3D-DIC measurement device and method based on multi-axis precision platform

Abstract

The application belongs to the technical field of optical measurement and digital image correlation, and discloses a 3D-DIC measuring device and method based on a multi-axis precision platform, which comprises the following steps: moving a speckle target with different diameters based on a multi-axis precision platform driving setting, performing 3D-DIC measurement at different moving distances, and determining an optimal speckle diameter; moving the speckle target with the optimal speckle diameter, performing 3D-DIC measurement through lenses with different focal lengths, and determining an optimal focal length; arranging multiple target points on the edge of a sample to be tested, driving the sample to be tested to displace along three-dimensional directions, performing 3D-DIC measurement to obtain three-dimensional measurement errors of the target points, and fitting to obtain an error correction model; setting measurement parameters according to the optimization result to perform 3D-DIC measurement on the sample to be tested to obtain original three-dimensional DIC measurement displacement; and performing edge correction on the original three-dimensional DIC measurement displacement through the error correction model. The application can improve measurement accuracy.

Description

Technical Field

[0001] This invention belongs to the field of optical measurement and digital image correlation (DIC) technology, specifically relating to a 3D-DIC measurement device and method based on a multi-axis precision platform. Background Technology

[0002] 3D-DIC measurement, as a non-contact, high-precision full-field measurement method, calculates the displacement and strain of pixels by comparing target images before and after deformation, and has become one of the core technologies in fields such as dynamic mechanical testing of materials and structural health monitoring. However, existing 3D-DIC measurements still face the following key technical bottlenecks, limiting their measurement accuracy and applicability: (1) Limited selection of speckle type and insufficient adaptability: In the existing technology, the speckle type commonly used in DIC measurement is mainly spray-coated. It only adapts to different scenarios by adjusting the speckle diameter, without considering the surface characteristics of the sample (such as the influence of rough and smooth surfaces on speckle adhesion and imaging contrast), testing requirements (differences in speckle durability between temporary and long-term testing), and accuracy requirements (different standards for speckle uniformity between ordinary and high-precision measurement). For example, when using spray-coated speckle on smooth metal surfaces, the paint layer is easy to fall off, causing measurement interruption; in temporary testing scenarios, the preparation process of spray-coated speckle (cleaning, priming, spraying, and curing) is time-consuming, reducing experimental efficiency; in high-precision measurement, the speckle uniformity deviation of traditional spraying process (usually >10%) will introduce additional measurement errors.

[0003] (2) Lens focal length selection is based on experience and lacks quantitative basis: The lens focal length directly determines the field of view (FOV) and spatial resolution of the 3D-DIC system: the larger the focal length, the smaller the field of view but the higher the resolution; the smaller the focal length, the larger the field of view but the lower the resolution. In the existing technology, the selection of lens focal length mostly depends on the operator's experience or the manufacturer's recommended parameters, without fully considering the measurement requirements (maximum field of view FOV). max Target measurement accuracy δ req This leads to two common problems: first, "insufficient field of view," meaning that the selected focal length is too small to cover the entire sample surface, requiring multiple camera movements for splicing measurements, which introduces splicing errors; second, "excessive resolution," meaning that the selected focal length is too large, which, although meeting the accuracy requirements, results in a small field of view, leading to low measurement efficiency and increased equipment costs.

[0004] (3) Significant edge errors in large format images with no effective compensation: In large format measurement scenarios, the measurement error in the edge area is significantly higher than that in the center area due to the following factors: perspective distortion: the camera optical axis is difficult to be completely perpendicular to the target surface, resulting in a difference between the projection relationship of edge pixels and the center pixels, introducing displacement measurement deviation; lens radial distortion: the optical structure of industrial lenses determines that the aberration in the edge area is greater than that in the center area, resulting in the offset of the imaging position of edge pixels; pixel response non-uniformity: the photosensitive sensitivity of edge pixels of camera sensors is usually 5%~10% lower than that of center pixels, resulting in a decrease in the grayscale contrast of the image in the edge area and a decrease in DIC matching accuracy.

[0005] Camera calibration (such as using a checkerboard calibration board) can correct some distortion, but it is difficult to accurately correct errors in large-format edge areas, resulting in edge area errors being much larger than those in the center area, failing to meet the measurement requirements for uniform accuracy across the entire field. In summary, there is an urgent need for a 3D-DIC measurement solution centered on "standardized measurement methods" to achieve a synergistic improvement in measurement accuracy, efficiency, and applicability. Summary of the Invention

[0006] To address the technical problems of poor adaptability and the inability to simultaneously achieve measurement accuracy and efficiency in existing 3D-DIC measurement technologies, this invention proposes a 3D-DIC measurement device and method based on a multi-axis precision platform, thereby achieving a synergistic improvement in measurement accuracy, efficiency, and applicability.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a 3D-DIC measurement method based on a multi-axis precision platform, comprising the following steps: Step 1: Drive the movement of speckle targets with different diameters using a multi-axis precision platform, perform 3D-DIC measurements at different movement distances, and determine the optimal speckle diameter based on the measurement results; Step 2: Drive the movement of the speckle target with the optimal speckle diameter based on the multi-axis precision platform, perform 3D-DIC measurement through lenses with different focal lengths, and determine the optimal focal length based on the measurement results; Step 3: Arrange multiple target points on the edge of the test sample. Drive the test sample to move along the three-dimensional direction using a multi-axis precision platform, and then perform 3D-DIC measurement to obtain the three-dimensional DIC measurement displacement of each target point. Combine the three-dimensional displacement of the multi-axis precision platform to calculate the three-dimensional measurement error of each target point. Based on the pixel coordinates of each target point and the corresponding measurement error, obtain an error correction model. The error correction model is as follows: ; ; ; in, Indicates the x-axis error. Indicates the y-axis error. Indicates the z-axis error. This represents pixel coordinates, and f represents the lens focal length. , , , , , , , , k1 represents the perspective distortion correction factor, and k2 represents the lens radial distortion factor. , , , , , , , , k1 was obtained through fitting; Step 4: Set a speckle target on the surface of the test sample according to the optimal speckle diameter. At the same time, select a lens according to the optimal focal length and perform 3D-DIC measurement on the test sample to obtain the original three-dimensional DIC measurement displacement. Step 5: Calculate the x-axis error, y-axis error, and z-axis error of the edge region using the error correction model, and perform edge correction on the original three-dimensional DIC measurement displacement based on the x-axis error, y-axis error, and z-axis error.

[0008] In step 5, edge correction is performed on the edge region, where the edge region refers to the distance from the image center. Greater than the edge threshold The formula for edge correction for the region corresponding to the pixel is: ; ; ; in, , , These represent the x-axis displacement, y-axis displacement, and z-axis displacement measured in the original 3D DIC; , and These represent the x-axis displacement, y-axis displacement, and z-axis displacement after edge correction, respectively. , and These represent the x-axis error, y-axis error, and z-axis error, respectively.

[0009] In step 4, the original three-dimensional DIC measurement displacement is calculated based on the 3D-DIC measurement image and the DIC algorithm. Before calculating the original three-dimensional measurement displacement based on the DIC algorithm, a preprocessing step of grayscale correction of the image is also included. The formula for grayscale correction is: ; in, Represents the original grayscale value. This represents the corrected grayscale value. This represents the local average gray value. This represents the average grayscale value of the entire image.

[0010] In step 1, the method for determining the optimal speckle diameter is as follows: Step 1.1: Based on the number of pixels that the speckle needs to cover, initially determine the diameter range of the speckle. Based on the diameter range of the speckle and the surface roughness of the sample to be tested, determine multiple candidate speckle diameters. Step 1.2: Determine the speckle type based on the sample surface parameters; Step 1.3: After setting the corresponding type of speckle target on the target plate, mount the target plate on a multi-axis precision platform. Control the multi-axis precision platform to make the speckle target move in steps along the preset direction multiple times. After each step, perform 3D-DIC measurement to obtain the DIC measurement displacement of the speckle target at each movement step length, and then calculate the average value of each DIC measurement displacement. Standard deviation σ d And the average calculation time t for each DIC measured displacement; Step 1.4: Change the diameter of the speckle target and repeat step 1.3; Step 1.5: Calculate the comprehensive fit index Q corresponding to each different speckle target diameter, and determine the speckle diameter based on the comprehensive fit index Q. The calculation formula is as follows: ; Where ω1 and ω2 represent weighting coefficients, and t0 represents the baseline time.

[0011] In step 1.1, the diameter range of the speckle pattern is: ; in, The diameter of the speckle is represented by k, k0 and k2 represent the lower and upper limits of the pixels covered by the speckle, respectively, and L represents the distance between the camera and the target. This indicates the focal length of the initially selected lens.

[0012] In step 2, the method for determining the optimal focal length is as follows: Step 2.1: Combine with the maximum field of view (FOV) max With target measurement accuracy δreq Determine the lower limit of the focal length; Step 2.2: Determine multiple sets of candidate focal lengths based on the lower limit of the focal length; Step 2.3: Set up a speckle target with the optimal speckle diameter on the surface of the test sample, install the corresponding lens according to the selected focal length, and adjust the camera position to ensure that the field of view covers the entire target; Step 2.4: After driving the speckle target along a preset direction with a minimum step displacement based on the multi-axis precision platform, perform 3D-DIC measurement to obtain the DIC measurement displacement and calculate the measurement deviation. Determine whether the measurement deviation meets the accuracy safety conditions. If not, gradually increase the step displacement value of the speckle target and repeat the 3D-DIC measurement until the measurement deviation meets the accuracy safety conditions. The corresponding step displacement value is the resolution limit at that focal length. At the same time, based on the resolution limit Determine the field of view and measurement error corresponding to this focal length; Step 2.5: Change the lens focal length to other values ​​among the candidate focal lengths, and repeat steps 2.3-2.4 until the resolution limit, field of view and measurement error corresponding to all candidate focal lengths are obtained; Step 2.6: Under the premise that the resolution limit and field of view meet the measurement requirements, select the focal length with the smallest measurement error as the optimal focal length.

[0013] In step 2.4, the accuracy safety condition is as follows: Δδ≤±δ req / k4; Where, δ req Δδ represents the target measurement accuracy, k4 represents the measurement deviation, and k4 represents the accuracy safety factor.

[0014] In step 2.1, the formula for calculating the lower limit of focal length is: ; in, Indicates the lower limit of focal length. Indicates the number of pixels horizontally in the camera. s The field of view (FOV) represents the physical size of a single pixel, L represents the distance between the camera and the target. max δ represents the maximum field of view. req Indicates the target measurement accuracy.

[0015] Furthermore, the present invention also provides a 3D-DIC measurement device based on a multi-axis precision platform, for implementing the aforementioned 3D-DIC measurement method based on a multi-axis precision platform, comprising: Multi-axis precision moving platform for installing target components; A 3D optical imaging system, comprising two industrial cameras and lenses with identical parameters, for acquiring 3D images; Lighting systems are used to provide light sources; A control and synchronization system is used to control the motion of the multi-axis precision moving platform and the timing of image acquisition; The data processing system is used to calculate the displacement information of the test sample based on the 3D image acquired by the 3D optical imaging system, and to perform edge correction on the displacement information of the test sample according to the error correction model.

[0016] Compared with the prior art, the present invention has the following advantages: This invention proposes a 3D-DIC measurement device and method based on a multi-axis precision platform. By adapting to different scenarios with multiple types of speckle, matching the lens focal length with a quantitative formula, and compensating for edge errors with a precise algorithm, the measurement accuracy, efficiency, and applicability can be synergistically improved. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a 3D-DIC measurement method based on a multi-axis precision platform provided in Embodiment 1 of the present invention. Figure 2 This is a schematic diagram of the structure of the multi-axis precision platform used in the embodiments of the present invention; Figure 3 for Figure 2 The right view; In the diagram: 1. Target placement plate; 2. Target plate connecting bracket; 3. Adapter plate; 4. Z-axis moving platform; 5. X-axis moving platform; 6. Y-axis moving platform; 7. X-axis transmission screw; 8. X-axis control motor; 9. Z-axis control motor; 10. Y-axis control motor; 13. Z-axis transmission screw; 14. Y-axis transmission screw. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 like Figure 1 As shown, Embodiment 1 of the present invention provides a 3D-DIC measurement method based on a multi-axis precision platform, comprising the following steps: Step 1: Drive the movement of speckle targets with different diameters using a multi-axis precision platform, perform 3D-DIC measurements at different movement distances, and determine the optimal speckle diameter based on the measurement results.

[0020] In step 1, the method for determining the optimal speckle diameter is as follows: Step 1.1: Based on the number of pixels the speckle needs to cover, initially determine the diameter range of the speckle. Based on the diameter range of the speckle and the surface roughness of the sample to be tested, determine m candidate speckle diameters. The value of m can be between 2 and 4.

[0021] Step 1.2: Determine the speckle type based on the sample surface parameters.

[0022] In this embodiment, the speckle type can be spraying, pasting, or etching, which is determined based on the surface parameters of the sample to be tested, such as roughness.

[0023] Step 1.3: After setting the corresponding type of speckle target on the target plate, mount the target plate on a multi-axis precision platform. Control the multi-axis precision platform to make the speckle target move in steps along the preset direction multiple times. After each step, perform 3D-DIC measurement to obtain the DIC measurement displacement of the speckle target at each movement step length, and then calculate the average value of each DIC measurement displacement. Standard deviation σ d And the average calculation time t for each DIC measured displacement.

[0024] Step 1.4: Change the diameter of the speckle target and repeat step 1.3 until the average value of the diameters of all candidate speckles is obtained. Standard deviation σ d The average calculation time t for DIC displacement measurement.

[0025] Step 1.5: Calculate the comprehensive fit index Q corresponding to each different candidate speckle diameter, and determine the optimal speckle diameter based on the comprehensive fit index Q. The calculation formula is as follows: ; Where ω1 and ω2 represent weighting coefficients, and t0 represents the baseline time, which is equal to the calculation time when using the standard speckle diameter.

[0026] In this embodiment, when determining the optimal speckle diameter, the speckle diameter with the smallest comprehensive adaptation index Q value is selected as the optimal speckle diameter. Further, in this embodiment, a multi-axis precision platform can be controlled to move the speckle target in steps along the x, y, and z directions respectively. The comprehensive adaptation index Q corresponding to the same candidate speckle diameter in the three directions is averaged or the extreme value is taken as the second comprehensive adaptation index Q'. Then, the speckle diameter with the smallest second comprehensive adaptation index Q' value is selected as the optimal speckle diameter.

[0027] Furthermore, in step 1.1, the diameter range of the speckle pattern is: ; in, The diameter of the speckle is represented by k, k0 and k2 represent the lower and upper limits of the pixels covered by the speckle, respectively, and L represents the distance between the camera and the target. This indicates the focal length of the initially selected lens.

[0028] Step 2: Drive the movement of the speckle target with the optimal speckle diameter based on the multi-axis precision platform, perform 3D-DIC measurement through lenses with different focal lengths, and determine the optimal focal length based on the measurement results.

[0029] Step 2, the method for determining the optimal focal length, specifically includes the following steps: Step 2.1: Combine with the maximum field of view (FOV) max With target measurement accuracy δ req Determine the lower limit of the focal length.

[0030] In step 2.1, the formula for calculating the lower limit of focal length is: ; in, Indicates the lower limit of focal length. Indicates the number of pixels horizontally in the camera. s The field of view (FOV) represents the physical size of a single pixel, L represents the distance between the camera and the target. max δ represents the maximum field of view. req Indicates the target measurement accuracy.

[0031] Step 2.2: Determine multiple sets of candidate focal lengths based on the lower limit of focal length.

[0032] Step 2.3: Set the speckle target with the optimal speckle diameter, set the speckle target on the multi-axis precision platform, install the corresponding lens according to the selected focal length, and adjust the camera position to ensure that the field of view covers the entire target.

[0033] Step 2.4: After driving the speckle target to make a minimum step displacement along a preset direction based on the multi-axis precision platform, perform 3D-DIC measurement to obtain the DIC measurement displacement. Determine whether the displacement deviation of the DIC measurement meets the accuracy safety conditions. If not, gradually increase the step displacement value of the speckle target and repeat the 3D-DIC measurement until the displacement deviation of the DIC measurement meets the accuracy safety conditions. The corresponding step displacement value is the resolution limit at that focal length. At the same time, based on the resolution limit Determine the field of view and measurement error corresponding to this focal length.

[0034] In step 2.4, the accuracy safety condition is as follows: Δδ≤±δ req / k4; Where, δ reqThe target measurement accuracy is represented by Δδ, which represents the displacement deviation, equal to the difference between the displacement measured by DIC and the displacement value of the multi-axis precision platform. k4 represents the accuracy safety factor, where k4≥3. In this embodiment, k4 is set to 3.

[0035] Furthermore, in step 2.3 of this embodiment, the speckle target can be driven to perform the above measurements along the x, y, and z directions. By determining the resolution limit in each of the three directions to determine the field of view and measurement error corresponding to the selected focal length, the device can meet the experimental accuracy in all three directions. Specifically, in this embodiment, the measurement error is equal to the step displacement value, which is equal to the resolution limit. The measurement deviation Δδ under the given conditions; furthermore, when the step displacement value equals the resolution limit. Under the premise that the average value of the measurement deviation Δδ obtained from multiple measurements can be used as the measurement error, or the extreme value of the measurement deviation Δδ obtained from multiple measurements can be used as the measurement error.

[0036] Step 2.5: Change the lens focal length to other values ​​among the candidate focal lengths, and repeat steps 2.3-2.4 until the resolution limit, field of view and measurement error corresponding to all candidate focal lengths are obtained; Step 2.6: Under the premise that the resolution limit and field of view meet the measurement requirements, select the focal length with the smallest measurement error as the optimal focal length.

[0037] In step 2.6, "the resolution limit and field of view satisfy the measurement requirements" means that the resolution limit corresponding to the selected focal length is... It should be less than or equal to the target measurement accuracy δ req And the field of view is greater than the maximum field of view (FOV). max .

[0038] Step 3: Arrange multiple target points on the edge of the test sample. Drive the test sample to move along the three-dimensional direction using a multi-axis precision platform, with the displacement amount consistent with the displacement order of the test sample. Then, perform 3D-DIC measurement to obtain the three-dimensional DIC measurement displacement of each target point. Combine the displacement amount of the multi-axis precision platform to calculate the three-dimensional measurement error of each target point. Based on the pixel coordinates of each target point and the corresponding measurement error, obtain the error correction model. Specifically, the formula for calculating the three-dimensional measurement error is: ; ; ; in, Indicates the x-axis error. Indicates the y-axis error. Indicates the z-axis error. , as well as Representing pixel coordinates The target point corresponds to the horizontal displacement, vertical displacement, and axial displacement of the DIC. , and This represents the horizontal, vertical, and axial displacements of a multi-axis precision platform. Pixel coordinates are also included. It can be read directly from 3D-DIC measurements.

[0039] The error correction model is as follows: ; ; ; in, Indicates the x-axis error. Indicates the y-axis error. Indicates the z-axis error. The pixel coordinates of the target point are represented by f, and the lens focal length is represented by f. , , , , , , , , k1 represents the perspective distortion correction factor, and k2 represents the lens radial distortion factor. , , , , , , , , k1 was obtained through fitting.

[0040] Specifically, in this embodiment, the number of target points can be set to 4×4, or 5×4 or more.

[0041] Step 4: Set a speckle target on the surface of the test sample according to the optimal speckle diameter. At the same time, after selecting the lens according to the optimal focal length, perform 3D-DIC measurement on the test sample to obtain the original three-dimensional DIC measurement displacement.

[0042] In this embodiment, the 3D-DIC measurement of the test sample also includes a step of adjusting the lighting system. Specifically, the light source is installed in a symmetrical layout, and the illuminance is adjusted to the initially selected range using a photometer. Then, speckle target images were acquired to verify image quality: average grayscale value. ), gray standard deviation 30. Contrast 2. Contrast ratio calculation formula: ; in, , These are the maximum and minimum grayscale values ​​of the target image, respectively.

[0043] When reflections or shadows are present, only fine-tune the brightness of the light source (not exceeding...). Alternatively, add supplementary lighting without changing the light source layout.

[0044] Step 5: Calculate the x-axis error, y-axis error, and z-axis error of the edge region using the error correction model, and perform edge correction on the original three-dimensional DIC measurement displacement based on the x-axis error, y-axis error, and z-axis error.

[0045] In step 5, edge correction is performed on the original DIC measurement displacement of the edge region, where the edge region refers to the distance from the image center. Greater than the edge threshold The formula for edge correction for the region corresponding to the pixel is: ; ; ; in, , , These represent the x-axis displacement, y-axis displacement, and z-axis displacement measured in the original 3D DIC; , and These represent the x-axis displacement, y-axis displacement, and z-axis displacement after edge correction, respectively. , and These represent the x-axis error, y-axis error, and z-axis error, respectively, which are calculated using the error correction model obtained from step 3.

[0046] Furthermore, in this embodiment, before calculating the original three-dimensional measurement displacement based on the DIC algorithm in step 5, a preprocessing step of grayscale correction of the image is included, wherein the formula for grayscale correction is: ; in, Represents the original grayscale value. This represents the corrected grayscale value. This represents the local average gray value, which is generally taken as the average gray value of the area where the target is located. This represents the average grayscale value of the entire image.

[0047] Example 2 Embodiment 2 of the present invention provides a 3D-DIC measurement device based on a multi-axis precision platform, used to implement the 3D-DIC measurement method based on a multi-axis precision platform described in Embodiment 1, comprising: Multi-axis precision moving platform for installing target components; A 3D optical imaging system, comprising two industrial cameras and lenses with identical parameters, for acquiring 3D images; Lighting systems are used to provide light sources; A control and synchronization system is used to control the motion of the multi-axis precision moving platform and the timing of image acquisition; The data processing system is used to calculate the displacement information of the test sample based on the 3D image acquired by the 3D optical imaging system, and to perform edge correction on the displacement information of the test sample according to the error correction model.

[0048] Furthermore, in this embodiment, the data processing system is also used to fit an error correction model.

[0049] like Figure 2 and Figure 3 As shown, in this embodiment, the multi-axis precision moving platform includes a three-dimensional precision moving platform, a transition plate 3, a target plate connecting bracket 2, and a target placement plate 1. The transition plate 3 is fixed on the three-dimensional precision moving platform, and the target placement plate 1 is mounted on the transition plate 3 via the target plate connecting bracket 2. The three-dimensional precision moving platform includes a Z-axis moving platform 4, an X-axis moving platform 5, a Y-axis moving platform 6, an X-axis transmission screw 7, an X-axis control motor 8, a Z-axis control motor 9, a Y-axis control motor 10, a Z-axis transmission screw 13, and a Y-axis transmission screw 14. The control motors in each direction control the movement of the corresponding directional moving platform through the transmission screws, achieving three-axis precision movement.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A 3D-DIC measurement method based on a multi-axis precision platform, characterized in that, Includes the following steps: Step 1: Drive the movement of speckle targets with different diameters using a multi-axis precision platform, perform 3D-DIC measurements at different movement distances, and determine the optimal speckle diameter based on the measurement results; Step 2: Drive the movement of the speckle target with the optimal speckle diameter based on the multi-axis precision platform, perform 3D-DIC measurement through lenses with different focal lengths, and determine the optimal focal length based on the measurement results; Step 3: Arrange multiple target points on the edge of the test sample. Drive the test sample to move along the three-dimensional direction using a multi-axis precision platform, and then perform 3D-DIC measurement to obtain the three-dimensional DIC measurement displacement of each target point. Combine the three-dimensional displacement of the multi-axis precision platform to calculate the three-dimensional measurement error of each target point. Based on the pixel coordinates of each target point and the corresponding measurement error, obtain an error correction model. The error correction model is as follows: ； ； ； in, Indicates the x-axis error. Indicates the y-axis error. Indicates the z-axis error. This represents pixel coordinates, and f represents the lens focal length. , , , , , , , , k1 represents the perspective distortion correction factor, and k2 represents the lens radial distortion factor. , , , , , , , , k1 was obtained through fitting; Step 4: Set a speckle target on the surface of the test sample according to the optimal speckle diameter. At the same time, select a lens according to the optimal focal length and perform 3D-DIC measurement on the test sample to obtain the original three-dimensional DIC measurement displacement. Step 5: Calculate the x-axis error, y-axis error, and z-axis error of the edge region using the error correction model, and perform edge correction on the original 3D DIC measurement displacement based on the x-axis error, y-axis error, and z-axis error; In step 5, edge correction is performed on the edge region, where the edge region refers to the distance from the image center. Greater than the edge threshold The formula for edge correction for the region corresponding to the pixel is: ； ； ； in, , , These represent the x-axis displacement, y-axis displacement, and z-axis displacement measured in the original 3D DIC; , and These represent the x-axis displacement, y-axis displacement, and z-axis displacement after edge correction, respectively. , and These represent the x-axis error, y-axis error, and z-axis error, respectively. In step 1, the method for determining the optimal speckle diameter is as follows: Step 1.1: Based on the number of pixels that the speckle needs to cover, initially determine the diameter range of the speckle. Based on the diameter range of the speckle and the surface roughness of the sample to be tested, determine multiple candidate speckle diameters. Step 1.2: Determine the speckle type based on the sample surface parameters; Step 1.3: After setting the corresponding type of speckle target on the target plate, mount the target plate on a multi-axis precision platform. Control the multi-axis precision platform to make the speckle target move in steps along the preset direction multiple times. After each step, perform 3D-DIC measurement to obtain the DIC measurement displacement of the speckle target at each movement step length, and then calculate the average value of each DIC measurement displacement. Standard deviation σ d And the average calculation time t for each DIC measured displacement; Step 1.4: Change the diameter of the speckle target and repeat step 1.3; Step 1.5: Calculate the comprehensive fit index Q corresponding to each different speckle target diameter, and determine the speckle diameter based on the comprehensive fit index Q. The calculation formula is as follows: ； Where ω1 and ω2 represent weighting coefficients, and t0 represents the baseline time.

2. The 3D-DIC measurement method based on a multi-axis precision platform according to claim 1, characterized in that, In step 4, the original three-dimensional DIC measurement displacement is calculated based on the 3D-DIC measurement image and the DIC algorithm. Before calculating the original three-dimensional measurement displacement based on the DIC algorithm, a preprocessing step of grayscale correction of the image is also included. The formula for grayscale correction is: ； in, Represents the original grayscale value. This represents the corrected grayscale value. This represents the local average gray value. This represents the average grayscale value of the entire image.

3. The 3D-DIC measurement method based on a multi-axis precision platform according to claim 1, characterized in that, In step 1.1, the diameter range of the speckle pattern is: ； in, The diameter of the speckle is represented by k, k0 and k2 represent the lower and upper limits of the pixels covered by the speckle, respectively, and L represents the distance between the camera and the target. This indicates the focal length of the initially selected lens.

4. The 3D-DIC measurement method based on a multi-axis precision platform according to claim 1, characterized in that, In step 2, the method for determining the optimal focal length is as follows: Step 2.1: Combine with the maximum field of view (FOV) max With target measurement accuracy δ req Determine the lower limit of the focal length; Step 2.2: Determine multiple sets of candidate focal lengths based on the lower limit of the focal length; Step 2.3: Set up a speckle target with the optimal speckle diameter on the surface of the test sample, install the corresponding lens according to the selected focal length, and adjust the camera position to ensure that the field of view covers the entire target; Step 2.4: After driving the speckle target along a preset direction with a minimum step displacement based on the multi-axis precision platform, perform 3D-DIC measurement to obtain the DIC measurement displacement and calculate the measurement deviation. Determine whether the measurement deviation meets the accuracy safety conditions. If not, gradually increase the step displacement value of the speckle target and repeat the 3D-DIC measurement until the measurement deviation meets the accuracy safety conditions. The corresponding step displacement value is the resolution limit at that focal length. At the same time, based on the resolution limit Determine the field of view and measurement error corresponding to this focal length; Step 2.5: Change the lens focal length to other values ​​among the candidate focal lengths, and repeat steps 2.3-2.4 until the resolution limit, field of view and measurement error corresponding to all candidate focal lengths are obtained; Step 2.6: Under the premise that the resolution limit and field of view meet the measurement requirements, select the focal length with the smallest measurement error as the optimal focal length.

5. The 3D-DIC measurement method based on a multi-axis precision platform according to claim 4, characterized in that, In step 2.4, the accuracy safety condition is as follows: Δδ≤±δ req / k4; Where, δ req Δδ represents the target measurement accuracy, k4 represents the measurement deviation, and k4 represents the accuracy safety factor.

6. The 3D-DIC measurement method based on a multi-axis precision platform according to claim 4, characterized in that, In step 2.1, the formula for calculating the lower limit of focal length is: ； in, Indicates the lower limit of focal length. Indicates the number of pixels horizontally in the camera. s The field of view (FOV) represents the physical size of a single pixel, L represents the distance between the camera and the target. max δ represents the maximum field of view. req Indicates the target measurement accuracy.

7. A 3D-DIC measurement device based on a multi-axis precision platform, used to implement the 3D-DIC measurement method based on a multi-axis precision platform as described in any one of claims 1-6, characterized in that, include: Multi-axis precision moving platform for installing target components; A 3D optical imaging system, comprising two industrial cameras and lenses with identical parameters, for acquiring 3D images; Lighting systems are used to provide light sources; A control and synchronization system is used to control the motion of the multi-axis precision moving platform and the timing of image acquisition; The data processing system is used to calculate the displacement information of the test sample based on the 3D image acquired by the 3D optical imaging system, and to perform edge correction on the displacement information of the test sample according to the error correction model.

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