CN110532725A - The recognition methods of engineering structure mechanics parameter and system based on digital picture - Google Patents
The recognition methods of engineering structure mechanics parameter and system based on digital picture Download PDFInfo
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Abstract
Disclose a kind of recognition methods of engineering structure mechanics parameter and system based on digital picture.This method may include: step 1: calculate the calculation formula of related variation parameter；Step 2: according to displacement initial value and related variation parameter, calculating displacement exact value, obtain displacement field；Step 3: according to displacement field, displacement gradient being calculated by strain window algorithm；Step 4: according to displacement gradient, calculating strain field.The present invention compares the deformation data of the remaining image based on reference picture by analysis, realizes based on digital image understanding technology in the monitoring and early warning of the deformation of structural elements.
Description
Technical field
The present invention relates to engineering structures to monitor field, more particularly, to a kind of engineering structure power based on digital picture
Learn parameter identification method and system.
Background technique
In recent years, flourishing with China's construction business, construction scale constantly expands, and construction speed is maked rapid progress.
At the same time, structure generates the intensity and stability that biggish deformation will directly affect structure because of bearing load, produces engineering
Raw associated safety potential problem.It mostly uses theoretical analysis and calculation currently, routinely solving structure safety problem method in engineering and shows
Two kinds of testing inspection of field.The correlation values simulation wherein carried out with finite element theory is the Typical Representative of theoretical analysis and calculation,
But the design conditions that this method is arranged when calculating are mostly ideal stress, it is more difficult to by the actual complex stress condition of structural elements
It is simulated, thus the result obtained when numerical simulation analysis calculating is carried out to same structure component and is existed centainly with actual value
Deviation；And field test detection method is usually that its related mechanics parameter is directly measured and obtained to structure, result tool
There is higher confidence level.
Structure will generate certain deformation after bearing related load, therefore malformation measurement is in live structural test measurement
One main content of the test.It is directly contacted according to whether measuring instrument has with measured structure surface, it can be by relevant measurement method
It is divided into contact, contactless two classes measurement method.Wherein instrument with contacts is with displacement meter, sensor and foil gauge etc.
It represents, has many advantages, such as that easy to operate, direct measured data reliability that is strong, obtaining is higher, continued to use and developed always.Phase
It answers ground contactless measurement mostly to involve the various waves such as light wave using such as ultrasonic wave, electromagnetism to be detected, common instrument has entirely
It stands instrument, GPS, Ultrasonic Nondestructive instrument etc..And using this method can make up using contact measurement method be not suitable for high temperature,
The defect of the special operations environment such as radiation and corrosivity.Though this method can solve more Practical Project measurement problem, it is suitable
Still there is certain limitation with condition, range and precision etc..Therefore, it is necessary to develop a kind of engineering structure based on digital picture
Mechanics parameter recognition methods and system.
The information for being disclosed in background of invention part is merely intended to deepen the reason to general background technique of the invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Summary of the invention
The invention proposes a kind of recognition methods of engineering structure mechanics parameter and system based on digital picture, can lead to
The deformation data that the remaining image based on reference picture is compared in analysis is crossed, is realized based on digital image understanding technology in structural elements
Deformation monitoring and early warning.
According to an aspect of the invention, it is proposed that a kind of engineering structure mechanics parameter recognition methods based on digital picture.
The method may include: step 1: calculating the calculation formula of related variation parameter；Step 2: according to displacement initial value with it is described
Related variation parameter calculates displacement exact value, obtains displacement field；Step 3: according to the displacement field, by straining window algorithm meter
Calculate displacement gradient；Step 4: according to the displacement gradient, calculating strain field.
Preferably, the step 2 includes: step 201: determining and calculates sub-district, calculates normalized crosscorrelation method metric；Step
Rapid 202: according to the normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the seed point
Related variation parameter and displacement exact value；Step 203: it determines and is not calculated a little apart from the seed point apart from recently multiple, meter
It calculates and the multiple does not calculate a little corresponding related variation parameter；Step 204: label the smallest do not calculate of related variation parameter is a little
Seed point calculates the displacement exact value of the seed point；Step 205: determine apart from multiple seed points distance it is nearest it is multiple not
Point is calculated, step 203-204 is repeated；Step 206: repeating step 205, do not calculated a little until not including in the calculating sub-district.
Preferably, related variation parameter is calculated by formula (1):
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding seat of Q' after deformation
Mark, f and g are respectively the reference and present image gray-scale intensity function in designated position, fmIt is average for reference picture sub-district gray scale
Value, gmFor the average gray of current deformation pattern sub-district.
Preferably, the step 3 includes: to carry out least square plane fitting according to the displacement field, after obtaining noise reduction
Shift value；According to the shift value after the noise reduction, the displacement gradient is calculated.
Preferably, the displacement gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u
For the shift value in the direction x, v is the shift value in the direction y.
According to another aspect of the invention, it is proposed that a kind of engineering structure mechanics parameter based on digital picture identifies system
System, which is characterized in that the system includes: memory, is stored with computer executable instructions；Processor, the processor operation
Computer executable instructions in the memory execute following steps: step 1: calculating the calculation formula of related variation parameter；
Step 2: according to displacement initial value and the related variation parameter, calculating displacement exact value, obtain displacement field；Step 3: according to institute
Displacement field is stated, displacement gradient is calculated by strain window algorithm；Step 4: according to the displacement gradient, calculating strain field.
Preferably, the step 2 includes: step 201: determining and calculates sub-district, calculates normalized crosscorrelation method metric；Step
Rapid 202: according to the normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the seed point
Related variation parameter and displacement exact value；Step 203: it determines and is not calculated a little apart from the seed point apart from recently multiple, meter
It calculates and the multiple does not calculate a little corresponding related variation parameter；Step 204: label the smallest do not calculate of related variation parameter is a little
Seed point calculates the displacement exact value of the seed point；Step 205: determine apart from multiple seed points distance it is nearest it is multiple not
Point is calculated, step 203-204 is repeated；Step 206: repeating step 205, do not calculated a little until not including in the calculating sub-district.
Preferably, related variation parameter is calculated by formula (1):
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding seat of Q' after deformation
Mark, f and g are respectively the reference and present image gray-scale intensity function in designated position, fmIt is average for reference picture sub-district gray scale
Value, gmFor the average gray of current deformation pattern sub-district.
Preferably, the step 3 includes: to carry out least square plane fitting according to the displacement field, after obtaining noise reduction
Shift value；According to the shift value after the noise reduction, the displacement gradient is calculated.
Preferably, the displacement gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u
For the shift value in the direction x, v is the shift value in the direction y.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages are attached from what is be incorporated herein
It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing being incorporated herein and subsequent specific reality
It applies in mode and is stated in detail, the drawings and the detailed description together serve to explain specific principles of the invention.
Detailed description of the invention
Exemplary embodiment of the present is described in more detail in conjunction with the accompanying drawings, of the invention is above-mentioned and other
Purpose, feature and advantage will be apparent, wherein in exemplary embodiments of the present invention, identical reference label is usual
Represent same parts.
Fig. 1 shows the stream of the step of engineering structure mechanics parameter recognition methods according to the present invention based on digital picture
Cheng Tu.
Fig. 2 shows the schematic diagrames of Digital Image Correlation Method basic principle.
Fig. 3 shows the schematic diagram of live image acquisition according to an embodiment of the invention.
Fig. 4 shows the schematic diagram of the digital picture of acquisition according to an embodiment of the invention.
Fig. 5 a, Fig. 5 b, Fig. 5 c, Fig. 5 d, Fig. 5 e, Fig. 5 f respectively illustrate 1st second according to an embodiment of the invention-
The schematic diagram of 6th second Aberration nephogram.
Fig. 6 a, Fig. 6 b, Fig. 6 c, Fig. 6 d, Fig. 6 e, Fig. 6 f respectively illustrate 7th second according to an embodiment of the invention-
The schematic diagram of 12nd second Aberration nephogram.
Fig. 7 a, Fig. 7 b, Fig. 7 c, Fig. 7 d, Fig. 7 e, Fig. 7 f respectively illustrate the according to an embodiment of the invention 13rd
The schematic diagram of the Aberration nephogram of-the 18 second second.
Fig. 8 a, Fig. 8 b, Fig. 8 c, Fig. 8 d, Fig. 8 e, Fig. 8 f respectively illustrate the according to an embodiment of the invention 19th
The schematic diagram of the Aberration nephogram of-the 24 second second.
Fig. 9 a, Fig. 9 b, Fig. 9 c, Fig. 9 d, Fig. 9 e, Fig. 9 f respectively illustrate the according to an embodiment of the invention 25th
The schematic diagram of the Aberration nephogram of-the 30 second second.
Specific embodiment
The present invention will be described in more detail below with reference to accompanying drawings.Although showing the preferred embodiment of the present invention in attached drawing,
However, it is to be appreciated that may be realized in various forms the present invention and should not be limited by the embodiments set forth herein.On the contrary, providing
These embodiments are of the invention more thorough and complete in order to make, and can will fully convey the scope of the invention to ability
The technical staff in domain.
Fig. 1 shows the stream of the step of engineering structure mechanics parameter recognition methods according to the present invention based on digital picture
Cheng Tu.
In this embodiment, the engineering structure mechanics parameter recognition methods according to the present invention based on digital picture can wrap
It includes: step 1: calculating the calculation formula of related variation parameter；Step 2: according to displacement initial value and related variation parameter, calculating position
Exact value is moved, displacement field is obtained；Step 3: according to displacement field, displacement gradient being calculated by strain window algorithm；Step 4: according to position
Gradient is moved, strain field is calculated.
In one example, step 2 includes: step 201: determining and calculates sub-district, calculates normalized crosscorrelation method metric；
Step 202: according to normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the related variation ginseng of seed point
Number and displacement exact value；Step 203: determining and do not calculated a little apart from seed point apart from recently multiple, calculate multiple does not calculate a little
Corresponding related variation parameter；Step 204: label related variation parameter is the smallest not to be calculated a little as seed point, and seed point is calculated
Displacement exact value；Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat step 203-
204；Step 206: repeating step 205, do not calculated a little until calculating and not including in sub-district.
In one example, related variation parameter is calculated by formula (1):
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding seat of Q' after deformation
Mark, f and g are respectively the reference and present image gray-scale intensity function in designated position, fmIt is average for reference picture sub-district gray scale
Value, gmFor the average gray of current deformation pattern sub-district.
In one example, step 3 includes: to carry out least square plane fitting according to displacement field, the position after obtaining noise reduction
Shifting value；According to the shift value after noise reduction, displacement gradient is calculated.
In one example, displacement gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u
For the shift value in the direction x, v is the shift value in the direction y.
Specifically, Digital Image Correlation Method has inexpensive, non-contact, complete as a kind of novel optical measurement method
Field property, is easy to implement the advantages of automation at high-precision, and more and more attention has been paid to also compensate for current civil engineering structure deformation
The deficiency of traditional measurement method in measurement.
Digital Image Correlation Method (Digital Image Correlation Method, abbreviation DICM) also known as counts
Word speckle correlation technique (Digital Speckle Correlation Method, abbreviation DSCM) is a kind of based on computer
With Digital image technology deformation measurement method.This method is by the speckle image of surface of test piece under record different conditions, with being based on
The correlation matching algorithm of image grayscale tracks out the position of surface of test piece point-of-interest in the picture, to obtain different conditions
The relative deformation information of lower surface of test piece.
Digital Image Correlation Method processing is the two width digital pictures for deforming front and back and recording, usually by the number before deformation
Image is known as " reference picture ", and deformed digital picture is known as " present image ".
In the DIC algorithm based on sub-district, reference picture is divided into the smaller area of sub-district or child window, and assumes every
Deformation inside a sub-district is uniformly, the son to have deformed corresponding with reference picture word then to be found in present image
Area.
Fig. 2 shows the schematic diagrames of Digital Image Correlation Method basic principle.
In calculating, sub-district is initially a continuous circular dot group, they are in the integer pixel positions of reference picture.
As shown in Fig. 2, reference picture sub-district has chosen with unknown point P (x0,y0) centered on (2N+1) × (2N+1) pixel coverage put
Rectangular area S, and the displacement of image subsection central point horizontal direction is u after deformation, is vertically v to shift value.When deformation pattern sub-district
Occur translation, stretch, the related variations such as compression when, the P point in reference picture sub-district deforms the P' become in deformation pattern
Point, it is as follows that deformation moves forward and backward corresponding relationship:
P={ u v ux uy vx vy}T (4)
Coordinate value (the x of initial reference image sub-district center P in above formula (3)0,y0), the seat of image subsection midpoint P' after deformation
Scale value (x0',y0').S is the set comprising all sub-district points in formula (3), and Δ x, Δ y are for indicating point relative in sub-district
The relative position of the heart, and establish the corresponding relationship in present image and reference picture between sub-district point.
Formula (4) then defines the broad sense deformation vector P of deformation front and back image subsection location and shape variation；ux、uy、vxAnd
vyIt for displacement components u, the partial derivative of v, while being the displacement gradient parameter of reference picture sub-district, for given sub-district, all parameters
Numerical value is all constant.Formula (3) can also be write with matrix form:
ξ is the enhancing vector comprising sub-district point and coordinate x, y in above formula, and Δ x and Δ y are Q in sub-district (or Q') points
The distance between sub-district center P (or P') point, w is a warp function.
In order to improve computational efficiency, and reach the calculating speed requirement of subsequent inverse matching algorithm, sets the son of reference picture
Area can deform in the picture, as follows:
The coordinate of initial reference image sub-district any point Q is in above formulaWithIt is reference picture of deformation
The coordinate value of Q point in area, the coordinate of Q' point areur、vrAlong x-axis, y both when for Q, Q' being placed in same image subsection
The distance of axis.Coordinate transform is carried out between two different coordinates in a reference image in formula (6).
The basic principle of images match be before being deformed after on associated picture, by comparing the size centered on two points
The correlation of the pixel RGB color of identical block of pixels image subsection, to differentiate whether they are identical point.It is compared herein
Relative coefficient be DIC algorithm when using related search method, be calculated by the correlation function introduced.This method uses
Two different correlation functions search initial value and carry out subsequent refinement to it.Initial value is by calculating normalizing in integer pixel positions
The correlation (NCC) for changing cross-correlation function obtains.
Engineering structure mechanics parameter recognition methods according to the present invention based on digital picture may include:
Step 1: the calculation formula of related variation parameter is calculated by formula (1)；
Step 2: according to displacement initial value and related variation parameter, calculating displacement exact value, obtain displacement field；Specific packet
It includes:
Step 201: it determines and calculates sub-district, calculate normalized crosscorrelation method metric by formula (7):
Function f and g are the reference and present image gray-scale intensity function in designated position, function f respectivelymFor reference picture
Sub-district average gray, gmFor the average gray of current deformation pattern sub-district:
N (S) is the quantity of the data point in sub-district S in above formula.What it is due to digital image recording is discrete grey's information, benefit
It is to be carried out with pixel whole in sub-district for search unit when carrying out relevant search with the correlation function of formula (7).Acquired results are
Rough whole pixel displacement will use non-linear optimizer by searching for most in next step to reach accurate displacement measurement
Small correlated condition come optimize these with subpixel resolution as a result, the result by CccAnd CLSTwo parameter larger impact.
Step 202: according to normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the phase of seed point
Close deformation parameter and displacement exact value；Step 203: determining and do not calculated a little apart from seed point apart from recently multiple, calculated multiple
A little corresponding related variation parameter is not calculated；Step 204: label related variation parameter is the smallest not to be calculated a little as seed point, meter
Calculate the displacement exact value of seed point；Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat to walk
Rapid 203-204；Step 206: repeating step 205, do not calculated a little until calculating and not including in sub-district.
Step 3: least square plane fitting being carried out according to displacement field, the shift value after obtaining noise reduction are as follows:
According to the shift value after noise reduction, displacement gradient is calculated by formula (2)；
Step 4: according to displacement gradient, calculating strain field, those skilled in the art can select to calculate as the case may be and answer
The method of variable field.
This method compares the deformation data of the remaining image based on reference picture by analysis, realizes and is known based on digital picture
The monitoring and early warning of deformation of the other technology in structural elements.
Using example
A concrete application example is given below in the scheme and its effect of the embodiment of the present invention for ease of understanding.This field
It should be understood to the one skilled in the art that the example is only for the purposes of understanding the present invention, any detail is not intended to be limited in any way
The system present invention.
Engineering structure mechanics parameter recognition methods according to the present invention based on digital picture may include:
Step 1: the calculation formula of related variation parameter is calculated by formula (1)；
Step 2: according to displacement initial value and related variation parameter, calculating displacement exact value, obtain displacement field；Specific packet
It includes:
Step 201: determining and calculate sub-district, calculate normalized crosscorrelation method metric by formula (7)；Reference picture sub-district
Average gray fmFor formula (8), the average gray g of current deformation pattern sub-districtmFor formula (9).Due to digital image recording
Be discrete grey's information, be single for search with pixel whole in sub-district when carrying out relevant search using the correlation function of formula (7)
What position carried out.Acquired results are that rough whole pixel displacement will use non-thread in next step to reach accurate displacement measurement
Property optimizer optimizes these results with subpixel resolution by searching for minimum correlated condition.
Step 202: according to normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the phase of seed point
Close deformation parameter and displacement exact value；Step 203: determining and do not calculated a little apart from seed point apart from recently multiple, calculated multiple
A little corresponding related variation parameter is not calculated；Step 204: label related variation parameter is the smallest not to be calculated a little as seed point, meter
Calculate the displacement exact value of seed point；Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat to walk
Rapid 203-204；Step 206: repeating step 205, do not calculated a little until calculating and not including in sub-district.
Step 3: least square plane fitting being carried out according to displacement field, the shift value after obtaining noise reduction is formula (10)-
(11), according to the shift value after noise reduction, displacement gradient is calculated by formula (2).
Step 4: according to displacement gradient, calculating strain field.
It is introduced by taking overhead bridge structure bottom plate monitoring data as an example.Field monitoring is carried out to operation phase Light Railway Bridge,
And corresponding calculating is expanded according to the related data of acquisition.The initial data of collection in worksite need to carry out Digital Image Correlation Method
It calculates, image could be converted to identifiable in engineering as a result, this section will be with measuring point acquisition immediately below the bottom plate of diameter river direction
It is calculated for bottom plate image when surface track train is current.
Fig. 3 shows the schematic diagram of live image acquisition according to an embodiment of the invention.
Fig. 4 shows the schematic diagram of the digital picture of acquisition according to an embodiment of the invention.
From the figure 3, it may be seen that the image capture position region direction x is parallel with sole-plate axis, the direction y is the cross of sole-plate
Cross-wise direction, while the direction x, y corresponds respectively to the horizontal and vertical direction of the digital picture acquired, the digital picture of acquisition is such as
Shown in Fig. 4.
Fig. 5 a, Fig. 5 b, Fig. 5 c, Fig. 5 d, Fig. 5 e, Fig. 5 f respectively illustrate 1st second according to an embodiment of the invention-
The schematic diagram of 6th second Aberration nephogram.
Fig. 6 a, Fig. 6 b, Fig. 6 c, Fig. 6 d, Fig. 6 e, Fig. 6 f respectively illustrate 7th second according to an embodiment of the invention-
The schematic diagram of 12nd second Aberration nephogram.
Fig. 7 a, Fig. 7 b, Fig. 7 c, Fig. 7 d, Fig. 7 e, Fig. 7 f respectively illustrate the according to an embodiment of the invention 13rd
The schematic diagram of the Aberration nephogram of-the 18 second second.
Fig. 8 a, Fig. 8 b, Fig. 8 c, Fig. 8 d, Fig. 8 e, Fig. 8 f respectively illustrate the according to an embodiment of the invention 19th
The schematic diagram of the Aberration nephogram of-the 24 second second.
Fig. 9 a, Fig. 9 b, Fig. 9 c, Fig. 9 d, Fig. 9 e, Fig. 9 f respectively illustrate the according to an embodiment of the invention 25th
The schematic diagram of the Aberration nephogram of-the 30 second second.
As seen from the figure, what Digital Image Correlation Method software calculated is the pixel deformation of image, to the pixel for calculating image
Size converts with actual test area size, can make to calculate output result deformation unit rice.It deforms within 1st second to the 8th second
Constant interval is -2 × 10-4M to 1.5 × 10-4M, the 9th second deformation constant interval are (- 4.5 × 10-4~0) m, since the 9th second
Amplitude is gradually increased the section amplitude within the 13rd second to 17 second period and reaches (- 3 × 10-3~-0.5 × 10-3) m deformation peak
Value, 8 second datas are significantly increased earlier above.After be gradually reduced, at the 23rd second deform section restore to (- 5 × 10-4~0) m, with
9th second identical, and latter 7 seconds deformation sections are (- 4 × 10-4~-1.5 × 10-4) m, it is close within the same 8 seconds.
The discovery of cloud atlas scale is observed, preceding 8 seconds cloud atlas scale greatest measure is maintained at positive value state, the 9th second beginning cloud atlas mark
It is negative value that ruler greatest measure, which becomes the 0, the 10th second to the 22nd second greatest measure, and it is maximum to become 0 subsequent recovery again again in 23 seconds
Value is positive state of value.In conjunction with on-the-spot record situation, at the 9th second, light rail train enters bridge pier in front of measuring point, and the 21st second when leaves this
The rear bridge pier of measuring point, overall process clock for 12 seconds.On-the-spot record situation confirms cloud atlas changed 9th second to the 22nd second
Reason, be by train passage caused by.Above situation confirms that Digital-image correlation method method is in the application of engineering component
Measurement feasible, that structural elements is deformed by bearing load can be identified and be calculated by digital picture.
In conclusion the present invention compares the deformation data of the remaining image based on reference picture by analysis, realization is based on
Digital image understanding technology is in the monitoring and early warning of the deformation of structural elements.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
According to an embodiment of the invention, a kind of engineering structure mechanics parameter identifying system based on digital picture is provided,
It is characterized in that, the system includes: memory, it is stored with computer executable instructions；Processor, described in processor operation
Computer executable instructions in memory execute following steps: step 1: calculating the calculation formula of related variation parameter；Step
2: according to displacement initial value and related variation parameter, calculating displacement exact value, obtain displacement field；Step 3: according to displacement field, leading to
Overstrain window algorithm calculates displacement gradient；Step 4: according to displacement gradient, calculating strain field.
In one example, step 2 includes: step 201: determining and calculates sub-district, calculates normalized crosscorrelation method metric；
Step 202: according to normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate the related variation ginseng of seed point
Number and displacement exact value；Step 203: determining and do not calculated a little apart from seed point apart from recently multiple, calculate multiple does not calculate a little
Corresponding related variation parameter；Step 204: label related variation parameter is the smallest not to be calculated a little as seed point, and seed point is calculated
Displacement exact value；Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat step 203-
204；Step 206: repeating step 205, do not calculated a little until calculating and not including in sub-district.
In one example, related variation parameter is calculated by formula (1):
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding seat of Q' after deformation
Mark, f and g are respectively the reference and present image gray-scale intensity function in designated position, fmIt is average for reference picture sub-district gray scale
Value, gmFor the average gray of current deformation pattern sub-district.
In one example, step 3 includes: to carry out least square plane fitting according to displacement field, the position after obtaining noise reduction
Shifting value；According to the shift value after noise reduction, displacement gradient is calculated.
In one example, displacement gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u
For the shift value in the direction x, v is the shift value in the direction y.
This system compares the deformation data of the remaining image based on reference picture by analysis, realizes and is known based on digital picture
The monitoring and early warning of deformation of the other technology in structural elements.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.
Claims (10)
1. a kind of engineering structure mechanics parameter recognition methods based on digital picture characterized by comprising
Step 1: calculating the calculation formula of related variation parameter；
Step 2: according to displacement initial value and the related variation parameter, calculating displacement exact value, obtain displacement field；
Step 3: according to the displacement field, displacement gradient being calculated by strain window algorithm；
Step 4: according to the displacement gradient, calculating strain field.
2. the engineering structure mechanics parameter recognition methods according to claim 1 based on digital picture, wherein the step
2 include:
Step 201: determining and calculate sub-district, calculate normalized crosscorrelation method metric；
Step 202: according to the normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate described kind
The related variation parameter and displacement exact value of son point；
Step 203: determining and do not calculated a little apart from the seed point apart from recently multiple, calculating is the multiple not to calculate a correspondence
Related variation parameter；
Step 204: label related variation parameter is the smallest not to be calculated a little for seed point, and the displacement for calculating the seed point is accurate
Value；
Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat step 203-204；
Step 206: repeating step 205, do not calculated a little until not including in the calculating sub-district.
3. the engineering structure mechanics parameter recognition methods according to claim 1 based on digital picture, wherein pass through formula
(1) related variation parameter is calculated:
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding coordinate of Q' after deformation, f
With reference and present image gray-scale intensity function that g is respectively in designated position, fmFor reference picture sub-district average gray, gm
For the average gray of current deformation pattern sub-district.
4. the engineering structure mechanics parameter recognition methods according to claim 1 based on digital picture, wherein the step
3 include:
Least square plane fitting is carried out according to the displacement field, the shift value after obtaining noise reduction；
According to the shift value after the noise reduction, the displacement gradient is calculated.
5. the engineering structure mechanics parameter recognition methods according to claim 1 based on digital picture, wherein the displacement
Gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u is the side x
To shift value, v be the direction y shift value.
6. a kind of engineering structure mechanics parameter identifying system based on digital picture, which is characterized in that the system includes:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Step 1: calculating the calculation formula of related variation parameter；
Step 2: according to displacement initial value and the related variation parameter, calculating displacement exact value, obtain displacement field；
Step 3: according to the displacement field, displacement gradient being calculated by strain window algorithm；
Step 4: according to the displacement gradient, calculating strain field.
7. the engineering structure mechanics parameter identifying system according to claim 6 based on digital picture, wherein the step
2 include:
Step 201: determining and calculate sub-district, calculate normalized crosscorrelation method metric；
Step 202: according to the normalized crosscorrelation method metric, determining the seed point for calculating sub-district, calculate described kind
The related variation parameter and displacement exact value of son point；
Step 203: determining and do not calculated a little apart from the seed point apart from recently multiple, calculating is the multiple not to calculate a correspondence
Related variation parameter；
Step 204: label related variation parameter is the smallest not to be calculated a little for seed point, and the displacement for calculating the seed point is accurate
Value；
Step 205: determining and do not calculated a little apart from multiple seed points apart from recently multiple, repeat step 203-204；
Step 206: repeating step 205, do not calculated a little until not including in the calculating sub-district.
8. the engineering structure mechanics parameter identifying system according to claim 6 based on digital picture, wherein pass through formula
(1) related variation parameter is calculated:
Wherein, CLSFor related variation parameter,For the coordinate of any point Q,For the corresponding coordinate of Q' after deformation, f
With reference and present image gray-scale intensity function that g is respectively in designated position, fmFor reference picture sub-district average gray, gm
For the average gray of current deformation pattern sub-district.
9. the engineering structure mechanics parameter identifying system according to claim 6 based on digital picture, wherein the step
3 include:
Least square plane fitting is carried out according to the displacement field, the shift value after obtaining noise reduction；
According to the shift value after the noise reduction, the displacement gradient is calculated.
10. the engineering structure mechanics parameter identifying system according to claim 6 based on digital picture, wherein institute's rheme
Move gradient are as follows:
Wherein, ExxFor the displacement gradient in the direction x, ExyFor the displacement gradient in the direction xy, EyyFor the displacement gradient in the direction y, u is the side x
To shift value, v be the direction y shift value.
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