US 2022/0164498 A1 · DEFORMATION PREDICTION METHOD OF MICRO-MILLING THIN-WALLED PARTS

Abstract

The present invention belongs to the precise and efficient processing field of micro parts, in particular to a deformation prediction method of micro-milling thin-walled parts. Firstly, based on the finite element simulation software, a finite element simulation model of micro-milling thin-walled parts is established. Johnson-Cook material model and failure criterion are used to describe the material properties and damage criteria of the machined materials, so as to realize the prediction of milling force in the micro-milling process. The accuracy of the model is verified by experiments. Then, based on the birth-death element method, a deformation prediction model of micro-milling thin-walled parts model is established, and the milling force output from the finite element simulation model is loaded into the deformation prediction model. Finally, the deformation prediction of d micro-milling thin-walled parts is realized.

A method for deformation prediction of micro-milling thin-walled parts, comprising steps of:

step 1:
establishment and assembly of tool and workpiece model for finite element simulation model of micro-milling thin-walled parts
establishing a finite element simulation model of micro-milling thin-walled parts based on SI unit system;
taking image of the tool by electron microscope, and importing the image into a two-dimensional modeling software to copy front contour of the tool;
using the front contour as benchmark of a three-dimensional modeling software to rotate and stretch into the three-dimensional tool;
carrying out cutting and optimization according to geometric dimensions of the tool obtained from side images, and obtaining a three-dimensional geometric model of the tool;
establishing a three-dimensional geometrical model of the workpiece by the finite element simulation software, the workpiece is thin-walled part;
the three-dimensional geometrical tool model and the three-dimensional geometrical workpiece model constitute the three-dimensional finite element simulation geometric model of micro-milling thin-walled parts;the three-dimensional geometric model of tool and workpiece needs to be meshed after being established;
importing the three-dimensional geometric model of tool into a finite element simulation software for meshing;
using curvature radius to mesh the tool model to ensure the non-lossy of the tool model;
using split functionality to refine the meshes at the tool tip and main and secondary cutting edges of the tool model, and dividing the rest of the meshes sparsely, ensuring the quality of key parts of the meshes;
dividing three-dimensional geometric model of the workpiece into machining and non-machining region;
the meshes of machining region are uniform and dense, while the meshes of non-machining region are rough and sparse;
carrying out assembly after the meshing of the tool model and the workpiece model is completed;
step 2:
material parameters and failure criteria of the finite element simulation model for micro-milling thin-walled parts
using Johnson-Cook model to characterize the material parameters and failure criteria;
Johnson-Cook constitutive model is expressed as Eq. (1):
σ
=
(
A
+
B
⁢
⁢
ɛ
n
)
⁡
[
1
+
C
⁢
⁢
ln
⁡
(
ɛ
.
ɛ
.
0
)
]
⁢
(
1
-
T
*
m
)
(
1
)
where, σ is stress;
A is yield stress;
B is strain hardening parameter;
C is strain rate coefficient;
n is work hardening parameter;
m is temperature softening parameter;
{dot over (ε)} is plastic strain rate;
{dot over (ε)}0 is reference strain rate;
T* is dimensionless temperature, the expression is Eq. (2)
T
*
=
T
-
T
r
T
m
-
T
r
(
2
)
where, T is deformation temperature;
Tr is room temperature;
Tm is melting temperature;
Johnson-Cook failure criterion is expressed as Eq. (3):
ɛ
q
′
=
[
d
1
+
d
2
⁢
exp
⁡
(
d
3
⁢
σ
c
σ
_
)
]
⁡
[
d
4
⁢
ln
⁡
(
ɛ
.
c
ɛ
.
0
)
+
1
]
⁡
[
d
5
⁢
T
*
+
1
]
(
3
)
where, ε′q is equivalent failure strain, σc is compressive stress;
σ is equivalent stress mean;
{dot over (ε)}c is equivalent strain rate;
{dot over (ε)}0 is reference strain rate;
d1-d5 are failure parameters and are initial fracture strain influence factor, exponential influence factor, stress influence factor, strain rate influence factor and temperature influence factor, respectively;
step 3:
interaction and load of finite element simulation model of micro-milling thin-walled parts
in the interaction setting, setting contact mode as point-surface contact formed by the geometric surface of the tool and the nodes of the workpiece machining area;
using the combination of “penalty” contact method and finite sliding to describe the interaction between tool and workpiece in the machining area;
in the “penalty” contact, setting normal behavior as hard contact, and setting tangential behavior as frictional contact;
setting friction coefficient according to the material properties of tool and workpiece;
according to the actual processing conditions, setting boundary condition of the workpiece to fix the bottom surface, and establishing node set of the bottom surface and setting as full constraint, that is, all six degrees of freedom of the workpiece model are fixed;
constraining the three-dimensional geometric model of the tool model to a reference point, and setting rotating speed, cutting depth and feed rate at the reference point;
step 4:
force prediction of the finite element simulation model for micro-milling thin-walled parts
according to steps 1-3, completing the finite element simulation model of micro-milling thin-walled parts by setting the boundary condition module of the load of the finite element simulation model of micro-milling thin-walled parts, including spindle speed, feed rate per tooth, axial cutting depth and radial cutting depth;
then checking the data and submitting the operation to predict the force of micro-milling thin-walled parts;
step 5:
geometric models and meshing of the deformation prediction model of micro-milling thin-walled parts
according to the processing requirements, setting workpiece size of the deformation prediction model of micro-milling thin-walled parts;
establishing geometrical model of the workpiece by using the finite element simulation software;
the material properties are consistent with Johnson-Cook model in Step 2, and dividing the meshes of the workpiece;
dividing the meshes according to the principle of accurate deformation data output by elements and nodes;
selecting static implicit and three-dimensional stresses for mesh element types;
step 6:
element coding and load of the deformation prediction model of micro-milling thin-walled parts
to realize the dynamic loading of deformation prediction model of micro-milling thin-walled parts and complete the element deletion to simulate the milling process, corresponding analysis steps need to be set, and each analysis step contains the element and node at the corresponding position;
renumbering the processing area in order from top to bottom and right to left by the method of element recoding;
using INP files to select the elements and nodes of the deformation prediction model of micro-milling thin-walled parts and set up the SET set;
then, recoding the elements that need to be encoded in the processing area from 1, and inputting each column of the SET into the INP file to process and remove part of the elements and their nodes to complete the coding and integration of the elements;
the node recoding method is consistent with the element recoding method;
according to step 4, using the finite element simulation model of micro-milling thin-walled parts to obtain the micro-milling force value under different cutting parameters;
in the deformation prediction model of micro-milling thin-walled parts, dynamically applying the micro-milling forces predicted by the finite element simulation model of micro-milling thin-walled parts to the SET set to complete the loading process;
step 7:
element deletion of the deformation prediction model of micro-milling thin-walled parts
in the establishment of the element deletion model of the deformation prediction model of micro-milling thin-walled parts, setting the micro-milling force loading of each SET, and deleting the element when reaching the failure condition e−8;
step 8:
deformation prediction of micro-milling thin-walled parts
according to steps 5-7, completing the deformation prediction model of micro-milling thin-walled parts;
applying dynamic micro-milling force and taking the node as the output point of the deformation of thin-walled part, which realizing the deformation prediction model of micro-milling thin-walled parts.

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Deformation prediction method of micro-milling thin-walled parts

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Deformation prediction method of micro-milling thin-walled parts

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Abstract

Claims1