CN105403469B - A kind of thermal parameter recognition methods based on affine transformation best match image - Google Patents
A kind of thermal parameter recognition methods based on affine transformation best match image Download PDFInfo
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- CN105403469B CN105403469B CN201510778335.0A CN201510778335A CN105403469B CN 105403469 B CN105403469 B CN 105403469B CN 201510778335 A CN201510778335 A CN 201510778335A CN 105403469 B CN105403469 B CN 105403469B
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Abstract
The application discloses a kind of thermal parameter recognition methods based on affine transformation best match image, including makes high-temperature speckle test specimen, and test specimen to be measured is fixed on 3 points of curved testing machines, acquires the speckle image before test piece deformation；Apply heating power load, acquires the speckle image after test piece deformation；Calibration region is chosen on speckle image before being deformed, completes the calibration of unit pixel physical length；Zoning is chosen on speckle image before being deformed, is that iteration initial value is arranged in amount to be optimized with thermal parameter to be measured；Affine transformation is carried out to deformed speckle image, obtains image before structural deformation；Image and the speckle image before deformation, treat the optimization of calorimetric force parameter subsequent iteration before matching construction deformation；Setting terminates iteration threshold, and iteration is terminated according to iteration threshold is terminated, and realizes image and the speckle image best match before deformation before structural deformation；It measures and excludes rigid body translation, rotation, while identifying the thermal parameter for including elasticity modulus, Poisson's ratio and coefficient of thermal expansion.
Description
Technical field
This application involves Experimental Mechanics high temperature field of measuring technique, specifically, being related to one kind being based on affine transformation most
The thermal parameter recognition methods of good matching image.
Background technology
The elasticity modulus of high-temperature material and Poisson's ratio measurement are mainly completed by tensile test at high temperature at present.It is warming up to
Predetermined value obtains elasticity modulus and pool to sample simple tension, record load capacity and measurement material draw direction and transverse strain
Loose ratio.Coefficient of thermal expansion is mainly measured by being warming up to the strain of predetermined value record.Conventional method heating power parameter must divide
Measurement is opened, needs to repeat to heat up, tedious process is of high cost
The patent CN103018111A that Yao Xuefeng is equal to invention in 2012 proposes to measure high temperature simultaneously based on virtual displacement field method
The method of elasticity modulus of materials, Poisson's ratio and coefficient of thermal expansion.But this method needs third party's digital picture related software to support
It obtains material deformation and moves forward and backward a strain field；It needs to have professional knowledge personnel and builds virtual displacement field, be further processed；
In view of there are rigid motions for practical operation, error can be introduced in the case where being not excluded for rigid body translation；Calculating process is cumbersome, consumption
Shi Duo.Therefore, easy to operate, third party software support is not needed, considers practical operation rigid body translation that may be present, processing speed
Measuring technique urgently proposes the heating power parameter of degree fast (＜ 10s) simultaneously.
Invention content
In view of this, there is provided one kind being based on affine transformation best match image for technical problems to be solved in this application
Thermal parameter recognition methods, it is easy to operate, do not need third party software support, consider that practical operation rigid body that may be present is flat
Dynamic, processing speed is fast.
In order to solve the above-mentioned technical problem, the application has following technical solution：
A kind of thermal parameter recognition methods based on affine transformation best match image, which is characterized in that including：
High-temperature speckle test specimen is made, the high-temperature speckle made test specimen to be measured is fixed on to 3 points of curved examinations with high-temperature cabinet
It tests on machine, acquires the speckle image a before the test piece deformation to be measured；
Apply heating power load, acquires the deformed speckle image b of test specimen to be measured；
Calibration region is chosen on speckle image a before being deformed, completes the calibration of unit pixel physical length；
Zoning is chosen on speckle image a before being deformed, with thermal parameter to be measured for amount to be optimized, at the beginning of iteration is set
Initial value p0：
p0=[U, V, θ, E, v, α]0
Wherein, U and V is translatable for rigid body, and θ is Rigid Body in Rotation With, and E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion；
Affine transformation is carried out to deformed speckle image b, obtains image c before structural deformation；
The image c and speckle image a before the deformation before the structural deformation is matched, calorimetric force parameter subsequent iteration is treated
Optimization；Setting terminates iteration threshold, and iteration is terminated according to the terminations iteration threshold, realize before the structural deformation image c and
Speckle image a best match before the deformation；
Rigid body translation, Rigid Body in Rotation With are measured and exclude, it is primary to identify simultaneously including elasticity modulus, Poisson's ratio and thermal expansion
The thermal parameter of coefficient.
Preferably, wherein it is described that affine transformation is carried out to deformed speckle image b, image c before structural deformation is obtained,
It is further：
Affine transformation is carried out to deformed speckle image b according to following equation, obtains image c before structural deformation：
x*=x+U+Uθ(θ, x, y)+Uf(E, v, x, y)+Ut(α, x, y)
y*=y+V+Vθ(θ, x, y)+Vf(E, v, x, y)+Vt(α, x, y)
Ut(α, x, y)=Δ T α x
Vt(α, x, y)=Δ T α y
Uθ(θ, x, y)=- θ y
Vθ(θ, x, y)=θ x
Wherein, x and y is the coordinate in speckle point after deformation image b, x*And y*For speckle point image c before structural deformation
In coordinate, U and V are rigid body translation, UθAnd VθFor Rigid Body in Rotation With, UfAnd VfFor power deformation under load, E, v be elasticity modulus of materials,
Poisson's ratio, UtAnd VtIt is deformed for thermal force, α is material thermal expansion coefficient, and f is 3 points of curved load, and Δ T is sweat box heating degree；
G is material modulus of shearing, is acquired by E, v；EI is test specimen bending stiffness, is acquired by sample dimensions and elasticity modulus.
Preferably, wherein the image c and speckle image a before the deformation before the matching structural deformation, to be measured
Thermal parameter subsequent iteration optimize, further for：
According to following equation, the image c and speckle image a before the deformation before the structural deformation is matched, calorimetric is treated
Force parameter subsequent iteration optimizes：
pk+1=pk+Δp
Wherein, Δ p is+1 iteration of kth parameter increment to be measured；J (x, y) is ash at (x, y) in image c before structural deformation
Angle value；I (x, y) is gray value at (x, y) in image a before original deformation；piIt is excellent to wait for
Change parameter i-th of component of p；pk+1For the K+1 times iteration optimization parameter value.
Preferably, wherein the setting terminates iteration threshold, further for：
Setting terminates iteration correlation coefficient threshold C0：
|C(pk+1)-C(pk) | ＜ C0
Wherein, C (pk+1) it is to construct not deformed image c and original not deformed+1 iteration related coefficient of image a kth；J
(x*, y*) it is to construct (x in not deformed image c*, y*) at gray value；I (x, y) is gray scale at (x, y) in original not deformed image a
Value；pk+1For+1 iteration measurement result of kth；C(pk) it is image c and image a before original deformation before kth time iterative construction deformation
Related coefficient；C(pk+1) it is image c and image a related coefficients before original deformation before+1 iterative construction deformation of kth；C0To terminate
Iteration correlation coefficient threshold.
Preferably, wherein the measurement simultaneously excludes rigid body translation, Rigid Body in Rotation With, primary to identify simultaneously including springform
Amount, the thermal parameter of Poisson's ratio and coefficient of thermal expansion are：
P=pk+1=[U, V, θ, E, v, α]k+1
Wherein, p is parameter to be optimized, pk+1For the K+1 times iteration optimization parameter value, U and V are translatable for rigid body, and θ is rigid body
Rotation, E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion.
Preferably, wherein the speckle pattern of surface of test piece is acquired using the monochromation illumination harvester of vertical surface of test piece,
The harvester includes monochromatic light source, doubly telecentric camera lens, the monochromatic light optical filter and CCD consistent with light source colour.
Compared with prior art, method described herein has reached following effect：
First, compared with conventional heat parameter measurement, the present invention measures elastic properties of materials mould simultaneously by a hot test
Amount, Poisson's ratio and coefficient of thermal expansion reduce repetition heating cost.
Second, compared with patent CN103018111A, the pretreatment that the present invention does not need third party's digital imaging software dissipates
Spot figure can be obtained displacement field strain field.
Third, the present invention are easy to operate, it is only necessary to which layman inputs sample dimensions, at the beginning of testing heating power load and iteration
Value chooses calibration region and zoning, you can start to calculate and export thermal parameter recognition result.
4th, recognition speed of the present invention is fast.During whole identification process are integrated in digital image analysis by the present invention, save
Remove the professional operations such as third party software pre-treatment and structure virtual displacement field.
5th, the present invention considers to be translatable in the rigid body face of test specimen in heating power load loading procedure, and rotation can be surveyed accurately
It measures and excludes；Using doubly telecentric camera lens, error caused by rigid body off-plane movement is eliminated, reduces systematic error type.
Description of the drawings
Attached drawing described herein is used for providing further understanding of the present application, constitutes part of this application, this Shen
Illustrative embodiments and their description please do not constitute the improper restriction to the application for explaining the application.In the accompanying drawings：
Fig. 1 is the flow chart of the thermal parameter recognition methods based on affine transformation best match image in the present invention；
Fig. 2 is affine transformation best match image method illustraton of model in the present invention in the present invention；
Fig. 3 is Principle of Affine Transformation figure in the present invention；
Fig. 4 is the selection schematic diagram of calibration region, zoning in the present invention；
Fig. 5 is the flow of the thermal parameter recognition methods based on affine transformation best match image in the embodiment of the present invention 3
Figure.
Specific implementation mode
Some vocabulary has such as been used to censure specific components in specification and claim.Those skilled in the art answer
It is understood that hardware manufacturer may call the same component with different nouns.This specification and claims are not with name
The difference of title is used as the mode for distinguishing component, but is used as the criterion of differentiation with the difference of component functionally.Such as logical
The "comprising" of piece specification and claim mentioned in is an open language, therefore should be construed to " include but do not limit
In "." substantially " refer in receivable error range, those skilled in the art can be described within a certain error range solution
Technical problem basically reaches the technique effect.In addition, " coupling " word includes any direct and indirect electric property coupling herein
Means.Therefore, if it is described herein that a first device is coupled to a second device, then representing the first device can directly electrical coupling
It is connected to the second device, or the second device indirectly electrically coupled through other devices or coupling means.Specification
Subsequent descriptions be implement the application better embodiment, so it is described description be for the purpose of the rule for illustrating the application,
It is not limited to scope of the present application.The protection domain of the application is when subject to appended claims institute defender.
Embodiment 1
Shown in Figure 1 is a kind of herein described thermal parameter recognition methods based on affine transformation best match image
Specific embodiment, method described in the present embodiment includes the following steps：
Step 101 makes high-temperature speckle test specimen, and the high-temperature speckle made test specimen to be measured is fixed on high-temperature cabinet
On 3 points of curved testing machines, the speckle image a before the test piece deformation to be measured is acquired；
Step 102 applies heating power load, acquires the deformed speckle image b of test specimen to be measured；
Calibration region is chosen in step 103, speckle image a before being deformed, completes the calibration of unit pixel physical length；
Zoning is chosen in step 104, speckle image a before being deformed, with thermal parameter to be measured for amount to be optimized, if
Set iteration initial value p0：
p0=[U, V, θ, E, v, α]0
Wherein, U and V is translatable for rigid body, and θ is Rigid Body in Rotation With, and E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion；
Step 105 carries out affine transformation to deformed speckle image b, obtains image c before structural deformation；
The image c and speckle image a before the deformation before step 106, the matching structural deformation, treats calorimetric force parameter
Subsequent iteration optimizes；Setting terminates iteration threshold, iteration is terminated according to the termination iteration threshold, before realizing the structural deformation
Image c and the speckle image a best match before the deformation；
Step 107 measures and excludes rigid body translation, Rigid Body in Rotation With, primary to identify simultaneously including elasticity modulus, Poisson's ratio
With the thermal parameter of coefficient of thermal expansion.
In above-mentioned steps 105, affine transformation is carried out to deformed speckle image b, obtains image c before structural deformation, into
One step is：
Affine transformation is carried out to deformed speckle image b according to following equation, obtains image c before structural deformation：
x*=x+U+Uθ(θ, x, y)+Uf(E, v, x, y)+Ut(α, x, y)
y*=y+V+Vθ(θ, x, y)+Vf(E, v, x, y)+Vt(α, x, y)
Ut(α, x, y)=Δ T α x
Vt(α, x, y)=Δ T α y
Uθ(θ, x, y)=- θ y
Vθ(θ, x, y)=θ x
Wherein, x and y is the coordinate in speckle point after deformation image b, x*And y*For speckle point image c before structural deformation
In coordinate, U and V are rigid body translation, UθAnd VθFor Rigid Body in Rotation With, UfAnd VfFor power deformation under load, E, v be elasticity modulus of materials,
Poisson's ratio, UtAnd VtIt is deformed for thermal force, α is material thermal expansion coefficient, and f is 3 points of curved load, and Δ T is sweat box heating degree；
G is material modulus of shearing, is acquired by E, v；EI is test specimen bending stiffness, is acquired by sample dimensions and elasticity modulus.
In above-mentioned steps 106, the image c and speckle image a before the deformation before the matching structural deformation is treated
Calorimetric force parameter subsequent iteration optimize, further for：
According to following equation, the image c and speckle image a before the deformation before the structural deformation is matched, calorimetric is treated
Force parameter subsequent iteration optimizes：
pk+1=pk+Δp
Wherein, Δ p is+1 iteration of kth parameter increment to be measured；J (x, y) is ash at (x, y) in image c before structural deformation
Angle value；I (x, y) is gray value at (x, y) in image a before original deformation；piIt is excellent to wait for
Change parameter i-th of component of p；pk+1For the K+1 times iteration optimization parameter value.
In above-mentioned steps 106, the setting terminates iteration threshold, further for：
Setting terminates iteration correlation coefficient threshold C0：
|C(pk+1)-C(pk) | ＜ C0
Wherein, C (pk+1) it is to construct not deformed image c and original not deformed+1 iteration related coefficient of image a kth；J
(x*, y*) it is to construct (x in not deformed image c*, y*) at gray value；I (x, y) is gray scale at (x, y) in original not deformed image a
Value；pk+1For+1 iteration measurement result of kth；C(pk) it is image c and image a before original deformation before kth time iterative construction deformation
Related coefficient；C(pk+1) it is image c and image a related coefficients before original deformation before+1 iterative construction deformation of kth；C0To terminate
Iteration correlation coefficient threshold.
In above-mentioned steps 107, the measurement simultaneously excludes rigid body translation, Rigid Body in Rotation With, primary to identify simultaneously including elasticity
The thermal parameter of modulus, Poisson's ratio and coefficient of thermal expansion is：
P=pk+1=[U, V, θ, E, v, α]k+1
Wherein, p is parameter to be optimized, pk+1For the K+1 times iteration optimization parameter value, U and V are translatable for rigid body, and θ is rigid body
Rotation, E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion.
In the above method of the present invention, surface of test piece is acquired using the monochromation illumination harvester of vertical surface of test piece
Speckle pattern, the harvester include monochromatic light source, doubly telecentric camera lens, the monochromatic light optical filter consistent with light source colour
And CCD.
Embodiment 2
Below for a kind of Application Example based on the method for the present invention, including：
1) high-temperature speckle is made in 3 points of curved surface of test piece.Zirconium oxide mixed alcohol is uniformly sprayed at surface of test piece conduct
White substrate.Cobalt oxide mixed alcohol is uniformly sprayed in white substrate and is used as black speckle.
2) speckle image before and after acquisition test piece deformation to be measured.3 angle coupling heads of pressure experiment machine are put into the height with observation window
In incubator.Test specimen to be measured is fixed on 3 bending apparatus.It is acquired using the monochromation illumination harvester of vertical surface of test piece
The moment surface of test piece whole audience speckle pattern, as image a before deformation.Harvester includes monochromatic light source (such as green light light
Source), doubly telecentric camera lens, the monochromatic light optical filter consistent with light source colour, the CCD that vertical surface of test piece is placed.By high temperature
Case is warming up to Δ T, and a power f is loaded using the compression test in 3 bending apparatus, acquires the moment surface of test piece whole audience and dissipates
Spot figure, as image b after deformation.
3) calibration region is chosen on image a before being deformed, unit pixel actual (tube) length scale is completed according to test specimen actual size
It is fixed, referring to Fig. 4.The calibration result will be used in the structure of affine transformation power load displacement field.
4) zoning is chosen on image a before being deformed, as shown in figure 4, with thermal parameter to be measured for amount to be optimized, setting
Iteration initial value：
p0=[U, V, θ, E, v, α]0
Initial value includes rigid body translation U, V, Rigid Body in Rotation With θ, elastic modulus E, Poisson's ratio v, thermalexpansioncoefficientα.Wherein just
Body movement is disturbing factor in experimentation, needs to measure and exclude；Elasticity modulus, Poisson's ratio and coefficient of thermal expansion are ginseng to be measured
Number.
5) image c before structural deformation is obtained to image b affine transformations after deformation according to following design equation：
x*=x+U+Uθ(θ, x, y)+Uf(E, v, x, y)+Ut(α, x, y)
y*=y+V+Vθ(θ, x, y)+Vf(E, v, x, y)+Vt(α, x, y)
Ut(α, x, y)=Δ T α x
Vt(α, x, y)=Δ T α y
Uθ(θ, x, y)=- θ y
Vθ(θ, x, y)=θ x
Wherein, x and y is the coordinate in speckle point after deformation image b, x*And y*For speckle point image c before structural deformation
In coordinate, U and V are rigid body translation, UθAnd VθFor Rigid Body in Rotation With, UfAnd VfFor power deformation under load, E, v be elasticity modulus of materials,
Poisson's ratio, UtAnd VtIt is deformed for thermal force, α is material thermal expansion coefficient, and f is 3 points of curved load, and Δ T is sweat box heating degree；
G is material modulus of shearing, is acquired by E, v；EI is test specimen bending stiffness, is acquired by sample dimensions and elasticity modulus.
6) according to following design equation, image c and image a before original deformation before matching construction deformation treats calorimetric power ginseng
Number subsequent iteration optimization：
pk+1=pk+Δp
Wherein, Δ p is+1 iteration of kth parameter increment to be measured；J (x, y) is ash at (x, y) in image c before structural deformation
Angle value；I (x, y) is gray value at (xy) in image a before original deformation；piIt is excellent to wait for
Change parameter i-th of component of p；pk+1For the K+1 times iteration optimization parameter value.
7) according to following design equation, setting terminates iteration correlation coefficient threshold C0：
|C(pk+1)-C(pk) | ＜ C0
Wherein, C (pk+1) it is to construct not deformed image c and original not deformed+1 iteration related coefficient of image a kth；J
(x*, y*) it is to construct (x in not deformed image c*, y*) at gray value；I (x, y) is gray scale at (x, y) in original not deformed image a
Value；pk+1For+1 iteration measurement result of kth；C(pk) it is image c and image a before original deformation before kth time iterative construction deformation
Related coefficient；C(pk+1) it is image c and image a related coefficients before original deformation before+1 iterative construction deformation of kth；C0To terminate
Iteration correlation coefficient threshold.
For 5) 6) iterative process, iteration is terminated according to threshold value set by 7), realizes image c and original deformation before structural deformation
Preceding image a best match, Fig. 2 are affine transformation best match iconic model, and affine varied configurations thermal parameter is closest to really
Thermal parameter.Rigid body translation U, V, Rigid Body in Rotation With θ is measured to be removed side by side.Elasticity modulus of materials E, Poisson's ratio v and thermalexpansioncoefficientα
It is identified simultaneously：
P=pk+1=[U, V, θ, E, v, α]k+1
Embodiment 3
Fig. 2 is affine transformation best match iconic model.Use speckle before monochromation illumination and harvester acquisition deformation
(image a), applies heating power load to image 1, and the control of unknown material parameter 2 generates heating power deformation under load 3, forms image 4 after deformation
(image b).According to thermal parameter to be optimized, it is assumed that iterative initial value 5.Affine transformation 6 is completed according to iterative initial value, obtains constructing not
(the image c) of deformation pattern 7.Using Optimized Iterative algorithm to image before structural deformation, that is, construct not deformed image 7 (image c) and
(image a) is iterated optimization 8 to image 1, when realizing best match 9, exports 10 measurement result of thermal parameter before deformation.
Fig. 3 is Principle of Affine Transformation figure.The affine transformation displacement is translatable by rigid body and rotation 12, thermal expansion deformation 13,
The fields power displacement field V 14, the fields U 15 form.(image b) speckle field thermomechanicals move image 11, obtain construction and become after eliminating deformation
(image c) completes affine transformation 17 to image 16 before shape.
Fig. 4 is calibration region, zoning selection.Region 18 is demarcated according to its Pixel Dimensions and actual size ratio, mark
Make unit pixel actual size.Zoning 19 is slightly less than calibration region, and compartment is BORDER PROCESSING.
Fig. 5 is the thermal parameter recognition methods flow chart based on affine transformation best match image.Including：
Step 20, surface of test piece high-temperature speckle make.High-temperature speckle substrate is sprayed at using white oxide zirconium mixed alcohol
Surface of test piece is made, and high-temperature speckle is sprayed at white substrate surface using cobalt oxide mixed alcohol and is formed.
Step 21 acquires speckle image a before 3 points of curved test piece deformations using monochromation illumination and monochromatic opto-collection system.
Step 22 is warming up to Δ T, reinforces load f, collects speckle pattern b after test piece deformation.
Step 23 chooses calibration region on image before being deformed.
Step 24 chooses zoning on image before being deformed.
Step 25, setting iterative initial value.
Step 26, with iterative initial value to image b affine transformations after deformation, obtain image c before structural deformation.Step 27 makes
Whether reach best match with image before structural deformation with before the original deformation of correlation function evaluation.
Step 28, not up to best match replace iterative initial value in step 25 with iteration result, recycle next round iteration,
And so on, until reaching best match.
Step 29 reaches best match, heat outputting measurement of force result.
By the above various embodiments it is found that advantageous effect existing for the application is：
First, compared with conventional heat parameter measurement, the present invention measures elastic properties of materials mould simultaneously by a hot test
Amount, Poisson's ratio and coefficient of thermal expansion reduce repetition heating cost.
Second, compared with patent CN103018111A, the pretreatment that the present invention does not need third party's digital imaging software dissipates
Spot figure can be obtained displacement field strain field.
Third, the present invention are easy to operate, it is only necessary to which layman inputs sample dimensions, at the beginning of testing heating power load and iteration
Value chooses calibration region and zoning, you can start to calculate and export thermal parameter recognition result.
4th, recognition speed of the present invention is fast.During whole identification process are integrated in digital image analysis by the present invention, save
Remove the professional operations such as third party software pre-treatment and structure virtual displacement field.
5th, the present invention considers to be translatable in the rigid body face of test specimen in heating power load loading procedure, and rotation can be surveyed accurately
It measures and excludes；Using doubly telecentric camera lens, error caused by rigid body off-plane movement is eliminated, reduces systematic error type.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, apparatus or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, the application can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
Several preferred embodiments of the application have shown and described in above description, but as previously described, it should be understood that the application
Be not limited to form disclosed herein, be not to be taken as excluding other embodiments, and can be used for various other combinations,
Modification and environment, and the above teachings or related fields of technology or knowledge can be passed through in the scope of the invention is set forth herein
It is modified.And changes and modifications made by those skilled in the art do not depart from spirit and scope, then it all should be in this Shen
It please be in the protection domain of appended claims.
Claims (5)
1. a kind of thermal parameter recognition methods based on affine transformation best match image, which is characterized in that including：
High-temperature speckle test specimen is made, the high-temperature speckle made test specimen to be measured is fixed on to 3 points of curved testing machines with high-temperature cabinet
On, acquire the speckle image a before the test piece deformation to be measured；
Apply heating power load, acquires the deformed speckle image b of test specimen to be measured；
Calibration region is chosen on speckle image a before being deformed, completes the calibration of unit pixel physical length；
Zoning is chosen on speckle image a before being deformed, with thermal parameter to be measured for amount to be optimized, iteration initial value is set
p0：
p0=[U, V, θ, E, v, α]0
Wherein, U and V is translatable for rigid body, and θ is Rigid Body in Rotation With, and E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion；
Affine transformation is carried out to deformed speckle image b, obtains image c before structural deformation；
The image c and speckle image a before the deformation before the structural deformation is matched, it is excellent to treat calorimetric force parameter subsequent iteration
Change；Setting terminates iteration threshold, terminates iteration according to the termination iteration threshold, realizes image c and institute before the structural deformation
State the speckle image a best match before deformation；
Rigid body translation, Rigid Body in Rotation With are measured and exclude, it is primary to identify simultaneously including elasticity modulus, Poisson's ratio and coefficient of thermal expansion
Thermal parameter；
The image c and speckle image a before the deformation before the matching structural deformation, treats calorimetric force parameter subsequent iteration
Optimization, further for：
According to following equation, the image c and speckle image a before the deformation before the structural deformation is matched, calorimetric power ginseng is treated
Number subsequent iteration optimization：
pk+1=pk+Δp
Wherein, Δ p is+1 iteration of kth parameter increment to be measured；J (x, y) is gray value at (x, y) in image c before structural deformation；
I (x, y) is gray value at (x, y) in image a before original deformation；PiFor i-th of component of parameter p to be optimized；Pk+1It is the K+1 times
Iteration optimization parameter value.
2. a kind of thermal parameter recognition methods based on affine transformation best match image according to claim 1, feature
It is,
It is described to deformed speckle image b carry out affine transformation, obtain image c before structural deformation, further for：
Affine transformation is carried out to deformed speckle image b according to following equation, obtains image c before structural deformation：
x*=x+U+Uθ(θ, x, y)+Uf(E, v, x, y)+Ut(α, x, y)
y*=y+V+Vθ(θ, x, y)+Vf(E, v, x, y)+Vt(α, x, y)
Ut(α x, y)=Δ T α x
Vt(α, x, y)=Δ T α y
Uθ(θ, x, y)=- θ y
Vθ(θ, x, y)=θ x
Wherein, x and y is the coordinate in speckle point after deformation image b, x*And y*It is speckle point before structural deformation in image c
Coordinate, U and V are translatable for rigid body, UθAnd VθFor Rigid Body in Rotation With, UfAnd VfFor power deformation under load, E, v are elasticity modulus of materials, Poisson
Than UtAnd VtIt is deformed for thermal force, α is material thermal expansion coefficient, and f is 3 points of curved load, and Δ T is sweat box heating degree；G is
Material modulus of shearing is acquired by E, v；EI is test specimen bending stiffness, is acquired by sample dimensions and elasticity modulus.
3. a kind of thermal parameter recognition methods based on affine transformation best match image according to claim 1, feature
It is,
The setting terminates iteration threshold, further for：
Setting terminates iteration correlation coefficient threshold C0：
|C(pk+1)-C(pk) | ＜ C0
Wherein, C (pk+1) it is to construct not deformed image c and original not deformed+1 iteration related coefficient of image a kth；J(x*, y*)
To construct (x in not deformed image c*, y*) at gray value；I (x, y) is gray value at (x, y) in original not deformed image a；pk+1
For+1 iteration measurement result of kth；C(pk) it is image c and image a phase relations before original deformation before kth time iterative construction deformation
Number；C0To terminate iteration correlation coefficient threshold.
4. a kind of thermal parameter recognition methods based on affine transformation best match image according to claim 3, feature
It is,
The measurement simultaneously excludes rigid body translation, Rigid Body in Rotation With, primary to identify simultaneously including elasticity modulus, Poisson's ratio and thermal expansion
The thermal parameter of coefficient is：
P=pk+1=[U, V, θ, E, v, α]k+1
Wherein, p is parameter to be optimized, pk+1For the K+1 times iteration optimization parameter value, U and V are translatable for rigid body, and θ is Rigid Body in Rotation With,
E is elasticity modulus, and v is Poisson's ratio, and α is coefficient of thermal expansion.
5. according to a kind of any thermal parameter identification side based on affine transformation best match image of Claims 1 to 4
Method, which is characterized in that
The speckle pattern of surface of test piece is acquired using the monochromation illumination harvester of vertical surface of test piece, the harvester includes
Monochromatic light source, doubly telecentric camera lens, the monochromatic light optical filter and CCD consistent with light source colour.
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