CN108563849A - A kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component - Google Patents
A kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component Download PDFInfo
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Abstract
The invention discloses a kind of antifatigue high-efficient milling parameter optimization control methods of titanium alloy thin wall component, establish titanium alloy thin wall component primary election milling process parameter field, carry out orthogonal test, measure the surface integrity parameter of test component, establish titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula, according to the thin-wall member milling process parameter and surface integrity characteristic relation formula, object function and milling process parameter constraints, establish the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component, the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component is solved by Optimization Toolbox in MATLAB, obtain the antifatigue high-efficient milling parameter of titanium alloy thin wall component；The present invention solves the problems, such as that titanium alloy thin wall component surface integrity feature difference and material removing rate present in milling process are low.
Description
【Technical field】
The invention belongs to antifatigue precision cutting process technical fields, and in particular to a kind of titanium alloy thin wall component is antifatigue
High-efficient milling parameter optimization control method.
【Background technology】
Titanium alloy material has excellent in mechanical performance, and density is small, and specific strength is high, and corrosion-resistant, high- and low-temperature resistance performance is good, is
Another important structural material after steel, trick.A variety of data and statistics indicate that, aircraft engine is replaced with titanium alloy
Steel material can mitigate the 30%~40% of engine structure weight.Therefore, titanium alloy is by a large amount of and be widely used in manufacture aircraft
Engine and body can effectively improve engine thrust-weight ratio and body mechanism efficiency, be conducive to alleviate thermal boundary phenomenon.So
And titanium alloy thermal coefficient is small, elasticity modulus low and high temperature chemism is big and big etc. special with other metal material friction coefficient
Point becomes a kind of typical difficult-to-machine material.
According to the result of study of pertinent literature and this paper it is found that in general, in the numerous characteristic parameters of surface integrity,
Depth of residual stress is maximum, followed by hardening depth, is finally only the depth of metallographic change layer.According to U.S.'s machining hand
The depth for the Milling Process surface integrity effect observed in volume compares it is found that when roughing, the depth of residual stress of formation
For 0.356mm, case depth 0.127mm, metallographic change layer is 0.076mm；When finishing, the residual stress layer depth of formation
Degree is 0.152mm, and case depth 0.013mm, metallographic change layer is 0.01mm.And milling depth when roughing is generally all
More than 1mm or more, milling depth when finishing is typically greater than 0.2mm, is far longer than the depth of metamorphic layer, therefore, practical
When processing, for a upper knife formed metamorphic layer, next knife is sure to be completely removed, thus we only considers finish when it is last
The milling parameter of one knife.When milling parameter is in surface integrity milling process state modulator domain, so that it may be added with obtaining highest
The milling parameter of work efficiency rate combines.In general, the machined parameters and highly-efficient processing parameter for ensureing surface integrity are often phase
Anti-, but as high as possible fatigue resistance and processing efficiency can be obtained under conditions of given surface integrality range, this
It just needs to advanced optimize the antifatigue high-efficient milling parameter of component in a certain range.
【Invention content】
The object of the present invention is to provide a kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component, with
Solve the problems, such as that titanium alloy thin wall component surface integrity feature difference and material removing rate present in milling process are low.
The present invention uses following technical scheme：A kind of antifatigue high-efficient milling parameter optimization controlling party of titanium alloy thin wall component
Method specifically includes following steps：
Step 1 establishes titanium alloy thin wall component primary election milling process parameter field, and carries out orthogonal test, measures experiment structure
The surface integrity parameter of part establishes titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula：
Wherein, RaFor the surface roughness of test component, σrFor the surface residual stress of test component, H is test component
Surface microhardness, fzFor feed engagement, vcFor Milling Speed, aeFor milling width, c0、c1、c2、c3、c10、c11、c12、c13、
c20、c21、c22、c23It is constant；
Step 2, according to thin-wall member milling process parameter and surface integrity characteristic relation formula, object function and milling work
Skill parameter constraints establish the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component：
Wherein, f (x) indicates object function, xl、x2、…、xnFor milling process parameter；gi(x) indicate that constraints, m are
The number of constraints；
Step 3, the optimization by Optimization Toolbox in MATLAB to the antifatigue high-efficient milling parameter of titanium alloy thin wall component
Model solution obtains the antifatigue high-efficient milling parameter of titanium alloy thin wall component.
Further, milling process parameter constraints specifically include the following conditions in step 2：
Surface integrity milling process parameter constraints：
Wherein, x1=lgvc, x2=lg (100fz), x3=lgap, x4=lgae, vcmaxAnd vcminIndicate the orthogonal of step 1
The maximum value and minimum value of selected Milling Speed in experiment；fzmaxAnd fzminIndicate selected per tooth in the orthogonal test of step 1
The maximum value and minimum value of the amount of feeding；apmaxAnd apminIndicate step 1 orthogonal test in selected milling depth maximum value and
Minimum value；aemaxAnd aeminIndicate the maximum value and minimum value of selected milling width in the orthogonal test of step 1；
Fatigue life constraints：
g9(x)=Nmin- N (x)≤0,
Wherein, N (x) is fatigue life prediction value, NminFor minimum fatigue life value；
Surface roughness constraints：
g10(x)=Ra(x)-Ramax≤ 0,
Wherein, Ra(x) Prediction of Surface Roughness value is indicated；RamaxIndicate NminCorresponding surface roughness maximum permissible value；
Surface microhardness constraints：
Wherein, H (x) indicates surface microhardness predicted value, HminAnd HmaxRespectively NminCorresponding surface roughness is minimum
And maximum permissible value；
Surface residual stress constraints：
Wherein, σr(x) surface residual stress predicted value, σ are indicatedrminAnd σrmaxRespectively NminCorresponding surface residual stress
Minimum and maximum permissible value.
Further, the specific method is as follows for step 1：
Step 1.1 determines titanium alloy thin wall component primary election milling process parameter field；
Step 1.2 carries out orthogonal examination according to primary election milling process parameter field using the design method of Three factors-levels
It tests；
The surface integrity characteristic parameter of each test component in step 1.3,1.2 orthogonal test of measuring process；
It is step 1.4, complete according to the surface measured in the milling process parameter and step 1.3 in step 1.2 orthogonal test
Property characteristic parameter, establishes titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula：
The beneficial effects of the invention are as follows：By establishing the antifatigue high-efficient milling technological parameter of titanium alloy thin wall component and surface
The relationship of integrity feature, with it is antifatigue, efficiently for target, obtain titanium alloy surface integrality high-efficient milling technological parameter,
Material removal can not only be significantly improved, and residual stress can be controlled well, unit interval metal material removal rate improves
40%, the surface integrity high-efficient milling of titanium alloy is realized, milling efficiency and Milling Accuracy is increased substantially, meets simultaneously
The highly reliable requirement with the long-life of aeroengine components.
【Description of the drawings】
Fig. 1 is the 3 d surface topography figure under 1# high-efficient milling technological parameters in the embodiment of the present invention；
Fig. 2 is the 3 d surface topography figure under 2# non-efficient milling process parameters in the embodiment of the present invention；
Fig. 3 is the micro-organization chart under 1# high-efficient milling technological parameters in the embodiment of the present invention；
Fig. 4 is the micro-organization chart under 2# non-efficient milling process parameters in the embodiment of the present invention；
Fig. 5 is the microhardness under 1# high-efficient milling technological parameters in the embodiment of the present invention along depth profile；
Fig. 6 is the microhardness under 2# non-efficient milling process parameters in the embodiment of the present invention along depth profile；
Fig. 7 is the residual stress under 1# high-efficient milling technological parameters in the embodiment of the present invention along depth profile；
Fig. 8 is the residual stress under 2# non-efficient milling process parameters in the embodiment of the present invention along depth profile.
【Specific implementation mode】
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
The invention discloses a kind of antifatigue high-efficient milling parameter optimization control methods of titanium alloy thin wall component, specifically include
Following steps：
Step 1 establishes titanium alloy thin wall component primary election milling process parameter field, and carries out orthogonal test, measures experiment structure
The surface integrity parameter of part establishes titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula, specifically
Method is as follows：
Step 1.1 determines titanium alloy thin wall component primary election milling process parameter field.
Ti1023 titanium alloys have been selected in the present embodiment, according to specific experiment condition, experience or documents and materials, formulate surface
Integrality milling process parameter field C1, wherein Ti1023 titanium alloy Specimen Shapes be cuboid block, size be 55mm × 50mm ×
25mm.All experiments all carry out on three coordinate vertical type numerically controlled machine of JOHNFORD VMC-850 types, and cutter for same is tetra- teeth of K44
Solid carbide end mill, a diameter of 10mm, processing method are climb cutting, are cooled down using emulsion.C1Design parameter is：Milling
Speed vc=60~140m/min；Feed engagement fz=0.04~0.12mm/z；Milling width ae=3~7mm；Milling depth
ap=0.1~0.6mm.
Step 1.2 carries out orthogonal examination according to primary election milling process parameter field using the design method of Three factors-levels
Test (three factors：Select feed engagement fz, Milling Speed vc, milling width aeThree factors carry out condition test；Three is horizontal：Often
A factor selects three different values to be tested).When due to finishing, milling depth is smaller, and therefore, when orthogonal test only examines
Consider Milling Speed, feed engagement and milling width.
The surface integrity characteristic parameter of each test component in step 1.3,1.2 orthogonal test of measuring process.To processing
Experiment test specimen carries out surface finish measurement, sample length using TR240 surface roughness testers along direction of feed afterwards
0.8mm, evaluation length 4.0mm, each test specimen measure 5 points and are averaged.Surface topography uses veeco 3D optical profilometers
NT1100 is observed, from surface topography map it is observed that the surface texture that workpiece surface generates, while can be processed
The overall distribution rule of surface profile, reflects the movement locus of tool in cutting sword.Surface microhardness is micro- hard using MHT-4
Degree measurement examination, each surface of test piece are tested 5 points and are averaged.Surface residual stress is answered using Canadian Proto-iXRD remnants
Power analyzer is tested, and each surface of test piece measures 3 points and is averaged, using Cu_K-Alpha targets.
Show that surface integrity milling process state modulator domain and surface integrity range are as shown in table 1 after test：
1. surface integrity milling process state modulator domain of table and surface integrity range
It is step 1.4, complete according to the surface measured in the milling process parameter and step 1.3 in step 1.2 orthogonal test
Property characteristic parameter, establishes titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula：
Wherein, RaFor the surface roughness of test component, σrFor the surface residual stress of test component, H is test component
Surface microhardness, fzFor feed engagement, vcFor Milling Speed, aeFor milling width, c0、c1、c2、c3、c10、c11、c12、c13、
c20、c21、c22、c23It is constant.
According to the parameter information of table 1 in the present embodiment, can obtain Ti1023 titanium alloy thin wall component milling process parameters with
Surface integrity characteristic relation formula：
Step 2, according to thin-wall member milling process parameter and surface integrity characteristic relation formula, object function and milling work
Skill parameter constraints establish the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component：
Wherein, f (x) indicates object function, xl、x2、…、xnFor milling process parameter；gi(x) indicate that constraints, m are
The number of constraints.
When finishing, milling depth generally determined according to surplus and change less, therefore on surface integrity influence compared with
It is small.In addition, milling width is generally determined according to the size of cutter diameter, so in Optimization of Milling Parameters, milling is not considered
The optimization of depth and milling width only considers the optimization of Milling Speed and feed engagement.Therefore, decision variable just becomes：
X=[vc,fz]。
Decision variable is established, that is, establishes the average Milling Process time t for completing a procedurew：
tw=tm+tct×nt+tot,
Wherein,Indicate the cutting time of process, Q=nfzzapaeFor unit time material removing rate, n is lathe
The speed of mainshaft passes throughIt obtains, d is the diameter of cutter, and z is the number of teeth of milling cutter, tctIndicate that tool changing is once consumed
Time, ntIndicate that number of changing knife, V are the volume of material to be removed, totIndicate other unproductive times.
When fixing tool change time and other unproductive times, it is only necessary to consider the cutting time t of optimization processm, and work as and wait for
When being fixed except the volume of material, optimization aim just becomes unit interval material removing rate Q, and Q is bigger, and processing efficiency is higher.Add
After work cutter is selected, what the diameter d and number of teeth z of cutter were to determine, at this point, optimization aim is exactly with Milling Speed vc, per tooth
Amount of feeding fz, milling depth apWith milling width aeFor the function of decision variable.
Therefore, optimization object function is established：Maxf (x)=f (x1,x2,x3,x4), then maxf (x)==vcfz, wherein x1
=lgvc, x2=lg (100fz), x3=lgap, x4=lgae.It is linearized by the method for taking logarithm, and due to linear programming side
It is nonnegative value that method, which requires each independent variable, while in view of commonly using f in Milling Processz<The case where 0.1mm/z, therefore take logarithm
When linearisation, x is enabled1=lgvc, x2=lg (100fz), establish Ti1023 titanium alloy surface integrality high-efficient milling parameter optimizations
Object function is linearized simplified：Maxf (x)=x1+x2.For optimization process convenience of calculation, object function can be turned to and be asked most
Small value problem, such as：Minf (x)=- x1-x2。
Milling process parameter constraints specifically include the following conditions：
Surface integrity milling process parameter constraints：
Wherein, x1=lgvc, x2=lg100fz, x3=lgap, x4=lgae, vcmaxAnd vcminIndicate the orthogonal examination of step 1
The maximum value and minimum value of selected Milling Speed in testing；fzmaxAnd fzminIndicate step 1 orthogonal test in selected per tooth into
To the maximum value and minimum value of amount；apmaxAnd apminIndicate the maximum value and most of selected milling depth in the orthogonal test of step 1
Small value；aemaxAnd aeminIndicate the maximum value and minimum value of selected milling width in the orthogonal test of step 1.
The control domain of Ti1023 titanium alloy surface integrality milling process parameters is：
{100≤vc≤ 140,0.04≤fz≤ 0.08 },
Namely：
{2≤x1≤ 2.15,0.6≤x2≤ 0.9 },
Being converted into canonical form has：
g1(x)=x1- 2.15≤0,
g2(x)=2-x1≤ 0,
g3(x)=x2- 0.9≤0,
g4(x)=0.6-x2≤0。
Fatigue life constraints：
g9(x)=Nmin- N (x)≤0,
Wherein, N (x) is fatigue life prediction value, NminFor minimum fatigue life value.
The relationship between median fatigue life and surface roughness and residual stress is established according to fatigue test results in table 2
Model：
N=53088.44Ra -0.191,
N=138.04 | σr|0.975,
Fatigue life threshold value is set, sets the average value 63200 for obtaining median fatigue life in table 2 to threshold value here,
I.e.：N≥63200.
2 milling test result of fatigue life of table
Surface roughness constraints is：
g10(x)=Ra(x)-Ramax≤ 0,
Wherein, Ra(x) Prediction of Surface Roughness value is indicated；RamaxIndicate NminCorresponding surface roughness maximum permissible value.
In titanium alloy Milling Processes, with the increase of surface roughness, fatigue life reduces, therefore surface roughness
Smaller value should be taken, is solved to obtain 0.40 μm of surface roughness according to the relational model of median fatigue life and surface roughness,
Then surface roughness maximum permissible value is 0.40 μm.
According to the empirical equation of titanium alloy Milling Process surface roughness, have
Ra=7.35fz 0.446vc -0.331ae -0.143≤ 0.40,
Since the present embodiment only considers that Milling Speed and feed engagement, milling width take 7mm, both sides to take logarithm,
And it carries out conversion and can be changed to
g5(x)=- 0.331x1+0.446x2-0.964≤0。
Surface microhardness constraints：
Wherein, H (x) indicates surface microhardness predicted value, HminAnd HmaxRespectively NminCorresponding surface roughness is minimum
And maximum permissible value.According to the empirical equation of titanium alloy Milling Process surface microhardness it is found that within the scope of experiment parameter, titanium
In alloy Milling Processes, surface microhardness variation is little, therefore, does not consider surface microhardness about in the present embodiment
Beam.
Surface residual stress constraints：
Wherein, σr(x) surface residual stress predicted value, σ are indicatedrminAnd σrmaxRespectively NminCorresponding surface residual stress
Minimum and maximum permissible value.
In titanium alloy Milling Processes, formation is all residual compressive stress, tired with the increase of surface compress residual stresses
The labor service life increases, and therefore, surface compress residual stresses should take larger value, according to the relationship mould of median fatigue life and residual stress
Type solves to obtain minimum surface residual compressive stress to be 536MPa, then minimum surface residual compressive stress is 536MPa.According to titanium alloy
The empirical equation of Milling Process surface residual stress, has
|σr|=84.3fz 0.218vc 0.357ae 0.322>=536,
Since the present embodiment only considers that Milling Speed and feed engagement, milling width take median 5mm, both sides to take
Logarithm, and carry out conversion and can be changed to：
g6(x)=- 0.357x1-0.218x2-0.49≤0。
In summary, Ti1023 titanium alloy surfaces integrality high-efficient milling process parameter optimizing model is：
Step 3 solves above formula by Optimization Toolbox in MATLAB, obtains the antifatigue high-efficiency milling of titanium alloy thin wall component
Cut parameter, x1=2.15, x2=0.9, therefore, vc=140m/min, fz=0.08mm/z.
In addition, also needing to carry out the antifatigue high-efficient milling parameter of the above-mentioned titanium alloy thin wall component obtained and other parameters single
The comparison of position time metal material removal rate and surface integrity, verifies optimum results.
Specifically verification process is：
Carry out metal material removal rate comparative analysis in the unit interval.The cutter diameter that experiment is selected is 10mm, four teeth, milling
It cuts width and takes 7mm.Surface roughness, surface topography, surface microhardness, hardness are carried out respectively along depth distribution, surface residual
Along the test of depth distribution, microstructure, correlation values are as shown in table 2 for stress, residual stress.
2. optimum results comparative analysis of table
As can be seen from the table, in surface integrity control domain, unit interval metal material removal rate be it is highest, with
The parameter compared improves 40% compared to unit interval metal material removal rate metal-cutting waste.Meanwhile it is complete using surface
Property high-efficient milling parameter, obtain surface integrity be preferable, surface roughness is low, surface microhardness is low, surface residual pressure
Stress is big, metamorphic layer depth as shallow.
Carry out surface topography comparative analysis.As shown in Figure 1 and Figure 2, it is the 3 d surface topography figure measured under different parameters,
Fig. 1 is the 3 d surface topography figure under 1# high-efficient milling technological parameters, Ra=0.325 μm, Fig. 2 joins for 2# non-efficient milling process
3 d surface topography figure under several, Ra=0.772 μm, it can be seen from the figure that being added using surface integrity high-efficient milling parameter
The surface roughness that work goes out is relatively low.
Carry out microstructure comparative analysis.As shown in Figure 3, Figure 4, microstructure sight has been carried out to sample under scanning electron microscope
It examines, on the section perpendicular to direction of feed, Fig. 3 is processed using surface integrity high-efficient milling parameter for the position of observation
1# test specimens, rotten layer depth is about 1~2 μm, and in this depth bounds, crystal grain has twisted phenomenon, does not find apparent phase transformation.Fig. 4
It it is about 10 μm for 2# surface of test piece metamorphic layers, the crystal grain generation on surface is twisted.
Carry out microhardness distribution comparative analysis.Microhardness depth distribution curve preparation method under surface is using oblique
What tangent plane method obtained, detailed step is as follows：The method for using Wire EDM first needs the position measured to cut in test specimen
Go out rectangular bulk measurement sample, one 3 ° of oblique angle is then cut into the place from test specimen one end 5mm, then carries out this test specimen
It inlays, keeps the section being cut into parallel with mosaic surface, then test specimen is ground, is polished, finally use microhardness testers pair
Burnishing surface measures, and the depth under surface is calculated according to the distance of test, to obtain Ti1023 titanium alloy millings surface layer
Microhardness is along depth distribution.
As shown in Figure 5, Figure 6, the overall trend showed is that surface produces certain hardening, with the increase of depth,
Hardness number continuously decreases, until tending to matrix hardness.As shown in figure 5, processed using surface integrity high-efficient milling parameter
1# test specimens, hardening depth are about 50 μm, as shown in fig. 6,2# test specimen hardening depths are about 150 μm.
Carry out residual stress comparative analysis.The preparation method of residual stress distribution curve of depth under surface is as follows：Stripping
The method that layer uses electrobrightening, residual stress test uses XStress3000 residual stress test instrument, first to surface of test piece
Residual stress test is carried out, electrobrightening is then successively continued, electrolyte uses the omnipotent electrolyte of Proto companies of Canada；
According to testing before the examination impeller ramming of titanium alloy, polishing velocity is calculated；Ensure every layer of polishing depth at 8~10 μm, until surveying
The residual-stress value tried out stops less than 13.8Mpa and when being held essentially constant, the Ti1023 milling surface residual stress of acquisition
The distribution curve of depth is as shown in Figure 7, Figure 8 under surface.From the figure, it can be seen that surface shows as residual compressive stress, with
The increase of depth, residual stress gradually goes to zero.As shown in fig. 7, processed using surface integrity high-efficient milling parameter
1# test specimens, residual stress depth are about 20 μm, as shown in figure 8,2# test specimen residual stress depth is about 30 μm.
It can be seen that implementing the optimal control of the antifatigue high-efficient milling parameter of titanium alloy thin wall component, feature in this example
To complete the process parameter control region constraint item for establishing the antifatigue high-efficient milling of titanium alloy thin wall component by optimization object function
Part and surface integrity characteristic parameter constraints, finally establish the optimization of the antifatigue high-efficient milling parameter of titanium alloy thin wall component
Object function, to improve fatigue resistance and improve processing efficiency as target, with the technological parameter of Milling Process, rough surface
Degree, surface microhardness and surface residual stress are constraint, are carried out to the antifatigue high-efficient milling parameter of titanium alloy thin wall component excellent
Change, obtains the Optimal Parameters of the antifatigue high-efficient milling parameter of Ti1023 titanium alloy thin wall components.It can be used for instructing thin-wall member anti-
Tired high-efficient milling Optimal Parameters optimal control, the milling surface integrity feature and material that can significantly improve thin-wall member are gone
Except rate, the high-quality and high-efficiency of component Milling Process ensure that.
It is excellent that the present invention establishes surface integrity high-efficient milling optimization model, multiple linear regression analysis and MATLAB
Change the solution that tool box carries out model, design and analysis method are reliable, obtain Ti1023 titanium alloy surface integrality high-efficiency millings
Cutting parameter combination is：vc=140m/min, fz=0.08mm/z, and unit interval metal material removal rate is calculated, test table
Face integrality, verifies optimum results, and unit interval metal material removal rate improves 40%, realizes titanium alloy
Surface integrity high-efficient milling increases substantially milling efficiency and Milling Accuracy, while meeting aeroengine components height can
By the requirement with the long-life.
Claims (3)
1. a kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component, which is characterized in that specifically include with
Lower step：
Step 1 establishes titanium alloy thin wall component primary election milling process parameter field, and carries out orthogonal test, measures test component
Surface integrity parameter establishes titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula：
Wherein, RaFor the surface roughness of test component, σrFor the surface residual stress of test component, H is the surface of test component
Microhardness, fzFor feed engagement, vcFor Milling Speed, aeFor milling width, c0、c1、c2、c3、c10、c11、c12、c13、c20、
c21、c22、c23It is constant；
Step 2, according to the thin-wall member milling process parameter and surface integrity characteristic relation formula, object function and milling work
Skill parameter constraints establish the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component：
Wherein, f (x) indicates object function, xl、x2、…、xnFor milling process parameter；gi(x) indicate that constraints, m are constraint item
The number of part；
Step 3, by Optimization Toolbox in MATLAB to the Optimized model of the antifatigue high-efficient milling parameter of titanium alloy thin wall component
It solves, obtains the antifatigue high-efficient milling parameter of titanium alloy thin wall component.
2. a kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component as described in claim 1, special
Sign is that milling process parameter constraints described in step 2 specifically includes the following conditions：
Surface integrity milling process parameter constraints：
Wherein, x1=lgvc, x2=lg (100fz), x3=lgap, x4=lgae, vcmaxAnd vcminIn the orthogonal test for indicating step 1
The maximum value and minimum value of selected Milling Speed；fzmaxAnd fzminIndicate selected feed engagement in the orthogonal test of step 1
Maximum value and minimum value；apmaxAnd apminIndicate the maximum value and minimum of selected milling depth in the orthogonal test of step 1
Value；aemaxAnd aeminIndicate the maximum value and minimum value of selected milling width in the orthogonal test of step 1；
Fatigue life constraints：
g9(x)=Nmin- N (x)≤0,
Wherein, N (x) is fatigue life prediction value, NminFor minimum fatigue life value；
Surface roughness constraints：
g10(x)=Ra(x)-Ramax≤ 0,
Wherein, Ra(x) Prediction of Surface Roughness value is indicated；RamaxIndicate NminCorresponding surface roughness maximum permissible value；
Surface microhardness constraints：
Wherein, H (x) indicates surface microhardness predicted value, HminAnd HmaxRespectively NminCorresponding surface roughness minimum and most
Big permissible value；
Surface residual stress constraints：
Wherein, σr(x) surface residual stress predicted value, σ are indicatedrminAnd σrmaxRespectively NminCorresponding surface residual stress is minimum
And maximum permissible value.
3. a kind of antifatigue high-efficient milling parameter optimization control method of titanium alloy thin wall component as claimed in claim 1 or 2,
It is characterized in that, the specific method is as follows for the step 1：
Step 1.1 determines titanium alloy thin wall component primary election milling process parameter field；
Step 1.2 carries out orthogonal examination according to the primary election milling process parameter field using the design method of Three factors-levels
It tests；
The surface integrity characteristic parameter of each test component in step 1.3,1.2 orthogonal test of measuring process；
It is step 1.4, special according to the surface integrity that is measured in the milling process parameter and step 1.3 in step 1.2 orthogonal test
Parameter is levied, titanium alloy thin wall component milling process parameter and surface integrity characteristic relation formula are established：
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| CN113894333A (en) * | 2021-09-26 | 2022-01-07 | 西北工业大学 | Titanium alloy thin-wall structure precision milling surface state robustness process control method |
| CN113894333B (en) * | 2021-09-26 | 2022-07-22 | 西北工业大学 | Titanium alloy thin-wall structure precision milling surface state robustness process control method |
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