CN115952614A - Bolt head lower fillet rolling process optimization method - Google Patents
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Abstract
The invention discloses a bolt head lower fillet rolling process optimization method, which comprises the following steps: obtaining a true stress-strain curve and mechanical property parameters of the bolt material through a tensile test; testing the roughness and fatigue life of the bolts corresponding to the non-rolling process and the different rolling processes; determining a proper grid size and fatigue algorithm by combining ABAQUS and FE-safe simulation, and calculating to obtain the fatigue life of the non-rolled bolt; on the basis, obtaining a residual stress distribution result and a fatigue life of the rolled bolt by ABAQUS and FE-safe simulation calculation, and optimizing and verifying a fatigue life prediction model according to a fatigue life experiment result; analyzing the relation between the fillet rolling process and the fatigue life by using the optimized fatigue life prediction model; and aiming at the bolt structure, selecting a fillet rolling process parameter range, calculating the fatigue life of the bolt after fillet rolling by using a fatigue life prediction model, and selecting a reasonable process parameter range according to the fatigue life.
Description
Technical Field
The invention belongs to the technical field of fasteners, and obtains a bolt fillet rolling technological parameter control range by establishing a method for effectively predicting the fatigue life of a bolt subjected to fillet rolling in consideration of the effect of fillet rolling on the surface appearance, work hardening and residual stress of the bolt.
Background
The fastener is widely applied, has the functions of connection, adjustment, even transmission and the like in mechanical equipment, is a core basic part which influences the assembly quality and the service life of the equipment, and is known as industrial meter. Bolts are the most widely used fasteners and fatigue failure is the primary cause of their failure. In the service process, the under head fillet is one of the main stress concentration parts of the bolt and is also a high-incidence part of fatigue fracture. Fillet rolling is a key process for manufacturing the bolt, and the fatigue strength of the head and the rod of the bolt can be obviously improved. The rolling of the fillet under the head can reduce the roughness of the fillet, reduce surface defects, enable the surface layer to be processed and hardened and form residual compressive stress, and inhibit the formation and the expansion of cracks, thereby greatly prolonging the fatigue life of the bolt.
The fillet rolling technological parameters of the bolt have complex strengthening effect on the bolt, the research on the fillet rolling technological parameters is less and is concentrated in the test part at present, and the numerical simulation analysis is rare. In the actual production process, rolling parameters are often determined according to field production experience, the technological parameters adopted by workpieces of different specifications and different materials do not form a systematic and standard specification, and a plurality of products often select the same technological parameter. The process-residual stress-fatigue performance is organically linked, which has guiding significance for optimizing process parameters, improving product performance and designing new product process.
Disclosure of Invention
At present, the research on the rolling process of the under-head fillet of the bolt is less and mainly takes tests, and the fatigue finite element analysis of the common bolt does not consider the effect of initial processing. According to the method, a finite element model of bolt fillet rolling and fatigue is established by combining ABAQUS and FE-safe, the finite element model is compared with a test result for verification, and the fatigue life of the bolt under different rolling processes is calculated based on the finite element model. The model not only considers the action of residual stress, but also introduces factors such as machining hardening, surface roughness and the like into the model, optimizes the grid size and the fatigue algorithm, has accurate fatigue life prediction result, and can provide guidance for the design and optimization of the bolt head lower fillet rolling process.
The invention provides a bolt fillet rolling and fatigue finite element model established based on ABAQUS and FE-safe to predict the fatigue life before and after bolt rolling, and the bolt fillet rolling process is optimized based on the fatigue life. The operation is as follows:
the invention discloses a method for optimizing a rolling process of a lower fillet of a bolt head, which comprises the following steps:
step 1, preparing a standard tensile sample from a metal material which has the same material quality and is in a processing state as a bolt, and performing a tensile test to obtain a true stress-strain curve and tensile strength of the corresponding material; rolling the bolt by adopting different rolling processes, and testing the roughness of the lower fillet of the bolt head before and after rolling; performing fatigue tests on bolts under the conditions of non-rolling and different rolling processes to obtain the fatigue life results of the bolts under the conditions of non-rolling and different rolling processes;
step 2, establishing a geometric model in ABAQUS according to the geometric dimension of the bolt, defining material parameters and grid division, applying constraint and fatigue load to the bolt, and solving by adopting different grid dimensions to obtain a finite element result file of stress distribution of the unrolled bolt under a periodic load; the material parameters comprise the elastic modulus, normal-temperature tensile stress-strain data, poisson's ratio and density of the material;
importing a finite element result file obtained by ABAQUS solution into FE-safe, inputting material parameters and adding a load spectrum, selecting a Morrow corrected fatigue life calculation file generated by adopting a maximum principal strain algorithm, and solving to obtain a first fatigue life simulation result; selecting the mesh size corresponding to the fatigue life value of which the actual fatigue life error value is less than or equal to 10% in the step 1 from the first simulation result as the mesh size of the bolt fillet position, and completing the establishment of the non-rolled bolt fatigue analysis finite element model; the material parameters input in the FE-safe comprise the type of the material, the elastic modulus of the material, the tensile strength of the material, the Poisson ratio of the material and the roughness of an unrolled bolt;
step 3, on the bolt mesh model obtained in the step 2, according to the actual rolling depth, rolling angle and roller fillet radius, establishing a fillet rolling model in ABAQUS, applying constraint and fatigue load to the bolt, and solving in ABAQUS to obtain a finite element result file of stress distribution of the rolled bolt under a periodic load;
importing a finite element result file obtained by ABAQUS solution into FE-safe, considering the work hardening and the roughness of the fillet surface, selecting different fatigue life algorithms to generate a fatigue life calculation file, and solving to obtain a second fatigue life simulation result considering the work hardening and the roughness of the fillet surface; selecting a fatigue life algorithm corresponding to the actually measured fatigue life of the bolt broken at the round corner in the step 1 from the second simulation result to be determined as the fatigue life algorithm of the bolt, wherein the error value of the actually measured fatigue life of the bolt broken at the round corner in the step 1 is less than or equal to 10 percent, or selecting a fatigue life algorithm corresponding to the actually measured fatigue life of the bolt broken at the thread in the step 1 from the second simulation result to be greater than or equal to the actual measured fatigue life of the bolt broken at the round corner in the step 1, and completing the establishment of a bolt round corner rolling-fatigue analysis finite element model;
step 4, according to the bolt rolling-fatigue analysis finite element model obtained in the step 3, inputting different rolling process conditions, solving to obtain the fatigue life of the bolt under different rolling conditions, selecting the process conditions, testing the fatigue life corresponding to different processes through a bolt fillet rolling process test, comparing the fatigue life with a calculated value, and verifying and optimizing the model when the simulation and test errors are within 10%;
and 5, determining the optimal fillet rolling process of the bolt through a bolt fillet rolling-fatigue analysis finite element model according to the actual bolt specification.
Preferably, the method for optimizing the rolling process of the lower fillet of the bolt head comprises the steps that the tensile test in the step 1 is in a GBT _228.1-2010 standard, the fatigue test is carried out according to a NASM1312-11 standard, the roughness test method is a sample block comparison method, and the measurement standard is GB/T1031-1995.
The invention relates to a method for optimizing a rolling process of a lower fillet of a bolt head, which comprises the following rolling process parameters: the rolling force is 800N, the rolling speed is 500rad/s, the rolling time is 2s, and the radius of the roller fillet is 0.45mm.
Preferably, according to the optimization method of the rolling process of the lower fillet of the bolt head, a geometric model is established in ABAQUS according to the geometric dimension of the bolt, and material parameters and meshing are defined; the material parameters include: elastic modulus, normal-temperature tensile stress-strain data, poisson's ratio and density;
importing a finite element result file obtained by solving ABAQUS into FE-safe, inputting material parameters and adding a load spectrum; wherein the material parameters input to FE-safe include material type, modulus of elasticity, tensile strength, poisson's ratio, roughness.
Preferably, the model in the steps 2 and 3 is consistent with the size of the sample, the sample is an M6 type flat head and countersunk TC4 titanium alloy high-locking bolt, and when the grid at the fillet is divided, the thickness of the grid is not more than 0.01mm.
In industrial application, in step 2, when the rest area of the bolt is divided into grids, the grids are divided based on the global scattering points.
Preferably, in the method for optimizing the rolling process of the lower fillet of the bolt head, in the step 2,
the expression of the fatigue model after Morrow correction is as follows:
in the formula,. DELTA.epsilon t -a total strain range; n is a radical of f -fatigue life; sigma' f -a fatigue strength factor; epsilon' f -a fatigue ductility factor; b-fatigue strength index; c-fatigue ductility index; e-modulus of elasticity of the material; sigma m Is the average stress. In the above formula, σ ' is determined by the tensile strength, poisson's ratio and roughness ' f 、ε′ f B, c.
Preferably, according to the optimization method of the rolling process of the lower fillet of the bolt head, the fatigue criterion selected by the bolt after rolling at the fillet in the step 3 is a Brown-Miller model, and the expression of the fatigue life model after Morrow correction is as follows:
where Δ γ and Δ ∈ are shear strain and positive strain on the critical plane, respectively. In the corrected model, the values of Δ γ, Δ ∈, b, and c are determined by the tensile strength, poisson's ratio, and roughness.
The invention relates to a method for optimizing a rolling process of a lower fillet of a bolt head, which comprises a step 3
The rolling technological parameters influence the residual stress, work hardening and fillet size change at the fillet to indirectly influence the fatigue life, for example, forging simulation is carried out, the influence of deformation temperature, deformation speed, die fatigue size, deformation amount and the like on forming is researched, a direct model expression does not exist, and finally, an equation can be fitted to a simulation result to reflect a rule.
The invention relates to an optimization method of a rolling process of a lower fillet of a bolt head, which comprises the following steps of: the rolling depth of the flat-head bolt is 0.02mm, the rolling angle is 45 degrees, the rolling depth of the flat-head bolt is 0.45mm, the rolling angle is 25 degrees, and the optimal roller radius of the flat-head bolt and the flat-head bolt is 90-95 percent of the size of the fillet of the bolt.
The invention relates to a method for optimizing a rolling process of a fillet under a bolt head, which comprises the following steps of: the radius of the roller fillet is 0.45mm, the rolling angle is 25 degrees, and the rolling depth is 0.045mm.
According to the invention, ABAQUS and FE-safe are utilized to establish a bolt fillet rolling and fatigue finite element model and test verification is carried out, the relation between the fatigue life of the bolt and the fillet rolling process is obtained, a feasible method is provided for the design and optimization of the bolt head lower fillet rolling process by accurately predicting the fatigue life, and the tedious process test process is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart of the fatigue calculation of ABAQUS in combination with FE-safe;
FIG. 2 is a graph showing the effect of the mesh size at the round corner on the fatigue life calculation result when the initial stress of the bolt is zero.
Fig. 3 is a cloud image of the prediction of the fatigue life of the bolt in example 1.
FIG. 4 is the fatigue life of the flush bolt at different rolling depths in example 1;
fig. 5 shows the fatigue life of the countersunk head bolt in the case of example 2 without rolling the angle.
FIG. 6 is a graph showing the prediction of the fatigue life of the bolt after rolling by the roller at different rolling angles in example 1;
FIG. 7 is a graph showing the predicted results of the fatigue life of bolts at different rolling depths in example 2;
FIG. 8 is a graph showing the predicted fatigue life of the bolt after rolling at different rolling angles of the roller in example 2;
FIG. 9 is a graph showing the predicted fatigue life of the bolts after rolling with rollers of different fillet sizes in example 2.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
A process optimization method based on the fatigue life of a bolt after fillet rolling comprises the following steps:
step 1: preparing a standard tensile sample of a material in the same state as the bolt, performing a tensile test to obtain a corresponding true stress-strain curve and mechanical property parameters, performing bolt fatigue tests under non-rolling and different rolling processes, and testing the roughness before and after rolling to obtain a corresponding fatigue life result;
in the embodiment, a TC4 flat-head high-locking bolt with an M6 specification is taken as a research object, a standard tensile sample of annealed Ti-6Al-4V is subjected to solution aging treatment according to GBT-228.1-2010 standard, then a tensile test is carried out on the tensile sample in a microcomputer control electronic universal testing machine WDW-300 (the temperature is 24 ℃, the relative humidity is 50%, and the deformation speed is 2 mm/min), and a high-precision extensometer (the extensometer measures the distance to be 25 mm) carried by equipment is utilized to record stress-strain data in the tensile process.
The parameters of the bolt rolling process are rolling force 800N, rolling speed 500rad/s and rolling time 2s. The roughness of the rounded surface was estimated by a block comparison method, and the measurement standard was GB/T1031-1995. The bolt fatigue test is carried out on a fatigue testing machine after being assembled according to the NASM1312-11 standard, the fatigue maximum load is about 8676N, the minimum load is 10 percent of the maximum load, and the loading frequency is 140HZ.
The fatigue test results are shown in table 1, the fatigue fracture positions of the bolts which are not rolled are all at the lower round corners of the bolt heads, and the fracture positions of the bolts which are rolled are all at the threads.
TABLE 1 fatigue test results for bolt samples (unit/thousand times)
And 2, step: and determining a proper grid size and fatigue algorithm by combining ABAQUS and FE-safe simulation to obtain the fatigue life of the non-rolled bolt. As shown in figure 1, according to the geometric shape of the bolt and the fatigue test standard, a geometric model of the bolt is established in ABAQUS, the static analysis of the bolt under the fatigue load is completed, the stress result is led into FE-safe to calculate the fatigue life, and the proper mesh size (wherein the mesh thickness is not more than 0.01 mm) at the fillet and the fatigue algorithm are determined according to the test result.
Specifically, the ABAQUS relates to material model parameters including: the elastic modulus, normal-temperature tensile stress-strain data, poisson's ratio, density, and the material model parameters related to FE-safe include: material type, modulus of elasticity, tensile strength, poisson's ratio, roughness. Based on the test results of step 1 and relevant literature, the stress-strain data of TC4 after solution aging is shown in Table 2, and the other parameter settings of the material model are shown in Table 3.
TABLE 2 true stress-strain data for TC4 quasi-static tensile plasticity stage
TABLE 3 Material model parameters
The quality of the grid is one of the most core factors influencing the finite element precision, and in order to determine the reasonable size of the grid, the influence of the size of the grid on the finite element result is analyzed. When the initial stress of the bolt is zero, a certain load is applied, the influence of the size of the grid at the round corner on fatigue calculation (the fatigue life is the minimum value of the predicted fatigue life of the bolt) is shown in fig. 2, and a fitting curve equation is as follows:
wherein x is the mesh size at the corner;
in order to balance the calculation precision and efficiency and facilitate subsequent data processing, the size of the grid at the fillet along the depth direction is selected to be 0.01mm, and the simulation result has good convergence.
And (3) the fatigue criterion selected in the step (2) is the maximum principal strain criterion, and Morrow average stress correction is carried out.
The fatigue model expression after Morrow correction is as follows:
in the formula,. DELTA.. Di-elect cons t -a total strain range; n is a radical of f -fatigue life; sigma' f -a fatigue strength factor; epsilon' f -coefficient of fatigue ductility; b-fatigue strength index; c-fatigue ductility index; e-modulus of elasticity of the material; sigma m Is the average stress. In the above formula, σ ' is determined by the tensile strength, poisson's ratio and roughness ' f 、ε′ f B, c.
The fatigue model is the formula, i.e. the criterion for calculating the fatigue life.
The fatigue finite element simulation result of the non-rolled bolt is shown in fig. 3a, the fatigue fracture position is also at the fillet position, the minimum fatigue life is 3.0 ten thousand times, the simulation calculation result is close to the test value, and the reliability of the fatigue simulation model is good.
And 3, step 3: and (3) based on the model in the step (2), simplifying the complex rolling process into a two-dimensional rolling model, and obtaining a residual stress distribution result after rolling and a stress spectrum under a fatigue load in ABAQUS. And (4) combining ABAQUS and FE-safe simulation calculation to obtain the residual stress and the fatigue life of the rolled bolt, and combining the test result to select a proper fatigue algorithm and optimize the model.
On the basis of the model of the step 2, the influence of rolling on the appearance of the bolt fillet and the work hardening is considered. Based on the experimental result of the step 1, the roughness of the rolled bolt is 0.8 μm, the surface grid strength of the rolled bolt is 1300MPa according to the general cold-working work hardening rate of the titanium alloy, and the parameters of the rest materials are consistent with those of the step 2. The parameters of the rolling process are that the rolling depth is 0.02mm, the radius of the roller fillet is 0.45mm, and the rolling angle is 45 degrees.
And 3, selecting a fatigue criterion for the bolt after fillet rolling in the step 3 as a Brown-Miller model, and correcting the Morrow average stress.
And 3, selecting a Brown-Miller model as the fatigue criterion of the rolled bolt at the round corner in the step 3, and expressing the fatigue life model after Morrow correction as follows:
where Δ γ and Δ ∈ are shear strain and positive strain on the critical plane, respectively. In the corrected model, the values of Δ γ, Δ ∈, b, and c are determined by the tensile strength, poisson's ratio, and roughness. The fatigue model is the formula, i.e. the criterion for calculating the fatigue life. The fatigue life of the bolt after rolling is calculated by simulation to be 49.4 ten thousand times (as shown in figure 3 b), and the fatigue life of the round corner is calculated by simulation because the influence of the thread is not considered in the model. The simulated calculation value of the round corner of the bolt is larger than the test value, and the actual service life of the round corner of the bolt is also larger than the test value, so that the analysis of the relation between the round corner rolling process and the fatigue life by adopting the model is reliable.
And 4, step 4: and obtaining the residual stress and fatigue life results of the bolt under different rolling conditions according to the optimized model, and obtaining optimized process parameters by taking the calculation result as the basis.
FIG. 4 is a fatigue life prediction for bolts at different rolling depths. Along with the increase of the rolling depth, the fatigue life of the bolt rapidly rises, the maximum value is about 49.4 ten thousand times when the rolling depth is about 0.02mm, the fatigue life of the bolt is improved by about 17 times compared with that before rolling, and the position of fatigue failure is the round angle of the bolt. However, as the rolling amount is further increased, the fatigue life of the bolt is rapidly decreased.
FIG. 5 shows the predicted results of the fatigue life of the bolts after rolling by rollers with different fillet sizes. The radius of the roller fillet is less than 0.4mm, and the fatigue life of the rolled bolt is less than 10 ten thousand times; when the fillet radius is 0.47mm, the fatigue life reaches the maximum value of about 75.9 ten thousand times, and the fatigue life of the bolt is improved by about 25 times compared with that before rolling; but the roller fillet radius is further increased and the fatigue life of the bolt is rapidly reduced.
FIG. 6 shows the fatigue life prediction of the bolt after rolling by the roller at different rolling angles. The rolling angle has relatively small influence on the fatigue life of the flat head bolt, and the rolling angle can only change within a very small range (10 degrees) due to the relation between the fillet of the flat head bolt and the rolling clamp. Thus, 45 ° may be an optimal rolling angle.
According to the calculation result, the rolling optimization process of the TC4 titanium alloy M6 flat-head high-locking bolt comprises the following steps: the radius of the roller fillet is 0.47mm, the rolling angle is 45 degrees and the rolling depth is 0.02mm. The fatigue life of the bolt is actually measured for more than 20 ten thousand times.
Example 2
Consistent with the steps of the embodiment 1, establishing a finite element model of fillet rolling and fatigue of the M6 specification 100-degree countersunk TC4 titanium alloy bolt by combining ABAQUS, and analyzing the relation between the technological parameters and the fatigue life through calculation to obtain an optimized technological parameter range.
FIG. 7 shows the predicted results of the fatigue life of the bolt with different rolling depths, wherein the rolling depth is increased, the fatigue life of the bolt is rapidly increased and reaches the maximum value when the rolling depth is about 0.045m m; as the rolling amount further increases, the fatigue life of the bolt is slightly decreased. According to the processing requirement, the maximum rolling depth at the round corner of the bolt cannot exceed 0.05mm.
FIG. 8 shows the predicted fatigue life of the bolt after rolling with different rolling angles. As the roll angle increases, the fatigue life of the bolt increases and decreases and reaches a maximum at 25 ° roll.
FIG. 9 shows the predicted fatigue life of the bolt after rolling with rollers of different fillet sizes. In the range of 0.2m m-0.45m m, the fatigue life of the bolts rises exponentially with increasing roller fillet radius.
According to the calculation result, the rolling optimization process of the TC4 titanium alloy M6 specification 100-degree countersunk head bolt comprises the following steps: the radius of the roller is 0.45m m, the rolling angle is 25 degrees, and the rolling depth is 0.045mm. The fatigue life of the bolt is actually measured for more than 20 ten thousand times.
The above examples are merely illustrative for clearly explaining the present invention and do not limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. Nor is it necessary or exhaustive for all embodiments. And obvious variations or modifications of the invention may be made without departing from the scope of the invention.
Claims (8)
1. A bolt head lower fillet rolling process optimization method is characterized by comprising the following steps:
step 1, preparing a standard tensile sample from a metal material which has the same material and processing state as the bolt, and performing a tensile test to obtain a true stress-strain curve and tensile strength of a corresponding material; rolling the bolt by adopting different rolling processes, and testing the roughness of the lower fillet of the bolt head before and after rolling; performing fatigue tests on bolts under the conditions of non-rolling and different rolling processes to obtain the fatigue life results of the bolts under the conditions of non-rolling and different rolling processes;
step 2, establishing a geometric model in ABAQUS according to the geometric dimension of the bolt, defining material parameters and grid division, applying constraint and fatigue load to the bolt, and solving by adopting different grid dimensions to obtain a finite element result file of stress distribution of the non-rolled bolt under a periodic load; the material parameters comprise the elastic modulus, normal-temperature tensile stress-strain data, poisson's ratio and density of the material;
importing a finite element result file obtained by ABAQUS solution into FE-safe, inputting material parameters and adding a load spectrum, selecting a Morrow corrected fatigue life calculation file generated by adopting a maximum principal strain algorithm, and solving to obtain a first fatigue life simulation result; selecting the mesh size corresponding to the fatigue life value with the actually measured fatigue life error value of less than or equal to 10% in the step 1 from the first simulation result as the mesh size of the bolt fillet position, and completing the establishment of a finite element mesh model for the fatigue analysis of the non-rolled bolt; the material parameters input in the FE-safe comprise the type of the material, the elastic modulus of the material, the tensile strength of the material, the Poisson ratio of the material and the roughness of an unrolled bolt;
step 3, on the bolt mesh model obtained in the step 2, according to the actual rolling depth, rolling angle and roller fillet radius, establishing a fillet rolling model in ABAQUS, applying constraint and fatigue load to the bolt, and solving in ABAQUS to obtain a finite element result file of stress distribution of the rolled bolt under a periodic load;
importing a finite element result file obtained by ABAQUS solution into FE-safe, considering the work hardening and the roughness of the surface of the fillet, selecting different fatigue life algorithms to generate a fatigue life calculation file, and solving to obtain a second simulation result of the fatigue life considering the work hardening and the roughness of the surface of the fillet; selecting a fatigue life algorithm corresponding to the actually measured fatigue life of the bolt broken at the round corner in the step 1 from the second simulation result to be determined as the fatigue life algorithm of the bolt, wherein the error value of the actually measured fatigue life of the bolt broken at the round corner in the step 1 is less than or equal to 10 percent, or selecting a fatigue life algorithm corresponding to the actually measured fatigue life of the bolt broken at the thread in the step 1 from the second simulation result to be greater than or equal to the actual measured fatigue life of the bolt broken at the round corner in the step 1, and completing the establishment of a bolt round corner rolling-fatigue analysis finite element model;
step 4, according to the bolt fillet rolling-fatigue analysis finite element model obtained in the step 3, inputting different rolling process conditions, solving to obtain the fatigue life of the bolt under different rolling conditions, selecting the process conditions, testing the fatigue life corresponding to different processes through a bolt fillet rolling process test, comparing the fatigue life with a calculated value, and verifying and optimizing the model when the simulation and test errors are within 10%;
and step 5, determining the optimal fillet rolling process of the bolt through the bolt fillet rolling-fatigue analysis finite element model obtained in the step 4 according to the actual bolt specification.
2. The optimization method for the bolt head lower fillet rolling process according to claim 1, wherein the method comprises the following steps: the tensile test in the step 1 is GBT _228.1-2010 standard, the fatigue test is carried out according to NASM1312-11 standard, the roughness test method is a sample block comparison method, and the measurement standard is GB/T1031-1995.
3. The optimization method for the bolt head lower fillet rolling process according to claim 1, wherein the method comprises the following steps: the parameters of the bolt rolling process are 800N of rolling force, 500rad/s of rolling speed, 2s of rolling time and 0.45mm of roller fillet radius.
4. The optimization method for the bolt head lower fillet rolling process according to claim 1, wherein the method comprises the following steps:
and (3) the model in the steps 2 and 3 is consistent with the size of the sample, the sample is an M6 type flat head and countersunk TC4 titanium alloy high-locking bolt, and when the grids at the round corners are divided, the thickness of the grids is not more than 0.01mm.
5. The optimization method for the bolt head lower fillet rolling process according to claim 1, which is characterized in that: in the step 2, the step of the method is carried out,
the expression of the fatigue model after Morrow correction is as follows:
in the formula,. DELTA.epsilon t Is the total strain range; n is a radical of f Fatigue life is considered; sigma' f The fatigue strength coefficient; epsilon' f The fatigue ductility coefficient; b is fatigue strength index; c is fatigue ductility index; e is the elastic modulus of the material; sigma m Is mean stress of σ' f 、ε′ f B and c are parameters automatically calculated and determined by the FE-safe according to the material model parameters; the material model parameters comprise tensile strength, poisson ratio and roughness of the material.
6. The optimization method for the bolt head lower fillet rolling process according to claim 1, wherein the method comprises the following steps:
the fatigue criterion selected by the rolled bolt at the round corner in the step 3 is a Brown-Miller model, and the expression of the fatigue life model after Morrow correction is as follows:
in which Deltagamma and Deltaepsilon n Shear strain and positive strain on critical surfaces, respectively.
7. The optimization method for the bolt head lower fillet rolling process according to claim 1, wherein the method comprises the following steps: the optimal rolling process of the TC4 titanium alloy M6 bolt comprises the following steps: the rolling depth of the flat-head bolt is 0.02mm, the rolling angle is 45 degrees, the rolling depth of the flat-head bolt is 0.45mm, the rolling angle is 25 degrees, and the optimal roller radius of the flat-head bolt and the flat-head bolt is 90-95 percent of the size of the fillet of the bolt.
8. The optimization method for the bolt head lower fillet rolling process according to claim 1, which is characterized in that: the rolling optimization process of the TC4 titanium alloy M6 specification 100-degree countersunk head bolt comprises the following steps: the radius of the roller fillet is 0.45mm, the rolling angle is 25 degrees, and the rolling depth is 0.045mm.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116384011A (en) * | 2023-06-02 | 2023-07-04 | 山东建筑大学 | Simulation method for rolling deformation correction and fatigue life prediction of aviation structural component |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116384011A (en) * | 2023-06-02 | 2023-07-04 | 山东建筑大学 | Simulation method for rolling deformation correction and fatigue life prediction of aviation structural component |
| CN116384011B (en) * | 2023-06-02 | 2023-08-01 | 山东建筑大学 | Simulation method for rolling deformation correction and fatigue life prediction of aviation structural component |
| CN118092221A (en) * | 2024-04-22 | 2024-05-28 | 航天精工股份有限公司 | Stress relation simulation control method for aluminum alloy high-lock nut |
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