Non-contact micro strain measurement method and device suitable for particle reinforced composite material, electronic equipment and medium

Abstract

The invention provides a non-contact micro strain measurement method and device suitable for a particle reinforced composite material, electronic equipment and a medium, the method comprises the following steps: generating a circular frame group by adopting an adaptive algorithm according to the gray difference between particles and a matrix, each circular frame in the circular frame group comprising one particle; calculating rigid body motion of particles in each circular frame in the circular frame group to obtain a particle displacement data group; and according to the particle displacement data group, fitting by adopting a moving least square method to obtain the strain of the matrix between the particles. According to the method, artificial preparation of stripes is not needed, and accurate measurement of the surface deformation of the particle reinforced composite material is realized only by means of the gray difference between the reinforcing phase and the matrix.

Description

Technical Field

[0001] The present invention belongs to the field of measurement technology and relates to a strain measurement method for particle reinforced composite materials, and in particular to a contactless microscopic strain measurement method, device, electronic equipment and medium suitable for particle reinforced composite materials. Background Art

[0002] As a non-uniform multi-phase material, particle reinforced composites are characterized by non-continuous particles as the reinforcement phase. Compared with homogeneous single-phase materials, particle reinforced composites have more complex deformation at the microscopic scale. In order to study the failure mechanism and particle reinforcement effect of particle reinforced composites, we need to measure the strain field inhomogeneity caused by the multi-phase structure of the material at the microscopic scale. The conventional measurement method is Digital Image Correlation (DIC), which obtains the displacement and deformation information of the surface by comparing the images of the material surface before and after deformation. However, for materials with less obvious surface grayscale differences, it is necessary to prepare artificial patterns on the material surface.

[0003] The particles on the surface of particle-reinforced composites can provide the speckles required by DIC technology, but the quality of the speckles is not high and cannot meet the needs of accurate deformation measurement. If the speckles are artificially prepared, the speckles will affect the observation of the reinforcement phase particles. Summary of the invention

[0004] In order to solve the technical problems existing in the prior art, the present invention provides a contactless microscopic strain measurement method, device, electronic equipment and medium suitable for particle reinforced composite materials. The method does not require artificial preparation of patterns, and only relies on the grayscale difference between the reinforcement phase and the matrix to achieve accurate measurement of the surface deformation of the particle reinforced composite material.

[0005] In order to achieve the above technical effects, the present invention adopts the following technical solutions:

[0006] One of the purposes of the present invention is to provide a non-contact microscopic strain measurement method applicable to particle reinforced composite materials, the measurement method comprising:

[0007] According to the grayscale difference between the particle and the matrix, a circular frame group is generated by using an adaptive algorithm, and each circular frame in the circular frame group contains one particle;

[0008] The DIC algorithm is used to calculate the rigid body motion of the particles in each circle in the circle group to obtain a particle displacement data group;

[0009] Based on the particle displacement data set, the strain of the matrix between each of the particles is obtained by using the moving least squares method.

[0010] As a preferred technical solution of the present invention, the number of grayscale gradients inside the circular frame is represented by the sum of squares of the grayscale gradients inside the circular frame, as shown in Formula 1;

[0011] Formula 1;

[0012] Among them, SSSIG represents the sum of the squares of the grayscale gradients of all pixels in the circular frame, ∇f_i represents the grayscale gradient of the i-th pixel in the circular frame, and i is the pixel number.

[0013] As a preferred technical solution of the present invention, the adaptive algorithm includes:

[0014] Selecting a continuous pixel region, in which the grayscale of each pixel is greater than a first threshold, assuming that the grayscale value of the particle is greater than the grayscale value of the matrix;

[0015] The grayscale weighted center of the calculated area is used as the center of the circular frame, and the initial radius of the circular frame is given;

[0016] Calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG0; increase the radius of the circular frame by one pixel, calculate the sum of squares of grayscale gradients in the circular frame again, recorded as SSSIG1; if (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, and SSSIG1 is greater than the third threshold, output the circular frame; if (SSSIG1-SSSIG0) / SSSIG0 is greater than the second threshold, increase the radius by one pixel again, calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG2, and determine the relationship between (SSSIG2-SSSIG1) / SSSIG1 and the second threshold; repeat the above steps until (SSSIG n -SSSIG n-1 ) / SSSIG n-1 is less than the second threshold, and SSSIG n is greater than the third threshold, then the circle is output; if SSSIG n If it is less than a third threshold, the area is abandoned, and n is an integer greater than or equal to 1.

[0017] As a preferred technical solution of the present invention, the first threshold is the grayscale at the interface between the matrix and the particles;

[0018] The second threshold is the minimum relative increment of the gray gradient square sum;

[0019] The third threshold is the sum of squares of grayscale gradients within the lowest circular frame.

[0020] As a preferred technical solution of the present invention, a DIC algorithm is used to calculate the rigid body motion of the particles in each circular frame in the circular frame group.

[0021] As a preferred technical solution of the present invention, the method of moving least squares fitting calculation includes:

[0022] A moving window is defined around the fitting calculation points of the matrix, wherein the moving window includes at least three particles;

[0023] The representation function of the displacement field of the moving window is selected, and the displacement of the particles in the moving window is fitted using the least square method to obtain the displacement field of the fitting calculation point, and the strain of the fitting calculation point is obtained by derivation of the displacement field of the fitting calculation point.

[0024] As a preferred technical solution of the present invention, the representation function of the displacement field of the moving window includes a polynomial function or a trigonometric function.

[0025] The second object of the present invention is to provide a non-contact microscopic strain measurement device suitable for particle reinforced composite materials, the measurement device comprising:

[0026] An adaptive particle selection module, used to generate a circular frame group using an adaptive algorithm according to the grayscale difference between the particle and the matrix, each circular frame in the circular frame group contains one particle;

[0027] A particle rigid body motion measurement module is used to calculate the rigid body motion of particles in each circular frame in the circular frame group to obtain a particle displacement data group;

[0028] The overall strain measurement module is used to obtain the strain of the matrix between each particle by fitting and calculating the particle displacement data set using the moving least square method.

[0029] A third object of the present invention is to provide an electronic device, the electronic device comprising:

[0030] at least one processor and a memory communicatively coupled to the at least one processor;

[0031] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the contactless microscopic strain measurement method applicable to particle-reinforced composite materials provided in accordance with one of the purposes of the present invention.

[0032] A fourth object of the present invention is to provide a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a processor to implement one of the objects of the present invention when executing the non-contact micro-strain measurement method suitable for particle-reinforced composite materials.

[0033] Compared with the prior art, the present invention has at least the following beneficial effects:

[0034] (1) The present invention provides a non-contact microscopic strain measurement method applicable to particle-reinforced composite materials. Since the method does not require the preparation of artificial speckles, the influence of artificial speckles on the microscopic structure observation of the composite materials can be avoided.

[0035] (2) The present invention provides a non-contact microscopic strain measurement method suitable for particle-reinforced composite materials. The method highly optimizes the circular frame, i.e., the solution area for the rigid body motion of a single particle, and includes as many grayscale gradients and less noise as possible, thereby improving the solution accuracy of the rigid body motion of a single particle;

[0036] (3) The present invention provides a non-contact microscopic strain measurement method suitable for particle-reinforced composite materials. In this method, the displacement and strain field of the matrix between particles are calculated by the moving least squares method, and the flexibility of fitting can be adjusted by selecting different polynomial orders or basis functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flowchart of an adaptive algorithm for generating a circle frame group in a specific implementation manner of the present invention;

[0038] Figure 2 An adaptive circular frame generated in a specific implementation of the present invention;

[0039] Figure 3 The displacement field calculated by the adaptive circular frame generated in the specific implementation mode of the present invention;

[0040] Figure 4 It is the strain field obtained by fitting the particle displacement field in a specific embodiment of the present invention.

[0041] The present invention is further described in detail below. However, the following examples are only simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described below through specific implementation methods.

[0043] The specific embodiment of the present invention provides a non-contact microscopic strain measurement method applicable to particle reinforced composite materials, the measurement method comprising:

[0044] According to the grayscale difference between the particle and the matrix, a circular frame group is generated by using an adaptive algorithm, and each circular frame in the circular frame group contains one particle;

[0045] The DIC algorithm is used to calculate the rigid body motion of the particles in each circle in the circle group to obtain a particle displacement data group;

[0046] Based on the particle displacement data set, the strain of the matrix between each of the particles is obtained by using the moving least squares method.

[0047] In the present invention, the movement area of ​​the particles is framed and the movement area, i.e., the circular frame, is optimized and solved so that the circular frame contains as many grayscale gradients as possible and as little noise as possible, thereby improving the solution accuracy of the particle uplift motion and eliminating the need to prepare artificial patterns, thereby avoiding the influence of artificial patterns on the microstructure observation of the composite material.

[0048] In a specific embodiment of the present invention, the materials of the particles and the matrix are not specifically limited, and the particles and the matrix that can be used to make the particle-reinforced composite material are suitable for the non-contact microscopic strain measurement method provided by the present invention. As an example, the material of the particles can be aluminum alloy, and the material of the matrix can be ceramic particles (such as TiB2).

[0049] In the present invention, the grayscale gradient within the circular frame determines the accuracy of the DIC algorithm in calculating the rigid body motion of the particles, so the circular frame needs to encompass the boundaries of the particles and the matrix as much as possible; at the same time, the size of the circular frame should not be too large to avoid including too much image noise inside the circular frame.

[0050] In a specific implementation of the present invention, the number of grayscale gradients within the circular frame is represented by the sum of squares of the grayscale gradients within the circular frame, as shown in Formula 1;

[0051] Formula 1;

[0052] Among them, SSSIG represents the sum of squares of grayscale gradients within the circle. Represents the i-th grayscale gradient value in the circular frame, i represents the number of grayscale gradients in the circular frame, and i is an integer not less than .

[0053] In one specific embodiment of the present invention, the process of the adaptive algorithm for generating the circle frame group is as follows: Figure 1 As shown, it specifically includes:

[0054] Selecting a continuous pixel region, in which the grayscale of each pixel is greater than a first threshold, assuming that the grayscale value of the particle is greater than the grayscale value of the matrix;

[0055] The grayscale weighted center of the calculated area is used as the center of the circular frame, and the initial radius of the circular frame is given;

[0056] Calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG0; increase the radius of the circular frame by one pixel, calculate the sum of squares of grayscale gradients in the circular frame again, recorded as SSSIG1; if (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, and SSSIG1 is greater than the third threshold, output the circular frame; if (SSSIG1-SSSIG0) / SSSIG0 is greater than the second threshold, increase the radius by one pixel again, calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG2, and determine the relationship between (SSSIG2-SSSIG1) / SSSIG1 and the second threshold; repeat the above steps until (SSSIG n -SSSIG n-1 ) / SSSIG n-1 is less than the second threshold, and SSSIG n is greater than the third threshold, then the circle is output; if SSSIG n If it is less than a third threshold, the area is abandoned, and n is an integer greater than or equal to 1.

[0057] In a specific embodiment of the present invention, the first threshold is set based on the average grayscale value of the matrix and the particles, ensuring that the selected circular frame is close to the boundary between the particles and the matrix.

[0058] In a specific embodiment of the present invention, the method for calculating the weighted center of grayscale in a continuous pixel area is:

[0059]

[0060]

[0061] in, , , are the x, y coordinates and grayscale values ​​of the pixel respectively.

[0062] In a specific implementation of the present invention, the initial radius of the circular frame is set based on an estimate of the average size of particles in the image, for example, it can be set to 5.

[0063] In a specific implementation of the present invention, the relationship between the sum of squares of the grayscale gradient inside the circular frame under the initial radius and the sum of squares of the grayscale gradient inside the circular frame under the first radius (initial radius + 1 pixel) is determined by the formula (SSSIG1-SSSIG0) / SSSIG0 and the second threshold. If (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, the next step of judgment is performed; if (SSSIG1-SSSIG0) / SSSIG0 is greater than or equal to the second threshold, the radius is continuously increased, and the judgment is repeated until (SSSIG1-SSSIG0) / SSSIG0 is greater than or equal to the second threshold. n -SSSIG n-1 ) / SSSIGn-1 When it is less than the second threshold, it proceeds to the next step of judgment. n-1 represents the sum of squares of grayscale gradients inside the circular frame at the n-1th radius (initial radius + n-1 pixels), n represents the sum of squares of grayscale gradients inside the circular frame at the nth radius (initial radius + n pixels), and n is an integer greater than or equal to 1.

[0064] In a specific embodiment of the present invention, the second threshold is set according to the actual situation. If it is too large, the circular frame may be too small to contain the entire particle. If it is too small, the circular frame may be too large and include too much matrix. It is usually set to 10%. In actual operation, a second threshold can be preset first and then adjusted according to the size of the circular frame.

[0065] In one specific embodiment of the present invention, when (SSSIG n -SSSIG n-1 ) / SSSIG n-1 When it is less than the second threshold (n is an integer greater than or equal to 1), the SSSIG n The relationship between the size of the third threshold is that if SSSIG n If SSSIG is greater than the third threshold, the circle is output. n If the value is less than the third threshold, the circle frame is discarded.

[0066] In a specific embodiment of the present invention, the third threshold is set according to the actual situation. If it is too small, the sum of squares of grayscale gradients contained in the circular frame is insufficient, affecting the DIC measurement accuracy. If it is too large, the number of available circular frames is too small, affecting the subsequent displacement field fitting. In the actual operation, a third threshold can be preset first, and then adjusted according to the number of circular frames. For example, it can be set to 5×10 8 .

[0067] In a specific embodiment of the present invention, since the rigidity of the reinforced particles is much higher than that of the matrix, they can be regarded as rigid bodies without considering deformation, so the rigid body motion of the particles can adopt the conventional rigid body motion DIC algorithm.

[0068] In one embodiment of the present invention, the moving least squares method is an algorithm for interpolating and smoothing data, which applies the least squares method within a local area.

[0069] In a specific implementation of the present invention, the method of moving least squares fitting calculation includes:

[0070] A moving window is defined around the fitting calculation point of the matrix, wherein the moving window includes at least two particles;

[0071] The representation function of the displacement field of the moving window is selected, and the displacement of the particles in the moving window is fitted using the least square method to obtain the displacement field of the fitting calculation point, and the strain of the fitting calculation point is obtained by derivation of the displacement field of the fitting calculation point.

[0072] In a specific implementation of the present invention, the moving window is a local area around the fitting calculation point, and the local area contains a number of particles, and the displacement data of each particle has been obtained in the previous step.

[0073] In a specific embodiment of the present invention, the representation function of the displacement field of the moving window can be a polynomial function, a trigonometric function, etc. Preferably, it is a polynomial function. In order to reflect the uniform displacement pattern, the representation function needs to include a constant term. In order to reflect the uniform strain pattern, the representation function needs to include the first-order terms of x and y. In order to reflect the inhomogeneity of the strain field, the representation function also needs to include the high-order terms of x and y. Here, only the quadratic terms are taken. The moving window contains at least three particles, and the three particles contain six degrees of freedom. Therefore, corresponding to the six basis functions of the selected fitting function, as an example, the representation function of the displacement field can be

[0074]

[0075] in, ~ are basis function coefficients.

[0076] A specific embodiment of the present invention provides a non-contact microscopic strain measurement device suitable for particle reinforced composite materials, the measurement device comprising:

[0077] An adaptive particle selection module, used to generate a circular frame group using an adaptive algorithm according to the grayscale difference between the particle and the matrix, each circular frame in the circular frame group contains one particle;

[0078] A particle rigid body motion measurement module is used to calculate the rigid body motion of particles in each circular frame in the circular frame group to obtain a particle displacement data group;

[0079] The overall strain measurement module is used to obtain the strain of the matrix between each particle by fitting and calculating the particle displacement data set using the moving least square method.

[0080] In a specific embodiment of the present invention, the adaptive particle selection module, the particle rigid body motion measurement module and the overall strain measurement module can be connected by any connection method that can achieve electromagnetic signal transmission while satisfying the operation order, and no specific limitation is made here.

[0081] A specific embodiment of the present invention provides an electronic device, the electronic device comprising:

[0082] at least one processor and a memory communicatively coupled to the at least one processor;

[0083] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the contactless microscopic strain measurement method applicable to particle-reinforced composite materials provided in the specific embodiment of the present invention.

[0084] A specific embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions. The computer instructions are used to enable a processor to implement the non-contact microscopic strain measurement method applicable to particle-reinforced composite materials provided by the specific embodiment of the present invention when executed.

[0085] To better illustrate the present invention and facilitate understanding of the technical solution of the present invention, typical but non-limiting embodiments of the present invention are as follows:

[0086] Example 1

[0087] This embodiment provides a non-contact microscopic strain measurement method applicable to particle-reinforced composite materials, wherein the matrix is ​​an aluminum alloy, the particles are TiB2 ceramic particles, the particle size is 1-10 μm, and the mass percentage of the particles is 6%. The measurement method includes:

[0088] According to the grayscale difference between the particles and the matrix, an adaptive algorithm is used to generate a circle frame group, each circle frame in the circle frame group contains a particle;

[0089] Adaptive algorithms include:

[0090] Selecting a continuous pixel region, wherein the grayscale of each pixel in the continuous pixel region is greater than a first threshold;

[0091] The grayscale weighted center of the calculated area is used as the center of the circular frame, and the initial radius of the circular frame is given;

[0092] Calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG0; increase the radius of the circular frame by one pixel, calculate the sum of squares of grayscale gradients in the circular frame again, recorded as SSSIG1; if (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, and SSSIG1 is greater than the third threshold, output the circular frame; if (SSSIG1-SSSIG0) / SSSIG0 is greater than the second threshold, increase the radius by one pixel again, calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG2, and determine the relationship between (SSSIG2-SSSIG1) / SSSIG1 and the second threshold; repeat the above steps until (SSSIG n -SSSIG n-1 ) / SSSIG n-1is less than the second threshold, but due to SSSIG n It is smaller than the third threshold, so the area is abandoned.

[0093] Example 2

[0094] This embodiment uses the same adaptive algorithm as in Embodiment 1 to generate the circular frame group, but reselects a continuous pixel region, where the grayscale of each pixel in the continuous pixel region is greater than the first threshold;

[0095] The grayscale weighted center of the calculated area is used as the center of the circular frame, and the initial radius of the circular frame is given;

[0096] Calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG0; increase the radius of the circular frame by one pixel, calculate the sum of squares of grayscale gradients in the circular frame again, recorded as SSSIG1; if (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, and SSSIG1 is greater than the third threshold, output the circular frame; if (SSSIG1-SSSIG0) / SSSIG0 is greater than the second threshold, increase the radius by one pixel again, calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG2, and determine the relationship between (SSSIG2-SSSIG1) / SSSIG1 and the second threshold; repeat the above steps until (SSSIG n -SSSIG n-1 ) / SSSIG n-1 is less than the second threshold, and SSSIG n It is greater than the third threshold, so the circle is output.

[0097] Repeat the process of Example 1 and Example 2 until a circular frame group is obtained, and the result is as follows: Figure 2 shown.

[0098] Example 3

[0099] This embodiment uses the DIC algorithm to calculate the rigid body motion of each particle in the circular frame group, and the result is as follows: Figure 3 shown.

[0100] Example 4

[0101] This embodiment uses the calculation results of Example 3 and the moving least squares method to calculate the overall strain of the particle reinforced composite material. The moving least squares method fitting calculation method includes:

[0102] A moving window is defined around the fitting calculation point of the matrix, wherein the moving window includes at least two particles;

[0103] The polynomial or basis function of the displacement field of the moving window is selected, and the displacement of the particles in the moving window is fitted using the least square method to obtain the displacement field of the fitting calculation point, and the displacement field of the fitting calculation point is derived to obtain the strain of the fitting calculation point.

[0104] In this embodiment, the polynomial or basis function selected is .

[0105] The matrix of the particle-reinforced composite material used in this embodiment is aluminum alloy, the particles are TiB2, the particle size is 1-10 μm, and the mass percentage of the particles is 6%.

[0106] The overall strain calculation results of the particle reinforced composite material are shown in Figure 4 shown.

[0107] Example 5

[0108] This embodiment provides a non-contact microscopic strain measurement device applicable to particle-reinforced composite materials, which is used in the non-contact microscopic strain measurement method applicable to particle-reinforced composite materials in embodiments 1-4. The measurement device includes:

[0109] An adaptive particle selection module, used to generate a circular frame group using an adaptive algorithm according to the grayscale difference between the particle and the matrix, each circular frame in the circular frame group contains one particle;

[0110] A particle rigid body motion measurement module is used to calculate the rigid body motion of particles in each circular frame in the circular frame group to obtain a particle displacement data group;

[0111] The overall strain measurement module is used to obtain the strain of the matrix between each particle using the interpolation method based on the particle displacement data set.

[0112] The applicant declares that the present invention illustrates the detailed structural features of the present invention through the above-mentioned embodiments, but the present invention is not limited to the above-mentioned detailed structural features, that is, it does not mean that the present invention must rely on the above-mentioned detailed structural features to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of the components selected by the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

[0113] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0114] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0115] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A non-contact microscopic strain measurement method suitable for particle reinforced composite materials, characterized in that: The measuring method comprises: According to the grayscale difference between the particle and the matrix, a circle frame group is generated by using an adaptive algorithm, each circle frame in the circle frame group contains one particle; Calculating the rigid body motion of the particles in each circular frame in the circular frame group to obtain a particle displacement data group; According to the particle displacement data set, the strain of the matrix between each of the particles is calculated by using the moving least squares fitting method.

2. The measuring method according to claim 1, characterized in that: The number of grayscale gradients inside the circular frame is represented by the sum of squares of the grayscale gradients inside the circular frame, as shown in Formula 1; Formula 1; Among them, SSSIG represents the sum of the squares of the grayscale gradients of all pixels in the circle. Represents the grayscale gradient of the i-th pixel in the circle, where i is the pixel number.

3. The measuring method according to claim 2, characterized in that: The adaptive algorithm includes: Selecting a continuous pixel region, wherein the grayscale of each pixel in the continuous pixel region is greater than a first threshold, assuming that the grayscale value of the particle is greater than the grayscale value of the matrix; Calculating the grayscale weighted center of the region as the center of the circular frame, and giving the initial radius of the circular frame; Calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG0; increase the radius of the circular frame by one pixel, calculate the sum of squares of grayscale gradients in the circular frame again, recorded as SSSIG1; if (SSSIG1-SSSIG0) / SSSIG0 is less than the second threshold, and SSSIG1 is greater than the third threshold, output the circular frame; if (SSSIG1-SSSIG0) / SSSIG0 is greater than the second threshold, increase the radius by one pixel again, calculate the sum of squares of grayscale gradients in the circular frame, recorded as SSSIG2, and determine the relationship between (SSSIG2-SSSIG1) / SSSIG1 and the second threshold; repeat the above steps until (SSSIG n -SSSIG n-1 ) / SSSIG n-1 is less than the second threshold, and SSSIG n is greater than the third threshold, then the circle is output; if SSSIG n If it is less than a third threshold, the area is abandoned, and n is an integer greater than or equal to 1.

4. The measuring method according to claim 3, characterized in that: The first threshold is the gray value at the junction of the matrix and the particle, ensuring that all pixels in the circle are at the particle; The second threshold is the minimum relative increment of the grayscale gradient square sum, ensuring that the grayscale gradient square sum in the selected circular frame does not increase significantly with the increase of the radius; The third threshold is the sum of squares of grayscale gradients in the lowest circular frame, ensuring that there is enough sum of squares of grayscale gradients in the selected circular frame to ensure the DIC measurement accuracy.

5. The measuring method according to claim 1, characterized in that: The DIC algorithm is used to calculate the rigid body motion of the particles in each circle in the circle group.

6. The measuring method according to claim 1, characterized in that: The moving least squares fitting calculation method includes: defining a moving window around the fitting calculation point of the matrix, wherein the moving window includes at least three particles; A representation function of the displacement field of the moving window is selected, and the displacement of the particles in the moving window is fitted using the least squares method to obtain the displacement field of the fitting calculation point, and the strain of the fitting calculation point is obtained by derivation of the displacement field of the fitting calculation point.

7. The measuring method according to claim 6, characterized in that: The representation function of the displacement field of the moving window includes a polynomial function or a trigonometric function.

8. A non-contact microscopic strain measurement device suitable for particle reinforced composite materials, characterized in that: The measuring device comprises: An adaptive particle selection module, used to generate a circle frame group using an adaptive algorithm according to the grayscale difference between the particle and the matrix, each circle frame in the circle frame group contains one particle; A particle rigid body motion measurement module is used to calculate the rigid body motion of the particles in each circular frame in the circular frame group to obtain a particle displacement data group; The overall strain measurement module is used to obtain the strain of the matrix between each of the particles by fitting and calculating the particle displacement data group using the moving least square method.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the contactless micro-strain measurement method applicable to particle-reinforced composite materials as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the non-contact microscopic strain measurement method applicable to particle-reinforced composite materials as described in any one of claims 1 to 7 when executed.

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