A method for optimizing a round cornering process of a bolt head

Abstract

This invention discloses an optimization method for the fillet rolling process of bolt heads, comprising the following steps: obtaining the true stress-strain curve and mechanical property parameters of the bolt material through tensile testing; testing the roughness and fatigue life of bolts without rolling and with different rolling processes; determining appropriate mesh size and fatigue algorithm by combining ABAQUS and FE-safe simulations, and calculating the fatigue life of the unrolled bolt; based on this, calculating the residual stress distribution and fatigue life of the rolled bolt using ABAQUS and FE-safe simulations, and optimizing and verifying the fatigue life prediction model based on the fatigue life experimental results; analyzing the relationship between the fillet rolling process and fatigue life using the optimized fatigue life prediction model; selecting the fillet rolling process parameter range for the bolt structure, calculating the fatigue life of the bolt after fillet rolling using the fatigue life prediction model, and selecting a reasonable process parameter range based on the fatigue life.

Description

Technical Field

[0001] This invention belongs to the field of fastener technology. Taking into account the effects of fillet rolling on bolt surface morphology, work hardening and residual stress, this invention establishes an effective method for predicting the fatigue life of bolts after fillet rolling, and obtains the control range of bolt fillet rolling process parameters. Background Technology

[0002] Fasteners are widely used in mechanical equipment, serving functions such as connection, adjustment, and even transmission. They are core foundational components affecting the overall quality and service life of equipment, often referred to as the "rice of industry." Bolts are the most widely used fasteners, and fatigue failure is their primary cause of failure. During service, the fillet under the bolt head is one of the main stress concentration points and a high-risk area for fatigue fracture. Fillet rolling is a key process in bolt manufacturing, significantly improving the fatigue strength of the bolt head and shank. Fillet rolling reduces fillet roughness, minimizes surface defects, induces work hardening in the surface layer, and creates residual compressive stress, inhibiting crack formation and propagation, thereby greatly extending the bolt's fatigue life.

[0003] The effect of bolt fillet rolling process parameters on bolt strengthening is complex, and current research in this area is limited and mainly focuses on experimental aspects, with numerical simulation analysis being even rarer. In actual production, rolling parameters are often determined based on on-site production experience, and there is no systematic and standardized specification for the process parameters adopted for workpieces of different specifications and materials; many products often select the same process parameters. Organically linking process, residual stress, and fatigue performance is of guiding significance for process parameter optimization, product performance improvement, and new product process design. Summary of the Invention

[0004] Current research on bolt head fillet rolling is limited and primarily experimental, while common bolt fatigue finite element analyses do not consider the effect of initial machining. This invention establishes a finite element model of bolt fillet rolling and fatigue using ABAQUS and FE-safe, and compares and verifies the results with experimental data. Based on this model, the fatigue life of bolts under different rolling processes is calculated. In addition to considering the effect of residual stress, the model also incorporates factors such as work hardening and surface roughness. Furthermore, the mesh size and fatigue algorithm are optimized, resulting in relatively accurate fatigue life predictions. This provides guidance for the design and optimization of bolt head fillet rolling processes.

[0005] This invention provides a finite element model of bolt fillet rolling and fatigue based on ABAQUS and FE-safe to predict the fatigue life of bolts before and after rolling, and to optimize the bolt fillet rolling process accordingly. The operation is as follows:

[0006] This invention provides an optimized method for the bolt head fillet rolling process, comprising the following steps:

[0007] Step 1: Prepare standard tensile specimens from metal materials of the same material and treatment as the bolts and conduct tensile tests to obtain the true stress-strain curves and tensile strength of the corresponding materials; roll the bolts using different rolling processes and test the roughness of the lower fillet of the bolt head before and after rolling; conduct fatigue tests on bolts without rolling and bolts under different rolling processes to obtain the fatigue life results of unrolled bolts and bolts under different rolling processes.

[0008] Step 2: Establish a geometric model in ABAQUS based on the bolt's geometric dimensions, define material parameters and mesh generation, apply constraints and fatigue loads to the bolt, and use different mesh sizes to obtain the finite element result file of the stress distribution of the unrolled bolt under a cyclic load; the material parameters include the material's elastic modulus, room temperature tensile stress-strain data, Poisson's ratio, and density;

[0009] Import the finite element results file obtained from ABAQUS into FE-safe, input material parameters and add load spectra, select the Morrow-corrected maximum principal strain algorithm to generate a fatigue life calculation file, and solve for the first simulation result of fatigue life; in the first simulation result, select the mesh size corresponding to the fatigue life value with an error value ≤10% compared with the measured fatigue life value in step 1 as the mesh size of the bolt fillet position, and complete the establishment of the finite element model for fatigue analysis of the unrolled bolt; the material parameters input in FE-safe include material type, elastic modulus of the material, tensile strength of the material, Poisson's ratio of the material, and roughness of the unrolled bolt;

[0010] Step 3: On the bolt mesh model obtained in Step 2, based on the actual rolling depth, rolling angle and roller fillet radius, establish a fillet rolling model in ABAQUS, then apply constraints and fatigue loads to the bolt, and solve the finite element result file of the stress distribution of the rolled bolt under a cyclic load in ABAQUS.

[0011] Import the finite element result file obtained from ABAQUS into FE-safe. Considering the work hardening and roughness of the fillet surface, select different fatigue life algorithms to generate fatigue life calculation files, and solve for the second simulation result of fatigue life considering the work hardening and roughness of the fillet surface. In the second simulation result, select the fatigue life algorithm corresponding to the measured fatigue life of the bolt that breaks at the fillet in step 1 with an error value ≤10% or greater than or equal to the measured fatigue life of the bolt that breaks at the thread in step 1. This determines the fatigue life algorithm of the bolt, and completes the establishment of the finite element model of bolt fillet rolling-fatigue analysis.

[0012] Step 4: Using the bolt rolling-fatigue analysis finite element model obtained in Step 3, input different rolling process conditions to solve for the fatigue life of the bolt under different rolling conditions. Select the process conditions and test the fatigue life corresponding to different processes through bolt fillet rolling process experiments, and compare it with the calculated value. The simulation and test error should be within 10% to verify and optimize the model.

[0013] Step 5: Based on the actual bolt specifications, determine the optimal fillet rolling process for the bolts using a finite element model of bolt fillet rolling-fatigue analysis.

[0014] As a preferred embodiment, the present invention provides an optimized method for the rolling process of the lower fillet of the bolt head. The tensile test in step 1 is performed according to the GBT_228.1-2010 standard, the fatigue test is performed according to the NASM1312-11 standard, the roughness test method is the sample comparison method, and the measurement standard is GB / T1031-1995.

[0015] This invention provides an optimized method for the bolt head fillet rolling process. The bolt rolling process parameters can be: rolling force 800N, rolling speed 500rad / s, rolling time 2s, and roller fillet radius 0.45mm.

[0016] As a preferred embodiment, the present invention provides an optimization method for the bolt head fillet rolling process, which establishes a geometric model in ABAQUS based on the bolt's geometric dimensions, defines material parameters and mesh generation; the material parameters include: elastic modulus, room temperature tensile stress-strain data, Poisson's ratio, and density;

[0017] Import the finite element result file obtained from ABAQUS into FE-safe, input the material parameters and add the load spectrum; the material parameters input into FE-safe include material type, elastic modulus, tensile strength, Poisson's ratio and roughness.

[0018] As a preferred embodiment, the present invention provides an optimization method for the fillet rolling process of bolt heads. In steps 2 and 3, the model and the sample are the same size. The sample is an M6 type flat head and countersunk head TC4 titanium alloy high-lock bolt. When dividing the grid at the fillet, the grid thickness is no more than 0.01 mm.

[0019] In industrial applications, during step 2, when the remaining area of ​​the bolt is meshed, the meshing is based on global point distribution.

[0020] As a preferred embodiment, in step 2 of the optimized method for the bolt head fillet rolling process of the present invention...

[0021] The fatigue model expression modified by Morrow is:

[0022]

[0023] In the formula Δε t -Total strain range; N f - Fatigue life; σ′ f - Fatigue strength coefficient; ε′ f - Fatigue ductility coefficient; b - Fatigue strength index; c - Fatigue ductility index; E - Elastic modulus of the material; σ m This represents the average stress. In the above formula, tensile strength, Poisson's ratio, and roughness determine σ′. f , ε′ f The values ​​of b and c.

[0024] As a preferred embodiment, in the bolt head fillet rolling process optimization method of the present invention, the fatigue criterion for selecting the bolt after fillet rolling in step 3 is the Brown-Miller model, and the fatigue life model expression after Morrow modification is as follows:

[0025]

[0026] In the formula, Δγ and Δε represent the shear strain and normal strain on the critical surface, respectively. In the modified model, tensile strength, Poisson's ratio, and roughness determine the values ​​of Δγ, Δε, b, and c.

[0027] This invention provides an optimized method for the bolt head fillet rolling process, in step 3.

[0028] The rolling process parameters indirectly affect fatigue life by influencing residual stress, work hardening, and changes in fillet size at the fillet. For example, when conducting forging simulations to study the effects of deformation temperature, deformation rate, die fatigue dimensions, and deformation amount on forming, there is no direct model expression. In the end, we can only fit an equation to the simulation results to reflect the law.

[0029] This invention provides an optimized method for the rolling process of bolt head fillet. After optimization, the optimal rolling process for TC4 titanium alloy M6 bolts is as follows: for flat head bolts, the rolling depth is 0.02mm and the rolling angle is 45°; for countersunk head bolts, the rolling depth is 0.45mm and the rolling angle is 25°. The optimal roller radius for both is 90%-95% of the bolt fillet size.

[0030] The present invention provides an optimized method for the rolling process of bolt head fillet. The optimized rolling process for TC4 titanium alloy M6 specification 100° countersunk bolts is as follows: roller fillet radius is 0.45mm, rolling angle is 25°, and rolling depth is 0.045mm.

[0031] This invention utilizes ABAQUS and FE-safe to establish finite element models of bolt fillet rolling and fatigue, and conducts experimental verification. It obtains the relationship between bolt fatigue life and fillet rolling process. By accurately predicting fatigue life, it provides a feasible method for the design and optimization of bolt head fillet rolling process, reducing the lengthy and cumbersome process testing. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0033] Figure 1 This is a flowchart of fatigue calculation using ABAQUS combined with FE-safe;

[0034] Figure 2 This shows the effect of the mesh size at the fillet on the fatigue life calculation results when the initial stress of the bolt is zero.

[0035] Figure 3 This is a prediction cloud map of bolt fatigue life in Example 1.

[0036] Figure 4 This refers to the fatigue life of the flat-head bolts under different rolling depths in Example 1;

[0037] Figure 5 This refers to the fatigue life of the countersunk bolt under the non-rolling angle in Example 2.

[0038] Figure 6 This is a fatigue life prediction diagram of the bolts after rolling with different rolling angles in Example 1;

[0039] Figure 7 The graph shows the predicted fatigue life of bolts with different rolling depths in Example 2.

[0040] Figure 8 This is a graph showing the predicted fatigue life of bolts after rolling with rollers at different rolling angles in Example 2;

[0041] Figure 9 The figure shows the predicted fatigue life of bolts after rolling with rollers of different fillet sizes in Example 2. Detailed Implementation

[0042] 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.

[0043] Example 1

[0044] A process optimization method based on the fatigue life of bolts after fillet rolling includes the following steps:

[0045] Step 1: Prepare standard tensile specimens of the same material as the bolts and conduct tensile tests to obtain the corresponding true stress-strain curves and mechanical property parameters. Perform bolt fatigue tests under unrolled and different rolling processes, test the roughness before and after rolling, and obtain the corresponding fatigue life results.

[0046] This example uses an M6 TC4 flat-head high-strength bolt as the research object. According to the GBT_228.1-2010 standard, the standard tensile specimen of annealed Ti-6Al-4V was subjected to tensile testing in a microcomputer-controlled electronic universal testing machine WDW-300 after solution aging treatment (temperature 24℃, relative humidity 50%, deformation speed 2mm / min). The stress-strain data during the tensile process were recorded using the high-precision extensometer (extensometer measuring distance 25mm) built into the equipment.

[0047] The bolt rolling process parameters were: rolling force 800 N, rolling speed 500 rad / s, and rolling time 2 s. The roughness of the fillet surface was estimated using the sample comparison method, with the measurement standard being GB / T1031-1995. Bolt fatigue tests were conducted on a fatigue testing machine after assembly according to NASM1312-11 standard. The maximum fatigue load was approximately 8676 N, the minimum load was 10% of the maximum load, and the loading frequency was 140 Hz.

[0048] The fatigue test results are shown in Table 1. The fatigue fracture locations of the unrolled bolts were all at the lower fillet of the bolt head, while the fracture locations of the rolled bolts were all at the threads.

[0049] Table 1. Fatigue test results of bolt specimens (unit: 1000 cycles)

[0050]

[0051] Step 2: Combine ABAQUS and FE-safe simulations to determine suitable mesh size and fatigue algorithm, and obtain the fatigue life of the unrolled bolts. For example... Figure 1As shown, based on the bolt geometry and fatigue test standards, a geometric model of the bolt is established in ABAQUS and a static analysis of the bolt under fatigue load is completed. The stress results are imported into FE-safe to calculate the fatigue life. Combined with the test results, the appropriate mesh size (where the mesh thickness does not exceed 0.01 mm) and fatigue algorithm are determined.

[0052] Specifically, the material model parameters involved in ABAQUS include: elastic modulus, room temperature tensile stress-strain data, Poisson's ratio, and density. The material model parameters involved in FE-safe include: material type, elastic modulus, tensile strength, Poisson's ratio, and roughness. Based on the experimental results of step 1 and relevant literature, the stress-strain data of TC4 after solution treatment and aging are shown in Table 2, and the other parameter settings of the material model are shown in Table 3.

[0053] Table 2 True stress-strain data of TC4 during the quasi-static tensile-plastic stage

[0054]

[0055] Table 3 Material Model Parameters

[0056]

[0057] Mesh quality is one of the most critical factors affecting the accuracy of finite element analysis (FEM). To determine a reasonable mesh size, the influence of mesh size on FEM results is analyzed. With the bolt initially under zero stress and a certain load applied, the effect of mesh size at the fillet on fatigue calculation (fatigue life is the minimum predicted fatigue life of the bolt) is as follows: Figure 2 As shown, the equation of the fitted curve is: Where x is the grid size at the rounded corner;

[0058] To achieve a balance between computational accuracy and efficiency, and to facilitate subsequent data processing, the mesh size along the depth direction at the rounded corners was selected to be 0.01 mm, at which point the simulation results showed good convergence.

[0059] Step 2 selects the maximum principal strain criterion as the fatigue criterion and performs Morrow mean stress correction.

[0060] The fatigue model expression modified by Morrow is:

[0061]

[0062] In the formula Δε t -Total strain range; N f - Fatigue life; σ′ f - Fatigue strength coefficient; ε′ f- Fatigue ductility coefficient; b - Fatigue strength index; c - Fatigue ductility index; E - Elastic modulus of the material; σ m This represents the average stress. In the above formula, tensile strength, Poisson's ratio, and roughness determine σ′. f , ε′ f The values ​​of b and c.

[0063] The fatigue model is the formula mentioned above, which is the criterion for calculating fatigue life.

[0064] The finite element simulation results of fatigue of unrolled bolts are as follows: Figure 3 As shown in Figure a, the fatigue fracture location is also at the rounded corner, and the minimum fatigue life is 30,000 cycles. The simulation results are close to the experimental values, indicating that the fatigue simulation model has good reliability.

[0065] Step 3: Based on the model in Step 2, the complex rolling process is simplified into a two-dimensional rolling model. The residual stress distribution after rolling and the stress spectrum under fatigue load are obtained in ABAQUS. The residual stress and fatigue life of the bolt after rolling are calculated by combining ABAQUS and FE-safe simulations. A suitable fatigue algorithm is selected and the model is optimized based on the experimental results.

[0066] Based on the model in step 2, the influence of rolling on the morphology of the bolt fillet and work hardening was considered. Based on the experimental results of step 1, the surface roughness of the rolled bolt was 0.8 μm. According to the general work hardening rate of titanium alloys during cold working, the surface mesh strength of the rolled bolt was set to 1300 MPa, with the remaining material parameters consistent with those in step 2. The rolling process parameters were: rolling depth 0.02 mm, roller fillet radius 0.45 mm, and rolling angle 45°.

[0067] In step 3, the fatigue criterion for the bolts after fillet rolling is the Brown-Miller model, and Morrow mean stress correction is performed.

[0068] In step 3, the fatigue criterion for the bolts after rounding at the corners is the Brown-Miller model. The Morrow-modified fatigue life model expression is as follows:

[0069]

[0070] In the formula, Δγ and Δε represent the shear strain and normal strain on the critical surface, respectively. In the modified model, tensile strength, Poisson's ratio, and roughness determine the values ​​of Δγ, Δε, b, and c. The fatigue model is based on the above formula, which is the criterion for calculating fatigue life. The simulated fatigue life after bolt rolling is 494,000 cycles (e.g., ...). Figure 3(b) Since the influence of the thread is not considered in the model, the simulated value is the fatigue life at the fillet. The simulated value at the bolt fillet is greater than the experimental value, and the actual life of the bolt fillet is also greater than the experimental value. Therefore, the analysis of the relationship between fillet rolling process and fatigue life using this model is reliable.

[0071] Step 4: Based on the optimized model, obtain the residual stress and fatigue life of the bolts under different rolling conditions, and obtain the optimized process parameters based on the calculation results.

[0072] Figure 4 Fatigue life prediction for bolts at different rolling depths was performed. With increasing rolling depth, the bolt fatigue life increased rapidly, reaching a maximum of approximately 494,000 cycles at a rolling depth of about 0.02 mm, representing a nearly 17-fold increase compared to before rolling. Fatigue failure occurred at the bolt's fillet. However, with further increases in rolling depth, the bolt fatigue life decreased rapidly.

[0073] Figure 5 The fatigue life prediction results for bolts after rolling with rollers of different fillet sizes are shown. When the fillet radius of the roller is less than 0.4 mm, the fatigue life of the bolt after rolling is less than 100,000 cycles; when the fillet radius is 0.47 mm, the fatigue life reaches the maximum value of about 759,000 cycles, which is nearly 25 times higher than before rolling; however, as the fillet radius of the roller increases further, the fatigue life of the bolt decreases rapidly.

[0074] Figure 6 This study aims to predict the fatigue life of bolts after rolling with different rolling angles using rollers. The rolling angle has a relatively small impact on the fatigue life of flat-head bolts, and due to the relationship between the fillet radius of the flat-head bolt and the rolling fixture, the rolling angle can only vary within a very small range (10°). Therefore, 45° can be considered the optimal rolling angle.

[0075] Based on the above calculations, the optimized rolling process for TC4 titanium alloy M6 flat-head high-strength bolts is as follows: roller radius of 0.47mm, rolling angle of 45°, and rolling depth of 0.02mm. The measured bolt fatigue life exceeds 200,000 cycles.

[0076] Example 2

[0077] Consistent with the steps in Example 1, a finite element model of fillet rolling and fatigue of M6 specification 100° countersunk TC4 titanium alloy bolts was established using ABAQUS. Through calculation, the relationship between process parameters and fatigue life was analyzed to obtain the optimized range of process parameters.

[0078] Figure 7The fatigue life prediction results for bolts with different rolling depths show that as the rolling depth increases, the bolt fatigue life rises rapidly, reaching its maximum at a rolling depth of approximately 0.045 mm. With further increases in rolling depth, the bolt fatigue life decreases slightly. According to processing requirements, the maximum rolling depth at the bolt fillet should not exceed 0.05 mm.

[0079] Figure 8 The fatigue life prediction results of bolts after rolling with rollers at different rolling angles are shown. As the rolling angle increases, the fatigue life of the bolts first increases and then decreases, reaching its maximum value at a rolling angle of 25°.

[0080] Figure 9 The fatigue life prediction results for bolts after rolling with rollers of different fillet sizes are shown. Within the range of 0.2 mm to 0.45 mm, the fatigue life of the bolts increases exponentially with the increase of the roller fillet radius.

[0081] Based on the above calculations, the optimized rolling process for TC4 titanium alloy M6 specification 100° countersunk bolts is as follows: roller fillet radius of 0.45mm, rolling angle of 25°, and rolling depth of 0.045mm. The measured bolt fatigue life exceeds 200,000 cycles.

[0082] The above embodiments are merely illustrative examples to clearly illustrate the present invention and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all embodiments here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. An optimized method for the fillet rolling process of bolt heads, characterized in that, Includes the following steps: Step 1: Prepare standard tensile specimens from metal materials of the same material and treatment as the bolts and conduct tensile tests to obtain the true stress-strain curves and tensile strength of the corresponding materials; roll the bolts using different rolling processes and test the roughness of the lower fillet of the bolt head before and after rolling; conduct fatigue tests on bolts without rolling and bolts under different rolling processes to obtain the fatigue life results of unrolled bolts and bolts under different rolling processes. Step 2: Establish a geometric model in ABAQUS based on the bolt's geometric dimensions, define material parameters and mesh generation, apply constraints and fatigue loads to the bolt, and use different mesh sizes to obtain the finite element result file of the stress distribution of the unrolled bolt under a cyclic load; the material parameters include the material's elastic modulus, room temperature tensile stress-strain data, Poisson's ratio, and density; Import the finite element result file obtained from ABAQUS into FE-safe, input material parameters and add load spectra, select the Morrow-corrected maximum principal strain algorithm to generate a fatigue life calculation file, and solve for the first simulation result of fatigue life; in the first simulation result, select the mesh size corresponding to the fatigue life value with an error value ≤10% compared with the measured fatigue life value in step 1 as the mesh size of the bolt fillet position, and complete the establishment of the finite element mesh model for fatigue analysis of the unrolled bolt; the material parameters input in FE-safe include material type, elastic modulus of the material, tensile strength of the material, Poisson's ratio of the material, and roughness of the unrolled bolt; Step 3: On the bolt mesh model obtained in Step 2, based on the actual rolling depth, rolling angle and roller fillet radius, establish a fillet rolling model in ABAQUS, then apply constraints and fatigue loads to the bolt, and solve the finite element result file of the stress distribution of the rolled bolt under a cyclic load in ABAQUS. Import the finite element result file obtained from ABAQUS into FE-safe. Considering the work hardening and roughness of the fillet surface, select different fatigue life algorithms to generate fatigue life calculation files, and solve for the second simulation result of fatigue life considering the work hardening and roughness of the fillet surface. In the second simulation result, select the fatigue life algorithm corresponding to the measured fatigue life of the bolt that breaks at the fillet in step 1 with an error value ≤10% or greater than or equal to the measured fatigue life of the bolt that breaks at the thread in step 1. This completes the establishment of the finite element model of bolt fillet rolling-fatigue analysis. In step 3, the fatigue criterion for the bolts after rounding at the corners is the Brown-Miller model. The Morrow-modified fatigue life model expression is as follows: ； In the formula and These are the shear strain and normal strain on the critical surface, respectively. Step 4: Using the bolt fillet rolling-fatigue analysis finite element model obtained in Step 3, input different rolling process conditions to solve for the fatigue life of the bolt under different rolling conditions. Select the process conditions and test the fatigue life corresponding to different processes through bolt fillet rolling process experiments, and compare it with the calculated value. The simulation and experimental error should be within 10% to verify and optimize the model. Step 5: Based on the actual bolt specifications, determine the optimal fillet rolling process for the bolt using the finite element model of bolt fillet rolling-fatigue analysis obtained in Step 4.

2. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: The tensile test in step 1 is performed according to the GBT_228.1-2010 standard, the fatigue test is performed according to the NASM1312-11 standard, the roughness test method is the sample comparison method, and the measurement standard is GB / T1031-1995.

3. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: The rolling process parameters for the bolts are: rolling force 800N, rolling speed 500rad / s, rolling time 2s, and roller fillet radius 0.45mm.

4. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: In steps 2 and 3, the model and the specimen are the same size. The specimen is an M6 type flat head and countersunk head TC4 titanium alloy high-strength bolt. When dividing the grid at the rounded corners, the grid thickness is no more than 0.01 mm.

5. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: In step 2, The fatigue model expression modified by Morrow is: ； In the formula This refers to the total strain range; For fatigue life; This is the fatigue strength coefficient; b is the fatigue ductility coefficient; b is the fatigue strength index; c is the fatigue ductility index; E is the elastic modulus of the material. The average stress is denoted as , where , b and c are parameters automatically calculated and determined by FE-safe based on material model parameters; the material model parameters include the tensile strength, Poisson's ratio, and roughness of the material.

6. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: The optimal rolling process for TC4 titanium alloy M6 bolts is as follows: for flat head bolts, the rolling depth is 0.02mm and the rolling angle is 45°; for countersunk head bolts, the rolling depth is 0.45mm and the rolling angle is 25°. The roller radius for both types of bolts should be 90%-95% of the bolt fillet radius.

7. The optimized method for the bolt head fillet rolling process according to claim 1, characterized in that: The optimized rolling process for TC4 titanium alloy M6 specification 100° countersunk bolts is as follows: roller radius of 0.45mm, rolling angle of 25°, and rolling depth of 0.045mm.

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