Brittle material crack detection and damage evaluation method based on box dimension

Abstract

The invention discloses a fragile material crack detection and damage evaluation method based on box dimension. Change information of a material surface displacement field is calculated by adopting a DIC technology (a digital image correlation technology), a main strain graph is obtained, then the box dimension of the material surface main strain field is calculated by combining a fractal theory, and the damage degree of the material is quantified based on change development of the box dimension. According to the invention, the development process of the cracks of the material test piece from no to penetrating through the test piece can be observed, the crack growth path can be obtained, the crack development can be quantified through the specific box dimension, the damage degree of the structure can be evaluated, and the early warning of the large crack propagation behavior is realized. The method has important practical engineering significance for health detection and risk assessment of fragile material structures such as steel fiber reinforced concrete.

Description

Technical Field

[0001] The present invention relates to the technical field of material damage detection, and particularly relates to a method for crack detection and damage assessment of brittle materials based on box dimension. Background Art

[0002] Concrete not only has excellent physical properties such as compressive strength and impact resistance, but also is easy to mold and economically applicable. Therefore, concrete is the most widely used building material in the world. In order to solve the relatively low tensile strength of concrete, steel fibers are usually added to concrete to form high-performance steel fiber concrete with more excellent comprehensive mechanical properties of compression and tension.

[0003] Steel fiber concrete is a typical heterogeneous multiphase composite material, and its macroscopic failure is an accumulative process of the evolution of various mesoscopic damages such as cracks inside the matrix, the interface between aggregate and matrix, or fiber pull-out. At the mesoscopic level, a large number of disordered microdefects are distributed among mortar, cement, and fibers. Under the action of external loads, the expansion of these microdefects (microcracks and pores) is random and irregular, and the development of cracks is closely related to the mechanical properties of fiber concrete. Therefore, analyzing the development of concrete cracks is of great significance; better evaluating the damage degree of steel fiber concrete has an important reference role for the damage detection of in-service steel fiber concrete buildings.

[0004] When macroscopic cracks appear on the surface of concrete, it indicates that the structure has cracked. Currently, acoustic emission technology is mostly used to study the damage mechanism of steel fiber concrete, but these methods cannot detect the development state of cracks, cannot conduct quantitative evaluation, and cannot even give early warnings for large crack activities. Summary of the Invention

[0005] In view of this, the present invention provides a method for crack detection and damage assessment of brittle materials based on box dimension, which can detect the development state of cracks and conduct quantitative evaluation, and realize early warning of large crack activities.

[0006] The method for material crack detection and damage assessment based on box dimension of the present invention includes:

[0007] Step 1, draw a number of scatter spots in the surface detection area of the material to be detected, and use a high-speed camera to take pictures of the detection area of the material to be detected;

[0008] Step 2, taking the first high-speed camera picture as a reference picture, use DIC technology to track and calculate the displacement field change information between the scatter spots on each high-speed camera picture and the reference picture, calculate the strain field of each high-speed camera picture, and obtain the principal strain diagram;

[0009] Step 3, use the box counting method to determine the box dimension of the principal strain diagram of each high-speed camera picture obtained in Step 2;

[0010] Step 4, plot the "box dimension - time" relationship graph; perform damage assessment on the material based on the relationship graph: if the box dimension is 1, it indicates that the material to be detected has no damage; if the box dimension is 2, it indicates that the material to be detected is completely damaged; if the box dimension increases in the "box dimension - time" relationship graph, it means that the damage degree of the material to be detected is gradually increasing; the larger the box dimension, the greater the damage degree of the material to be detected. When the box dimension reaches the peak value, it means that the material to be detected is about to break.

[0011] Preferably, in step 1, first spray matte white paint in the middle area of the material to be detected, and then dot the speckles with a black oil-based pen.

[0012] Preferably, the density of the speckles is 50%.

[0013] Preferably, in step 2, select a high-resolution picture every time the peak load increases by 10% in the pre-peak stage, and select a high-resolution picture every 50 s in the post-peak stage. Use the DIC technology to calculate its strain field to obtain the principal strain diagram, and then perform step 3.

[0014] Preferably, in step 2, use Ncorr software to calculate the strain field and principal strain band of each high-resolution picture; then adopt an image processing method to remove the strain regions in the picture except the principal strain band to obtain the principal strain diagram, and then perform step 3.

[0015] Preferably, step 3 is specifically: for each principal strain diagram obtained in step 2,

[0016] S31, cover the principal strain band region of the principal strain diagram with a square grid with a side length of r, count the number of grids containing strain information, and record it as N(r);

[0017] S32, change the grid size r, repeat S31, and obtain the corresponding N(r);

[0018] S33, repeat S32 to obtain N(r) corresponding to different r; perform a linear fit on lnN(r)-lnr, and the slope of the fitted straight line is the box dimension of the principal strain diagram.

[0019] Preferably, the material to be detected is steel fiber concrete, concrete, rock or ceramic.

[0020] Preferably, the material to be detected is steel fiber concrete. When the box dimension reaches 1.7, the material to be detected is about to break.

[0021] Beneficial effects:

[0022] (1) The present invention uses DIC technology (Digital Image Correlation technology) to calculate the change information of the displacement field on the material surface, obtain the principal strain diagram, and then combines with the fractal theory to calculate the box dimension of the principal strain field on the material surface. Based on the change of the box dimension, the degree of material damage is quantified. The present invention can observe the development process of internal cracks in the material specimen from non-existent to penetrating, obtain the crack growth path, and can also quantify the crack development through the specific box dimension, evaluate the degree of structural damage, realize the early warning of the propagation behavior of large cracks, and has important practical engineering significance for the health detection and risk assessment of steel fiber concrete material structures.

[0023] (2) The present invention can not only be used for the crack development and damage degree evaluation of steel fiber concrete structures, but also for the damage evaluation of brittle materials such as concrete, rock, and ceramics. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a schematic flow diagram in the specific embodiment of the present invention;

[0025] Figure 2 is a schematic diagram of a three-point bending experiment in the specific embodiment of the present invention;

[0026] Figure 3 is a strain field diagram in the peak point observation area in the specific embodiment of the present invention;

[0027] Figure 4 is a schematic diagram of the principal strain at the peak point after being processed by Photoshop in the specific embodiment of the present invention;

[0028] Figure 5 is a schematic diagram of the fitting result of lnN(r)-lnr at the peak point in the specific embodiment of the present invention;

[0029] Figure 6 is a determined strain growth process diagram in the specific embodiment of the present invention;

[0030] Figure 7 is a diagram of the relationship between load, box dimension and time in the specific embodiment of the present invention. SPECIFIC EMBODIMENTS

[0031] The present invention will be described in detail below with reference to the accompanying drawings and by way of examples.

[0032] The present invention provides a method for detecting material cracks and evaluating damage based on box dimension, as Figure 1 shown, including the following steps:

[0033] Step 1: Draw a number of upper scatter spots on the detection area on the surface of the material structure to be tested. Matte white paint can be sprayed on the specimen detection area first, and then random scatter spots are dot-painted with a black oil-based marker pen, and the scatter spot density is about 50%.

[0034] Step 2: Place the test piece on a three-point bending test machine, and align a high-speed camera with the detection area of the test piece. Set the control parameters of the test machine, adjust the focal length and aperture of the high-speed camera lens, and set appropriate resolution and frame rate.

[0035] Step 3: Start the test machine and the high-speed camera simultaneously to conduct a three-point bending test.

[0036] Step 4: Using the high-speed camera image before the deformation of the test piece as the reference image, adopt the DIC technology to track and calculate the spatial changes between the speckles on the reference image and the high-speed camera image after the deformation of the test piece, and obtain the strain field and the principal strain band of each high-speed camera picture.

[0037] Step 5: Since the fracture path of the test piece is mainly reflected in the principal strain area, use image processing software such as Photoshop to perform image processing, remove the strain areas in the picture except for the principal strain band, and obtain the principal strain diagram. Extract the principal strain field pictures of the test piece at the moments when the principal strain begins to concentrate, expand, and reach a stable stage, etc.

[0038] Step 6: Use the box-counting method to determine the box dimension of the principal strain diagram in Step 5.

[0039] The calculation formula for the box dimension D is as follows:

[0040]

[0041] where r is the side length of the grid, and N(r) is the number of grids containing strain information.

[0042] In practical applications, the side length r of the grid cannot be zero. Therefore, the present invention adopts the slope method: First, cover the picture obtained in Step 5 with square grids with a side length of r, count the number of grids containing strain information, and denote it as N(r). Then change the grid size r to change the grid density and record the total number of grids covering the strain information, and draw a double logarithmic lnN(r)-lnr graph. Use the least squares method to linearly fit the data points in the double logarithmic lnN(r)-lnr graph, and the slope of the fitted straight line is the box dimension.

[0043] Step 7: Draw a graph of the relationship between the box dimension, load, and time, determine the relationship between the degree of material damage and the box dimension, and perform crack detection and damage assessment on the material based on the relationship graph.

[0044] Example 1

[0045] In this example, a three-point bending test is conducted on a concrete beam test piece containing 15 kg / m 3 steel fibers. The size of the concrete beam test piece is 400 mm × 100 mm × 100 mm. A prefabricated notch with a size of 0.5 mm × 100 mm × 25 mm is cut in the middle of the beam.

[0046] Step 1: Figure 2 As shown, the 80×100 mm area in the middle of the steel fiber reinforced concrete beam specimen was first sprayed with matte white paint, and then the speckle pattern was dotted with a black oil pen to ensure that the density of the speckle was about 50%.

[0047] Step 2, place the test piece on the testing machine. Set the testing machine to displacement control and the speed of the pressure head to 0.05mm / min. Place the high-speed camera on the tripod in front of the testing machine, adjust the camera height and lens angle to ensure that the camera optical axis is perpendicular to the sprayed speckle surface of the test piece to avoid experimental errors caused by lens distortion. Adjust the focal length of the lens to ensure that the image is as clear as possible. Use a data cable to connect the high-speed camera to the control microcomputer for data transmission. In this embodiment, the resolution is set to 512×512 and the frame rate is 24fps. In addition, supplement the lighting source according to experimental needs.

[0048] Step 3: Turn on the control switches of the testing machine and the high-speed camera at the same time, and turn off the testing machine after the storage space of the high-speed camera is full.

[0049] Step 4: According to the load curve of the test machine, in this embodiment, a high-speed image is selected for every 10% increase in peak load in the pre-peak stage of the load curve, and a high-speed image is selected every 50 seconds in the post-peak stage. The first high-speed image is set as the reference image, and the Ncorr software is used to calculate the strain field of other high-speed images.

[0050] Step 5: Use Photoshop software to delete the strain area except the main strain band in the strain field image obtained in step 4 and export the image with a resolution of 1840×1200 and a JPG format. In this embodiment, taking the peak point as an example, Figure 3 is the peak full-field strain, Figure 4 This is the principal strain diagram left after processing with Photoshop software.

[0051] Step 6: Taking the peak point strain as an example, the grid size is set to 20×20 resolution for coverage for the first time, and the number of boxes containing strain information is 289, that is, N(r) = 289. The grid size is set to 10×10 for the second time, and the statistical N(r) is 996. Then draw a plot of ln N(r)-ln r points and use the least squares method for linear fitting.

[0052] The curve formula for box dimension fitting in this embodiment is:

[0053]

[0054] Where D is the box dimension and t is the time.

[0055] The fitting results are as followsFigure 5 As shown, the slope of the straight line is -1.7144, so the box dimension is 1.7144.

[0056] Step 7: In this embodiment, strain concentration starts at about 70% strain and then develops rapidly. After the peak load, the strain growth begins to slow down and the width gradually increases. The change in strain is consistent with the actual crack change. Attached Figure 6 As shown, 12 main strain growth moments are selected in this embodiment to measure the box dimension.

[0057] Quantifying the damage degree of steel fiber reinforced concrete structures based on the box dimension theory of the present invention is a very effective method. When there is no damage to the specimen structure, the box dimension at this time is 1, and when the specimen structure is completely damaged, the box dimension is 2. In this embodiment, the relationship between the experimental load and the box dimension and time is as Figure 7 shown. The fitted box dimension-time curve has a good correspondence with the damage of the concrete structure. The fitted box dimension-time curve is mainly divided into two parts: the pre-peak part and the post-peak part. In the pre-peak stage, when the main strain field is concentrated, the box dimension is about 1.3, and then it increases rapidly with the growth of the main strain band, tending to be consistent with the growth of the load. In the pre-peak stage, the increase in the box dimension indicates that the damage degree is gradually increasing. The box dimension of the strain field of the concrete beam is 1.714 at the peak, and after the peak, the main strain (crack) increases slowly and the box dimension also increases slowly. The damage degree of the specimen is positively correlated with the box dimension value. In this embodiment, when the box dimension reaches 1.7, it means that the specimen is about to fracture.

[0058] The present invention also generalizes formula (2) to:

[0059]

[0060] In the formula, the parameter D0 is related to the box dimension of the main strain, and it is appropriate to take the box dimension of the maximum main strain; t0 is the moment of initial strain concentration; w is a parameter related to the content of steel fibers, w > 0, and the greater the content of steel fibers, the greater the value of w. The value of w determines the box dimension in the pre-peak stage. The greater the value of w, the smaller the box dimension in the pre-peak stage.

[0061] The results of this embodiment show that the damage degree of high-performance steel fiber reinforced concrete can be evaluated based on the box dimension method. The relationship between the damage degree and the box dimension is summarized as follows:

[0062] 1) In the pre-peak stage (the specimen is not damaged), the higher the box dimension, the higher the possibility of specimen damage; when the box dimension reaches 1.7, it implies that the specimen is about to be damaged.

[0063] 2) In the post-peak stage (the specimen is damaged), the box dimension is positively correlated with the damage degree; the higher the box dimension, the higher the damage degree.

[0064] In summary, the above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for crack detection and damage assessment of brittle materials based on box dimension, characterized in that, Including: Step 1: Draw a number of scattered spots in the surface detection area of the material to be detected, and use a high-speed camera to take pictures of the detection area of the material to be detected; Step 2: Using the first high-speed camera picture as the reference picture, use DIC technology to track and calculate the displacement field change information between the scattered spots on each high-speed camera picture and the reference picture, calculate the strain field of each high-speed camera picture, and obtain the principal strain diagram; Step 3: Use the box-counting method to determine the box dimension of the principal strain diagram of each high-speed camera picture obtained in Step 2; Step 4: Draw a "box dimension - time" relationship diagram; conduct damage assessment on the material based on the relationship diagram: If the box dimension is 1, it indicates that the material to be detected has no damage; if the box dimension is 2, it indicates that the material to be detected is completely damaged; if in the "box dimension - time" relationship diagram, the box dimension increases, it means that the damage degree of the material to be detected is gradually increasing; the larger the box dimension, the greater the damage degree of the material to be detected. When the box dimension reaches the peak value, it means that the material to be detected is about to break.

2. The method according to claim 1, wherein In Step 1, first spray matte white paint in the middle area of the material to be detected, and then dot the scattered spots with a black oil-based pen.

3. The method according to claim 1 or 2, characterized in that, The density of the scattered spots is 50%.

4. The method according to claim 1, characterized in that In Step 2, in the pre-peak stage, select one high-speed camera picture for every 10% increase in the peak load, and in the post-peak stage, select one high-speed camera picture every 50 s. Use DIC technology to calculate its strain field, obtain the principal strain diagram, and execute Step 3.

5. The method according to claim 1 or 4, characterized in that, In Step 2, use Ncorr software to calculate the strain field and principal strain band of each high-speed camera picture; then use an image processing method to remove the strain area in the picture except for the principal strain band to obtain the principal strain diagram, and execute Step 3.

6. The method according to claim 1, wherein The specific content of Step 3 is as follows: For each principal strain diagram obtained in Step 2, S31: Cover the principal strain band area of the principal strain diagram with a square grid with a side length of r, count the number of grids containing strain information, and record it as N(r); S32: Change the grid size r, repeat S31, and obtain the corresponding N(r); S33: Repeat S32 to obtain N(r) corresponding to different r; perform a linear fit on lnN(r) - lnr, and the slope of the fitted straight line is the box dimension of the principal strain diagram.

7. The method according to claim 1, characterized in that The material to be detected is steel fiber concrete, concrete, rock or ceramic.

8. The method according to claim 1, wherein When the material to be detected is steel fiber concrete, the curve formula for fitting the box dimension is: Among them, the parameter D0 is related to the box dimension of the principal strain; t0 is the moment when initial strain concentration occurs; w is a parameter related to the content of steel fibers.

9. The method according to claim 1 or 8, characterized in that, When the material to be detected is steel fiber concrete, when the box dimension reaches 1.7, the material to be detected is about to break.

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