CN114675611A - Turning technological parameter optimization method for cantilever beam-shaped weak-rigidity micro-turning tool excircle turning groove - Google Patents
Turning technological parameter optimization method for cantilever beam-shaped weak-rigidity micro-turning tool excircle turning groove Download PDFInfo
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Abstract
A turning technological parameter optimization method for turning a groove on an excircle of a cantilever beam-shaped weak-rigidity micro-turning tool relates to the field of ultra-precise weak-rigidity micro-groove turning, and aims to solve the problem that in the prior art, optimization is not performed on a machining error caused by deflection deformation of the cantilever beam-shaped weak-rigidity micro-turning tool. The specific process is as follows: step one, analyzing a cutting force component influencing deflection deformation of a cutter, and establishing a function model of the cutting force component; step two, establishing a function model of deflection deformation according to the cutting force component function model; step three, establishing a function model of the actual feeding distance according to the deflection deformation function model; step four, substituting the actual feeding distance function model into the function model of deflection deformation to perform cycle calculation to obtain a final actual feeding distance function model; and step five, establishing a function model of the groove depth error according to the function model of the final actual feeding distance, and optimizing each parameter by analyzing the influence rule of each parameter on the groove depth error.
Description
Technical Field
The invention relates to the field of ultra-precise weak-rigidity micro-groove turning, in particular to a turning process parameter optimization method for a cantilever-beam-shaped weak-rigidity micro-lathe tool excircle turning groove.
Background
The excircle microgrooves of the micro component (the overall structural size of the component is less than 3mm, the microgrooves with the width of 50-300 mu m and the depth-to-width ratio of more than 3 need to be turned on the surface of the component) are used as a special surface texture structure, and have wide industrial application value. For example, in a microfluidic chip with an overall size of less than 10mm, the micro-groove is an important container for carrying a fluidic liquid, and the processing quality of the micro-groove, such as the groove width precision and the groove depth precision, directly determines the use performance of the microfluidic chip. In addition, the micro-grooves also play an important role in the field of manufacturing functional surfaces (such as condensation heat transfer, surface self-cleaning, anti-icing, defrosting and the like). Researches show that the closed micro-groove structure plays a key role in adjusting the fluid mechanics of liquid drop coalescence, and further influences the jumping speed and the energy conversion efficiency of the liquid drop, so that the groove depth and the groove width precision need to be improved as much as possible in the micro-groove processing process.
In ultra-precision turning, particularly in deep groove processing when the depth and width of the groove are less than 300 μm and the depth-to-width ratio of the groove is greater than 3:1, the microgrooves are often formed in one step, because the existing microgroove processing technology cannot ensure the profile precision of the second microgroove shaping, and the second shaping procedure can increase the processing cost and reduce the economic benefit. The existing turning parameter optimization method is mainly carried out by adopting a Taguchi experiment mode, and the key point of the turning parameter optimization is mainly surface roughness. The experimental cost of the Tankou experimental method is high, and the method has no universality; on the other hand, in the field of ultra-precise micro-groove turning, the lower surface roughness of the groove bottom is easier to achieve, and the higher dimensional precision of the micro-groove is difficult to obtain. When the surface of a micro-cylinder component with the diameter of 1-3mm needs to be turned into a groove with the width of 50-300 microns, the depth-to-width ratio is more than 3:1, need adopt the width less and possess the fine lathe tool of great overhang volume and accomplish processing during the microgroove, this kind of fine lathe tool can be equivalent to the cantilever beam structure, and cutter rigidity is weaker simultaneously, often can take place the amount of deflection deformation under the effect of turning power in the turning process, and then influences the size precision of processing the microgroove. In the field of micro-machining, in particular to ultra-precise turning with the width of a cutter being less than 300 mu m, few experimental process records can be used for reference, and relevant literature reports on a turning parameter optimization method of a weak-rigidity micro-turning tool are not reported at home and abroad. Therefore, the design of a novel micro-groove turning processing parameter optimization mode is very critical for realizing stable and controllable removal of materials in the ultra-precise turning process, and meanwhile, the method has important significance for improving the size precision of the micro-groove, reducing the trial and error cost of the parameter optimization process and shortening the parameter optimization period.
Disclosure of Invention
The technical problem to be solved by the invention is as follows:
the problem of optimizing processing errors caused by deflection deformation of a cantilever beam-shaped weak-rigidity micro-lathe tool is solved in the prior art.
The invention adopts the technical scheme for solving the technical problems that:
the utility model provides a turning technological parameter optimization method to little lathe tool excircle turning groove of cantilever beam form weak rigidity, because of the machining error that the deflection warp arouses when little component surface annular microgroove is turned to the little rigidity cutter of cantilever beam form, adopt the multivariate function to carry out parameter characterization to machining error, optimize the machining parameter through minimizing the error, the concrete process is:
the method comprises the steps of firstly, carrying out stress analysis on micro grooves on the surface of a micro-scale component turned by a cantilever beam-shaped weak-stiffness cutter, analyzing to obtain a cutting force component influencing deflection deformation of the cutter, respectively determining the functional relations among the cutting force component, a cutting force coefficient and a cutting ratio, and establishing a functional model of the cutting force component, cutting speed, cutting depth, a cutter front angle and cutter width by combining the three functional relations;
step two, establishing a function model of deflection deformation according to the cutting force component function model obtained in the step one;
step three, establishing a function model of the actual feeding distance in the turning process according to the deflection deformation function model obtained in the step two;
step four, substituting the actual feeding distance function model obtained in the step three into the function model of deflection deformation in the step two for cyclic calculation, stopping the cyclic calculation when the time is the processing time, and obtaining the final function model of the actual feeding distance;
and step five, establishing a function model of the groove depth error according to the function model of the final actual feeding distance obtained in the step four, obtaining the function models of the groove depth error, the workpiece rotation speed, the cutting depth and the cutter front angle, and optimizing each parameter by analyzing the influence rule of each parameter on the groove depth error.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the cutting force is expressed as a function of the cutting speed, the cutting depth and the front angle of the cutter, so that accurate modeling of the cutting force under different technological parameters in the turning process of an external cylindrical member with the diameter of 1-3mm can be realized.
And secondly, establishing a machining error model caused by deflection deformation of the cutter in the actual cutting process by introducing the deflection deformation influence of the cutter of the cantilever beam-shaped weak-rigidity micro lathe tool, wherein the error model has reference significance for the analysis of machining errors of other types of weak-rigidity cutters.
Thirdly, the rotation speed, the cutting depth and the front angle of the cutter of the workpiece in the turning process are optimized in a mode of minimizing machining errors, and the method can reduce the error of the groove depth by 0.3% through rotation speed optimization; the front angle optimization of the cutter can reduce the error of the groove depth by 11.2 percent; the cutting depth optimization can reduce the error of the groove depth by 70.8%; through comprehensive optimization of all parameters, the error of the groove depth can be reduced by 71 percent.
And fourthly, the method can also be used for optimizing parameters such as the height-width ratio of the cutter, the overhanging length of the cutter, the gyration radius of the initial workpiece and the like. The parameters can be used as independent variables causing deflection deformation, and the deflection deformation is reduced by optimizing the independent variables to achieve the aim of optimizing the parameters.
The method has certain universality and can be popularized and used in the optimization of machining parameters of various micro-miniature component machining.
Drawings
FIG. 1 is a force analysis diagram of a turning process in an embodiment of the present invention;
FIG. 2 is a schematic illustration of a cutting process in an embodiment of the present invention;
FIG. 3 is an image of cut rate as a function of depth of cut and cutting speed for an embodiment of the present invention;
FIG. 4 is an image of cutting force as a function of depth of cut, cutting speed and tool rake angle for an embodiment of the present invention;
FIG. 5 is a stress analysis diagram of the cantilever beam weak stiffness micro lathe tool in the embodiment of the invention during turning;
FIG. 6 is a schematic diagram illustrating deformation of a cantilever beam weak-stiffness micro-lathe tool in the embodiment of the present invention;
FIG. 7 is a schematic cross-sectional view of a cantilever weak-stiffness micro-lathe tool in an embodiment of the invention;
FIG. 8 is a flowchart of a programmed implementation of a final actual feed distance determination process in an embodiment of the present invention;
FIG. 9 is a graph showing the result of optimizing the rotational speed of the workpiece according to the embodiment of the present invention;
FIG. 10 is a graph showing the results of optimizing the rake angle of the tool according to the embodiment of the present invention;
fig. 11 is a diagram showing the optimization result of the cutting depth in the embodiment of the present invention.
Detailed Description
In the description of the present invention, it should be noted that the terms "first", "second" and "third" mentioned in the embodiments of the present invention are only used for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include one or more of that feature.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
The first specific embodiment is as follows: with reference to fig. 1 to 11, the present invention provides a method for optimizing parameters of a turning process for turning a groove on an outer circle of a cantilever-shaped weak-stiffness micro turning tool, which is directed to a processing error caused by deflection deformation when a cantilever-shaped weak-stiffness turning tool turns an annular micro groove on a surface of a micro member, and the method adopts a multivariate function to perform parameter representation on the processing error, and optimizes a processing parameter by minimizing the error, wherein the specific process is as follows:
the method comprises the steps of firstly, carrying out stress analysis on micro grooves on the surface of a micro-scale component turned by a cantilever beam-shaped weak-stiffness cutter, analyzing to obtain a cutting force component influencing deflection deformation of the cutter, respectively determining the functional relations among the cutting force component, a cutting force coefficient and a cutting ratio, and establishing a functional model of the cutting force component, cutting speed, cutting depth, a cutter front angle and cutter width by combining the three functional relations;
step two, establishing a function model of deflection deformation according to the cutting force component function model obtained in the step one;
step three, establishing a function model of the actual feeding distance in the turning process according to the deflection deformation function model obtained in the step two;
step four, substituting the actual feeding distance function model obtained in the step three into the function model of deflection deformation in the step two for cyclic calculation, stopping the cyclic calculation when the time is the processing time, and obtaining the final function model of the actual feeding distance;
and step five, establishing a function model of the groove depth error according to the function model of the final actual feeding distance obtained in the step four, obtaining the function models of the groove depth error, the workpiece rotation speed, the cutting depth and the cutter front angle, and optimizing each parameter by analyzing the influence rule of each parameter on the groove depth error.
The method in the embodiment can realize that the diameter of the workpiece is 1-3mm, the width of the micro-groove is 50-300 mu m, and the depth-to-width ratio is more than 3:1, optimizing parameters of the ultra-precise micro-groove turning process.
The method in the embodiment is also suitable for the machining error caused by deflection deformation of the workpiece, and the parameter optimization is carried out on the machining error.
The second specific embodiment: with reference to fig. 1 to 4, in the first step, stress analysis is performed on the micro-scale component surface micro-grooves turned by the cantilever-beam-shaped weak-stiffness tool, and the analysis shows that the cutting force of the tool in the turning process can be decomposed into a tangential force Ft, a radial force Fr and an axial force Fa, wherein the cutting force component causing the deflection deformation of the tool is the tangential force Ft;
the tangential force Ft is a function of a tangential cutting force coefficient, a cutting depth and a cutter width, and the specific expression is as follows:
Ft＝Ktc×h×b (1)
in the formula, KtcThe coefficient of cutting force, h the depth of cut, and b the width of the tool. The rest of this embodiment is the same as the first embodiment.
The third concrete implementation scheme is as follows: in the step one, the cutting force coefficient is a function of cutting speed, cutting depth, tool rake angle and chip ratio, and the specific expression is as follows:
in the formula, gammanThe method comprises the steps of cutting a front angle of a cutter, v is cutting speed m/min, h is cutting depth mum, r is cutting ratio, bg is a Berger vector, a is an empirical constant, G is shear modulus of a workpiece material, A, B and C are material constants of a Johnson-Cook constitutive model, specifically A is yield stress, B is a strain strengthening parameter, C is an empirical strain rate sensitive coefficient,
as a reference strain rate, betamIs a material constant size effect. The rest of this embodiment is the same as the second embodiment.
The specific calculation process of the cutting force coefficient in this embodiment is:
in the formula (I), the compound is shown in the specification,
is the shear angle, ηcIs the chip flow angle of the rake face, betanFor the angle of friction, i is the bevel tilt angle, τ' flow stress, τ shear flow stress, η is the consideration of the micro-cut dimensionThe equivalent strain gradient of the effect, n and m are material constants of a Johnson-Cook constitutive model, specifically n is a strain strengthening parameter, m is a temperature softening effect,
for reference strain rates, T is the dimensionless temperature.
i is a beveling inclination angle, i.e., an angle between a cutting edge and a direction perpendicular to a cutting speed, i is a value greater than 0 DEG and less than 90 DEG for an oblique cutting i, i is equal to 0 for an orthogonal cutting i, i can be obtained when a cutting form (oblique cutting or orthogonal cutting) is determined, and a chip flow angle eta of a rake facecCan be considered approximately equal to i. Tool geometry determination of rear tool rake angle gammanIs known, so when the chip ratio is found, all angles used to represent the forward shear coefficient Ktc are known.
The shear flow stress τ takes into account the ordinary stress strain, material hardening or softening caused by cutting speed, and the change in flow stress caused by temperature. In ultra-precise turning, the cutting depth is small, the heat generated by cutting is small, and the temperature softening effect can be ignored.
Reference strain rate
The quasi-static tensile or compressive test strain rate is typically taken and may be considered a constant value for a particular material.
Since the flow stress of the material is hardly affected by the change of the strain rate by one order of magnitude, the strain rate of the shearing process can be adjusted
Expressed as a function of average strain, cutting speed and depth of cut.
The fourth specific embodiment: in the first step, the chip ratio is a function of cutting speed and cutting depth, and the specific expression is as follows:
r＝cr-kr1*v+kr2*(kr3^h) (12)
where cr is a basic chip ratio constant, kr1 is a scaling factor of cutting speed with respect to chip ratio, kr2 is a slope factor in an exponential progression model of chip ratio with respect to cutting depth, and kr3 is a decimal factor in an exponential progression model of chip ratio with respect to cutting depth. The rest of this embodiment is the same as the third embodiment.
The basic chip rate constant cr in the present embodiment represents the magnitude of the numerical value to which the chip rate approaches when the cutting depth gradually increases; this constant can be obtained by cutting experiments with gradually increasing cutting depth. The scale factor kr1 of cutting speed with respect to chip ratio indicates that when the cutting depth is fixed, the chip ratio and the cutting speed are in a linear relationship, and the magnitude of the value can be obtained by performing cutting experiments at different cutting speeds. The slope factor kr2 and the base factor kr3 in the exponential progression model of the chip ratio with respect to the depth of cut can be obtained by fitting the chip ratio data at different depths of cut.
The cut ratio is defined as: r ═ tcH, in general, is a number greater than 1, where tcThe thickness is cut for deformation.
Since the main factors affecting the chip rate are the depth of cut h and the cutting speed v, the influence of the depth of cut is generally greater than that of the cutting speed. The chip rate generally decreases non-linearly with depth of cut and cutting speed. The cutting rate changes substantially in the same manner with respect to the cutting speed at different cutting depths, and the chip rate changes substantially in the same manner with respect to the cutting depth at different cutting speeds. Therefore, a function image of the chip ratio with respect to the cutting depth and the cutting speed can be fitted through the chip ratio change conditions at different cutting speeds and different cutting depths.
As shown in fig. 3, a graph of the cutting rate fitted for diamond turning of pure copper as a function of depth of cut and cutting speed was obtained. When the cutting speed is 7.2m/min, the relation between the chip rate and the cutting depth can be obtained by fitting a curve, wherein the formula is that r is 1.670+2.431 multiplied by 0.0295hRepresents;
at a fixed cutting depth, the relationship between the chip rate and the cutting speed can be obtained by using a fitted curve, and the formula is that r is 0.376×e(-v/7.578)The chip ratio is reduced along with the increase of the cutting speed, and a three-dimensional curved surface image of the chip ratio about the cutting depth and the cutting speed is drawn by combining the influence rule of the cutting depth and the cutting speed on the chip ratio, and the influence of the cutting depth on the chip ratio is relatively large.
The fifth concrete implementation scheme is as follows: in the first step, a function model of tangential force Ft is established by combining formulas (1), (2) and (12), wherein the tangential force is a function of cutting speed, chip depth, a tool rake angle and tool width, and the specific expression is as follows:
the rest of this embodiment is the same as the fourth embodiment.
The image shown in fig. 4 in this embodiment is a three-dimensional function image of the cutting force with respect to the cutting depth, the cutting speed, and the rake angle of the tool when the tool width is 30 μm, and is presented in a sectional combination manner in order to clearly express the numerical value of the three-dimensional function.
The sixth specific embodiment: as shown in fig. 5 to 7, in the second step, a function model of deflection deformation of the tool is established according to the stress mode of the weak-rigidity tool; under the action of the tangential force Ft, the cutter generates cutter deflection deformation in the feeding direction and cutter deflection deformation in the cutting speed direction, and the specific calculation process is as follows:
v＝2π×(rw-d(t))×ω (17)
by combining equations (14), (15), (16) and (17):
wherein, Deltay is the deflection deformation of the cutter in the feeding direction, Deltaz is the deflection deformation of the cutter in the cutting speed direction, z is the distance from any point on the cutter interface to the neutral axis of the cantilever beam, rwThe initial radius of the workpiece, omega is the rotation speed of the workpiece, w is the height of the cross section of the cutter, E is the elastic modulus of the material of the cutter, L is the length of the cutter, I is the inertia moment of the cross section of the cutter about the X axis, and d (t) is the actual feeding distance. The rest of this embodiment is the same as the fifth embodiment.
In this embodiment, in combination with the formulae (14), (15) and (16), the following can be obtained:
further, Δ y (t) is obtained according to the formula (19) and the formula (17).
The seventh specific embodiment: the establishment process of the actual feeding distance function model in the third step is as follows:
Ps,y(t)＝fy×t-Δy(t) (20)
the final function model of the actual feed distance is established in conjunction with equations (20), (21) and (22) as:
in the formula, Ps,y(t) is the magnitude of the displacement of the tool, fyIs a target feed speed, fy aIs the actual feed rate. The rest of this embodiment is the same as the sixth embodiment.
As shown in fig. 8, the obtained actual feeding distance function model is substituted into the function model of deflection deformation of the formula (18) to perform cyclic calculation, and when the time is the machining time, the cyclic calculation is stopped to obtain the final actual feeding distance function model;
the specific embodiment eight: the function model of the groove depth error in the fifth step is specifically as follows:
wherein T is the processing time. The rest of this embodiment is the same as the seventh embodiment.
The specific embodiment is nine: as shown in fig. 9 to 11, the rotation speed of the workpiece, the cutting depth, and the rake angle of the tool are preferably selected by the single-factor variable method. The rest of this embodiment is the same as the eighth embodiment.
In the embodiment, a single-factor variable method is adopted, three parameters of different rotation speeds, cutting depths and tool rake angles are substituted into a groove depth error expression, and the parameters are optimized by analyzing the influence rule of each parameter on the groove depth error. In the optimization of the rotation speed, a fixed numerical value of the cutting depth and the front angle of the cutter is given, different rotation speed parameters are substituted into a groove depth error expression, the influence of the rotation speed on the groove depth error is analyzed by drawing an influence curve of the rotation speed of the workpiece on the groove depth error, and the working rotation speed corresponding to the minimum point of the groove depth error on the influence curve is the optimal rotation speed. In the optimization of the cutting depth, a fixed numerical value of the workpiece rotation speed and the cutter front angle is given, different cutting depth parameters are substituted into a groove depth error expression, the influence of the cutting depth on the groove depth error is analyzed by drawing an influence curve of the cutting depth on the groove depth error, and the cutting depth corresponding to the minimum point of the groove depth error on the influence curve is the optimal cutting depth. In the optimization of the tool front angle, a fixed numerical value of the workpiece rotation speed and the cutting depth is given, different tool front angle parameters are substituted into a groove depth error expression, the influence of the tool front angle on the groove depth error is analyzed by drawing an influence curve of the tool front angle on the groove depth error, and the tool front angle corresponding to the minimum groove depth error point on the influence curve is the optimal tool front angle.
In this embodiment, when the initial radius of the workpiece is 500 μm and the width of the tool is 30 μm, the rotation speed, the cutting depth and the rake angle of the tool are optimized, wherein the optimized range of the rotation speed of the workpiece is 5000-10000rpm, and the optimized range of the rotation speed can be selected according to the rotation speed range commonly used in actual processing. The optimized range of the cutting depth is 0.02-2 mu m, the range of the cutting depth can be correspondingly set according to the thickness of the cutter and the commonly selected range of the cutting depth for precision turning, and the smaller range of the cutting depth is selected for enabling the turning process to be equivalent to the plane strain process due to the smaller thickness of the cutter. The optimized range of the front angle of the cutter is 0-0.35 rad (0-20 degrees).
The specific embodiment ten: and step five, obtaining the following through analysis: the rotation speed of the workpiece is 5000rpm and is the optimal rotation speed, the front angle of the cutter is 15 degrees and is the optimal angle, and the cutting depth is 0.2 mu m and is the optimal depth. The rest of this embodiment is the same as the embodiment nine.
As shown in fig. 9, the machining error was 1.090 μm, which was the smallest when the rotational speed was 5000 rpm; as shown in fig. 10, the machining error is gradually reduced as the tool rake angle increases, and is 1.02 μm when the tool rake angle is 20 °. On the other hand, when the tool rake angle is 15 °, the machining error is 1.03 μm, which is similar to the error result when the rake angle is 20 °, whereas when the rake angle is 15 °, the tool strength is higher than when the rake angle is 20 °, and thus the tool rake angle of 15 ° is considered to be the optimum rake angle; as shown in fig. 11, when the cutting depth is 0.2 μm, the machining error is minimized.
In order to comprehensively compare the influence of each parameter on the groove depth error, selecting a workpiece rotation speed of 8000rpm, a cutter front angle of 0 degree and a cutting depth of 2 mu m, substituting the workpiece rotation speed, the cutter front angle of 0 degree and the cutting depth of 2 mu m into a formula (25) to solve the groove depth error, wherein the error result is 2.442 mu m; the rotation speed of a workpiece is 5000rpm, the front angle of a cutter is 15 degrees and the cutting depth is 0.2 mu m, the groove depth error is obtained by substituting the rotation speed and the front angle of the cutter into a formula (25), the error result is 0.708 mu m, and the groove depth error can be reduced by 71 percent. The influence of each parameter on the error is added according to the law, the cutting depth is obtained, the machining error can be reduced by 70.8%, and the machining error can be reduced by 11.2% by the front angle of the cutter; the rotating speed of the workpiece can reduce the machining error by 0.3%; by comprehensively optimizing the cutting depth, the front angle of the cutter and the rotating speed of the workpiece, the machining error can be reduced by 71 percent.
As shown in fig. 9 to 11, the variation width of the groove depth error is 1.7 μm in the range of the cutting depth of 0 to 2 μm; the rake angle of the cutter is within the range of 0-20 degrees, and the variation amplitude of the groove depth error is 0.14 mu m; the rotating speed of the workpiece is 5000-10000rpm, and the variation range of the groove depth error is 0.003 mu m. The analysis shows that the influence of the cutting depth on the machining precision is the largest, and the influence of the rotation speed of the workpiece is the smallest after the front angle of the cutter.
Although the present disclosure has been described with reference to the above embodiments, the scope of the present disclosure is not limited thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present disclosure, and these changes and modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. The method for optimizing the turning technological parameters of the excircle turning groove of the cantilever beam-shaped weak-rigidity micro turning tool is characterized in that a multivariate function is adopted to carry out parameter representation on the machining errors caused by deflection deformation when the cantilever beam-shaped weak-rigidity tool turns the annular micro groove on the surface of a micro component, and the machining parameters are optimized through the minimized errors, and the specific process is as follows:
firstly, carrying out stress analysis when a micro-scale component surface micro-groove is turned on a cantilever beam-shaped weak-rigidity cutter, analyzing to obtain a cutting force component influencing deflection deformation of the cutter, respectively determining the functional relations of the cutting force component, the cutting force coefficient and the cutting ratio, and establishing a functional model of the cutting force component, the cutting speed, the cutting depth, the cutter front angle and the cutter width by combining the three functional relations;
step two, establishing a function model of deflection deformation according to the cutting force component function model obtained in the step one;
step three, establishing a function model of the actual feeding distance in the turning process according to the deflection deformation function model obtained in the step two;
step four, substituting the actual feeding distance function model obtained in the step three into the function model of deflection deformation in the step two for cyclic calculation, stopping the cyclic calculation when the time is the processing time, and obtaining the final function model of the actual feeding distance;
and step five, establishing a function model of the groove depth error according to the function model of the final actual feeding distance obtained in the step four, obtaining the function models of the groove depth error, the workpiece rotation speed, the cutting depth and the cutter front angle, and optimizing each parameter by analyzing the influence rule of each parameter on the groove depth error.
2. The method for optimizing the turning technological parameters of the cantilever-beam-shaped weak-rigidity micro turning tool excircle groove turning is characterized in that in the step one, stress analysis is carried out when the cantilever-beam-shaped weak-rigidity tool turns the micro groove on the surface of the micro scale component, and the analysis shows that the cutting force of the tool in the turning process can be decomposed into a tangential force Ft, a radial force Fr and an axial force Fa, wherein the cutting force component causing the tool to generate deflection deformation is the tangential force Ft;
the tangential force Ft is a function of a tangential cutting force coefficient, a cutting depth and a cutter width, and the specific expression is as follows:
Ft＝Ktc×h×b (1)
in the formula, KtcIs the coefficient of cutting force, h is the depth of cut, b is the toolHaving a width.
3. The method for optimizing the parameters of the turning process aiming at the cantilever-beam-shaped weak-rigidity micro turning tool outer circular groove turning according to claim 2, wherein the coefficient of the cutting force in the step one is a function of the cutting speed, the cutting depth, the tool rake angle and the chip ratio, and the specific expression is as follows:
in the formula, gammanThe method comprises the steps of cutting a front angle of a cutter, v is cutting speed m/min, h is cutting depth mum, r is cutting ratio, bg is a Berger vector, a is an empirical constant, G is shear modulus of a workpiece material, A, B and C are material constants of a Johnson-Cook constitutive model, specifically A is yield stress, B is a strain strengthening parameter, C is an empirical strain rate sensitive coefficient,
for reference strain rate, betamIs a material constant size effect.
4. The method for optimizing the parameters of the turning process aiming at the cantilever-beam-shaped weak-rigidity micro turning tool outer circular groove turning according to claim 3, wherein the chip rate in the step one is a function of the cutting speed and the cutting depth, and the specific expression is as follows:
r＝cr-kr1*v+kr2*(kr3^h) (3)
where cr is a basic chip ratio constant, kr1 is a scaling factor of cutting speed with respect to chip ratio, kr2 is a slope factor in an exponential progression model of chip ratio with respect to cutting depth, and kr3 is a decimal factor in an exponential progression model of chip ratio with respect to cutting depth.
5. The method for optimizing the parameters of the turning process for grooving the outer circle of the cantilever-beam-shaped weak-stiffness micro-turning tool according to claim 3, wherein a function model of a tangential force Ft is established in the step one in combination with the equations (1), (2) and (3), the tangential force is a function of a cutting speed, a cutting depth, a tool rake angle and a tool width, and the specific expression is as follows:
6. the method for optimizing the parameters of the turning process for grooving the outer circle of the cantilever-beam-shaped weak-rigidity micro-turning tool according to claim 5 is characterized in that a function model of the deflection deformation of the tool is established according to the stress mode of the weak-rigidity tool in the second step; under the action of the tangential force Ft, the cutter generates cutter deflection deformation in the feeding direction and cutter deflection deformation in the cutting speed direction, and the specific calculation process is as follows:
v＝2π×(rw-d(t))×ω (8)
the following can be obtained by combining equations (5), (6), (7) and (8):
wherein, Deltay is the deflection deformation of the cutter in the feeding direction, Deltaz is the deflection deformation of the cutter in the cutting speed direction, z is the distance from any point on the cutter interface to the neutral axis of the cantilever beam, rwIs the initial radius of the workpiece, omega is the workThe speed of rotation of the part, w the height of the cross section of the tool, E the modulus of elasticity of the tool material, L the length of the tool, I the moment of inertia of the tool section about the X-axis, and d (t) the actual feed distance.
7. The method for optimizing the parameters of the turning process aiming at the cantilever-beam-shaped weak-rigidity micro turning tool outer circular turning groove according to claim 6, wherein the establishment process of the actual feed distance function model in the third step is as follows:
Ps,y(t)＝fy×t-Δy(t) (10)
the final function model of the actual feed distance is established in combination with equations (10), (11) and (12) as:
in the formula, Ps,y(t) is the magnitude of the displacement of the tool, fyIs a target feed speed, fy aIs the actual feed rate.
8. The turning process parameter optimization method for cantilever-beam-shaped weak-rigidity micro-turning tool excircle turning groove according to claim 7, characterized in that a function model of groove depth errors in the fifth step is specifically as follows:
wherein T is the processing time.
9. The method for optimizing the parameters of the turning process aiming at the cantilever-beam-shaped weak-rigidity micro turning tool excircle groove turning according to claim 8, characterized in that a single-factor variable method is adopted to optimize the parameters of the workpiece rotation speed, the cutting depth and the tool rake angle.
10. The method for optimizing the parameters of the turning process for turning the outer circular groove of the cantilever-beam-shaped weak-rigidity micro-lathe tool according to claim 9 is characterized in that the parameters are obtained by analysis in the fifth step: the rotation speed of the workpiece is 5000rpm and is the optimal rotation speed, the front angle of the cutter is 15 degrees and is the optimal angle, and the cutting depth is 0.2 mu m and is the optimal depth.
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