Milling aviation aluminum alloy mechanical stress calculation and workpiece local temperature rise calculation method based on fluctuation mechanics

Abstract

The invention discloses a fluctuation mechanics-based milling aviation aluminum alloy mechanical stress calculation and workpiece local temperature rise calculation method, which comprises the following steps of: defining a linear path along a direction vertical to the surface of a workpiece by taking a position under a tool nose during tool retracting as an origin of coordinates, and extracting normal stress distribution data in a y direction at different moments on the path; by introducing the stress wave attenuation function, the stress wave propagation and attenuation conditions in the cutting process are effectively analyzed and optimized, and vibration and deformation caused by stress waves in the cutting process are reduced; the change rule of material stress in the cutting process is deeply analyzed through a resolving method of mechanical stress generated by wave power; the influence of the temperature field on the material performance is predicted, cutting parameters, a cooling system and cutter selection are optimized, and thermal deformation and tool abrasion caused by overheating are reduced; by reasonably controlling the cutting temperature rise, the machining precision is improved, the service life of a tool is prolonged, the energy consumption is reduced, and the machining defects caused by too high temperature are reduced.

Description

Technical Field

[0001] This invention relates to the field of aerospace aluminum alloy technology, specifically to a method for calculating mechanical stress and local temperature rise of workpieces in milled aerospace aluminum alloys based on wave dynamics. Background Technology

[0002] In the aerospace industry, aluminum alloys are widely used due to their superior properties. Most chords, ribs, frames, beams, hubs, airfoils, turbine blades, shells, bulkheads, and skin panels are manufactured using aluminum alloys. Milling, as a widely used metalworking method in modern manufacturing, plays a crucial role in aerospace, automotive manufacturing, and other fields. However, during the milling of aerospace aluminum alloys, the unique properties of aluminum alloys generate significant cutting heat and stress waves, which can affect machining quality and even lead to tool wear and workpiece deformation.

[0003] During milling, stress waves are generated when the tool contacts the workpiece. These stress waves propagate through the material, potentially leading to decreased cutting quality and even unnecessary machining errors. Due to the complexity of the microstructure of aluminum alloys, the propagation and attenuation characteristics of stress waves exhibit high nonlinearity, making accurate description of their behavior particularly difficult. High stress waves in the initial stage may induce lattice distortion or microcrack initiation in localized areas. These microscopic changes further superimpose onto the residual stress field, resulting in a non-uniform distribution of residual stress. In the theoretical derivation of the wave equation, it is typically assumed that stress waves are unaffected by attenuation during propagation. However, in reality, stress wave propagation is influenced by various factors, particularly dispersion and unloading effects, which cause attenuation during propagation. The attenuation mechanism of stress waves is complex, typically resulting from the combined effects of thermal effects and microstructural changes in the material. To more accurately describe the attenuation characteristics of stress waves, an attenuation function is introduced.

[0004] The generation of stress waves is unavoidable during milling, and these stress waves cause changes in mechanical stress, thus affecting the stability of the machining process. Existing stress wave calculation methods often have limitations in accuracy and efficiency, especially in the machining of complex aluminum alloy materials. Traditional stress wave calculation methods cannot accurately describe the stress distribution of the material at high cutting rates, resulting in significant errors between the calculated results and the actual machining process. To address this issue, a new mechanical stress calculation method is needed that can accurately predict the impact of stress waves on aluminum alloy materials during milling, thereby optimizing the machining process.

[0005] Cutting temperature rise has a direct impact on milling quality. Excessive temperature not only accelerates tool wear but also affects the surface quality and dimensional accuracy of the workpiece. Existing temperature rise calculation methods mostly focus on single cutting conditions, neglecting the interaction of multiple factors during actual machining, such as cutting speed, tool material, and coolant usage. Furthermore, the calculation of temperature rise distribution within the workpiece has not been effectively studied, especially for aluminum alloys. Under complex milling conditions, traditional temperature rise calculation models often fail to accurately reflect the actual situation. Therefore, accurately calculating the cutting temperature rise at any point within the workpiece and optimizing process parameters is one of the key technologies for improving milling accuracy and extending tool life.

[0006] To address this, we introduce a method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics. Summary of the Invention

[0007] The purpose of this invention is to provide a method for calculating mechanical stress and local temperature rise of workpieces in milled aerospace aluminum alloys based on wave dynamics, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for calculating mechanical stress and local temperature rise of workpieces in milling aerospace aluminum alloys based on wave dynamics, comprising: taking the position directly below the tool tip when the tool is retracted as the origin of the coordinate system, defining a straight path along the direction perpendicular to the workpiece surface, and extracting the normal stress distribution data in the y direction at different times on the path to reveal the dynamic evolution characteristics of stress wave as it changes with the propagation space.

[0009] To reveal the evolution characteristics of stress wave propagation over time, five time points were selected after the stress wave started unloading: 0.2 μs, 0.4 μs, 0.6 μs, 0.8 μs, and 1.0 μs. The stress distribution of the workpiece at these times was extracted.

[0010] To evaluate the accuracy of the fitted function, the root mean square error "MSE" and the coefficient of determination "R²" are introduced. 2 These two metrics, "MSE" and "R," are used to measure the deviation between model predictions and actual data. MSE is the average of the squared differences between predicted and actual values. 2 The "" is used to measure the model's ability to explain data variability, reflecting how much of the target variable's variation the model can explain. The calculation method is as follows:

[0011]

[0012] In the formula: n is the number of data; y i This is the actual value; This is a predicted value;

[0013] The attenuation function of the elastoplastic stress wave during end milling of aluminum alloy is:

[0014] g(n,v f ,a p ,a e ,x)=e bx ;

[0015] In the formula: n is the rotational speed, v f For the feed rate, a p For the depth of cut, a e denoted as the cutting width, and x as the propagation distance.

[0016] The attenuation characteristics of stress waves with propagation distance during the above milling process are shown above. During the propagation of stress waves, the attenuation rate of stress waves is determined by parameter b, and the value of b is affected by the combination of machining process parameters.

[0017] Based on the rotational speed n and the cutting width a e The effects on stress wave attenuation characteristics all show a trend of first increasing and then decreasing, and the feed rate v f The effect on stress wave attenuation characteristics shows a monotonically increasing trend, with the rate of increase gradually decreasing, and the cutting depth a... p The effect on stress wave attenuation characteristics shows a trend of first decreasing, then increasing, and then decreasing again.

[0018] By fitting the attenuation rate b with a cubic function, the functional expression of b as a function of the processing parameters is obtained:

[0019]

[0020] In the formula: a n b n c n a vf a ap b ap c ap d ap a ae b ae c ae All are undetermined coefficients, where n is the rotational speed and v is the rotational speed. f For feed rate;

[0021] Preferably, by fitting the attenuation function and calculating the relative error, the real-domain stress wave function of aluminum alloy milled by the end mill is obtained as a function of space:

[0022]

[0023] In the formula, the rotational speed is n and the cutting width is a. e The feed rate is v f The cutting depth is a p , σi (t) represents the stress wave that varies with time t, x represents the propagation distance, and σ represents the stress wave. i (t) represents the stress wave that varies with time t;

[0024] Preferably, the milling cutter is cut along its axial direction, and the cutting edge is discretized to form several cutting micro-elements. In a homogeneous, continuous, and isotropic elastoplastic deformable body, the stress wave is simplified to have the same value in every direction, and the mechanical stress generated by the wave force is:

[0025]

[0026] Where: σ f xx Normal stress in the x-direction is caused by wave dynamics, σ f yy Normal stress in the y-direction is caused by wave dynamics; τ f xz This represents the shear stress caused by wave forces in the x-direction, where t represents time, n is the rotational speed, and v is the shear stress. f For the feed rate, a p For the depth of cut, a e Where x is the cutting width, σ is the propagation distance, and σ is the cutting width. i (t) represents the stress wave that varies with time t.

[0027] Preferably, due to the thermal stress caused by the uneven distribution of the internal temperature field of the workpiece during the cutting process, to characterize this process, it is assumed that the temperature field is mainly concentrated in the shear band heat source region and the flank friction heat source region. The unmachined and machined surfaces of the workpiece are considered as adiabatic boundaries, and the shear band heat source is also considered as an adiabatic boundary. In the temperature field analysis of the shear band heat source and the flank friction heat source, the concept of heating time is involved. The heating time is defined as the time required for a certain point inside the workpiece to pass through the heat source. Therefore, the heating time of the shear band heat source and the flank friction heat source is respectively the projection of its heat source length in the cutting speed direction divided by the cutting speed:

[0028]

[0029] The internal formula of the workpiece in the model is:

[0030]

[0031] in:

[0032]

[0033] In the formula, VB represents the wear width of the flank face. γ is the modified Bessel function in the integral function of the temperature field of the heat source in the shear band; B represents the heat source intensity correction coefficient; M represents the position of a point M in the workpiece, and the temperature rise at that position is calculated; γ0 represents the tool rake angle.

[0034] Preferably, in the formula: T primary =T imaginary ;q shear Shear surface heat release intensity, W / mm 2 °; a is the thermal diffusivity (mm). 2 / s), λ is the thermal conductivity, ρ0 is the density, and C is the specific heat capacity;

[0035] L is the length of the heat source; l i This is a differential segment of the heat source.

[0036] Preferred, dl i Along its width relative to its upper end, in cm.

[0037] Preferably, V is the cutting speed. h is the shear angle. D This represents the instantaneous cutting layer thickness.

[0038] Preferred, F t For tangential force; F c ω is the cutting force; x is the angular velocity; z is the position of a point on the workpiece along the x-axis; z is the position of a point on the workpiece along the z-axis.

[0039] Preferably, the MSE value is significantly lower than that of the fitted function, and the R-value is also lower. 2 The value is close to 1, so this function can describe the attenuation characteristics of stress waves. The attenuation function of stress wave propagation is determined to be the exponential function y = ae^(-1 / 2). bx .

[0040] Preferably, in the formula, the rotational speed n and the cutting width a e feed rate v f Cutting depth a p， x is the propagation distance, σ i(t) This represents the stress wave that varies with time t.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] (1) By introducing the stress wave attenuation function, the propagation and attenuation of stress waves during the cutting process can be effectively analyzed and optimized, thereby reducing vibration and deformation caused by stress waves during the cutting process; the mechanical stress calculation method generated by wave dynamics can be used to deeply analyze the change law of material stress during the cutting process; the cutting temperature rise calculation method at a point in the workpiece can accurately calculate the temperature change of the workpiece during the processing process; this not only helps to predict the influence of the temperature field on material properties, but also optimizes cutting parameters, cooling system and tool selection, and reduces thermal deformation and tool wear caused by overheating; by reasonably controlling the cutting temperature rise, the machining accuracy can be improved, the tool life can be extended, energy consumption can be reduced, and machining defects caused by excessively high temperatures can be reduced. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the stress wave extraction path of the present invention;

[0044] Figure 2 This is a schematic diagram of the internal stress distribution field of the workpiece of the present invention;

[0045] Figure 3 This is a schematic diagram of the actual values ​​and fitted curves of the present invention;

[0046] Figure 4 This is a schematic diagram of the evaluation indexes calculated by different fitting methods of the present invention;

[0047] Figure 5 This is a schematic diagram of the fitting results of the attenuation function of the present invention;

[0048] Figure 6 This is a schematic diagram of the bevel milling micro-element of the present invention;

[0049] Figure 7 This is a schematic diagram showing the setting of the thermal insulation boundary and the frictional heat source on the workpiece of the present invention. Detailed Implementation

[0050] 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.

[0051] Example

[0052] Please see Figure 1-7This invention provides a technical solution: a method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics, comprising: a stress wave attenuation function for milled aerospace aluminum alloys; to determine the functional form of the stress wave attenuation function for milled aerospace aluminum alloys, a straight path is defined along the direction perpendicular to the workpiece surface, with the position directly below the tool tip during tool retraction as the origin, and the normal stress distribution data in the y-direction at different times along this path is extracted to reveal the dynamic evolution characteristics of stress waves as they propagate through space, such as... Figure 1 As shown;

[0053] To reveal the evolution characteristics of stress wave propagation over time, five time points—0.2 μs, 0.4 μs, 0.6 μs, 0.8 μs, and 1.0 μs—were selected after the stress wave began unloading. The stress distribution of the workpiece at these times was extracted, as shown below. Figure 2 As shown.

[0054] like Figure 2 As shown, after the tool is unloaded, the stress distribution at different times exhibits a peak, and the peak amplitude gradually decreases with increasing propagation distance, indicating that the stress wave undergoes significant attenuation during propagation within the material. In the initial period after unloading, the stress wave propagates with a high energy density, resulting in a large peak amplitude and a relatively fast attenuation rate; however, as time progresses, the peak amplitude gradually decreases, and the attenuation rate slows down. To study the attenuation characteristics of the stress wave, five peak values ​​were fitted with different functions to obtain the attenuation characteristics of the stress wave with propagation distance. Furthermore, since the stress direction is the same as the simulation coordinate axis direction, all values ​​are positive, representing actual compressive stress.

[0055] To evaluate the accuracy of the fitted function, the root mean square error (MSE) and the coefficient of determination (R²) are introduced. 2 These two metrics are: MSE (Mean Separation), which is the average of the squared differences between predicted and actual values, and is mainly used to measure the deviation between the model's predictions and the actual data. The smaller the MSE value, the better the model's fit. 2 This is used to measure the model's ability to explain data variability, reflecting how much of the target variable's variation the model can explain. The closer its value is to 1, the better the model can capture the data's trends and variability, and the more ideal the fit. The calculation method is shown in equations (1) and (2).

[0056]

[0057] In the formula: n is the number of data; y i This is the actual value; These are predicted values.

[0058] The results obtained through fitting calculations and equations (1) and (2) are as follows: Figure 3-4 As shown.

[0059] Figure 3-4 This paper compares the MSE and R² evaluation metrics for different fitting functions. The analysis reveals that the exponential decay function has lower MSE and R² values. 2 It exhibits superior performance across all metrics, with its MSE value significantly lower than other fitted functions, and R0... 2 A value close to 1 indicates that the function can well describe the attenuation characteristics of stress waves. Therefore, the attenuation function for stress wave propagation can be determined as the exponential function y = ae^(-1 / 2). bx Therefore, the attenuation function of the elastoplastic stress wave during end milling of aluminum alloy 7050-T7451 is:

[0060] g(n,v f ,a p ,a e ,x)=e bx (3)

[0061] In the formula: n is the rotational speed, v f For the feed rate, a p For the depth of cut, a e denoted as the cutting width, and x as the propagation distance.

[0062] Equation (3) describes the attenuation characteristics of stress waves with propagation distance during milling. During the propagation of stress waves, the attenuation rate of stress waves is determined by parameter b, and the value of b is affected by the combination of machining process parameters.

[0063] Rotational speed n and cutting width a e The effects on stress wave attenuation characteristics all show a trend of first increasing and then decreasing; therefore, a quadratic function form can be considered for parameter fitting. (Feed speed v) f The effect on stress wave attenuation characteristics shows a monotonically increasing trend, with the rate of increase gradually decreasing; therefore, an exponential function form can be considered for fitting. Cutting depth a p The effect on the stress wave attenuation characteristics shows a trend of first decreasing, then increasing, and then decreasing again. Therefore, a cubic function form can be considered for fitting.

[0064] Thus, the function expression of the attenuation rate b with respect to the processing parameters is shown in equation (4).

[0065]

[0066] In the formula: a n b n c n a vf a ap b ap c ap d ap a ae bae c ae All are undetermined coefficients, where n is the rotational speed and v is the rotational speed. f This refers to the feed rate.

[0067] The attenuation function was fitted and the relative error was calculated, and the result is as follows: Figure 5 As shown in the figure, the maximum relative error of the fitting function was calculated to be 14.2%, and the average relative error was 3.26%, indicating that the fitting function has a good fitting result.

[0068] Therefore, the stress wave in the real domain as a function of space for milling aluminum alloy 7070-T7451 with an end mill is obtained as follows:

[0069]

[0070] In the formula, the rotational speed n and the cutting width a e feed rate v f Cutting depth a p , σ i (t) represents the stress wave that varies with time t, and x represents the propagation distance. The values ​​of the undetermined coefficients are shown in Table 1.

[0071] Table 1. Values ​​of undetermined coefficients in the attenuation function.

[0072] Undetermined coefficients a b c d n <![CDATA[2.773×10 -7 ]]> -0.001 <![CDATA[-9.193×10 4 ]]> / <![CDATA[v f ]]> -0.043 / / / <![CDATA[a p ]]> 0.055 -0.439 1.139 <![CDATA[8.886×10 4 ]]> <![CDATA[a e ]]> 0.350 -0.769 <![CDATA[3.070×10 3 ]]> /

[0073] like Figure 6 Methods for calculating mechanical stress generated by wave forces

[0074] During the cutting and machining of metal materials, the workpiece is affected by the dynamic force-thermal-vibration impact load field caused by the milling cutter's entry impact, the rake face shearing, and the flank face extrusion friction, which will form cutting residual stress on the surface of the workpiece.

[0075] In the process of milling aluminum alloys, in order to simplify the mathematical model under milling and thermal loads, the following basic assumptions are made:

[0076] 1. Initial stress assumption: The initial residual stress of the aluminum alloy 7050-T7451 workpiece is not considered;

[0077] 2. Material elastic-plastic assumption: The material is a homogeneous, continuous, and isotropic elastic-plastic deformable body, and the elastic-plastic deformation conforms to the loading and unloading deformation characteristics of classical elastic-plastic theory.

[0078] In milling, the cutting edges of the milling cutter are helically distributed, resulting in varying cutting thicknesses at different positions on the cutting edge. Therefore, it is necessary to discretize the milling cutter along its axis, forming several micro-cutting elements. In this case, the contact between each micro-element and the workpiece can be considered as an angled cutting process.

[0079] Figure 6 In the middle, P s It is the cutting plane, parallel to the cutting velocity direction and tangent to the cutting edge; P n It is the cutting plane, perpendicular to the cutting edge and P. s Plane; o-x0z0 and ox s z s These are the workpiece coordinate system and the principal shear plane coordinate system of the first deformation zone, respectively; V is the cutting speed; r ε For the cutting edge tip radius; h ch This represents the chip thickness.

[0080] In a homogeneous, continuous, and isotropic elastoplastic deformable body, stress waves can be simplified to have equal values ​​in every direction. The mechanical stress generated by the wave force is:

[0081]

[0082] In the formula, σ f xx Normal stress in the x-direction is caused by wave dynamics, σ f yy Normal stress in the y-direction is caused by wave dynamics; τ f xz This represents the shear stress caused by wave forces in the x-direction, where t represents time, n is the rotational speed, and v is the shear stress. f For the feed rate, a p For the depth of cut, a e Where x is the cutting width, σ is the propagation distance, and σ is the cutting width. i (t) represents the stress wave that varies with time t.

[0083] like Figure 7 This paper describes a method for calculating the temperature rise at any location on a milled aerospace aluminum alloy workpiece. Thermal stress is caused by the uneven distribution of the internal temperature field of the workpiece during the cutting process. To characterize this process, it is assumed that the temperature field is mainly concentrated in the shear band heat source region and the flank friction heat source region. The unmachined and machined surfaces of the workpiece are considered as adiabatic boundaries, and the shear band heat source is also considered as an adiabatic boundary. Figure 7 As shown.

[0084] In the temperature field analysis of both the shear band heat source and the flank friction band heat source, the concept of heating time is involved. Heating time is defined as the time required for a point inside the workpiece to pass through the heat source. Therefore, the heating time of both the shear band heat source and the flank friction band heat source is the projection of its heat source length along the cutting speed direction divided by the cutting speed:

[0085]

[0086] The internal formula of the workpiece in the model is:

[0087]

[0088] in:

[0089]

[0090] In the formula, VB represents the wear width of the flank face. γ is the modified Bessel function in the integral function of the temperature field of the heat source in the shear band; B represents the heat source intensity correction coefficient; M represents the position of a point M in the workpiece, and the temperature rise at that position is calculated; γ0 represents the tool rake angle.

[0091] In the formula: T primary =T imaginary ;q shear Shear surface heat release intensity, W / mm 2 °; a is the thermal diffusivity (mm). 2 / s), λ is the thermal conductivity, ρ0 is the density, and C is the specific heat capacity;

[0092] L is the length of the heat source; l i For the differential small segment of the heat source; dl i The width is measured in cm relative to its upper end; V is the cutting speed. h is the shear angle. D F represents the instantaneous cutting layer thickness. t For tangential force; F c ω is the cutting force; x is the angular velocity; z is the position of a point on the workpiece along the x-axis; z is the position of a point on the workpiece along the z-axis.

[0093] Existing stress wave attenuation functions typically describe the attenuation characteristics of stress waves propagating in materials, but they are generally simplified and fail to consider the specific impact of process parameters during cutting on attenuation. Temperature rise calculations are usually based on simplified assumptions, assuming that the thermal conductivity and heat capacity of the workpiece material are constant during cutting, and do not consider the precise description of the dynamic changes in the temperature field caused by heat sources from the shear band and flank friction. Current thermal stress analyses mainly focus on the shear band and flank friction zone, but the definition and specific calculation process of heating time are not analyzed in depth as this patent does, through more detailed heat source projection and heating time calculations.

[0094] The difference between this invention and existing technologies lies in its more detailed and precise modeling approach, particularly its innovative approach to stress wave attenuation and temperature rise calculations. Existing technologies typically neglect the specific influence of processing parameters in stress wave attenuation calculations, but this invention provides optimization schemes for different process parameters through a refined fitting function. Similarly, in temperature rise calculations, a precise method for calculating heating time is introduced, making the temperature field analysis closer to the actual processing, thereby improving the stability and accuracy of the process.

[0095] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics, characterized in that, Includes the following steps: S1. Constructing the stress wave attenuation function for milling aerospace aluminum alloys. Using the position directly below the tool tip when the tool is retracted as the origin of the coordinate system, a straight path is defined along the direction perpendicular to the workpiece surface. The normal stress distribution data in the y direction at different times along this path are extracted to reveal the dynamic evolution characteristics of stress wave as it propagates through space. To reveal the evolution characteristics of stress wave propagation over time, five time points were selected after the stress wave started unloading: 0.2 μs, 0.4 μs, 0.6 μs, 0.8 μs, and 1.0 μs. The stress distribution of the workpiece at these times was extracted. To evaluate the accuracy of the fitted function, the root mean square error "MSE" and the coefficient of determination "R" are introduced. 2 "These two metrics, 'MSE' is the average of the squared differences between the predicted and actual values, primarily used to measure the deviation between model predictions and actual data, and 'R'..." 2 The "" is used to measure the model's ability to explain data variability, reflecting how much of the target variable's variation the model can explain. The calculation method is as follows: In the formula: n is the number of data; y i This is the actual value; This is a predicted value; The attenuation function of the elastoplastic stress wave during end milling of aluminum alloy is: g(n,v f ,a p ,a e ,x)=e bx ; In the formula, n is the rotational speed, and v is the rotational speed. f For the feed rate, a p For the depth of cut, a e x is the cutting width, and x is the propagation distance; The attenuation characteristics of stress waves with propagation distance during the above milling process are shown. During the propagation of stress waves, the attenuation rate of stress waves is determined by parameter b, and the value of b is affected by the combination of machining process parameters. Based on the rotational speed n and the cutting width a e The effects on stress wave attenuation characteristics all show a trend of first increasing and then decreasing, and the feed rate v f The effect on stress wave attenuation characteristics shows a monotonically increasing trend, with the rate of increase gradually decreasing, and the cutting depth a... p The effect on the stress wave attenuation characteristics shows a trend of first decreasing, then increasing, and then decreasing again. A cubic function is used to fit the attenuation rate b, yielding a functional expression for b as a function of the processing parameters: S2, Calculate the mechanical stress generated by the wave dynamics. Initial stress and material elastic-plasticity assumptions are made; the milling cutter is cut along the axial direction, and the cutting edge is discretized to form several cutting micro-elements. The contact between each micro-element and the workpiece is regarded as an oblique cutting process; based on the three-dimensional semi-infinite space elastic contact mechanics theory, combined with the stress wave attenuation function constructed in step S1, the mechanical stress generated by the wave force is obtained as follows: In the formula: Normal stress in the x-direction is caused by wave dynamics. The normal stress in the y-direction is caused by wave dynamics. This represents the shear stress caused by wave forces in the x-direction, where t represents time, n is the rotational speed, and v is the shear stress. f For the feed rate, a p For the depth of cut, a e Where x is the cutting width, σ is the propagation distance, and σ is the cutting width. i (t) represents the stress wave that varies with time t; S3. Calculate the temperature rise at any location on a milled aerospace aluminum alloy workpiece. Assuming the temperature field is mainly concentrated in the shear band heat source region and the flank friction heat source region, the unmachined surface, machined surface, and shear band heat source of the workpiece are considered as adiabatic boundaries; the heating time is defined as the time required for a certain point inside the workpiece to pass through the heat source, where the heating time of the shear band heat source is shown in the following formula: The internal formula of the workpiece in the model is: in: In the formula, VB represents the wear width of the flank face. γ is the modified Bessel function in the integral function of the temperature field of the heat source in the shear band; B represents the heat source intensity correction coefficient; M represents the position of a point M in the workpiece, and the temperature rise at that position is calculated; γ0 represents the tool rake angle.

2. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: By fitting the attenuation function and calculating the relative error, the real-domain stress wave function of aluminum alloy milled by an end mill is obtained as a function of space: In the formula, the rotational speed is n and the cutting width is a. e The feed rate is v f The cutting depth is a p， x is the propagation distance, σ i (t) represents the stress wave that varies with time t.

3. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: S3 Chinese style: T primary =T imaginary ;q shear Shear surface heat release intensity, W / mm 2 °; a is the thermal diffusivity (mm). 2 / s), λ is the thermal conductivity, ρ0 is the density, and C is the specific heat capacity; L is the length of the heat source; l i This is a differential segment of the heat source.

4. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In S3, dl i Along its width relative to its upper end, in cm.

5. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In S3, V is the cutting speed. h is the shear angle. D This represents the instantaneous cutting layer thickness.

6. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In S3, F t For tangential force; F c ω is the cutting force; x is the angular velocity; z is the position of a point on the workpiece along the x-axis; z is the position of a point on the workpiece along the z-axis.

7. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: The MSE value is significantly lower than that of the fitted function, and the R-value is also lower. 2 The value is close to 1, so this function can describe the attenuation characteristics of stress waves. The attenuation function of stress wave propagation is determined to be the exponential function y = ae^(-1 / 2). bx .

8. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In the process of constructing the stress wave attenuation function in S1, a relative error analysis is performed on the fitting function. The maximum relative error of the fitting function does not exceed 14.2%, and the average relative error is 3.26%.

9. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In formula S1: a n b n c n a vf a ap b ap c ap d ap a ae b ae c ae All are undetermined coefficients, where n is the rotational speed and v is the rotational speed. f This refers to the feed rate.

10. The method for calculating mechanical stress and local temperature rise of milled aerospace aluminum alloys based on wave dynamics according to claim 1, characterized in that: In formula S2, the rotational speed n and the cutting width a e feed rate v f Cutting depth a p， x is the propagation distance, σ i (t) represents the stress wave that varies with time t.

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