynamic response data at the end, the internal stress law of the specimen can be fitted and identified through objective function construction and optimization of the solution behavior, thereby obtaining a stress distribution function that can truly reflect the internal stress gradient and overall bearing capacity of the specimen.

[0110] Compared to traditional methods that rely on end measuring points and the assumption of uniform stress, this embodiment can restore the complete stress structure inside the specimen on a unified physical basis, providing a highly continuous and reliable real stress basis for subsequent target stress data calculation and mechanical performance judgment, thereby improving the accuracy and reliability of the dynamic load-bearing level analysis of the specimen.

[0111] Optionally, in the step of substituting the stress distribution function into the dynamic response reconstruction model to determine the target stress data of the target specimen, the method further includes inputting the stress distribution function as an input parameter into the dynamic response reconstruction model to calculate the force response of the target specimen during dynamic loading, thereby obtaining force response calculation data; based on the force response calculation data, extracting and processing the characteristics of the internal force of the target specimen changing with time and along the spatial location to obtain time distribution feature data and spatial distribution feature data; and based on the time distribution feature data and spatial distribution feature data, analyzing the overall stress state of the target specimen to obtain the target stress data.

[0112] In this embodiment of the invention, the above-mentioned stress response calculation data can be the data results obtained by the target specimen stress testing platform based on the average stress distribution after inputting the stress distribution function into the dynamic response reconstruction model, and through the model solving process, which are used to characterize the stress change law of the target specimen during dynamic loading. This includes, but is not limited to, the temporal change of the internal force of the specimen, the attenuation trend of stress along the propagation direction, the location of the stress peak, and the overall characteristics of the stress response change with the loading process.

[0113] In one possible embodiment, the target specimen stress testing platform based on the average stress distribution can perform feature analysis and data filtering on the stress change patterns contained in the stress response calculation data, separating the time-varying and spatial-positioning characteristics describing the internal dynamic mechanical state of the specimen from the calculation data. For example, this can be achieved by performing structured identification, feature point separation, and peak conversion relationship analysis on the stress change trends in the calculation data.

[0114] Furthermore, the aforementioned time distribution characteristic data can refer to the characteristic information of the specimen's stress changing over time extracted from the stress response calculation data, used to describe the evolution trend of the internal stress of the specimen throughout the entire dynamic loading process. This data can reflect the changing patterns of the internal stress of the specimen from the moment of loading, including the growth stage, the time of peak occurrence, the stress decay process, and the response stabilization stage.

[0115] It can also be used to characterize the mechanical response path of the specimen during the impact process. For example, whether the peak force appears earlier, whether there is hysteresis in the force response, and whether the stress wave response has two peaks can all be reflected by time distribution characteristic data.

[0116] The aforementioned spatial characteristic distribution data can refer to the characteristic data extracted from the force response calculation data to describe the variation law of the force inside the specimen along the spatial position. It can also reflect the magnitude of the force, the trend of the peak force, and the attenuation behavior of the force along the propagation path at different positions during the propagation of the shock wave inside the specimen.

[0117] More specifically, it can also identify the load-bearing differences at different spatial points inside the specimen. For example, the side closer to the impact surface may bear a higher instantaneous impact force, while the deeper internal areas gradually bear less force due to propagation attenuation; or there may be a localized area with concentrated force, which may become a potential failure location.

[0118] In another possible embodiment, the target specimen stress testing platform based on the average stress distribution is used to comprehensively analyze and identify the overall stress state of the specimen during dynamic loading based on time distribution characteristic data and spatial characteristic distribution data, thereby achieving the purpose of obtaining target stress data by analyzing the data.

[0119] More specifically, it can identify areas of concentrated stress, peak stress state, dynamic stress evolution trend, and whether there are structural weak points in the specimen, and generate target stress data to uniformly express the overall load-bearing capacity of the specimen.

[0120] The above methods and steps enable the full-domain identification and structured analysis of the true internal stress state of the specimen under dynamic loading conditions.

[0121] Optionally, the step of analyzing the overall stress state of the target specimen based on time distribution characteristic data and spatial distribution characteristic data to obtain target stress data further includes: determining first stress characteristic data based on time distribution characteristic data, which reflects the dynamic stress change law of the target specimen; determining second stress characteristic data based on spatial distribution characteristic data, which reflects the internal stress distribution state of the target specimen; and performing correlation calculations based on the first and second stress characteristic data to obtain target stress data, which characterizes the overall stress state of the target specimen.

[0122] In this embodiment of the invention, the first force characteristic data mentioned above can refer to dynamic characteristic parameters determined based on time distribution characteristic data, used to reflect the law of force change with time during dynamic loading of the target specimen. These parameters can be obtained from the internal force change behavior corresponding to each time point in the force response calculation results of the target specimen, including the force growth stage, the peak appearance stage, the peak decay process, and the stable segment after loading.

[0123] Furthermore, the aforementioned first stress characteristic data can reflect the dynamic stress evolution process of the specimen under impact load, such as: whether the stress rises rapidly over time; whether there is a delay in the appearance of the stress peak; and whether there is an obvious decline or softening trend after the peak.

[0124] By identifying the patterns of change in these time dimensions, the aforementioned first stress characteristic data can be used to determine the specimen's response capability, energy absorption characteristics, and strength change trend under dynamic stress.

[0125] The aforementioned second stress characteristic data can refer to characteristic parameters determined based on spatial distribution characteristic data, used to reflect the differences in stress state at different spatial locations inside the target specimen during dynamic loading. By analyzing the stress calculation results at multiple locations inside the target specimen, the stress distribution pattern inside the specimen can be obtained, including stress concentration areas, stress gradient change areas, and stress attenuation areas.

[0126] It should be noted that the above-mentioned second stress characteristic data can be used to describe the non-uniformity of the internal stress of the specimen in the spatial range, such as: whether there is a concentration of stress peaks near the loading end; whether the internal region experiences stress attenuation as the wave propagates; and whether there are local stress anomalies or possible weak areas of failure.

[0127] By identifying the peak level and variation trend of internal forces at different spatial locations, the second stress characteristic data can be used to analyze the distribution of the load-bearing capacity of the internal structure of the specimen, providing a basis for determining whether there are potential failure locations in the specimen under dynamic stress.

[0128] In one possible embodiment, the specimen stress data processing platform based on the average stress distribution can also perform correlation calculations on the stress characteristic data of the two different dimensions, combining the temporal behavior characteristics such as the time of occurrence of the specimen stress peak, the duration of stress, and the rate of stress decay with the spatial behavior characteristics such as the magnitude of the stress peak in different internal regions and the phenomenon of stress gradient decay, so that the formation process of the specimen's load-bearing capacity has complete structural information.

[0129] For example, when the time dimension features indicate that the specimen experiences a sharp increase in stress at the beginning of the impact loading, while the spatial dimension features show that the stress is concentrated in the area near the loading end and the peak amplitude is significantly higher than that in the internal area, the correlation calculation can determine that the specimen may have an overstress area or an internal local failure risk during this period.

[0130] By using the above methods and steps, not only can the overall state inference error caused by single-point measurement at the end of the traditional test method be avoided, but a unified parameter basis can also be provided for the calculation of target stress data. The target stress data obtained under the joint expression of time response and spatial distribution characteristics not only get rid of the single judgment method of equivalent calculation based on end face stress measurement in the traditional way, but also can reveal the internal bearing nature of the specimen in a way that is closer to the real stress mechanism, so that the dynamic evaluation results are more consistent with the actual working stress environment.

[0131] Optionally, the step of testing and judging the suitability or failure risk of the target specimen under preset working conditions based on the target stress data further includes: constructing a dynamic stress-strain response curve of the target specimen based on the target stress data; determining the mechanical performance data of the target specimen under preset working conditions based on the dynamic stress-strain response curve, the mechanical performance data including the stress threshold, structural limit, and deformation characteristics; and testing and judging the suitability or failure risk of the target specimen under preset working conditions based on the stress threshold, structural limit, and deformation characteristics of the target specimen under preset working conditions.

[0132] In this embodiment of the invention, after obtaining the target stress data of the target specimen based on the average stress distribution, the specimen stress data processing platform can further test and judge the applicability or failure risk of the specimen under preset working conditions.

[0133] Specifically, based on the target stress data obtained from the dynamic response reconstruction model in this embodiment, the specimen stress data processing platform based on the mean stress distribution can correlate and map the stress response value and deformation behavior of the corresponding specimen during impact loading to construct the dynamic stress-strain response curve of the target specimen. This curve describes the complete trajectory of stress change with deformation under dynamic stress conditions, and includes characteristic information such as the initial stress segment, linear elastic segment, yield transition segment, peak strength segment, and damage attenuation segment of the specimen during the impact process.

[0134] This curve provides a clear visual representation of the specimen's load-bearing capacity, deformation energy absorption capacity, and structural toughness behavior under high strain rate conditions, offering a data foundation for subsequent structural safety assessments. For example, when a target specimen exhibits a significant nonlinear deformation path or a decreasing trend in peak strength, its corresponding stress-strain curve will show a clear inflection point or softening segment, thus indicating the risk of material failure.

[0135] Furthermore, the aforementioned specimen stress data processing platform based on the mean stress distribution can identify key dynamic mechanical property data of the target specimen under preset working conditions based on the dynamic stress-strain response curve, including but not limited to:

[0136] Stress threshold: The critical stress point at which the specimen yields or undergoes a change in properties under dynamic loading;

[0137] Structural limit: The highest load-bearing capacity or critical strength position that the specimen can withstand under impact;

[0138] Deformation characteristics: corresponding to the plastic deformation capacity, failure transition behavior, and structural stiffness change trend of the specimen during the impact process.

[0139] Among these, the stress threshold can be identified by the inflection point or yield point of the curve, the structural limit can reflect the peak position of the curve, and the deformation characteristics can be determined based on the changes in the nonlinear segment or softening section of the curve. These mechanical property data are used to quantify the actual load-bearing capacity and deformation energy absorption performance of the specimen under impact conditions, and can serve as important indicators for applicability testing and risk screening.

[0140] In this embodiment, the specimen stress data processing platform based on the average stress distribution can also determine whether the target specimen meets the load-bearing requirements or has a risk of performance degradation under preset working conditions based on performance data such as stress threshold, structural limit, and deformation characteristics. When the stress capacity of the target specimen reaches the preset structural strength range and the stress-strain curve shows stable characteristics, it indicates that the specimen is suitable for the corresponding impact condition; when the curve shows strength decay, a sudden increase in deformation, or the structural limit is lower than the preset threshold, it can be considered that the specimen may have a failure trend and needs to be marked as being in a risky state.

[0141] For example, in a high-impact equipment application scenario, if the dynamic stress-strain response curve of the target specimen shows a significant downward path, it means that the material will soften or be damaged after the impact strength approaches the structural limit, thus generating a potential failure risk. In this case, it can be determined that it does not have the ability to be used safely under this working condition.

[0142] By using the above methods and steps, the complete mechanical behavior of the specimen under dynamic loading can be reconstructed based on the target stress data, and key performance parameters can be identified using the dynamic stress-strain response curve, thereby achieving an accurate evaluation of the specimen's true load-bearing capacity.

[0143] like Figure 3 As shown, this embodiment of the invention also provides a specimen stress data processing device 300 based on the average stress distribution value. The specimen stress data processing device 300 based on the average stress distribution value includes:

[0144] The first acquisition module 301 is used to determine the average stress distribution of the target specimen;

[0145] The first construction module 302 is used to construct a dynamic response reconstruction model based on the mean stress distribution.

[0146] The second construction module 303 is used to construct the stress distribution function of the target specimen through a preset optimization algorithm;

[0147] The first determining module 304 is used to substitute the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen.

[0148] The test module 305 is used to test and judge the applicability or failure risk of the target specimen under preset working conditions based on the target stress data.

[0149] Optionally, the first acquisition module 301 mentioned above includes:

[0150] The first acquisition submodule is used to collect the force response of the target specimen at a preset position in real time to obtain the dynamic response data of the target specimen. The dynamic response data is used to describe the end force change of the target specimen.

[0151] The second acquisition submodule is used to calculate and process the internal force distribution of the target specimen based on the dynamic response data to obtain the average stress distribution.

[0152] Optionally, the first building module 302 mentioned above includes:

[0153] The first construction submodule is used to determine the target correlation parameters of the target specimen based on the mean stress distribution. The target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen.

[0154] The second construction submodule is used to construct the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model based on the target correlation parameters.

[0155] Optionally, the second building module 303 mentioned above includes:

[0156] The third construction submodule is used to determine the objective function based on the dynamic response data of the target specimen and the mean stress distribution. The objective function is used to characterize the internal stress distribution characteristics of the target specimen.

[0157] The fourth construction submodule is used to solve the objective function using the preset optimization algorithm to obtain the stress distribution function.

[0158] Optionally, the first determining module 304 mentioned above includes:

[0159] The first determining submodule is used to input the stress distribution function as an input parameter into the dynamic response reconstruction model, calculate the stress response of the target specimen during the dynamic loading process, and obtain stress response calculation data.

[0160] The second determining submodule is used to extract and process the characteristics of the internal force of the target specimen changing with time and the characteristics of the force changing along the spatial position based on the force response calculation data, so as to obtain time distribution feature data and spatial distribution feature data.

[0161] The third determination submodule is used to analyze the overall stress state of the target specimen based on the time distribution characteristic data and spatial distribution characteristic data to obtain target stress data.

[0162] Optionally, the third determining submodule mentioned above includes:

[0163] The first determining unit is used to determine the first stress characteristic data based on the time distribution characteristic data, wherein the first stress characteristic data is used to reflect the dynamic stress change law of the target specimen;

[0164] The second determining unit is used to determine the second stress characteristic data based on the spatial distribution characteristic data. The second stress characteristic data is used to reflect the internal stress distribution state of the target specimen.

[0165] The third determining unit is used to perform correlation calculations based on the first stress characteristic data and the second stress characteristic data to obtain target stress data, which is used to characterize the overall stress state of the target specimen.

[0166] Optionally, the above test module 305 includes:

[0167] The first testing submodule is used to construct the dynamic stress-strain response curve of the target specimen based on the target stress data;

[0168] The second testing submodule is used to determine the mechanical performance data of the target specimen under preset working conditions based on the dynamic stress-strain response curve. The mechanical performance data includes the stress threshold, structural limit, and deformation characteristics.

[0169] The third testing submodule is used to test and judge the applicability or failure risk of the target specimen under the preset working conditions based on the stress threshold, structural limit and deformation characteristics of the target specimen under the preset working conditions.

[0170] like Figure 4 As shown, this embodiment of the invention also provides an electronic device 400, including a processor, which can execute any of the above-mentioned specimen stress data processing methods based on the mean stress distribution.

[0171] Specifically, it includes a processor 401 and a memory 402, as well as a computer program stored in the memory 402 and capable of running on the processor 401, which executes a specimen stress data processing method based on the mean stress distribution, wherein:

[0172] The processor 401 executes the calculator program stored in memory 402, which is a specimen stress data processing method based on the mean stress distribution, and performs the following steps:

[0173] Determine the mean stress distribution of the target specimen;

[0174] Based on the mean stress distribution, a dynamic response reconstruction model is constructed;

[0175] The stress distribution function of the target specimen is constructed using a preset optimization algorithm;

[0176] The stress distribution function is substituted into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen.

[0177] Based on the target stress data, the applicability or failure risk of the target specimen under preset working conditions is tested and judged.

[0178] Optionally, the processor 401 performs the determination of the mean stress distribution of the target specimen, including:

[0179] The force response of the target specimen at a preset position is collected in real time to obtain the dynamic response data of the target specimen. The dynamic response data is used to describe the change in the end force of the target specimen.

[0180] Based on the dynamic response data, the internal stress distribution of the target specimen is calculated to obtain the average stress distribution.

[0181] Optionally, the processor 401 executes the dynamic response reconstruction model, which includes a stress reconstruction model, a strain reconstruction model, and a strain rate reconstruction model. The step of constructing the dynamic response reconstruction model based on the mean stress distribution includes:

[0182] Based on the mean stress distribution, target correlation parameters of the target specimen are determined, and the target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen.

[0183] Based on the target correlation parameters, the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model are constructed respectively.

[0184] Optionally, the processor 401 executes the process of constructing the stress distribution function of the target specimen using a preset optimization algorithm, including:

[0185] Based on the dynamic response data of the target specimen and the mean stress distribution, an objective function is determined, which is used to characterize the internal stress distribution characteristics of the target specimen.

[0186] The objective function is solved using the preset optimization algorithm to obtain the stress distribution function.

[0187] Optionally, the processor 401 performs the calculation by substituting the stress distribution function into the dynamic response reconstruction model to determine the target stress data of the target specimen, including:

[0188] The stress distribution function is used as an input parameter to the dynamic response reconstruction model to calculate the stress response of the target specimen during dynamic loading, thereby obtaining stress response calculation data.

[0189] Based on the force response calculation data, the characteristics of the internal force of the target specimen changing with time and the characteristics of the force changing along the spatial position are extracted and processed to obtain time distribution characteristic data and spatial distribution characteristic data.

[0190] Based on the time distribution characteristic data and spatial distribution characteristic data, the overall stress state of the target specimen is analyzed to obtain the target stress data.

[0191] Optionally, the processor 401 executes the analysis of the overall stress state of the target specimen based on the time distribution feature data and spatial distribution feature data to obtain target stress data, including:

[0192] Based on the time distribution characteristic data, the first force characteristic data is determined, which is used to reflect the dynamic force change law of the target specimen;

[0193] Based on the spatial distribution characteristic data, second force characteristic data is determined, which is used to reflect the internal force distribution state of the target specimen.

[0194] The target stress data is obtained by correlating the first stress characteristic data and the second stress characteristic data. The target stress data is used to characterize the overall stress state of the target specimen.

[0195] Optionally, the processor 401 performs the test and judgment on the suitability or failure risk of the target specimen under preset working conditions based on the target stress data, including:

[0196] Based on the target stress data, the dynamic stress-strain response curve of the target specimen is constructed;

[0197] Based on the dynamic stress-strain response curve, the mechanical performance data of the target specimen under the preset working conditions are determined. The mechanical performance data includes the stress threshold, structural limit, and deformation characteristics.

[0198] Based on the stress threshold, structural limit, and deformation characteristics of the target specimen under preset working conditions, the applicability or failure risk of the target specimen under the preset working conditions is tested and judged.

[0199] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the specimen stress data processing method based on the mean stress distribution provided in this invention, or the application-side specimen stress data processing method based on the mean stress distribution, and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0200] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be done by a computer program instructing related hardware, and can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0201] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for processing specimen stress data based on the mean stress distribution, characterized in that, include: Determine the mean stress distribution of the target specimen; Based on the mean stress distribution, a dynamic response reconstruction model is constructed; The stress distribution function of the target specimen is constructed using a preset optimization algorithm; The stress distribution function is substituted into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen. Based on the target stress data, the applicability or failure risk of the target specimen under the preset working conditions is tested and judged. Determining the mean stress distribution of the target specimen includes: The force response of the target specimen at a preset position is collected in real time to obtain the dynamic response data of the target specimen. The dynamic response data is used to describe the end force change of the target specimen. Based on the dynamic response data, the internal stress distribution of the target specimen is calculated to obtain the average stress distribution. The dynamic response reconstruction model includes a stress reconstruction model, a strain reconstruction model, and a strain rate reconstruction model. The construction of the dynamic response reconstruction model based on the mean stress distribution includes: Based on the mean stress distribution, target correlation parameters of the target specimen are determined, and the target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen. Based on the target correlation parameters, the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model are constructed respectively. The step of constructing the stress distribution function of the target specimen through a preset optimization algorithm includes: Based on the dynamic response data of the target specimen and the mean stress distribution, an objective function is determined, which is used to characterize the internal stress distribution characteristics of the target specimen. The objective function is solved using the preset optimization algorithm to obtain the stress distribution function.

2. The specimen stress data processing method based on the mean stress distribution as described in claim 1, characterized in that, The step of substituting the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen includes: The stress distribution function is used as an input parameter to the dynamic response reconstruction model to calculate the stress response of the target specimen during dynamic loading, thereby obtaining stress response calculation data. Based on the force response calculation data, the characteristics of the internal force of the target specimen changing with time and the characteristics of the force changing along the spatial position are extracted and processed to obtain time distribution characteristic data and spatial distribution characteristic data. Based on the time distribution characteristic data and spatial distribution characteristic data, the overall stress state of the target specimen is analyzed to obtain the target stress data.

3. The specimen stress data processing method based on the mean stress distribution as described in claim 2, characterized in that, The overall stress state of the target specimen is analyzed based on the time distribution characteristic data and spatial distribution characteristic data to obtain target stress data, including: Based on the time distribution characteristic data, the first force characteristic data is determined, which is used to reflect the dynamic force change law of the target specimen; Based on the spatial distribution characteristic data, second force characteristic data is determined, which is used to reflect the internal force distribution state of the target specimen. The target stress data is obtained by correlating the first stress characteristic data and the second stress characteristic data. The target stress data is used to characterize the overall stress state of the target specimen.

4. The specimen stress data processing method based on the mean stress distribution as described in claim 1, characterized in that, The step of testing and judging the suitability or failure risk of the target specimen under preset working conditions based on the target stress data includes: Based on the target stress data, the dynamic stress-strain response curve of the target specimen is constructed; Based on the dynamic stress-strain response curve, the mechanical performance data of the target specimen under the preset working conditions are determined. The mechanical performance data includes the stress threshold, structural limit, and deformation characteristics. Based on the stress threshold, structural limit, and deformation characteristics of the target specimen under preset working conditions, the applicability or failure risk of the target specimen under the preset working conditions is tested and judged.

5. A specimen stress data processing device based on the mean stress distribution, characterized in that, include: The first acquisition module is used to determine the mean stress distribution of the target specimen; The first construction module is used to construct a dynamic response reconstruction model based on the mean stress distribution. The second construction module is used to construct the stress distribution function of the target specimen through a preset optimization algorithm; The first determining module is used to substitute the stress distribution function into the dynamic response reconstruction model for calculation to determine the target stress data of the target specimen. The testing module is used to test and judge the applicability or failure risk of the target specimen under preset working conditions based on the target stress data. The first construction module is further configured to collect the force response of the target specimen at a preset position in real time to obtain the dynamic response data of the target specimen, the dynamic response data being used to describe the end force change of the target specimen; based on the dynamic response data, the internal force distribution of the target specimen is calculated and processed to obtain the average stress distribution; The second construction module is further configured to determine the target correlation parameters of the target specimen based on the mean stress distribution, wherein the target correlation parameters are used to uniformly characterize the dynamic stress state of the target specimen; The dynamic response reconstruction model includes a stress reconstruction model, a strain reconstruction model, and a strain rate reconstruction model; based on the target correlation parameters, the stress reconstruction model, strain reconstruction model, and strain rate reconstruction model are constructed respectively. The step of constructing the stress distribution function of the target specimen through a preset optimization algorithm includes: determining the target function based on the dynamic response data of the target specimen and the mean stress distribution, wherein the target function is used to characterize the internal stress distribution characteristics of the target specimen; The objective function is solved using the preset optimization algorithm to obtain the stress distribution function.

6. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps in the specimen stress data processing method based on the mean stress distribution as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps in the specimen stress data processing method based on the mean stress distribution as described in any one of claims 1 to 4.

Images