CN110147602A - A kind of method and its application for establishing bending springback angle prediction model - Google Patents
A kind of method and its application for establishing bending springback angle prediction model Download PDFInfo
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- CN110147602A CN110147602A CN201910400673.9A CN201910400673A CN110147602A CN 110147602 A CN110147602 A CN 110147602A CN 201910400673 A CN201910400673 A CN 201910400673A CN 110147602 A CN110147602 A CN 110147602A
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Abstract
The present invention provides a kind of method and its application for establishing bending springback angle prediction model, the method for establishing bending springback angle prediction model, including establishes sliding block volume under pressure model for free bending；Orthogonal test table is designed, spring-back research analysis is carried out with analogue simulation software, obtains the springback angle of different experiments scheme, the pretreatment of data is carried out with standardized method；According to orthogonal experiments, selecting inverse more quadratic functions is basic function, establishes free bending sheet forming rebound radial basis function approximate model.Preferable springback angle precision of prediction can be obtained using the bending springback angle prediction model that the present invention establishes.
Description
Technical field
The present invention relates to sheet metal bending forming technology field, especially a kind of method for establishing bending springback angle prediction model
And its application.
Background technique
V-type free bending moulding process can process the part of more specification by less die assembly, therefore
It has a wide range of applications in the manufacturing fields such as aviation, automobile and household electrical appliances.During metal plate bending and molding, slab interior can occur
Flexible deformation and plastic deformation, after plus load is unloaded, the plastic deformation of metal plate retains, and flexible deformation disappears, workpiece hair
Raw rebound phenomenon.Rebound is phenomenon inevitable in cold stamping forming process, due to there is the influence factor much to intercouple,
To show the non-linear of height, along with the shape complicated and changeable of actual production conditions, so that rebound problem always cannot be very
An important factor for solving well, being always limit product quality is the significant deficiency in sheet-metal formed, drastically influences bender
The formed precision of part.
The rebound of part is the cumulative effect of entire forming history, and the performance parameter of the forming of plate and material, plate
The many factors such as thickness and the geometric parameter of mold it is closely related, therefore the rebound problem of sheet material forming is more complicated.Existing rank
Section, for sheet metal bending Form springback research mainly there are three aspect, be analytic method, laboratory method and finite element modelling respectively
Simulation method.Analytic method will usually simplify mechanical model, and spring back by many factors effect of intercoupling, so as to cause solution
Analysis method solving precision is poor, in some instances it may even be possible to the result of mistake occurs；For the deficiency of analytic method, many experts and engineering staff attempt
Solved by experimental method, experimental result will be influenced by field experiment condition, and with the processing method of experimental data, warp
It is related to test application conditions of formula etc., can be only applied to similar in experimentation production in, if carry out many experiments if,
It necessarily will affect production efficiency and economic benefit.
Summary of the invention
In view of the foregoing deficiencies of prior art, the prediction of bending springback angle is established the purpose of the present invention is to provide a kind of
The method and its application of model, for solve precision of prediction existing for springback Prediction method in the prior art it is low, it is at high cost and
The technical issues of low efficiency.
In order to achieve the above objects and other related objects, the present invention provides a kind of side for establishing bending springback angle prediction model
Method, the method for establishing bending springback angle prediction model include:
Sliding block volume under pressure model is established for workpiece free bending process, to obtain the volume under pressure of unloading front-slider；
Orthogonal test table is designed, to obtain multiple testing programs, each experimental program is as a sample point；
Molding resilience sunykatuib analysis is carried out to each sample point using the volume under pressure of the sliding block before unloading, to obtain
Take the numerical value of the corresponding springback angle of each sample point；
The data of each sample point are standardized；
Choose bending springback angle prediction model function；
According to the data of each sample point of standardization and the springback angle corresponding with each sample point
The weighting coefficient of the bending springback angle prediction model function is found out, to complete the foundation of bending springback angle prediction model.
Optionally, test impact factor is elasticity modulus, sheet thickness, upper mold radius of corner and lower die open width, examination
Testing index is the springback angle.
Optionally, the volume under pressure formula of the sliding block before unloading are as follows:
Wherein, W lower die open width, R are lower die radius of corner, and α is bending angle, and β is the V-arrangement angle of lower die V-shaped groove, and k is
Bending arc radius coefficient, ξ are workpiece ironing coefficient, and T is the sheet thickness of workpiece.
Optionally, the bending angle α includes 90 °.
Optionally, the step of being standardized to the data of each sample point includes being standardized using Z-score
The data of each sample point are normalized in method.
Optionally, the volume under pressure using the sliding block before unloading carries out molding resilience mould to each sample point
The step of quasi- analysis, numerical value to obtain the corresponding springback angle of each sample point includes:
The volume under pressure of the sliding block before unloading is input in analogue simulation software；
Molding resilience sunykatuib analysis is carried out to each sample point with the analogue simulation software, it is each described to obtain
The numerical value of the corresponding springback angle of sample point.
Optionally, the analogue simulation software includes engineering simulation finite element software, such as can be ABAQUS software.
Optionally, after the weighting coefficient for finding out the radial basis function approximate model, further include, separately take several sample points
The step of experimental verification and accuracy evaluation are carried out to the radial basis function approximate model of foundation.
Optionally, the bending springback angle prediction model function includes radial basis function.
Optionally, the basic function of the bending springback angle prediction model function includes inverse more quadratic functions.
Optionally, the basic function expression formula of the bending springback angle prediction model function are as follows:
In formula, c is nonnegative constant.
Optionally, the expression formula of the bending springback angle prediction model is
Wherein, ηiFor i-th weighting coefficient, xiCoordinate for i-th of sample spot in design space, | | x-xi||
For x with i-th of sample spot at a distance from design space,For basic function, | | | | it is Euclidean Norm, m is the sample
The number of this point.
In order to achieve the above objects and other related objects, the present invention also provides a kind of bending springback compensation method, the foldings
Curved springback compensation method includes:
It is sprung back using the bending that the method for establishing bending springback angle prediction model according to above-mentioned any one is established
Angle prediction model predicts the free bending springback angle to bending workpieces；
Free bending springback angle according to prediction to bending workpieces finds out the volume under pressure offset of sliding block；
The volume under pressure of the sliding block is compensated with the volume under pressure offset；
The depression distance of the sliding block is controlled according to the volume under pressure of the compensated sliding block, it is described to bending to complete
The bending and molding of workpiece.
Realize above-mentioned purpose and other related purposes, the present invention also provides a kind of free bending system, the free bendings
System includes:
Bending machine has sliding block；
Control system, the control system are connected with the bending machine；
When treating bending workpieces progress bending and molding, the control system is controlled according to above-mentioned bending springback compensation method
The depression distance of the sliding block is made, to complete to the bending and molding to bending workpieces.
The present invention uses orthogonal test method, and choosing test impact factor is elasticity modulus, sheet thickness, upper mold fillet half
Diameter and lower die open width, each impact factor take 5 levels respectively, orthogonal to spring back the differences of front and rear angles as test index
Test has balanced dispersibility and neat comparativity, to keep test number (TN) few, effect is good, simple and convenient, high-efficient；
The present invention is by orthogonal test, on the basis of V-arrangement free bending sliding block volume under pressure model, with ABAQUS software
Sheet forming is sprung back and carries out simulation analysis, plate material to rebound is predicted using radial basis function approximate model, radial base letter
Exponential model is different with the difference of used kernel function form, and flexibility is good, and structure is simple, and calculation amount is relatively fewer and imitates
Rate is higher；
The present invention is normalized sample data using Z-score standardized method, eliminates each technique number
The difference of unit and dimension between avoids that directly forming parameters being input in processing software (such as MATLAB), by
Bury in oblivion caused by the data precision of system compared with small parameter, subsequent mathematical modeling work can not be carried out；
The present invention using foundation radial basis function approximate model to separately obtained in trial stretch sample point spring back it is pre-
It surveys, respectively compared with practical bending result and the result of ABAQUS rebound emulation, springback Prediction precision with higher；
The radial basis function approximate model established using the present invention, can directly be calculated according to workpiece (plate) and die parameters
Springback angle is added to pushing offset in the first time volume under pressure of sliding block by springback compensation formula, realizes disposable more high-precision
Bending is spent, it is time saving and energy saving.
Detailed description of the invention
Fig. 1 is shown as the flow diagram of the method for establishing bending springback angle prediction model of the invention.
Fig. 2 is shown as free bending theoretical model figure of the invention.
Fig. 3 is shown as springback angle schematic diagram of the invention.
Fig. 4 is shown as limit element artificial module figure of the invention.
Fig. 5 is shown as bending machine structural schematic diagram of the invention.
Specific embodiment
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.
Please refer to Fig. 1-5.It should be noted that only the invention is illustrated in a schematic way for diagram provided in the present embodiment
Basic conception, only shown in schema then with related component in the present invention rather than component count, shape when according to actual implementation
Shape and size are drawn, when actual implementation kenel, quantity and the ratio of each component can arbitrarily change for one kind, and its component cloth
Office's kenel may also be increasingly complex.
As shown in Figure 1, the present embodiment provides a kind of method for establishing bending springback angle prediction model, to be used for plate (work
Part): the prediction of the springback angle when carrying out the molding of V-type free bending.The method for establishing bending springback angle prediction model
The following steps are included:
It executes step S10, establish sliding block volume under pressure model for workpiece free bending process, to obtain unloading front-slider
Volume under pressure.
Specifically, sliding block volume under pressure model is established for V-arrangement free bending, theoretical model is as shown in Figure 1, by several in figure
What relationship obtains:
And
R=kW (4)
The volume under pressure Y of the sliding block is expressed as before then unloading
In above formula, a1、y1And y2It is intermediate variable, specific geometrical relationship is shown in Fig. 2；W lower die open width；R is lower die circle
Angular radius；α is bending angle；β is the V-arrangement angle of lower die V-shaped groove；K is bending arc radius coefficient；ξ is workpiece ironing coefficient, according to
Experience and related data are chosen；R is radius bend, and radius bend r is related with the opening width W of lower die, is detailed in formula (4), and k is
Arc radius coefficient, k is between 0.15-0.17.
In the present embodiment, bending angle α for example can choose 90 °；The V-arrangement angle beta of lower die V-shaped groove for example can choose 88 °；
Workpiece ironing coefficient ξ can for example take 0.98；Lower die radius of corner R can for example take 1.5mm, arc radius coefficient k value example
0.156 can be such as selected as.It should be noted that the numerical value that arc radius coefficient k various countries provide is different, Deutsche industry norm (DIN)
DIN6935-2010 value 0.156, LVD company value are 5/32, Beyeler value 0.16, and k value is chosen in bending franchise
It plays an important role, generally rule of thumb data are chosen.In addition, the V-arrangement angle beta of the bending angle α, lower die V-shaped groove, lower die circle
Angular radius R and workpiece ironing coefficient ξ also can according to need the suitable value of selection.
Step S20, design orthogonal test table are executed, to obtain multiple testing programs, each experimental program is as a sample
This point.
Since orthogonal test has balanced dispersibility and neat comparativity, to keep test number (TN) few, effect is good, simple side
Just, high-efficient, therefore, in the present embodiment, orthogonal test is designed, choosing test impact factor is elastic modulus E, sheet thickness
T, upper mold radius of corner r0(see Fig. 4) and lower die open width W, each impact factor have several horizontal (values) respectively, to return
Play angle (the difference α of rebound front and rear angles0- α is shown in Fig. 3) it is test index, by several value generations of each test impact factor
Enter orthogonal arrage to obtain testing program table, includes multiple testing programs, each experimental program is as a sample point.
As an example, each impact factor for example takes 5 levels respectively, the orthogonal arrage for example can be orthogonal arrage L25
(54), 5 horizontal orthogonal arrages that substitute into of each test impact factor can be obtained into testing program table as shown in Table 1, including
25 testing programs.
1 testing program of table and test result analysis table
It should be noted that in other embodiments, the horizontal value of each test impact factor, orthogonal arrage can bases
Actual demand is adjusted flexibly.
It should be noted that in the present embodiment, choosing elastic modulus E, sheet thickness T, upper mold radius of corner r0With under
For mould opening width W as test impact factor, this is inventor after studying multiple possible factors influenced, is chosen
Springback angle is influenced more significant several, the springback angle prediction essence of the radial basis function approximate model of foundation can be effectively improved
Degree.
It executes step S30, molding resilience is carried out to each sample point using the volume under pressure of the sliding block before unloading
Sunykatuib analysis, to obtain the corresponding springback angle of each sample point.
Specifically, the volume under pressure of the sliding block before unloading is input in analogue simulation software, with the emulation mould
Quasi- software carries out molding resilience sunykatuib analysis to each sample point, to obtain the corresponding springback angle of each sample point
Numerical value (see Table 3 for details)；
As an example, the analogue simulation software includes the engineering simulation finite element software of ABAQUS, it should be noted that
Also other suitable engineering simulation finite element softwares be can choose.
It executes step S40, the data of each sample point is standardized.
In the present embodiment, sample data is normalized using Z-score standardized method, to selected
The value of four impact factors is converted, and detailed process is as follows
Wherein, n is the number of each impact factor value, biFor script numerical value, c acquired by each influence factoriTo pass through
The value of each influence factor after normalized, obtained new serial mean are 0, variance 1, and dimensionless.
It should be noted that sample data is normalized using Z-score standardized method, eliminate each
The difference of unit and dimension between process data avoids that forming parameters are directly input to processing software (such as MATLAB)
It is interior, bury in oblivion as caused by the data precision of system compared with small parameter, subsequent mathematical modeling work can not be carried out.
It executes step S50, choose bending springback angle prediction model function.
Specifically, radial basis function is chosen as radial basis function bending springback angle prediction model function is established, first really
Determine known sample point x1,x2,…,xmFunctional value F (x) is obtained at mapping relations therewith；Secondly, using f (x) as will establish
Approximate model function, Selection of FunctionBasic function as f (x) function is also referred to as kernel function, and wherein γ is referred between sample
Euclidean distance；Then by basic functionLinear superposition is carried out to constitute with F (x) in the one-to-one approximate function f of sample point
(x).Multidimensional problem is converted into one-dimensional problem by Euclidean distance by radial basis function, is mentioned for the foundation of plate material to rebound prediction model
It has supplied to greatly facilitate, specific modeling process is as follows:
Wherein, it enables
In formula (9), γi(x)=| | x-xi| | it is x and ith sample point xiDistance in design space,For base letter
Number, | | | | it is Euclidean Norm, c is nonnegative constant, and η is basic functionWeighting coefficient, m be sample point number, this
In embodiment, m 25.Any function may be expressed as the weighted sum of one group of basic function under normal circumstances, it is possible to real
A kind of now Nonlinear Mapping from input sample to basic function between output.
Bending springback angle prediction model function can be generally expressed as follows
Wherein, ηiFor i-th weighting coefficient, | | x-xi| | for x with i-th of sample spot at a distance from design space,For basic function, | | | | it is Euclidean Norm, m is the number of the sample point, in the present embodiment, m 25.
Execute step S60, according to the data of each sample point of standardization and corresponding with each sample point
The springback angle find out the weighting coefficient of the bending springback angle prediction model function, to complete bending springback angle prediction model
Foundation.
Specifically, when using formula (10) as prediction model, it needs to meet following interpolation condition:
f(xi)=F (xi) (i=1 ..., m) (11)
Wherein, m is the number of sample point, in the present embodiment, m 25.
In (11) formula generation, is returned into (10) formula, enables γij=| | xi-xj| | (i, j=1,2 ..., m), then
It enables
Then
A η=F (12)
Formula (12) is not overlapped in sample point, and basic functionExistence and unique solution is when for positive definite integral form to get coefficient matrix
η=A-1·F (13)
Compare by the analysis to basic function characteristic, in the present embodiment, selects inverse more quadratic functions, expression formula is as follows
It is shown:
In formula, c is nonnegative constant, and in the present embodiment, c can for example take 1.
Need to illustrate when, the basic function of bending springback angle prediction model functionIt can flexibly be selected as needed
It selects, however it is not limited to the structure of formula (14).
It can be obtained by 1 data of table
x1=(xA1,xB1,xC1,xD1)=(0.8,160,0.5,20) → (- 1.2649, -1.2649, -1.2649, -
1.2649)
x2=(xA1,xB2,xC2,xD2)=(0.8,180,0.75,22) → (- 1.2649, -0.6325, -0.6325, -
0.6325)...
x25=(xA5,xB5,xC4,xD3)=(1.2,240,1.25,24) → (1.2649,1.2649,0.6325,0)
Wherein, an intermediate Xiang Weiyuan numerical value, behind one to pass through the numerical value after step S40 normalized.
It can be obtained according to the test result of table 1
By formula γij=| | xi-xj| | (i, j=1,2 ..., m)
,
By formula
,
It is acquired by formula coefficient matrix formula (13)
η=[5.6349 0.1019 1.8874 0.3990 3.1221 1.7063-1.5206 1.1746 1.0306
0.7666 4.5323 -0.2552 -0.0684 -0.4471 0.4092 0.6526 -0.3195 -0.6325
-0.4513 -1.0250 2.1023 1.8729 -0.6122 -0.3890 -0.2564]-1
After finding out η, that is, it can determine V-arrangement free bending springback angle prediction model f (x)=A η, the square that the η is 25 × 1
Battle array.
Need to illustrate when, using radial basis function approximate model (bending springback angle prediction model) to plate material to rebound carry out
Prediction, radial basis function model is different with the difference of used kernel function form, and flexibility is good, and structure is simple, calculation amount
Relatively fewer and efficiency is higher.
It executes step S70, several sample points is separately taken to carry out experimental verification and essence to the radial basis function approximate model of foundation
Degree assessment.
Specifically, in the present embodiment, in order to verify foundation approximate model accuracy and guarantee approximate model
Validity, separately takes 7 sample points (being shown in Table 2), on the one hand carries out the emulation of ABAQUS finite element Form springback, is on the other hand cooperating
Anhui Donghai Machine Tool Co., Ltd., enterprise carries out practical bending, material selection galvanized steel plain sheet, according to mechanical design handbook (the
Four editions), springform measures 206GPa, and bending angle α is 90 °, and Practical Project value (springback angle of actual processing procedural test) has
It limits first analogue simulation value (springback angle of finite element simulation simulation) and receptance function predicted value (is returned using the above-mentioned bending of the present embodiment
Play the springback angle of angle prediction model prediction) as shown in table 3, wherein error angle refers to that Practical Project value and receptance function are predicted
The differential seat angle of value.
2 accuracy evaluation sample point of table
Table 3 springs back experiment value, analogue simulation value and radial basis function predicted value
Note: "-" indicates that experiment condition is unsatisfactory for, and can not measure experiment value.
It should be noted that using the above-mentioned bending springback angle prediction model of the present embodiment come springback angle when, need first basis
The data of each sample point are normalized in S40 identical step, reuse the value progress springback angle after normalization
Prediction.
Common approximate model error evaluation index has following two:
(1) coefficient of determination R2
R2Value range in [0,1].
(2) opposite root-mean-square error (root mean squared error, RMSE)
RSME indicates the difference degree between true value and response surface.
Wherein, yiResponse (the Practical Project value in table 3) or 3 finite element simulation of the table simulation obtained for actual experimental
Value,It is the value (the receptance function predicted value in table 3) being calculated according to the approximate model established,It is rung for actual experimental
The mean value that should be worth, k refer to the number for the sample point that verifying model separately takes.
Above-mentioned approximate model evaluation index has certain correlation, in general, RSME is closer to 0, R2It is closer
In 1, illustrate that the precision of approximate model is higher, fitting effect is also better.
Using formula (15) and formula (16), the approximate model of the present embodiment under ABAQUS finite element software platform can be obtained
The results are shown in Table 4 for accuracy evaluation, the approximate model accuracy evaluation under Anhui Donghai Machine Tool Co., Ltd.'s experiment porch
The results are shown in Table 5.
4 approximate model accuracy evaluation table of table
5 approximate model accuracy evaluation table of table
Contrast table 4 and table 5, RSME is close to 0, R2All close to 1, due to the shadow by experimental field uncontrollable factor etc.
Ring, field experiment ratio of precision simulation software precision is slightly lower, but either ABAQUS finite element software emulation platform also
It is to carry out experimental verification in Anhui Donghai Machine Tool Co., Ltd., which all has preferable predictive ability.
A kind of bending springback compensation method is also disclosed in the present embodiment, and the bending springback compensation method includes: using basis
The bending springback angle prediction model of above-mentioned foundation predicts the free bending springback angle to bending workpieces (plate)；According to prediction
The free bending springback angle to bending workpieces finds out the volume under pressure offset of sliding block；With the volume under pressure offset to described
The volume under pressure of sliding block compensates；Controlled according to the volume under pressure of the compensated sliding block pushing of the sliding block of bending machine away from
From to complete the bending and molding to bending workpieces.
Specifically, in V-arrangement bending and forming, the bending angle of plate is realized by sliding block volume under pressure, so to rebound
The compensation of amount is also to be realized by the compensation to volume under pressure.Since the compensation rate to volume under pressure is relative to volume under pressure very little, institute
To set volume under pressure offset as Δ Y, then have
Wherein, Δ α is that plate surveys angle and programs the difference of angle.
It is available by the differential of doubling bent angle α in the calculation formula (5) of volume under pressure
In formula, the value of Δ α can be obtained directly by above-mentioned bending springback angle prediction model, at this time sliding block volume under pressure Yu
For
Yu=Y+ Δ Y (17)
Bending is carried out according to compensated sliding block volume under pressure.
A kind of free bending system is also disclosed in the present embodiment, and the free bending system includes: bending machine, has sliding block 3；
Control system, the control system are connected with the bending machine.Fig. 5 shows a kind of structural schematic diagram of bending machine, such as Fig. 5 institute
Show, the bending machine includes rack 1, hydraulic cylinder group 2, sliding block 3, workbench 6, servo motor 8, transmission mechanism 7 and back material stopping
9；The top of the rack 1 is symmetrically arranged with hydraulic cylinder group 2, and the movable end of the hydraulic cylinder group 2 is connected with sliding block 3, the cunning
Block 3 and the upper mold 4 of mold are connected and fixed, and the lower part of the rack 1 is provided with workbench 6, and the lower die 5 of the mold is fixed on institute
It states on workbench 6, for carrying to bending workpieces 10, the lower die 5 has V-shaped groove；Servo motor 8 is mounted on rack 1
Rear end, the back material stopping 9 by transmission mechanism 7 be connected and fixed on servo motor 8 treats bending workpieces carry out bending and molding
When, the control system controls the depression distance of the sliding block according to above-mentioned bending springback compensation method, to control lower die 5
Amount of feed, with complete to the bending and molding to bending workpieces.Specifically, pass through hydraulic cylinder group 2 when the control system
Group controls the volume under pressure of sliding block 3.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology all without departing from the spirit and scope of the present invention, carries out modifications and changes to above-described embodiment.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should be covered by the claims of the present invention.
Claims (10)
1. a kind of method for establishing bending springback angle prediction model characterized by comprising
Sliding block volume under pressure model is established for workpiece free bending process, to obtain the volume under pressure of unloading front-slider；
Orthogonal test table is designed, to obtain multiple testing programs, each experimental program is as a sample point；
Molding resilience sunykatuib analysis is carried out to each sample point using the volume under pressure of the sliding block before unloading, it is each to obtain
The numerical value of the corresponding springback angle of the sample point；
The data of each sample point are standardized；
Choose bending springback angle prediction model function；
It is found out according to the data of each sample point of standardization and the springback angle corresponding with each sample point
The weighting coefficient of the bending springback angle prediction model function, to complete the foundation of bending springback angle prediction model.
2. the method according to claim 1 for establishing bending springback angle prediction model, which is characterized in that test impact factor
For elasticity modulus, sheet thickness, upper mold radius of corner and lower die open width, test index is the springback angle.
3. the method according to claim 1 for establishing bending springback angle prediction model, which is characterized in that the cunning before unloading
The volume under pressure formula of block are as follows:
Wherein, W lower die open width, R are lower die radius of corner, and α is bending angle, and β is the V-arrangement angle of lower die V-shaped groove, and k is bending
Arc radius coefficient, ξ are workpiece ironing coefficient, and T is the sheet thickness of workpiece.
4. the method according to claim 1 for establishing bending springback angle prediction model, which is characterized in that each sample
The step of data of point are standardized includes being carried out using data of the Z-score standardized method to each sample point
Normalized.
5. the method according to claim 1 for establishing bending springback angle prediction model, which is characterized in that find out the bending
It after the weighting coefficient of springback angle prediction model function, further include separately taking several sample points to the radial basis function of foundation
Approximate model carries out the step of experimental verification and accuracy evaluation.
6. the method for bending springback angle prediction model is established described in -5 any one according to claim 1, which is characterized in that institute
Stating bending springback angle prediction model function includes radial basis function.
7. the method according to claim 6 for establishing bending springback angle prediction model, which is characterized in that the bending rebound
The basic function of angle prediction model function includes inverse more quadratic functions.
8. the method according to claim 6 for establishing bending springback angle prediction model, which is characterized in that the bending rebound
The expression formula of angle prediction model function is
Wherein, ηiFor i-th weighting coefficient, xiCoordinate for i-th of sample spot in design space, | | x-xi| | for x with
I-th of sample spot design space distance,For basic function, | | | | it is Euclidean Norm, m is the sample point
Number.
9. a kind of bending springback compensation method characterized by comprising
It is returned using the bending that the method according to any one of claims 1 to 8 for establishing bending springback angle prediction model is established
Angle prediction model is played to predict the free bending springback angle to bending workpieces；
Free bending springback angle according to prediction to bending workpieces finds out the volume under pressure offset of sliding block；
The volume under pressure of the sliding block is compensated with the volume under pressure offset；
The depression distance of the sliding block is controlled according to the volume under pressure of the compensated sliding block, it is described to bending workpieces to complete
Bending and molding.
10. a kind of free bending system characterized by comprising
Bending machine has sliding block；
Control system, the control system are connected with the bending machine；
When treating bending workpieces progress bending and molding, the control system bending springback compensation side according to claim 9
Method controls the depression distance of the sliding block, to complete to the bending and molding to bending workpieces.
Priority Applications (1)
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| CN113221398A (en) * | 2021-03-31 | 2021-08-06 | 成都飞机工业（集团）有限责任公司 | Method for predicting L-shaped composite material part curing deformation rebound angle |
| CN113540839A (en) * | 2021-06-22 | 2021-10-22 | 浙江创特新材科技有限公司 | Bent terminal wire and manufacturing method thereof |
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| CN113540839B (en) * | 2021-06-22 | 2023-09-15 | 浙江创特新材科技有限公司 | Bending terminal wire and manufacturing method thereof |
| CN113435089A (en) * | 2021-06-28 | 2021-09-24 | 江苏特威机床制造有限公司 | Plate bending resilience prediction method based on Gaussian process |
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