Method and Device for Monitoring Shear Cracks in Reinforced Concrete Beams Based on Digital Imaging Technology

Abstract

This invention discloses a method for monitoring shear cracks in reinforced concrete beams based on digital image technology, comprising the following steps: Step 1, acquiring a surface image of a reinforced concrete beam specimen and using the DIC digital image detection method to obtain the principal tensile strain across the entire field in the reinforced concrete beam specimen; Step 2, generating a crack skeleton line corresponding to the crack based on the principal tensile strain across the entire field; Step 3, setting multiple sets of crack measurement reference points on both sides of the crack skeleton line and calculating the motion vector of the cracked area on both sides of each set of crack measurement reference points; Step 4, generating the overall motion of the corresponding crack based on the motion vectors of the multiple sets of crack measurement reference points and outputting the corresponding motion vector result image based on the motion. This invention also provides a device for monitoring shear cracks in reinforced concrete beams. The method provided by this invention can effectively assess the safety and residual life of concrete structures.

Description

Technical Field

[0001] This invention belongs to the field of crack detection in concrete structures, and particularly relates to a method and device for monitoring shear cracks in reinforced concrete beams based on digital image technology. Background Technology

[0002] Concrete possesses excellent durability and strength properties, making it widely used in various building, bridge, and road engineering projects. However, due to repeated pouring, vibration, and external forces during construction, concrete is prone to cracking. This not only reduces the strength and service life of the concrete but also affects the aesthetics and safety of the building. Therefore, a comprehensive and systematic detection and evaluation of cracks in concrete structures is essential. Traditional measurement methods often use visual inspection, strain gauges, and displacement meters to record the mechanical response information of the structure during testing. However, these methods are time-consuming and labor-intensive, and can only reflect measurement information at single points, exhibiting considerable limitations. As a non-contact, full-field measurement method, Digital Image Correlation (DIC) technology has been successfully applied to the recording and analysis of test data for various new composite materials, different structural systems, and application scenarios. For example, DIC technology is used to qualitatively monitor crack conditions in large bridge decks; in the low-cycle repeated failure test of shear walls, the DIC method is used to compare with manual and displacement meter records, and the displacement information obtained using the DIC method provides a preliminary analysis of shear wall structural damage. These tests demonstrate that the accuracy of DIC technology for displacement and strain monitoring is comparable to that of traditional methods, and it also has advantages such as full-field monitoring that traditional measurement methods cannot achieve.

[0003] In shear tests of concrete specimens, the crack propagation patterns are complex and diverse, and the crack propagation direction is often arbitrary. For concrete cracks propagating in arbitrary directions, existing DIC methods struggle to achieve high-precision extraction and quantification, and existing theoretical models also struggle to accurately predict and characterize the entire evolution of concrete shear cracks. This poses challenges to a deeper understanding of the mechanical properties of damaged concrete.

[0004] Therefore, to ensure the scientific rigor and effectiveness of concrete testing and subsequent theoretical analysis, and to gain a deeper understanding of the properties of damaged concrete, the primary challenge is to address the accurate observation, recording, and information extraction of cracks throughout the entire testing process. Achieving rapid and accurate extraction and quantification of cracks in any direction across the entire field, based on effective observation of the components, remains a significant challenge.

[0005] Patent document CN116797703A discloses an image-based method for processing strain distribution in concrete crack areas, comprising: Step 1: acquiring multiple images of the concrete specimen to be tested taken consecutively; Step 2: using the first frame image as a reference image, selecting the calculation area in the reference image, setting calculation points, and setting the subset and search range size; Step 3: calculating the gradient and the inverse of the Hessian matrix on the selected initial reference image; Step 4: performing integer pixel displacement calculation on all calculation points, performing sub-pixel displacement calculation based on the integer pixel calculation results, and rendering the displacement field; Step 5: calculating the strain field based on the displacement field and rendering the strain field cloud map.

[0006] Patent document CN116309305A discloses a micro-crack damage identification method based on machine vision and digital images, including the following steps: S1, obtaining speckle image data of concrete material surface through an image acquisition system; S2, processing the acquired speckle image data using the DIC image algorithm with FreeDIC software to obtain displacement field data and strain contour map data of the speckle image data; S3, processing the strain contour map data using machine vision technology with Matlab software to extract crack skeleton data of the obtained image; S4, obtaining crack quantization data of the speckle image data based on the displacement field data of crack skeleton data and speckle image data through the calculation principle of crack normal and tangential displacement of position vector. This method selects only four adjacent reference points around each crack reference point to reduce computational difficulty, but this also affects its final accuracy. Summary of the Invention

[0007] The purpose of this invention is to provide a method and device for monitoring shear cracks in reinforced concrete beams based on digital imaging technology. This method can effectively assess the safety and residual life of concrete structures.

[0008] To achieve the first objective of this invention, a method for monitoring shear cracks in reinforced concrete beams based on digital imaging technology is provided, comprising the following steps:

[0009] Step 1: Obtain a surface image of the reinforced concrete beam specimen and use the DIC digital image detection method to obtain the full-field principal tensile strain in the reinforced concrete beam specimen.

[0010] Step 2: Binarize the surface image based on the full-field principal tensile strain to determine the location of cracks, and generate crack skeleton lines corresponding to the cracks based on morphological operations.

[0011] Step 3: Set multiple sets of crack measurement reference points on both sides of the crack skeleton line, and calculate the motion vector of the cracked area on both sides of each set of crack measurement reference points;

[0012] Step 4: Based on the motion vectors of multiple sets of crack measurement reference points, generate the overall motion of the corresponding crack and output the corresponding motion vector result image based on the motion. The motion includes crack opening and slippage.

[0013] This invention uses DIC technology to extract, quantify, and monitor shear cracks in reinforced concrete beams in any direction. It avoids the dependence on the crack propagation direction when extracting crack information in traditional methods, and can achieve high-precision extraction of crack opening and slip information in any direction at any stage, which helps to deeply understand and evaluate the performance of damaged concrete.

[0014] Specifically, the process of obtaining the principal tensile strain across the entire field in step 1 is as follows:

[0015] The region of interest is delineated in the surface image, which includes a reference subset before loading deformation and a target subset after loading deformation.

[0016] The similarity between the reference subset and the target subset is evaluated based on the least squares correlation function to obtain the full-field principal tensile strain of the reinforced concrete beam specimen and save it as a matrix.

[0017] Specifically, a mapping function is used to transform each point in the reference subset into a corresponding target subset. The expression of the mapping function is as follows:

[0018]

[0019]

[0020] Where u and v are the displacements of the subset center point P(x0,y0) in the x and y directions, respectively; Δx and Δy are the distances from P to any point Q(x,y) within the subset; u x u y v x v y Let be the first derivatives of u and v in the x and y directions, respectively.

[0021] Specifically, when iterating through the Newton-Raphson method to solve the least squares correlation function to obtain the corresponding extreme value, a displacement field containing the horizontal strain field, vertical strain field and shear strain field is constructed, and the least squares method is used to locally fit the displacement field to obtain the corresponding full-field principal tensile strain.

[0022] The expression for the least squares correlation function is as follows:

[0023]

[0024] Among them, f m g m These are the average gray levels of the reference subset and the target subset, respectively. These are the six displacement vectors that need to be calculated;

[0025] The local fitting formula for the principal tensile strain across the entire field is as follows:

[0026]

[0027] Where ε1 is the principal tensile strain on the surface of the specimen, ε x ε represents the horizontal strain on the surface of the specimen. y γ is the vertical strain on the surface of the specimen. xy The shear strain is the surface strain of the specimen.

[0028] Specifically, the process of determining the existence of cracks in step 2 is as follows:

[0029] The judgment is based on the surface image after binarization. When the pixel color in the surface image is color1, the part with strain greater than the elastic strain threshold of the material is considered as crack.

[0030] When the pixel color in the surface image is color2, the portion with strain less than the threshold is considered uncracked.

[0031] Specifically, the morphological operation process is as follows:

[0032] MATLAB was used to perform image processing and edge detection on the binarized surface image in order to construct a crack skeleton line with a width of one pixel.

[0033] Specifically, the method for setting the crack measurement reference point is as follows:

[0034] Take any point on the crack skeleton line and denote it as point i. Denote the cracked areas on both sides of point i as side A and side B. Define n first reference points on side A and n second reference points on side B respectively.

[0035] Connect the first reference point on side A to the corresponding second reference point on side B in sequence, ensuring that the line connecting the first and second reference points is perpendicular to the crack skeleton line, and that the line connecting reference points on the same side is parallel to the crack skeleton line.

[0036] Specifically, in step 3, the motion vector expression for the cracked areas on both sides of each set of crack measurement reference points is as follows:

[0037] A-side region: δ Ai =(R Ai o i +t Ai )-o i

[0038] B-side region: δ Bi =(RBi o i +t Bi )-o i

[0039] Among them, R Aioi R represents the rotation vector of region A. Bioi The rotation vector t represents the region on side B. Ai t represents the translation vector of region A. Bi o represents the translation vector of region B. i The location of the crack point i in the undeformed state.

[0040] To achieve the second objective of the present invention, a device for monitoring shear cracks in reinforced concrete beams is provided, comprising a memory and one or more processors. The memory stores executable code, and when the one or more processors execute the executable code, they are used to implement the above-described method for monitoring shear cracks in reinforced concrete beams based on digital image technology.

[0041] The specific steps are as follows: obtain a surface image of the reinforced concrete beam specimen, and process the surface image using a method for monitoring shear cracks in reinforced concrete beams to output the corresponding motion vector result image.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] A method for extracting, quantifying, and monitoring shear cracks in reinforced concrete beams in any direction based on DIC technology avoids the dependence on crack propagation direction when extracting crack information in traditional methods. It can achieve high-precision extraction of crack opening and slip information in any direction at any stage, which helps to deeply understand and evaluate the performance of damaged concrete and has important application prospects in the safety evaluation and residual life prediction of concrete engineering structures. Attached Figure Description

[0044] Figure 1 This is a flowchart of the method for monitoring shear cracks in reinforced concrete beams provided in this embodiment;

[0045] Figure 2 This is a schematic diagram of the loading system layout during the loading process provided in this embodiment;

[0046] Figure 3 This is a schematic diagram showing the arrangement of the specimen and camera during the loading process provided in this embodiment;

[0047] Figure 4 This is a schematic diagram illustrating the basic principle of the DIC digital image detection method provided in this embodiment;

[0048] Figure 5 This is a schematic diagram of the binarization operation provided in this embodiment;

[0049] Figure 6 This is a schematic diagram of crack skeleton line extraction provided in this embodiment;

[0050] Figure 7 This is a schematic diagram illustrating the definition of crack measurement reference points provided in this embodiment;

[0051] Figure 8 This is a schematic diagram of crack motion calculation provided in this embodiment;

[0052] Figure 9 This example compares the crack initiation information provided with manually recorded crack information. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, this embodiment provides a method for monitoring shear cracks in reinforced concrete beams based on digital image correlation (DIC) technology, including the following steps:

[0055] (1) Loading was applied to the prepared reinforced concrete specimens, and digital image correlation (DIC) was used to monitor the entire loading process. Crack skeleton lines were identified and extracted from the DIC results of the specimen loading using threshold segmentation and morphological operations.

[0056] Step (1) includes the following sub-steps:

[0057] (1.1) Pre-treatment of the surface of the prepared reinforced concrete specimen: First, spray a uniform matte white paint on the surface of the concrete specimen, and then spray a black random speckle pattern to obtain a high-precision, high-contrast random uniform speckle field.

[0058] (1.2) Loading system of concrete beam members as follows Figure 2As shown. Throughout the loading process, a high-resolution camera (greater than 20 megapixels) was used to monitor the surface of the specimen. The camera's optical axis should be perpendicular to the specimen surface and maintained at a constant distance from it. To reduce the influence of external light on the experiment during the long loading period, supplementary lights were placed on both sides of the specimen, and black light-blocking cloths were suspended behind the supplementary lights. The relative positions of the specimen and the camera during the loading process are shown in the figure. Figure 3 As shown.

[0059] (1.3) Based on the captured images of the specimen surface, the displacement field of the specimen surface during loading is obtained using digital image correlation (DIC) technology. Here, in-plane deformation of the specimen is generally considered, i.e., deformation within a two-dimensional plane. A region of interest (ROI), typically a square, is delineated on the specimen surface. The ROI before loading deformation is called the reference subset, and the ROI after loading deformation is called the target subset. Assuming that a set of adjacent points in the reference subset remains adjacent in the deformed target subset, when the reference subset is sufficiently small, it is assumed that the points in the reference subset will be transformed into the target subset as follows:

[0060]

[0061]

[0062] Where u and v are the displacements of the subset center point P(x0,y0) in the x and y directions, respectively; Δx and Δy are the distances from P to any point Q(x,y) within the subset; u x u y v x v y Let be the first derivatives of u and v in the x and y directions, respectively.

[0063] To solve for the displacement vectors before and after deformation, let f(x,y) and g(x',y') represent the grayscale distributions of the reference subset and the target subset, respectively. A correlation function (in this embodiment, the standardized least squares correlation function) is defined to evaluate the similarity between the two subsets:

[0064]

[0065] Where f m g m These are the average gray levels of the reference subset and the target subset, respectively. These are the six displacement vectors that need to be calculated. The Newton-Raphson method is typically used to iteratively solve the correlation function. When the correlation function reaches its extreme value, the reference subset and the target subset are most similar, at which point the displacements on the specimen surface can be obtained. The basic principles of digital image correlation technology are as follows Figure 4 As shown.

[0066] (1.4) Obtain the horizontal strain field, vertical strain field, and shear strain field of the specimen surface through the displacement field and save them in matrix format. Considering the unavoidable noise when calculating the displacement field, the strain field cannot be obtained by directly differentiating the displacement field. The least squares method is used to locally fit the displacement field. At this time, the least squares method acts as a two-dimensional differentiator, and the local strain is obtained by convolving it with the local displacement field. This two-dimensional differentiator slides on the specimen surface to calculate the full-field strain (horizontal strain, vertical strain, and shear strain).

[0067] (1.5) The principal tensile strain of the whole field is obtained through three strain fields, and the formula is as follows:

[0068]

[0069] Where ε1 is the principal tensile strain on the surface of the specimen, ε x ε represents the horizontal strain on the surface of the specimen. y γ is the vertical strain on the surface of the specimen. xy The shear strain is the value at the surface of the specimen. The principal tensile strains at each point on the specimen surface are calculated and saved as a matrix.

[0070] (1.6) Binarize the principal strain data image of the specimen surface calculated by DIC. The portion of strain greater than the material's elastic strain threshold is considered cracked, and the pixel color is color1 (black in this example); the portion of strain less than the threshold is considered uncracked, and the pixel color is color2 (white in this example). The binarization operation is illustrated below. Figure 5 As shown;

[0071] (1.7) Perform morphological operations on the binarized image. Use the image processing edge detection operator in MATLAB to obtain the skeleton line of the crack with a width of only one pixel, while maintaining the connectivity of the crack skeleton. The crack skeleton line extraction is as follows: Figure 6 As shown.

[0072] (2) Define multiple sets of crack measurement reference points on both sides of the crack skeleton line;

[0073] Step (2) includes the following sub-steps:

[0074] (2.1) Take any point on the crack skeleton line, denoted as point i. Denote the cracked areas on both sides of point i as side A and side B, and define a set of n reference points on each side. The line connecting the first reference points on both sides of the crack, i.e., Ai1 and Bi1, should be perpendicular to the crack skeleton line. The distance between Ai1 and Bi1 should be determined according to the crack situation (30 pixels in this example). If the cracks are dense, the distance should be appropriately reduced. For each point on each side (Ai1~Ai... n Bi1~Bi nThe line connecting Ai1 and Ai2 should be parallel to the crack skeleton line (in this example, Ai1 to Ai2). n The distance is 20 pixels. The reference point is defined as follows: Figure 7 As shown.

[0075] (3) Calculate the motion vectors of the cracked areas on both sides of the crack measurement point based on the motion of the specimen during loading;

[0076] Step (3) includes the following sub-steps:

[0077] (3.1) After shear deformation, the cracked area A side of the reinforced concrete beam specimen is analyzed. By fitting the motion vectors (including rotation and translation vectors) of all n reference points at crack point i, the motion vector of the cracked area A side can be obtained as shown in the following formula:

[0078]

[0079]

[0080] in This refers to the rotation angle of side A of the cracked area during the loading process.

[0081] The fitted displacement vector R can be obtained by minimizing the residual between the true displacement vector of the reference point (which can be directly obtained through DIC displacement field calculation) and the fitted displacement vector. Ai and t Ai :

[0082]

[0083] Where a ij It is the in-plane position of the reference point in the undeformed state, δ ij It is the corresponding displacement vector.

[0084] Based on the above formula, the motion vector of the cracked side A at crack point i can finally be written in the following form:

[0085] δ Ai =(R Ai o i +t Ai )-o i

[0086] Among them, o i The location of the crack point i in the undeformed state.

[0087] Similarly, the motion vector of the cracked side B can be obtained:

[0088] δ Bi =(R Bi o i +t Bi)-o i

[0089] (4) By calculating the motion vectors of the cracked areas on both sides of the crack measurement point, the overall motion of the crack is obtained, including the opening and slippage of the crack.

[0090] Step (4) includes the following sub-steps:

[0091] (4.1) By calculating the motion vectors of the cracked areas on both sides of the crack measurement point, the motion vector δ at point i of the crack is obtained. i :

[0092] δ i =δ Bi -δ Ai

[0093] Furthermore, the crack motion vector δ i It can be decomposed into the opening δ of the crack. n,i With slip δ t,i :

[0094] δ n,i =sin(θ) r,i )||δ i ||

[0095] δ t,i =cos(θ) r,i )||δ i ||

[0096] Where, θ r,i The local crack inclination angle at point i can be obtained by the following formula:

[0097]

[0098]

[0099] A schematic diagram of crack motion calculation is shown in Figure 8.

[0100] It can be seen that the rotation of the concrete specimen during loading was taken into account in the calculation of crack movement. θ is obtained. r,i After obtaining the parameters, the motion vector of the crack will be calculated more accurately.

[0101] The opening and slippage of a crack can be calculated from the above operations. In concrete member loading tests, by analyzing the DIC results under different load levels, the variation law of the width / slippage of multiple cracks with load can be calculated, thereby achieving real-time monitoring of the crack development process.

[0102] In the multiple shear tests of concrete beams conducted in this embodiment, a 1000t electro-hydraulic servo actuator was used to load the concrete beams until failure. Throughout the loading process, the DIC system was used to record the specimen response, and the crack monitoring method described in this invention was employed for crack extraction and quantification. Simultaneously, the location and propagation of cracks under each load level were manually recorded. A comparison was made between the crack initiation information calculated by this invention and the manually recorded crack information. Figure 9 As shown, the two results show a high degree of agreement, fully demonstrating the accuracy of the crack extraction quantification method of this invention.

[0103] This embodiment also provides a shear crack monitoring device for reinforced concrete beams, including a memory and one or more processors. The memory stores executable code. When the one or more processors execute the executable code, they are used to implement the shear crack monitoring method for reinforced concrete beams based on digital image technology provided in the above embodiment. The specific steps are as follows: the surface image of the reinforced concrete beam specimen is obtained, and the surface image is processed by the shear crack monitoring method for reinforced concrete beams to output the corresponding motion vector result image.

[0104] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions 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, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for monitoring shear cracks in reinforced concrete beams based on digital image technology, characterized by, The method comprises the following steps: Step 1: obtaining the surface image of the reinforced concrete beam specimen, and obtaining the full-field principal tensile strain in the reinforced concrete beam specimen by using a digital image detection method; Step 2: performing a binaryzation operation on the surface image based on the full-field principal tensile strain to determine the position of the existing crack, and performing a morphological operation to generate a crack skeleton line corresponding to the crack; Step 3: setting a plurality of crack measurement reference points on both sides of the crack skeleton line, and calculating the motion vector of the cracking area on both sides of each group of crack measurement reference points; The crack measurement reference points are set as follows: Take any point on the crack skeleton line and mark it as point i , the i crack region on both sides of the point is marked as side A and side B, and n first reference points are defined on side A and n second reference points are defined on side B, respectively. The first reference point on the A side is connected with the corresponding second reference point on the B side in sequence, and the connecting line of the first reference point and the second reference point is perpendicular to the crack skeleton line, and the connecting line of the reference points on the same side is parallel to the crack skeleton line; The motion vector expression of the crack region on both sides of each group of crack measurement reference points is as follows: the A-side region: ; the B-side region: ; wherein, represents the rotation vector of the A-side region, represents the rotation vector of the B-side region, represents the translation vector of the A-side region, represents the translation vector of the B-side region, denotes the position of the crack point in the undeformed state; i Step 4: based on the motion vectors of multiple groups of crack measurement reference points, the motion of the corresponding crack as a whole is generated, and a corresponding motion vector result image is output based on the motion, wherein the motion includes the opening and sliding of the crack.

2. The method for monitoring shear cracks of reinforced concrete beams based on digital image technology according to claim 1, characterized in that, In step 1, the full-field principal tensile strain is obtained as follows: An interested region is demarcated in the surface image, which includes a reference subset before loading deformation and a target subset after loading deformation; The similarity between the reference subset and the target subset is evaluated based on a least square correlation function to obtain the full-field principal tensile strain of the reinforced concrete beam specimen and save it in a matrix format.

3. The method of monitoring shear cracks in reinforced concrete beams based on digital image technology according to claim 2, wherein, The points in the reference subset are converted to the corresponding target subset by a mapping function whose expression is as follows: ; ; wherein, u , v is the displacement of the subset center point P ( x 0 , y 0) in the x and y directions, respectively; and are the distances between P to any point Q ( x , y ) in the subset, respectively; , , , are the first derivatives of u , v in the x and y directions, respectively.

4. The method for monitoring shear cracks of reinforced concrete beams based on digital image technology according to claim 2, characterized in that, By solving the least square correlation function through Newton-Raphson method to obtain the corresponding extreme value, a displacement field including horizontal strain field, vertical strain field and shear strain field is constructed, and the least square method is used to locally fit the displacement field to obtain the corresponding full-field principal tensile strain; the expression of the least square correlation function is as follows: ; wherein, f m , g m respectively are the average gray scale of the reference subset and the target subset; is the displacement vector to be calculated; the local fitting formula of the full-field principal tensile strain is as follows: ; wherein, is the principal tensile strain on the surface of the test piece, is the horizontal strain on the surface of the test piece, is the vertical strain on the surface of the test piece, is the shear strain on the surface of the test piece.

5. The method for monitoring shear cracks of reinforced concrete beams based on digital image technology according to claim 1, wherein, In step 2, the process of determining the existing crack is as follows: Based on the binaryzation operation, the surface image is judged, and when the pixel color in the surface image is color1, the part with a strain greater than the material elastic strain threshold is considered to be cracked; When the pixel color in the surface image is color2, the part with a strain less than the threshold is considered to be uncracked.

6. The digital image technology based method for monitoring shear cracks in reinforced concrete beams according to claim 1, wherein, The specific process of the morphological operation is as follows: The surface image after the binaryzation operation is subjected to image processing edge detection by using MATLAB to construct a crack skeleton line with a width of one pixel.

7. The digital image technology based method for monitoring shear cracks in reinforced concrete beams as claimed in claim 1 wherein, The calculation of the motion at step 4 is as follows: ; ; ; where, is the motion vector at the crack i point, , is the opening and slip of the crack at the crack i point, respectively, is the local crack inclination at the i point.

8. A reinforced concrete beam shear crack monitoring device, characterized by, The method comprises a memory and one or more processors, the memory stores executable code, and the one or more processors execute the executable code to implement the reinforced concrete beam shear crack monitoring method based on the digital image technology as claimed in any one of claims 1-7, and the specific steps are as follows: the surface image of the reinforced concrete beam specimen is obtained, and the surface image is processed by the reinforced concrete beam shear crack monitoring method to output the corresponding motion vector result image.

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