Visual deformation measurement system based on monocular three dimensions

Abstract

A monocular three-dimensional-based visual deformation measurement system provided by the present invention comprises an integrated platform, the upper surface of the integrated platform is provided with an image acquisition assembly, a light splitting assembly, two groups of light reflecting assemblies and two groups of light supplementing lamps, the image acquisition assembly is arranged on the rear side of the light splitting assembly, and the two groups of light reflecting assemblies are arranged on the left and right sides of the light splitting assembly in a bilateral symmetry manner. The two light supplementing lamps are arranged on the sides, away from the light splitting assembly, of the two light reflecting assemblies correspondingly and rotationally connected to the upper surface of the integrated platform. Compared with a contact type strain gauge, three-dimensional full-field deformation and strain measurement can be achieved, and meanwhile the response speed is higher. Compared with a binocular three-dimensional DIC technology, the calibration difficulty is reduced, meanwhile, the demand quantity of CCD cameras is reduced, and the hardware cost is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of optical measurement experimental mechanics, and particularly to a visual deformation measurement system based on monocular three-dimensional. Background Art

[0002] With the vigorous development of the national industry, the detection of deformation in mechanical properties has become very popular. How to accurately and efficiently detect deformation is becoming more and more important. The detection of deformation can be applied to various material and structure tests. On the one hand, it is used to ensure the quality of products, and on the other hand, it is used to verify the rationality of material and structure designs. Especially in the military and scientific research fields, more and more materials and parts need to verify their mechanical properties through high-speed loading tests, and it is necessary to detect the deformation generated by the parts.

[0003] One of the traditional deformation measurement methods is the contact measurement method, which measures the deformation amount of materials through a contact strain gauge. However, it has poor accuracy, complex operation, and limited use scenarios, and can only provide measurement results in a single-dimensional direction, such as a contact strain gauge disclosed in the patent document with the publication number 201680056644.X.

[0004] Another method is the binocular three-dimensional DIC technology, which consists of a binocular image acquisition device and an optical path system that cooperates with the binocular three-dimensional DIC algorithm. This method can achieve three-dimensional strain measurement, but it has a complex structure. The camera, lens, and light source cannot be fixed, the light source is placed independently, and calibration is required every time it is used. The operation is complex and the test time is long, such as a three-dimensional DIC technology based on digital speckle disclosed in the patent document with the publication number CN 103575227A.

[0005] Now, there is a need for a device that can more efficiently and at a lower cost measure deformation and strain in high-speed loading tests. Summary of the Invention

[0006] The present invention provides a visual deformation measurement system based on monocular three-dimensional to solve the defect of an existing device that can more efficiently and at a lower cost measure deformation and strain in high-speed loading tests.

[0007] On the one hand, the present invention provides a visual deformation measurement system based on monocular three-dimensional, including an integration platform. An image acquisition component, a light splitting component, two groups of reflecting components, and two groups of supplementary lights are arranged on the upper surface of the integration platform. The image acquisition component is arranged behind the light splitting component. The two groups of reflecting components are symmetrically arranged on the left and right sides of the light splitting component. The two groups of supplementary lights are respectively arranged on the sides of the two groups of reflecting components away from the light splitting component, and the supplementary lights are rotatably connected to the upper surface of the integration platform.

[0008] Preferably, the image acquisition component includes a first XY-axis moving platform, which is fixedly connected to the upper surface of the integrated platform, and a ccd camera is installed on the upper surface of the first XY-axis moving platform.

[0009] Preferably, the beam splitting component includes a second XY-axis moving platform, which is fixedly connected to the upper surface of the integrated platform. A first rotating platform is rotatably connected to the upper surface of the second XY-axis moving platform, and a triangular prism is fixedly connected to the upper surface of the rotating platform.

[0010] Preferably, the reflecting component includes a third XY-axis moving platform, which is fixedly connected to the upper surface of the integrated platform. A second rotating platform is rotatably connected to the upper surface of the third XY-axis moving platform, and a reflecting lens is fixedly connected to the upper surface of the rotating platform.

[0011] Preferably, it further includes a measurement and calculation module, and the measurement and calculation module includes:

[0012] An image acquisition unit for acquiring the speckle image on the surface of the specimen;

[0013] A pixel feature recognition unit for identifying the feature points in the speckle image;

[0014] A region definition unit for dividing the speckle image into several feature regions according to the distribution of the feature points;

[0015] A parameter setting unit for setting the analysis parameters based on the experimental requirements;

[0016] A strain calculation unit for analyzing the speckle images during the loading process using the sub-pixel displacement measurement algorithm based on the set analysis parameters to obtain the three-dimensional strain distribution on the surface of the specimen.

[0017] Preferably, the analysis parameters include: the distribution of the calculation region, the calculation step size, and the calculation starting point. The parameter setting unit includes:

[0018] A calculation region setting sub-unit for selecting several feature regions as the calculation region according to the analysis requirements of the specimen;

[0019] A step size setting sub-unit for setting the calculation step size according to the required calculation accuracy;

[0020] A starting point setting sub-unit for setting the calculation starting point.

[0021] Preferably, the strain calculation unit includes:

[0022] A feature point matching sub-unit for matching the feature points in the speckle images before and after the deformation of the specimen;

[0023] A strain calculation sub - unit, which non - linearly solves each feature point based on the sub - pixel displacement measurement algorithm to obtain the strain information of each feature point. The strain information includes the displacement information of the feature point and the strain value of the feature point;

[0024] A comprehensive reconstruction sub - unit, which integrates the strain information of each feature point through a numerical reconstruction method to obtain a three - dimensional strain distribution model of the entire specimen surface.

[0025] Preferably, the comprehensive reconstruction sub - unit includes:

[0026] An information integration unit, which integrates the strain information of each feature point to obtain a first strain distribution model;

[0027] A reliability evaluation block, which is used to evaluate the reliability of the first strain distribution model;

[0028] where R is the reliability evaluation parameter of the first strain distribution model, α 1 、α 2 、α 3 are the weighted calculation coefficients of the spatial consistency error, the reconstruction geometric error, and the material constraint error respectively; M is the total number of feature points; W i is the importance coefficient of the i - th feature point; is the strain gradient of the i - th feature point; σ 1 is the preset comparison standard value of the strain gradient; P Si is the reconstruction position of the i - th feature point; P Ri is the original position of the i - th feature point; max is the maximum value function; ∈ i is the strain value of the i - th feature point; ∈ b is the yield limit of the specimen material; ∈ 0 is the unit strain;

[0029] When the reliability evaluation parameter of the first strain distribution model is less than the reliability judgment threshold, it is determined that the reliability of the first strain distribution model meets the requirements; otherwise, it is determined that the reliability of the first strain distribution model does not meet the requirements;

[0030] An information optimization block, which is used to iteratively optimize the first strain distribution model with insufficient reliability for the set standard;

[0031] A model output block, which outputs the first strain distribution model with satisfied reliability as the three - dimensional strain distribution model.

[0032] Preferably, the information optimization block includes:

[0033] A strain update block, which is used to update the strain value of each feature point in the first strain distribution model;

[0034]

[0035] wherein, ∈ ix is the strain value of the i-th feature point after update; ∈ ij is the strain value of the i-th feature point before update; γ is the preset step size; α 1 and α 3 are the weighted calculation coefficients of the spatial consistency error and the material constraint error respectively; M is the total number of feature points; W i is the importance coefficient of the i-th feature point; is the strain gradient of the i-th feature point; σ 1 is the comparison standard value of the preset strain gradient; max is the maximum value function; ∈ b is the yield limit of the specimen material; ∈ 0 is the unit strain; E 1 is the spatial consistency error; E 2 is the material constraint error; is the partial derivative of the spatial consistency error with respect to the strain value of the i-th feature point before update; is the partial derivative of the material constraint error with respect to the strain value of the i-th feature point before update;

[0036] Model reconstruction block, which regenerates the first strain distribution model based on the updated strain values of each feature point;

[0037] Loop control block, which is used to judge the reliability of the regenerated first strain distribution model. If the reliability of the first strain distribution model does not meet the requirements, continue to loop to update the strain values of each feature point and regenerate the first strain distribution model. Otherwise, stop updating the strain values of each feature point and regenerating the first strain distribution model.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] Compared with the contact strain gauge, it can only measure the strain at a local point and in a one-dimensional direction, and the response speed is limited. The present invention integrates a monocular high-speed image acquisition device, two reflective devices, and a spectroscopic device to form a monocular three-dimensional high-speed image acquisition device, and combines it with three-dimensional DIC calculation and analysis software, so as to realize three-dimensional full-field deformation and strain measurement, and at the same time, the response speed is faster.

[0040] Compared with the binocular three-dimensional DIC technology, which requires two CCD cameras, has a complex structure, and takes a lot of time to complete the calibration between the two CCD cameras in terms of operation mode, the cost is extremely expensive. The present invention integrates a monocular high-speed image acquisition device, two reflecting devices, and a beam splitting device to form a monocular three-dimensional high-speed image acquisition device, which is combined with three-dimensional DIC calculation and analysis software, and thus can realize three-dimensional full-field deformation and strain measurement. The calibration difficulty is reduced, and at the same time, the demand for CCD cameras is reduced, greatly reducing the hardware cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 is a top view structural schematic diagram of the present invention;

[0043] Figure 2 is a structural schematic diagram of the image acquisition component of the present invention;

[0044] Figure 3 is a structural schematic diagram of the beam splitting component of the present invention;

[0045] Figure 4 is a structural schematic diagram of the reflecting component of the present invention;

[0046] Figure 5 is a schematic diagram of the optical path propagation of the present invention.

[0047] REFERENCE SIGNS:

[0048] 1, integrated platform; 2, image acquisition component; 3, beam splitting component; 4, reflecting component; 5, fill light; 6, first XY-axis moving platform; 7, ccd camera; 8, second XY-axis moving platform; 9, first rotating platform; 10, triangular prism; 11, third XY-axis moving platform; 12, second rotating platform; 13, reflecting mirror; 14, specimen; 15, left virtual image; 16, right virtual image. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] To make the objectives, technical solutions and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0050] In addition, in the present invention, descriptions such as "first" and "second" are only for descriptive purposes, and do not particularly refer to the meaning of order or sequence, nor are they used to limit the present invention. They are merely used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions and technical features between various embodiments can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0051] Embodiment 1

[0052] The embodiment of the present invention provides a visual deformation measurement system based on monocular three-dimensional, including an integration platform 1. An image acquisition component 2, a beam splitting component 3, two groups of reflective components 4 and two groups of supplementary lights 5 are arranged on the upper surface of the integration platform 1. The image acquisition component 2 is arranged behind the beam splitting component 3. The two groups of reflective components 4 are symmetrically arranged on the left and right sides of the beam splitting component 3. The two groups of supplementary lights 5 are respectively arranged on the sides of the two groups of reflective components 4 away from the beam splitting component 3. The supplementary lights 5 are rotatably connected to the upper surface of the integration platform 1.

[0053] Preferably, the image acquisition component 2 includes a first XY-axis moving platform 6. The first XY-axis moving platform 6 is fixedly connected to the upper surface of the integration platform 1. A ccd camera 7 is installed on the upper surface of the first XY-axis moving platform 6.

[0054] Preferably, the beam splitting component 3 includes a second XY-axis moving platform 8. The second XY-axis moving platform 8 is fixedly connected to the upper surface of the integration platform 1. A first rotating platform 9 is rotatably connected to the upper surface of the second XY-axis moving platform 8. A triangular prism 10 is fixedly connected to the upper surface of the rotating platform.

[0055] Preferably, the reflective component 4 includes a third XY-axis moving platform 11. The third XY-axis moving platform 11 is fixedly connected to the upper surface of the integration platform 1. A second rotating platform 12 is rotatably connected to the upper surface of the third XY-axis moving platform 11. A reflective lens 13 is fixedly connected to the upper surface of the rotating platform.

[0056] In this embodiment, the first XY-axis moving platform 6, the second XY-axis moving platform 8, and the third XY-axis moving platform 11 are all prior arts, such as the XY-axis moving platform in a precision laser engraving machine for visual precise positioning and depth measurement disclosed in CN118744284A.

[0057] In this embodiment, the images of the specimen 14 enter the spectroscopic component 3 through the reflection of the two-sided reflection components 4 on both sides. Through the spectroscopy of the spectroscopic component 3, a left virtual image 15 and a right virtual image 16 are formed. The image acquisition component 2 takes pictures of the triangular prism 10 in the spectroscopic component 3 to realize the monocular high-speed three-dimensional image acquisition of the specimen 14.

[0058] The beneficial effects of the above technical solutions are as follows:

[0059] When a loading test is performed on the specimen 14, the specimen 14 is placed at the loading position. By adjusting the rotation angles of the horizontal positions of the image acquisition component 2, the spectroscopic component 3, the reflection component 4, and the fill light 5, the calibration of the deformation measurement system is completed. Thus, the speckle image on the surface of the specimen 14 is obtained in real time through the image acquisition component 2. By analyzing the speckle images before and after the deformation of the specimen 14, the three-dimensional strain distribution on the surface of the specimen 14 can be accurately obtained.

[0060] Through the settings of the reflection component 4 and the spectroscopic component 3, based on the principle of light reflection, the deformation and strain measurements of the three-dimensional full field can be realized by using a group of image acquisition components 2, greatly reducing the hardware cost.

[0061] Embodiment 2

[0062] On the basis of Embodiment 1, it further includes a measurement and calculation module, and the measurement and calculation module includes:

[0063] An image acquisition unit for acquiring the speckle image on the surface of the specimen;

[0064] A pixel feature recognition unit for identifying the feature points in the speckle image;

[0065] A region definition unit for dividing the speckle image into several feature regions according to the distribution of the feature points;

[0066] A parameter setting unit for setting the analysis parameters based on the experimental requirements;

[0067] A strain calculation unit for analyzing the speckle images during the loading process by using the sub-pixel displacement measurement algorithm based on the set analysis parameters to obtain the three-dimensional strain distribution on the surface of the specimen.

[0068] Preferably, the analysis parameters include: the distribution of the calculation region, the calculation step size, and the calculation starting point. The parameter setting unit includes:

[0069] A calculation area setting subunit, configured to select a plurality of characteristic areas as calculation areas according to the analysis requirements of the specimen;

[0070] A step size setting subunit, configured to set a calculation step size according to the required calculation accuracy;

[0071] A starting point setting subunit, configured to set a calculation starting point.

[0072] Preferably, the strain calculation unit includes:

[0073] A feature point matching subunit, configured to match and correspond the feature points in the speckle images before and after the deformation of the specimen;

[0074] A strain calculation subunit, which performs a non-linear solution for each feature point based on a sub-pixel displacement measurement algorithm to obtain the strain information of each feature point, and the strain information includes the displacement information of the feature point and the strain value of the feature point;

[0075] A comprehensive reconstruction subunit, which integrates the strain information of each feature point through a numerical reconstruction method to obtain a three-dimensional strain distribution model of the entire surface of the specimen.

[0076] Beneficial effects of the above technical solution:

[0077] This solution can achieve accurate measurement of the surface deformation of the specimen 14 through the sub-pixel displacement measurement algorithm. Through careful feature point matching and non-linear solution, the strain information of each feature point can be accurately obtained, thereby improving the accuracy of strain calculation. The solution uses a numerical reconstruction method to integrate the strain information of feature points and obtain a three-dimensional strain distribution on the surface of the specimen 14. The accuracy of the strain analysis result is improved. The system can automatically complete multiple steps such as speckle image acquisition, feature point recognition, area division, and displacement calculation, greatly improving the measurement efficiency and reducing the error of manual operation. This system supports setting different analysis parameters according to experimental requirements, including the selection of the calculation area, the setting of the step size, and the setting of the calculation starting point, making the measurement process more flexible and capable of adapting to the measurement requirements of different materials, different deformation states, and different calculation accuracies. Traditional three-dimensional strain measurement often requires complex instrument equipment, while this system uses a monocular camera for measurement, reducing the equipment cost and the calibration difficulty of the equipment, and greatly improving the deformation analysis efficiency.

[0078] Embodiment 3

[0079] Based on Embodiment 2, the comprehensive reconstruction subunit includes:

[0080] An information integration unit, which integrates the strain information of each feature point to obtain a first strain distribution model;

[0081] A reliability evaluation block for evaluating the reliability of the first strain distribution model;

[0082] where R is the reliability evaluation parameter of the first strain distribution model, and α 1 , α 2 , α 3 are the weighted calculation coefficients of the spatial consistency error, the reconstructed geometry error, and the material constraint error respectively; M is the total number of feature points; W i is the importance coefficient of the i-th feature point; is the strain gradient of the i-th feature point; σ 1 is the comparison standard value of the preset strain gradient; P Si is the reconstructed position of the i-th feature point; P Ri is the original position of the i-th feature point; max is the maximum value function; ∈ i is the strain value of the i-th feature point; ∈ b is the yield limit of the specimen material; ∈ 0 is the unit strain;

[0083] When the reliability evaluation parameter of the first strain distribution model is less than the reliability judgment threshold, it is judged that the reliability of the first strain distribution model meets the requirements; otherwise, it is judged that the reliability of the first strain distribution model does not meet the requirements;

[0084] An information optimization block for iteratively optimizing the first strain distribution model with insufficient reliability of the set standard;

[0085] A model output block that outputs the first strain distribution model with satisfactory reliability as the three-dimensional strain distribution model.

[0086] Preferably, the information optimization block includes:

[0087] A strain update block for updating the strain value of each feature point in the first strain distribution model;

[0088]

[0089] where ∈ ix is the updated strain value of the i-th feature point; v ij is the strain value of the i-th feature point before update; γ is the preset step size; α 1 , α 3 are the weighted calculation coefficients of the spatial consistency error and the material constraint error respectively; M is the total number of feature points; W i is the importance coefficient of the i-th feature point; is the strain gradient of the i-th feature point; σ 1is the contrast standard value of the preset strain gradient; max is the maximum value function; ∈ b is the yield limit of the specimen material; ∈ 0 is the unit strain; E 1 is the spatial consistency error; E 2 is the material constraint error; is the partial derivative of the spatial consistency error with respect to the strain value of the i-th feature point before update; is the partial derivative of the material constraint error with respect to the strain value of the i-th feature point before update;

[0090] The model reconstruction block regenerates the first strain distribution model based on the updated strain values of each feature point;

[0091] The loop control block is used to judge the reliability of the regenerated first strain distribution model. If the reliability of the first strain distribution model does not meet the requirements, continue to loop for the update of the strain values of each feature point and the regeneration of the first strain distribution model. Otherwise, stop the update of the strain values of each feature point and the regeneration of the first strain distribution model.

[0092] In this embodiment, the reliability judgment threshold is obtained by referring to the calculation accuracy - reliability judgment threshold correspondence table based on the required calculation accuracy. The corresponding data in the calculation accuracy - reliability judgment threshold correspondence table comes from experimental determination.

[0093] The beneficial effects of the above technical solution are as follows:

[0094] After generating the first strain distribution model, by evaluating the reliability of the first strain distribution model, it is ensured that the reliability of the first strain distribution model meets the preset calculation accuracy, thereby ensuring that the reliability of the finally output three-dimensional strain distribution model meets the currently set calculation accuracy. Through multiple evaluations and adjustments, a more reliable model is finally obtained, which can more accurately describe the three-dimensional strain distribution and meet the requirements of practical applications. By determining the reliability judgment adjustment of the three-dimensional strain distribution model according to different calculation accuracies, when obtaining the three-dimensional strain distribution model with low calculation accuracy, the number of iterative optimizations can be effectively reduced, thereby saving computing resources and improving the output efficiency of the three-dimensional strain distribution model. By performing multiple iterative optimizations on the first strain distribution model, the accuracy of the model is gradually improved and the error tends to be minimized, thus ensuring that the finally output three-dimensional strain distribution model meets the set calculation accuracy and improving the reliability of the model.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monocular three-dimensional visual deformation measurement system, characterized in that: The integrated platform (1) comprises an image acquisition component (2), a light splitting component (3), two groups of reflective components (4) and two groups of fill-in lights (5) arranged on the upper surface of the integrated platform (1); the image acquisition component (2) is arranged on the rear side of the light splitting component (3); the two groups of reflective components (4) are symmetrically arranged on the left and right sides of the light splitting component (3); the two groups of fill-in lights (5) are respectively arranged on the side of the two groups of reflective components (4) away from the light splitting component (3); and the fill-in lights (5) are rotatably connected to the upper surface of the integrated platform (1).

2. The monocular three-dimensional visual deformation measurement system according to claim 1, characterized in that: The image acquisition component (2) comprises a first XY axis moving platform (6), the first XY axis moving platform (6) is fixedly connected to the upper surface of the integrated platform (1), and a CCD camera (7) is installed on the upper surface of the first XY axis moving platform (6).

3. The monocular three-dimensional visual deformation measurement system according to claim 1, characterized in that: The light splitting component (3) comprises a second XY axis moving platform (8), the second XY axis moving platform (8) is fixedly connected to the upper surface of the integrated platform (1), the upper surface of the second XY axis moving platform (8) is rotatably connected to the first rotating platform (9), and the upper surface of the rotating platform is fixedly connected to a triangular prism (10).

4. The monocular three-dimensional visual deformation measurement system according to claim 1, characterized in that: The reflective component (4) comprises a third XY axis moving platform (11), the third XY axis moving platform (11) is fixedly connected to the upper surface of the integrated platform (1), the upper surface of the third XY axis moving platform (11) is rotatably connected to the second rotating platform (12), and the upper surface of the rotating platform is fixedly connected to a reflective lens (13).

5. The monocular three-dimensional visual deformation measurement system according to claim 1, characterized in that: It also includes a measurement and calculation module, which includes: An image acquisition unit, used for acquiring a speckle image on the surface of the sample; A pixel feature recognition unit, used to identify feature points in the speckle image; A region definition unit, used for dividing the speckle image into a number of characteristic regions according to the distribution of characteristic points; Parameter setting unit, used to set analysis parameters based on experimental requirements; The strain calculation unit is used to analyze the speckle image of the loading process based on the set analysis parameters using a sub-pixel displacement measurement algorithm to obtain the three-dimensional strain distribution on the sample surface.

6. The monocular three-dimensional visual deformation measurement system according to claim 5, characterized in that: The analysis parameters include: calculation area distribution, calculation step and calculation starting point. The parameter setting unit includes: The calculation area setting subunit is used to select several characteristic areas as calculation areas according to the analysis requirements of the sample; The step size setting subunit is used to set the calculation step size according to the required calculation accuracy; The starting point setting subunit is used to set the calculation starting point.

7. The monocular three-dimensional visual deformation measurement system according to claim 5, characterized in that: The strain calculation unit includes: A feature point matching subunit is used to match the feature points in the speckle image before and after the deformation of the sample; The strain calculation subunit performs nonlinear solution on each feature point based on the sub-pixel displacement measurement algorithm to obtain strain information of each feature point, and the strain information includes displacement information of the feature point and strain value of the feature point; The subunits are fully reconstructed, and the strain information of each feature point is integrated through the numerical reconstruction method to obtain the three-dimensional strain distribution model of the entire specimen surface.

8. The monocular three-dimensional visual deformation measurement system according to claim 7, characterized in that: The fully restructured subunits include: An information integration unit, which obtains a first strain distribution model by integrating strain information of each feature point; A reliability evaluation block, used to evaluate the reliability of the first strain distribution model; Where R is the reliability evaluation parameter of the first strain distribution model, α1, α2, and α3 are the weighted calculation coefficients of spatial consistency error, reconstructed geometric error, and material constraint error, respectively; M is the total number of feature points; W i is the importance coefficient of the i-th feature point; is the strain gradient of the i-th feature point; σ1 is the preset comparison standard value of the strain gradient; P Si is the reconstructed position of the i-th feature point; P Ri is the original position of the i-th feature point; max is the maximum value function; ∈ i is the strain value of the i-th feature point; ∈ b is the yield limit of the specimen material; ∈0 is the unit strain; When the reliability evaluation parameter of the first strain distribution model is less than the reliability judgment threshold, it is judged that the reliability of the first strain distribution model meets the requirement; otherwise, it is judged that the reliability of the first strain distribution model does not meet the requirement; an information optimization block for iteratively optimizing a first strain distribution model of a set standard that is insufficient in reliability; The model output block outputs the first strain distribution model that meets the reliability requirements as a three-dimensional strain distribution model.

9. The monocular three-dimensional visual deformation measurement system according to claim 8, characterized in that: The information optimization block includes: A strain update block, used for updating the strain value of each characteristic point in the first strain distribution model; Among them, ∈ ix is the strain value of the i-th feature point after update; ∈ ij is the strain value of the i-th feature point before updating; γ is the preset step size; α1 and α3 are the weighted calculation coefficients of spatial consistency error and material constraint error respectively; M is the total number of feature points; W i is the importance coefficient of the i-th feature point; is the strain gradient of the i-th feature point; σ1 is the preset comparison standard value of the strain gradient; max is the maximum value function; ∈ b is the yield limit of the specimen material; ∈0 is the unit strain; E1 is the spatial consistency error; E2 is the material constraint error; is the partial derivative of the spatial consistency error with respect to the strain value of the i-th feature point before updating; is the partial derivative of the material constraint error with respect to the strain value of the i-th feature point before updating; A model reconstruction block regenerates the first strain distribution model based on the updated strain value of each feature point; The loop control block is used to determine the reliability of the regenerated first strain distribution model. If the reliability of the first strain distribution model does not meet the requirements, the update of the strain value of each feature point and the regeneration of the first strain distribution model are continued in a loop; otherwise, the update of the strain value of each feature point and the regeneration of the first strain distribution model are stopped.

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