Milling parameter optimization method for aluminum alloy by pre-adding initial residual stress for simulation

Abstract

The present invention relates to the technical field of aluminum alloy processing, and provides an aluminum alloy milling parameter optimization method for simulation by pre-adding initial residual stress, including: constructing a three-dimensional milling model of aluminum alloy without initial residual stress; determining the residual stress standard of milling processing; single-factor simulation and multi-factor orthogonal simulation of aluminum alloy milling without initial residual stress; determining the influence law of each milling parameter on the maximum residual stress of milling processing based on the single-factor simulation experiment results; determining the primary and secondary relationship of the influence of each milling parameter on the maximum residual stress of milling processing based on the multi-factor orthogonal simulation experiment results, obtaining a milling parameter optimization scheme to preliminarily optimize the milling parameters; aluminum alloy milling simulation with pre-adding initial residual stress; aluminum alloy milling parameter optimization with pre-adding initial residual stress. The present invention can make the simulation process more accurately reflect the actual situation of the workpiece, reduce the complexity and cost of experimental operation, and improve the processing accuracy of aluminum alloy structural parts.

Description

Technical Field

[0001] The invention relates to the technical field of aluminum alloy processing, and in particular to an aluminum alloy milling parameter optimization method for simulating by pre-adding initial residual stress. Background Art

[0002] In recent years, the aviation industry has an increasingly urgent demand for integral structural parts. Aluminum alloys are widely used in aerospace due to their low density, high specific strength, and good corrosion resistance. The commonly used deformed aluminum alloys in the aviation manufacturing industry are mostly 2000 series alloys and 7000 series alloys. 7055 aluminum alloy is a new type of aluminum alloy obtained by reducing the Fe and Si content and increasing the Zn and Cu content on the basis of 7050. It has high strength and high fracture toughness. It is widely used as integral structural parts such as wing lower wall panels and trusses on Airbus A380 and Boeing 747 aircraft.

[0003] The overall structural parts have the characteristics of complex structure, high material removal rate and poor rigidity. During the processing, residual stress will be generated inside the structural parts under the influence of various factors such as clamping force, milling force and milling heat. The release process will cause the workpiece to warp, bend, twist or a combination of the three, which seriously affects the yield rate of the overall structural parts. At the same time, the deformation caused by the release of residual stress during service will also bring serious safety hazards to the aircraft. Before actual processing, simulation is often used to simulate the actual situation of the workpiece to obtain optimized processing parameters. Among the existing simulation technologies for aluminum alloy processing, some consider the initial residual stress for simulation, but only to determine the final residual stress and predict the processing deformation under the existing processing parameters when the workpiece has the initial residual stress, without considering the influence of the initial residual stress to optimize the aluminum alloy processing parameters. It can be seen that the existing technologies for optimizing aluminum alloy processing parameters using simulation do not consider the initial residual stress, resulting in low simulation accuracy and difficulty in reflecting the actual situation of the workpiece. The yield rate of aluminum alloy structural parts processed under the processing parameters obtained by simulation is low, which brings safety hazards to the application process and increases the complexity and cost of experimental operation. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides an aluminum alloy milling parameter optimization method for simulation by pre-adding initial residual stress, which can make the simulation process more accurately reflect the actual situation of the workpiece, reduce the complexity and cost of experimental operations, and improve the processing accuracy of aluminum alloy integral structural parts.

[0005] The technical solution of the present invention is:

[0006] A method for optimizing aluminum alloy milling parameters by pre-adding initial residual stress for simulation, characterized in that it comprises the following steps;

[0007] Step 1: Construct a 3D milling model of aluminum alloy without initial residual stress

[0008] Step 2: Determine the residual stress standard for milling; the residual stress standard is the maximum allowable residual stress;

[0009] Step 3: Aluminum alloy milling simulation without initial residual stress

[0010] Taking milling parameters as independent variables, single-factor simulation experiment scheme and multi-factor orthogonal simulation experiment scheme were designed, and finite element simulation software was used to simulate aluminum alloy milling, and the maximum residual stress of milling on aluminum alloy workpiece without initial residual stress in each simulation experiment was obtained;

[0011] Step 4: Analysis of simulation results without initial residual stress

[0012] The single-factor simulation experiment results are plotted with each milling parameter as the horizontal axis and the maximum residual stress of milling as the vertical axis to determine the influence of each milling parameter on the maximum residual stress of milling; the multi-factor orthogonal simulation experiment results are used to determine the primary and secondary relationships of the influence of each milling parameter on the maximum residual stress of milling based on the range analysis, and the milling parameter optimization scheme is obtained in combination with the influence rule and the residual stress standard, and the milling parameters are preliminarily optimized using the milling parameter optimization scheme;

[0013] Step 5: Aluminum alloy milling simulation with initial residual stress

[0014] Pre-adding initial residual stress to the aluminum alloy three-dimensional milling model without initial residual stress, and using preliminary optimized milling parameters to perform aluminum alloy milling simulation, to obtain the maximum residual stress of milling on the aluminum alloy workpiece after pre-adding initial residual stress;

[0015] Step 6: Optimization of milling parameters for aluminum alloy with initial residual stress

[0016] By comparing the difference between the maximum residual stress of milling processing on the aluminum alloy workpiece after pre-adding initial residual stress and the residual stress standard, the milling parameters are re-optimized using the milling parameter optimization scheme, and the aluminum alloy milling simulation is performed using the re-optimized milling parameters. If the maximum residual stress of milling processing on the aluminum alloy workpiece under the re-optimized milling parameters after pre-adding initial residual stress does not reach the target, the re-optimization is continued; if the target is achieved, the re-optimized milling parameters are the final milling parameters.

[0017] Furthermore, in step 1, the aluminum alloy three-dimensional milling model includes a workpiece model and a milling cutter model; the workpiece model is divided into a chip layer, a transition layer, and a base layer, and the material is selected as an aluminum alloy; the milling cutter model sets the tool rake angle, back angle, helix angle, and number of cutting edges, and the tool is selected as a carbide milling cutter.

[0018] Furthermore, in step 3, the milling parameters include milling speed, feed per tooth, milling depth, and milling width, and the number of experimental points selected for each milling parameter is greater than 3.

[0019] Furthermore, in step 3, the finite element simulation software is ANSYS.

[0020] Furthermore, in step 5, the initial residual stress is obtained by using an X-ray diffraction method on the actual plate.

[0021] Furthermore, in step 5, the pre-applied initial residual stress is applied at each node of the aluminum alloy workpiece.

[0022] The beneficial effects of the present invention are:

[0023] The present invention optimizes aluminum alloy milling parameters by pre-adding initial residual stress to perform aluminum alloy milling simulation, which can improve simulation accuracy, make the simulation process more accurately reflect the actual situation of the workpiece, and reduce the complexity and cost of experimental operations. The processing accuracy of the aluminum alloy integral structural parts under the optimized milling parameters is high, the yield of the aluminum alloy structural parts is improved, and the safety hazards in the application process of the aluminum alloy structural parts are eliminated. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of the aluminum alloy milling parameter optimization method for simulating pre-applied initial residual stress according to the present invention.

[0025] Figure 2 The stress cloud diagram of the aluminum alloy workpiece under the preliminarily optimized milling parameters without initial residual stress during the process of optimizing the milling parameters of 7055 aluminum alloy by the aluminum alloy milling parameter optimization method of simulating pre-applied initial residual stress in the specific implementation manner.

[0026] Figure 3 The stress cloud diagram of the aluminum alloy workpiece under the preliminary optimized milling parameters after pre-adding initial residual stress during the optimization of the milling parameters of 7055 aluminum alloy by the aluminum alloy milling parameter optimization method for simulating pre-adding initial residual stress in the specific implementation manner of the present invention.

[0027] Figure 4 The stress cloud diagram of the aluminum alloy workpiece under the milling parameters optimized again after pre-adding initial residual stress during the optimization of the milling parameters of 7055 aluminum alloy by the aluminum alloy milling parameter optimization method for simulating pre-adding initial residual stress in the specific implementation manner of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods.

[0029] like Figure 1 As shown, the aluminum alloy milling parameter optimization method for simulating the pre-addition of initial residual stress of the present invention comprises the following steps:

[0030] Step 1: Construct a 3D milling model of aluminum alloy without initial residual stress

[0031] Step 2: Determine the residual stress standard for milling; the residual stress standard is the maximum allowable residual stress;

[0032] Step 3: Aluminum alloy milling simulation without initial residual stress

[0033] Taking milling parameters as independent variables, single-factor simulation experiment scheme and multi-factor orthogonal simulation experiment scheme were designed, and finite element simulation software was used to simulate aluminum alloy milling, and the maximum residual stress of milling on aluminum alloy workpiece without initial residual stress in each simulation experiment was obtained;

[0034] Step 4: Analysis of simulation results without initial residual stress

[0035] The single-factor simulation experiment results are plotted with each milling parameter as the horizontal axis and the maximum residual stress of milling as the vertical axis to determine the influence of each milling parameter on the maximum residual stress of milling; the multi-factor orthogonal simulation experiment results are used to determine the primary and secondary relationships of the influence of each milling parameter on the maximum residual stress of milling based on the range analysis, and the milling parameter optimization scheme is obtained in combination with the influence rule and the residual stress standard, and the milling parameters are preliminarily optimized using the milling parameter optimization scheme;

[0036] Step 5: Aluminum alloy milling simulation with initial residual stress

[0037] Pre-adding initial residual stress to the aluminum alloy three-dimensional milling model without initial residual stress, and using preliminary optimized milling parameters to perform aluminum alloy milling simulation, to obtain the maximum residual stress of milling on the aluminum alloy workpiece after pre-adding initial residual stress;

[0038] Step 6: Optimization of milling parameters for aluminum alloy with initial residual stress

[0039] By comparing the difference between the maximum residual stress of milling processing on the aluminum alloy workpiece after pre-adding initial residual stress and the residual stress standard, the milling parameters are re-optimized using the milling parameter optimization scheme, and the aluminum alloy milling simulation is performed using the re-optimized milling parameters. If the maximum residual stress of milling processing on the aluminum alloy workpiece under the re-optimized milling parameters after pre-adding initial residual stress does not reach the target, the re-optimization is continued; if the target is achieved, the re-optimized milling parameters are the final milling parameters.

[0040] In this embodiment, the aluminum alloy three-dimensional milling model includes a workpiece model and a milling cutter model; the workpiece model is divided into a chip layer, a transition layer, and a base layer, and the material is selected as an aluminum alloy; the milling cutter model is used to set the tool rake angle, back angle, helix angle, and number of cutting edges, and the tool is selected as a carbide milling cutter. The milling parameters include milling speed, feed per tooth, milling depth, and milling width, and the number of experimental points selected for each milling parameter is greater than 3. The pre-applied initial residual stress can be applied at each node of the aluminum alloy workpiece to achieve precise application of residual stress at any position of the plate.

[0041] In this embodiment, the aluminum alloy is 7055 aluminum alloy. The working principle of the present invention is described below with reference to the accompanying drawings:

[0042] (1) Constructing a three-dimensional milling model of 7055 aluminum alloy without initial residual stress:

[0043] a. Modeling: The DM module of the finite element software ANSYS is used to establish a 3D milling model of aluminum alloy. The workpiece is a rectangular plate with a size of 60mm×20mm×15mm. The workpiece is divided into a chip layer, a transition layer and a base layer. The tool is a three-tooth end mill with a diameter of 12mm and a helix angle of 30°.

[0044] b. Import the model: Select the Explicit Dynamics module in the workbench of the finite element software ANSYS, and import the built milling model into the Geometry submodule under the module;

[0045] c. Define materials: Create 7055 aluminum alloy and cemented carbide in the Engineering Data submodule, define the density, elasticity (Young's modulus, Poisson's ratio), plasticity and failure of the materials, and specifically set the plasticity and failure to Johnson-Cook;

[0046] d. Grid division: In the Model submodule, define the workpiece material as 7055 aluminum alloy and the tool material as cemented carbide. Use tetrahedral grids to grid the tool and workpiece: define the workpiece chip layer grid size as 0.5mm, the base layer grid size as 2mm; the tool grid size as 2mm;

[0047] e. Set up contact pairs: Insert Connections in the Model, establish body-interaction with the tool cutting edge as the primary surface and the chip layer as the secondary surface; establish body-interaction with the back tool face as the primary surface and the transition layer as the secondary surface; set Friction Cofficient to 0.3 and Dynamic Cofficient to 0.1;

[0048] f. Set the analysis step and boundary conditions: Set the steptime to 0.01s in the Analysis Setting of the Model submodule; fix the bottom of the plate; establish cylindrical coordinates with the center axis of the milling cutter as the Z axis, and set the tool speed based on this; set the tool initial speed (feed speed) based on the overall coordinates;

[0049] g. Submit the task for solution.

[0050] (2) The residual stress standard for milling processing is determined to be ±24MPa.

[0051] (3) With milling parameters as independent variables, set up a single-factor simulation experiment and a multi-factor orthogonal experiment. Return to the workbench main interface, copy the modules in (1) with the same number as the experimental scheme, set the milling depth and milling width in a, and the milling speed and feed per tooth in f in each module according to the experimental scheme, submit the task, and obtain the maximum residual stress of milling corresponding to each simulation experiment.

[0052] (4) The single-factor simulation experiment results are plotted with each milling parameter as the horizontal axis and the maximum residual stress of milling processing as the vertical axis to determine the influence of each milling parameter on the maximum residual stress of milling processing; the multi-factor orthogonal simulation experiment results are used to determine the primary and secondary relationships of the influence of each milling parameter on the maximum residual stress of milling processing based on the extreme difference analysis, and the milling parameter optimization scheme is obtained by combining the influence law and the residual stress standard, and the milling parameter optimization scheme is used to preliminarily optimize the milling parameters.

[0053] In this embodiment, by analyzing the results of single-factor simulation experiments, it is obtained that the influence of each milling parameter on the maximum residual stress of milling processing is as follows: the maximum residual stress increases with the increase of milling speed, increases with the increase of feed per tooth, increases with the increase of milling depth, and increases with the increase of milling width (the upward trend is small); by performing extreme difference analysis on the results of multi-factor orthogonal simulation experiments, it is obtained that the primary and secondary relationships of the influence of each milling parameter on the maximum residual stress of milling processing are: milling speed>feed per tooth>milling depth>milling width). In this embodiment, in combination with the primary and secondary relationships, influence rules and residual stress standards, a milling parameter optimization scheme is obtained, the milling parameter optimization scheme is used to preliminarily optimize the milling parameters, and the preliminarily optimized milling parameters are used to simulate the milling of 7055 aluminum alloy without initial residual stress. The obtained stress cloud diagram is as follows: Figure 2 As shown. Figure 2It can be seen that the residual stress of 7055 aluminum alloy under the initial optimized milling parameters without initial residual stress is -16.461~23.802MPa, which meets the residual stress standard. Among them, in the milling parameter optimization scheme, the milling parameters are optimized according to the primary and secondary relationship. Only one milling parameter can be optimized, or multiple milling parameters can be comprehensively optimized. The optimization of milling parameters must comply with the influence law, and the residual stress standard is used as the optimization target.

[0054] (5) The initial residual stress is obtained by X-ray diffraction method on the actual aluminum alloy plate. The input files of the above milling simulation without initial residual stress are exported, and initial residual stress is applied to each input file. Each input file is imported into the workbench and submitted to obtain the maximum residual stress cloud map of the milling process on the aluminum alloy workpiece under the preliminary optimized milling parameters after the initial residual stress is pre-applied. Figure 3 shown.

[0055] (6) Compare the difference between the maximum residual stress of milling on the aluminum alloy workpiece after pre-adding the initial residual stress and the residual stress standard, use the milling parameter optimization scheme to optimize the milling parameters again, and use the re-optimized milling parameters to simulate the aluminum alloy milling. If the maximum residual stress of milling on the aluminum alloy workpiece under the re-optimized milling parameters after pre-adding the initial residual stress does not reach the target, continue to optimize again; if the target is reached, the re-optimized milling parameters are the final milling parameters. In this embodiment, the maximum residual stress cloud diagram of the milling of the aluminum alloy workpiece under the re-optimized milling parameters after pre-adding the initial residual stress is as follows: Figure 4 shown.

[0056] Figure 3 In the figure, the maximum residual stress of milling on the aluminum alloy workpiece under the initial optimized milling parameters after pre-adding the initial residual stress is -22.881~26.665MPa, which cannot meet the residual stress standard. It can be seen that after pre-adding the initial residual stress, the maximum residual stress of milling on the aluminum alloy workpiece becomes larger, so the milling parameters need to be optimized again. Figure 4 In the figure, after pre-adding the initial residual stress, the maximum residual stress of the aluminum alloy workpiece during milling is -23.715~15.911MPa under the milling parameters optimized again. It can be seen that the maximum residual stress of the aluminum alloy workpiece during milling is reduced under the milling parameters optimized again. The subsequent use of the final optimized milling parameters can greatly improve the machining accuracy of the overall aluminum alloy structural parts, improve the yield of aluminum alloy structural parts, and eliminate the safety hazards in the application process of aluminum alloy structural parts.

[0057] Obviously, the above embodiments are only some embodiments of the present invention, rather than all embodiments. The above embodiments are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention. Based on the above embodiments, all other embodiments obtained by those skilled in the art without making creative work, that is, all modifications, equivalent substitutions and improvements made within the spirit and principles of this application, fall within the protection scope required by the present invention.

Claims

1. A method for optimizing aluminum alloy milling parameters by pre-adding initial residual stress for simulation, characterized in that: The method comprises the following steps: Step 1: Construct a 3D milling model of aluminum alloy without initial residual stress Step 2: Determine the residual stress standard for milling; the residual stress standard is the maximum allowable residual stress; Step 3: Aluminum alloy milling simulation without initial residual stress Taking milling parameters as independent variables, single-factor simulation experiment scheme and multi-factor orthogonal simulation experiment scheme were designed, and finite element simulation software was used to simulate aluminum alloy milling, and the maximum residual stress of milling on aluminum alloy workpiece without initial residual stress in each simulation experiment was obtained; Step 4: Analysis of simulation results without initial residual stress The single-factor simulation experiment results are plotted with each milling parameter as the horizontal axis and the maximum residual stress of milling as the vertical axis to determine the influence of each milling parameter on the maximum residual stress of milling; the multi-factor orthogonal simulation experiment results are used to determine the primary and secondary relationships of the influence of each milling parameter on the maximum residual stress of milling based on the range analysis, and the milling parameter optimization scheme is obtained in combination with the influence rule and the residual stress standard, and the milling parameters are preliminarily optimized using the milling parameter optimization scheme; Step 5: Aluminum alloy milling simulation with initial residual stress Pre-adding initial residual stress to the aluminum alloy three-dimensional milling model without initial residual stress, and using preliminary optimized milling parameters to perform aluminum alloy milling simulation, to obtain the maximum residual stress of milling on the aluminum alloy workpiece after pre-adding initial residual stress; Step 6: Optimization of milling parameters for aluminum alloy with initial residual stress By comparing the difference between the maximum residual stress of milling processing on the aluminum alloy workpiece after pre-adding initial residual stress and the residual stress standard, the milling parameters are re-optimized using the milling parameter optimization scheme, and the aluminum alloy milling simulation is performed using the re-optimized milling parameters. If the maximum residual stress of milling processing on the aluminum alloy workpiece under the re-optimized milling parameters after pre-adding initial residual stress does not reach the target, the re-optimization is continued; if the target is achieved, the re-optimized milling parameters are the final milling parameters.

2. The aluminum alloy milling parameter optimization method for simulating the pre-initial residual stress according to claim 1 is characterized in that: In step 1, the aluminum alloy three-dimensional milling model includes a workpiece model and a milling cutter model; the workpiece model is divided into a chip layer, a transition layer, and a base layer, and the material is selected as an aluminum alloy; the milling cutter model is used to set the tool rake angle, back angle, helix angle, and number of cutting edges, and the tool is selected as a carbide milling cutter.

3. The aluminum alloy milling parameter optimization method for simulating the pre-initial residual stress according to claim 1 is characterized in that: In step 3, the milling parameters include milling speed, feed per tooth, milling depth, and milling width, and the number of experimental points selected for each milling parameter is greater than 3.

4. The aluminum alloy milling parameter optimization method for simulating the pre-initial residual stress according to claim 1 is characterized in that: In step 3, the finite element simulation software is ANSYS.

5. The aluminum alloy milling parameter optimization method for simulating the pre-initial residual stress according to claim 1 is characterized in that: In the step 5, the initial residual stress is obtained by using an X-ray diffraction method on the actual plate.

6. The aluminum alloy milling parameter optimization method for simulating the pre-initial residual stress according to claim 1 is characterized in that: In step 5, the pre-applied initial residual stress is applied at each node of the aluminum alloy workpiece.

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