Titanium alloy fatigue limit prediction method and device, computer equipment and medium

Abstract

The invention relates to the field of structural fatigue life prediction, and discloses a titanium alloy fatigue limit prediction method and device, computer equipment and a medium, and the method comprises the following steps: preparing a defect fatigue sample by using a smooth sample of a preset material; performing simulated impact on the defective fatigue sample based on a preset impact condition to obtain a local stress ratio of an impact defect on the defective fatigue sample and a projection area value in the load axis direction; and the Vickers hardness value of the smooth sample is obtained, and the fatigue limit prediction value of the defective fatigue sample is calculated according to the Vickers hardness value, the local stress ratio and the projection area value. The method solves the problem that the existing structure fatigue limit prediction method cannot consider the residual stress and is difficult to predict the fatigue limit when facing materials with impact defects due to the fact that the defect local stress ratio is not considered.

Description

Technical Field

[0001] The present invention relates to the field of structural fatigue life prediction, and in particular to a method, device, computer equipment and medium for predicting the fatigue limit of titanium alloy. Background Art

[0002] In structural design and application, the traditional safety life design method is based on the assumption of no defects, ignoring the initial undetected defects or accidental damage that may occur in the process from raw materials to manufacturing, delivery and service. These defects will greatly reduce the service life of the structure and threaten service safety. For this reason, the defect tolerance safety life design method is proposed. This method considers the fatigue life and behavior of defective materials and structures. Impact defects are caused by pits on the surface of parts due to the fall of tools during processing and maintenance. The local stress level and state of materials and structures are changed through local stress concentration and residual stress to control the fatigue limit.

[0003] The existing structural fatigue limit prediction methods have the problem of failing to consider the local stress ratio of defects, which has a significant impact on fatigue limit. When facing impact defects, due to the presence of local compressive plastic deformation and compressive / tensile residual stress, the local stress ratio of the defect is related to the impact conditions and defect size and is not a constant. As a result, the existing technology cannot consider residual stress and is difficult to apply to the fatigue limit prediction of materials containing impact defects, although it may be applicable when facing defects such as scratches and corrosion. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method, device, computer equipment and medium for predicting the fatigue limit of titanium alloy to solve the problem that the existing structural fatigue limit prediction method does not consider the local stress ratio of the defect, and when facing materials containing impact defects, it is impossible to consider the residual stress and it is difficult to predict its fatigue limit.

[0005] In a first aspect, an embodiment of the present invention provides a method for predicting fatigue limit of a titanium alloy, the method comprising:

[0006] Preparation of defect fatigue specimens using smooth specimens of preset materials;

[0007] Performing a simulated impact on the defect fatigue specimen based on a preset impact condition to obtain a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis;

[0008] The Vickers hardness value of the smooth sample is obtained, and the fatigue limit prediction value of the defective fatigue sample is calculated according to the Vickers hardness value, the local stress ratio and the projection area value.

[0009] Furthermore, the simulated impact is performed on the defect fatigue specimen based on the preset impact condition to obtain the local stress ratio of the impact defect on the defect fatigue specimen and the projected area value in the load axis direction, including:

[0010] constructing a virtual model using the defective fatigue specimen;

[0011] Performing a simulated impact on the virtual model based on a preset impact condition to obtain local residual stress field data of the impact defect on the virtual model;

[0012] Importing the local residual stress field data into the virtual model as an initial stress state to obtain a target virtual model;

[0013] The local stress ratio and the projected area value are calculated according to the target virtual model.

[0014] Further, the calculating the local stress ratio and the projection area value according to the target virtual model includes:

[0015] Obtain the original fatigue limit value of the smooth specimen;

[0016] Applying the original fatigue limit value as an axial load parameter to the target virtual model to obtain a change in the local stress state of the impact defect;

[0017] The local stress ratio of the impact defect is calculated according to the change of the local stress state, and the projection area value in the load axis direction is calculated according to the impact defect of the target virtual model.

[0018] Furthermore, the projection area value of the impact defect of the target virtual model in the load axis direction includes:

[0019] Scanning the impact defect of the defect fatigue specimen to obtain profile data;

[0020] Extracting a depth value and a local radius value from the contour data;

[0021] The projection area value of the impact defect in the load axis direction is calculated according to the depth value and the local radius value.

[0022] Further, the calculation of the fatigue limit prediction value of the defective fatigue specimen according to the Vickers hardness value, the local stress ratio and the projected area value includes:

[0023] Substituting the Vickers hardness value, the local stress ratio and the projected area value into a preset relationship;

[0024] The fatigue limit prediction value of the defective fatigue specimen is calculated based on the preset relationship.

[0025] Furthermore, the preset relationship is as follows:

[0026]

[0027] in, is the fatigue limit prediction value; k = 0.85 coefficient; HV is the Vickers hardness value; R is the local stress ratio; area0 is the projected area; α = 0.226 + HV 10 -4 .

[0028] Further, after calculating the fatigue limit prediction value of the defective fatigue specimen according to the Vickers hardness value, the local stress ratio and the projected area value, the method further includes:

[0029] Applying cyclic stress to the defective fatigue specimen according to the preset test parameters until the defective fatigue specimen is in a failure state, and obtaining an actual value of the fatigue limit;

[0030] Comparing the fatigue limit prediction value with the fatigue limit actual value to obtain a comparison result;

[0031] The prediction accuracy for the defective fatigue specimen is calculated according to the comparison result.

[0032] In a second aspect, an embodiment of the present invention provides a device for predicting fatigue limit of titanium alloy, the device comprising:

[0033] A preparation module for preparing defect fatigue specimens using smooth specimens of preset materials;

[0034] A simulation module, used for performing a simulated impact on the defect fatigue specimen based on a preset impact condition, and obtaining a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis;

[0035] A prediction module is used to obtain the Vickers hardness value of the smooth sample, and calculate the fatigue limit prediction value of the defective fatigue sample according to the Vickers hardness value, the local stress ratio and the projection area value.

[0036] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0037] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0038] The method provided in the embodiment of the present application has the following beneficial effects:

[0039] The method provided in the embodiment of the present application uses a smooth sample of a preset material to prepare a defect fatigue sample, simulates the impact defect situation of the material in practice, provides a real and effective sample for subsequent research, and makes the prediction more in line with the actual application scenario. Then, based on the preset impact conditions, the defect fatigue sample is simulated to obtain the local stress ratio and the projected area value. The process obtains the target virtual model by constructing a virtual model, simulating the impact, and importing the residual stress data, and then calculates the relevant parameters. In this way, it can not only accurately simulate the internal stress changes of the material during the impact process, but also reflect the influence of the impact defect on the stress state of the material by obtaining key parameters, laying the foundation for accurately predicting the fatigue limit. Finally, the Vickers hardness value of the smooth sample is obtained, and the fatigue limit prediction value is calculated in combination with the local stress ratio and the projected area value. The material hardness, defect stress ratio and defect size and other factors are comprehensively considered, and the preset relationship is used for calculation, so that the prediction result is more scientific and accurate, which effectively overcomes the problem that the existing technology does not consider the defect local stress ratio and cannot accurately predict the fatigue limit of the material containing impact defects, and provides a reliable method for predicting the fatigue limit of titanium alloy materials containing impact defects in actual engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 is a schematic flow chart of a method for predicting fatigue limit of titanium alloy according to an embodiment of the present invention;

[0042] Figure 2 is an engineering drawing of a defect fatigue specimen according to an embodiment of the present invention;

[0043] Figure 3 is a solid diagram of a defective fatigue specimen according to an embodiment of the present invention;

[0044] Figure 4 is a schematic diagram of an impact defect projection area according to an embodiment of the present invention;

[0045] Figure 5 is a finite element cloud diagram of tension and compression after impact according to an embodiment of the present invention;

[0046] Figure 6 is a schematic diagram of a defective material fatigue limit prediction process according to an embodiment of the present invention;

[0047] Figure 7 is a structural block diagram of a device for predicting fatigue limit of titanium alloy according to an embodiment of the present invention;

[0048] Figure 8 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0050] According to an embodiment of the present invention, a method, apparatus, computer device and medium for predicting the fatigue limit of titanium alloy are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0051] In this embodiment, a method for predicting the fatigue limit of titanium alloy is provided. Figure 1 : is a flow chart of a method for predicting fatigue limit of titanium alloy according to an embodiment of the present invention, such as Figure 1 As shown, the process includes the following steps:

[0052] Step S11, preparing a defect fatigue specimen using a smooth specimen of a preset material.

[0053] In the embodiment of the present application, the preparation of defect fatigue specimens is to transform them into defect fatigue specimens by creating defects on smooth specimens, laying the foundation for a series of subsequent simulations, tests and calculations. In actual operation, taking the TC4 titanium alloy commonly used in the aviation industry as an example, the drop hammer test method is often used to prepare impact defects on the surface of the parallel section of the fatigue test using an impact head of a given diameter. This method can accurately simulate the impact pits caused by the possible tool drop during the service or maintenance of aircraft and helicopter load-bearing components, thereby creating conditions for accurately predicting the fatigue limit of defective materials.

[0054] It should be noted that the engineering drawings of defect fatigue specimens, such as Figure 2 As shown in the figure, the upper specimen is in the shape of a long strip with a circular hole in the middle, with dimensions, tolerances, surface roughness, and symbols; the lower specimen is also in the shape of a long strip but with an opening or slot in the middle. Figure 3 As shown, its appearance is a long strip with a shape change in the middle, corresponding to the special structure in the engineering drawing.

[0055] Step S12, performing a simulated impact on the defect fatigue specimen based on a preset impact condition, and obtaining a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis.

[0056] In the embodiment of the present application, step S12 includes the following steps A1-A4:

[0057] Step A1, constructing a virtual model using a defective fatigue specimen.

[0058] Specifically, the construction of a virtual model aims to provide a digital foundation for subsequent simulation of impact and related analysis. The specific process includes but is not limited to: using high-precision measuring instruments (such as a three-coordinate measuring machine) to measure the overall and impact defect geometric dimensions of defect fatigue specimens; determining the elastic modulus, Poisson's ratio, yield strength and other mechanical performance parameters of the TC4 titanium alloy material, obtaining them through material manuals, relevant standards or previous tests and inputting them into the modeling software; meshing the model with defined geometric shapes and material properties in the modeling software, using fine grids for stress-complex areas near the impact defects, and appropriately sparse grids for areas far away; setting boundary conditions based on actual conditions, simulating the way the specimens are fixed in actual tests to impose fixed constraints, and setting impact direction, speed and other impact-related conditions at the same time, thereby constructing a virtual model that can accurately simulate the mechanical behavior under actual impact conditions, laying a solid foundation for subsequent analysis.

[0059] Step A2: simulate impact on the virtual model based on preset impact conditions to obtain local residual stress field data of the impact defect on the virtual model.

[0060] Specifically, the impact simulation is based on the principle of dynamics. According to the theory of material mechanics and dynamics, the effect of the actual impact scene on the defect fatigue specimen is converted into a numerical calculation process. By inputting the preset impact conditions such as impact energy, speed, angle, etc., such as the impact head hitting the specimen at a certain speed, the internal stress of the specimen is changed based on the law of conservation of momentum and energy. The process is as follows: first, a suitable numerical algorithm is selected, such as the explicit dynamics algorithm is used for highly nonlinear dynamic problems such as high-speed impact to simulate the large deformation of the material and the propagation of stress waves at the moment of impact; according to the actual impact situation, the impact head shape, size, mass and initial impact speed, direction and other parameters are accurately input into the simulation software, such as the drop hammer test needs to set the drop hammer mass, drop height and impact point position; start the simulation calculation, divide the virtual model into small units, solve the dynamic equations of each unit at different times, simulate the whole impact process and stress-strain response; after the impact, use the simulation software to extract the local residual stress field data around the impact defect, such as the residual stress cloud map obtained by the post-processing function, to provide key data for subsequent analysis.

[0061] Step A3: import the local residual stress field data into the virtual model as the initial stress state to obtain the target virtual model.

[0062] Specifically, considering that the residual stress inside the material after the actual impact will significantly affect its subsequent mechanical behavior, the local residual stress field data obtained from the simulated impact is re-imported into the virtual model as the initial stress state, so that the virtual model can more realistically reflect the stress state of the material after the actual impact, and lay a more realistic foundation for the subsequent simulation of the stress response of the material under load and the calculation of related parameters. The specific operation is to use the function of the simulation software to map the residual stress field data that records the local stress information of the impact defect to the model according to the virtual model node and unit distribution as a new initial state. In this way, when other load simulations such as the fatigue limit of smooth specimens are applied to the model, the mechanical behavior of the material under actual working conditions can be simulated based on the initial state containing residual stress, and the situation in which the interaction between residual stress and external load affects the fatigue performance of the component in reality can be reproduced, providing a model basis for in-depth research on the influence of impact defects on the fatigue performance of materials, so as to calculate key parameters and achieve accurate prediction of the fatigue limit of titanium alloys containing impact defects.

[0063] Step A4, calculating the local stress ratio and the projection area value according to the target virtual model.

[0064] It should be noted that Figure 4 It is a schematic diagram of the impact defect projection area, showing a plane with an impact pit, marking the radius r, depth h0 and projection area area0 of the impact pit on the plane, and establishing X, Y, and Z coordinate axes for positioning and description.

[0065] In the embodiment of the present application, step A4 includes the following steps A41-A43:

[0066] Step A41, obtaining the original fatigue limit value of the smooth specimen.

[0067] Specifically, the original fatigue limit value of the smooth specimen is the alternating stress limit that the material can withstand in a defect-free state, which reflects the inherent fatigue performance of the material itself. Obtaining this value provides an important benchmark for subsequent simulation of the stress response of the material under actual defective working conditions. Because in actual applications, the presence of impact defects will change the stress distribution of the material, thereby affecting the fatigue limit, and the original fatigue limit value, as a reference standard, helps to analyze the specific impact of impact defects on the fatigue performance of the material.

[0068] Step A42: applying the original fatigue limit value as the axial load parameter to the target virtual model to obtain the local stress state change of the impact defect.

[0069] Specifically, the original fatigue limit value of the smooth specimen is applied as an axial load to the target virtual model, which simulates the stress state of the material under actual conditions when subjected to alternating loads. Since the target virtual model already contains the residual stress after impact, after the load is applied, the impact defect site in the model will produce local stress state changes due to effects such as stress superposition. This simulation can more realistically reflect how the stress at the impact defect evolves when the material containing the impact defect is subjected to load in actual use, providing key data for the accurate calculation of the local stress ratio.

[0070] It should be noted that after the simulated impact, the impact defects need to be stretched / compressed, etc. Figure 5 As shown, the finite element cloud diagram of the subsequent processing of the impact defect after the simulated impact is displayed, where Figure a is the tensile situation and Figure b is the compression situation. The stress or strain of the material under different stress states is intuitively displayed through the deep and shallow distribution.

[0071] Step A43, calculating the local stress ratio of the impact defect according to the change of the local stress state, and calculating the projection area value in the load axis direction according to the impact defect of the target virtual model.

[0072] Specifically, in material fatigue analysis, stress ratio is a key parameter to measure fatigue characteristics, which reflects the ratio of the minimum stress to the maximum stress in the stress cycle. In this step, according to the change in the local stress state of the impact defect, the maximum stress value σ of the area during the stress cycle is determined. max and the minimum stress value σ min By formula The local stress ratio R of the impact defect can be calculated. This stress ratio is very important for evaluating the fatigue life of materials containing impact defects, because different stress ratios will cause the material to exhibit different fatigue properties under the same loading conditions. For example, a higher stress ratio means that the material is more susceptible to fatigue failure at a lower stress level.

[0073] In an embodiment of the present application, according to the projection area value of the impact defect of the target virtual model in the load axis direction, it includes: scanning the impact defect of the defect fatigue specimen to obtain contour data; extracting the depth value and the local radius value in the contour data; and calculating the projection area value of the impact defect in the load axis direction according to the depth value and the local radius value.

[0074] Specifically, first, use a suitable measuring device, such as a 3D optical profiler (such as Zeta TM -20 three-dimensional profiler) is used to scan the impact defects on the defect fatigue specimen. Secondly, from the acquired profile data, the depth value d and the local radius value r of the impact defect are identified and extracted through data analysis and processing technology. The depth value represents the maximum size of the impact defect in the direction perpendicular to the surface of the specimen, while the local radius value describes the extension degree of the impact defect in the horizontal direction. Finally, the projection area value of the impact defect in the direction of the load axis is calculated based on the depth value and the local radius value. Taking the impact defect approximating a hemispherical impact defect as an example, the projection area A in the direction of the load axis can be calculated by the formula A=πr 2 Calculated (if it is a semi-ellipse, the calculation formula will change accordingly, such as A=πab, where a and b are the major and minor semi-axis of the ellipse, respectively. Here, a and b can be determined according to the depth value and the local radius value). The projected area value reflects the equivalent size of the impact defect in the direction of material force. In the process of predicting the fatigue limit of titanium alloys containing impact defects, it works together with parameters such as local stress ratio and material Vickers hardness to affect the calculation results of the fatigue limit. A larger projected area usually means that the impact defect has a more significant effect on the fatigue properties of the material, because it will cause greater stress concentration, thereby reducing the fatigue limit of the material.

[0075] Step S13, obtaining the Vickers hardness value of the smooth sample, and calculating the fatigue limit prediction value of the defective fatigue sample according to the Vickers hardness value, the local stress ratio and the projected area value.

[0076] In the embodiment of the present application, the fatigue limit prediction value of the defective fatigue specimen is calculated according to the Vickers hardness value, the local stress ratio and the projected area value, including the following steps B1-B2:

[0077] Step B1, substituting the Vickers hardness value, the local stress ratio and the projected area value into a preset relationship.

[0078] Specifically, the Vickers hardness value (HV), local stress ratio (R) and projected area value (area0) are substituted into the preset relationship. The purpose of this formula is to comprehensively consider the Vickers hardness of the material, the local stress ratio and the projected area of ​​the impact defect in the load axis direction to predict the fatigue limit of the material containing impact defects. By substituting these parameters into the formula, a more accurate fatigue limit prediction value can be obtained, which helps to evaluate the fatigue performance of materials containing impact defects in actual use.

[0079] Step B2, calculating the fatigue limit prediction value of the defective fatigue specimen based on a preset relationship.

[0080] In the embodiment of the present application, the preset relationship is as follows:

[0081]

[0082] in, is the fatigue limit prediction value; k = 0.85 coefficient; HV is the Vickers hardness value; R is the local stress ratio; area0 is the projected area; α = 0.226 + HV 10 -4 .

[0083] Figure 6 The figure is a schematic diagram of the fatigue limit prediction process of defective materials. The process starts with the preparation of impact defects, followed by the preparation of smooth fatigue specimens, and the finite element simulation of the impact process, followed by the impact subsequent tension / compression simulation, thereby obtaining the local stress ratio. At the same time, the Vickers hardness test is performed after the hardness specimen is prepared to obtain the Vickers hardness. In addition, the smooth fatigue specimen will also undergo fatigue limit tests to obtain the fatigue limit of defective materials and the fatigue limit of smooth specimens, and the size of the defects related to the fatigue limit of defective materials will be measured to calculate the defect projection area. Finally, the fatigue limit is obtained through the fatigue limit mathematical model by combining the defect projection area, Vickers hardness and local stress ratio. The entire process presents a multi-step, interrelated system for accurately predicting the fatigue limit of defective materials.

[0084] In the embodiment of the present application, after calculating the fatigue limit prediction value of the defective fatigue specimen according to the Vickers hardness value, the local stress ratio and the projected area value, the method further includes the following steps C1-C3:

[0085] Step C1, applying cyclic stress to the defective fatigue specimen according to preset test parameters until the defective fatigue specimen is in a failure state, and obtaining an actual value of the fatigue limit.

[0086] Specifically, the actual value of fatigue limit is used to compare with the predicted value of fatigue limit calculated by the previous formula to evaluate the accuracy of the prediction method. The operation method is to apply cyclic stress to the defective fatigue specimen according to the preset test parameters determined by the relevant standards and experimental requirements, and continuously observe the state of the specimen during the application process. When the specimen has cracks, fractures, or reaches the specified deformation and other failure states, the actual value of fatigue limit that can reflect the fatigue performance of the specimen containing impact defects under actual stress conditions can be obtained, providing key data support for evaluating the accuracy of the prediction method.

[0087] Step C2, comparing the fatigue limit prediction value with the fatigue limit actual value to obtain a comparison result.

[0088] Specifically, the actual value of the fatigue limit obtained by applying cyclic stress to the defective fatigue specimen until it fails in step C1, and the predicted value of the fatigue limit calculated by the preset relationship in step B2 are obtained. Then, the two values ​​are compared. For example, if the predicted value of the fatigue limit is XMPa and the actual value of the fatigue limit is YMPa, the comparison result is determined by calculating the difference between the two or the ratio between the two. This comparison result can reflect the accuracy of the prediction method. The smaller the difference or the closer the ratio is to 1, the more accurate the prediction method is.

[0089] Step C3, calculating the prediction accuracy for the defective fatigue specimen according to the comparison result.

[0090] Specifically, the accuracy of the fatigue limit prediction method of titanium alloy containing impact defects for the defective fatigue specimen is quantitatively evaluated based on the comparison results, providing data support for judging its effectiveness and reliability. There are various calculation methods, such as the absolute error method, which measures the prediction accuracy by calculating the ratio of the absolute error to the actual value of the fatigue limit; the relative error method, which uses the relative error to calculate the prediction accuracy; and other statistical methods, such as the root mean square error, mean absolute percentage error, etc., according to specific needs, using multiple groups of predicted values ​​and actual values ​​of multiple tests to calculate RMSE, and then determine the prediction accuracy based on the specific relationship between RMSE and the actual value of the fatigue limit. The prediction accuracy calculated in this step intuitively reflects the reliability of predicting the fatigue limit of titanium alloy containing impact defects. The high prediction accuracy shows that this method has good practicality and accuracy in predicting the fatigue limit of such materials.

[0091] In this embodiment, a device for predicting fatigue limit of titanium alloy is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceivable.

[0092] This embodiment provides a device for predicting the fatigue limit of titanium alloy. Figure 7 As shown, including:

[0093] A preparation module 71, used for preparing defect fatigue specimens using smooth specimens of preset materials;

[0094] A simulation module 72 is used to simulate the impact on the defect fatigue specimen based on a preset impact condition to obtain a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis;

[0095] The prediction module 73 is used to obtain the Vickers hardness value of the smooth sample, and calculate the fatigue limit prediction value of the defective fatigue sample according to the Vickers hardness value, the local stress ratio and the projected area value.

[0096] In an optional embodiment of the present application, the simulation module 72 is used to construct a virtual model using a defective fatigue specimen; simulate the impact on the virtual model based on preset impact conditions to obtain local residual stress field data of the impact defect on the virtual model; import the local residual stress field data into the virtual model as the initial stress state to obtain a target virtual model; calculate the local stress ratio and the projection area value according to the target virtual model.

[0097] In an optional embodiment of the present application, the simulation module 72 is used to obtain the original fatigue limit value of the smooth specimen; apply the original fatigue limit value as the axial load parameter to the target virtual model to obtain the local stress state change of the impact defect; calculate the local stress ratio of the impact defect according to the local stress state change, and calculate the projection area value in the load axis direction according to the impact defect of the target virtual model.

[0098] In an optional embodiment of the present application, the simulation module 72 is used to scan the impact defect of the defect fatigue specimen to obtain contour data; extract the depth value and the local radius value in the contour data; and calculate the projection area value of the impact defect in the load axis direction according to the depth value and the local radius value.

[0099] In an optional embodiment of the present application, the prediction module 73 is used to substitute the Vickers hardness value, the local stress ratio and the projected area value into a preset relationship; and calculate the fatigue limit prediction value of the defective fatigue specimen based on the preset relationship.

[0100] In an optional embodiment of the present application, the device also includes: a calculation module, which is used to apply cyclic stress to the defective fatigue specimen according to preset test parameters until the defective fatigue specimen is in a failure state, and obtain an actual value of the fatigue limit; compare the predicted value of the fatigue limit with the actual value of the fatigue limit to obtain a comparison result; and calculate the prediction accuracy for the defective fatigue specimen based on the comparison result.

[0101] See also Figure 8 , Figure 8 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 8 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0102] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0103] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0104] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0106] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0107] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0108] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for predicting fatigue limit of titanium alloy, characterized in that: The method comprises: Preparation of defect fatigue specimens using smooth specimens of preset materials; Performing a simulated impact on the defect fatigue specimen based on a preset impact condition to obtain a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis; The Vickers hardness value of the smooth sample is obtained, and the fatigue limit prediction value of the defective fatigue sample is calculated according to the Vickers hardness value, the local stress ratio and the projection area value.

2. The method according to claim 1, characterized in that The method of performing a simulated impact on the defect fatigue specimen based on a preset impact condition to obtain a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis includes: constructing a virtual model using the defective fatigue specimen; Performing a simulated impact on the virtual model based on a preset impact condition to obtain local residual stress field data of the impact defect on the virtual model; Importing the local residual stress field data into the virtual model as an initial stress state to obtain a target virtual model; The local stress ratio and the projected area value are calculated according to the target virtual model.

3. The method according to claim 2, characterized in that The calculating the local stress ratio and the projection area value according to the target virtual model includes: Obtain the original fatigue limit value of the smooth specimen; Applying the original fatigue limit value as an axial load parameter to the target virtual model to obtain a change in the local stress state of the impact defect; The local stress ratio of the impact defect is calculated according to the change of the local stress state, and the projection area value in the load axis direction is calculated according to the impact defect of the target virtual model.

4. The method according to claim 3, characterized in that The projection area value of the impact defect of the target virtual model in the load axis direction includes: Scanning the impact defect of the defect fatigue specimen to obtain profile data; Extracting a depth value and a local radius value from the contour data; The projection area value of the impact defect in the load axis direction is calculated according to the depth value and the local radius value.

5. The method according to claim 1, characterized in that The step of calculating the fatigue limit prediction value of the defective fatigue specimen according to the Vickers hardness value, the local stress ratio and the projected area value comprises: Substituting the Vickers hardness value, the local stress ratio and the projected area value into a preset relationship; The fatigue limit prediction value of the defective fatigue specimen is calculated based on the preset relationship.

6. The method according to claim 5, characterized in that The preset relationship is as follows: in, is the fatigue limit prediction value; k = 0.85 coefficient; HV is the Vickers hardness value; R is the local stress ratio; area0 is the projected area; α = 0.226 + HV 10 -4 index.

7. The method according to claim 1, characterized in that After calculating the fatigue limit prediction value of the defective fatigue specimen according to the Vickers hardness value, the local stress ratio and the projected area value, the method further includes: Applying cyclic stress to the defective fatigue specimen according to preset test parameters until the defective fatigue specimen is in a failure state, and obtaining an actual value of the fatigue limit; Comparing the fatigue limit prediction value with the fatigue limit actual value to obtain a comparison result; The prediction accuracy for the defective fatigue specimen is calculated according to the comparison result.

8. A device for predicting fatigue limit of titanium alloy, characterized in that: The device comprises: A preparation module for preparing defect fatigue specimens using smooth specimens of preset materials; A simulation module, used for performing a simulated impact on the defect fatigue specimen based on a preset impact condition, and obtaining a local stress ratio of the impact defect on the defect fatigue specimen and a projected area value in the direction of the load axis; A prediction module is used to obtain the Vickers hardness value of the smooth sample, and calculate the fatigue limit prediction value of the defective fatigue sample according to the Vickers hardness value, the local stress ratio and the projection area value.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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