Structure cracking post-sealing layer thickness prediction and design method based on image grayscale recognition

Abstract

A structure cracking post-sealing layer thickness prediction method based on image gray recognition, comprising: S1, based on two concrete test piece reserved gaps, carrying out sealing layer axial tension test and shooting to obtain gray scale image and gray value in sealing layer stretching process, recording sealing layer thickness value corresponding to each gray value, and drawing fitting curve of sealing layer thickness value and gray value; S2, using concrete beam four-point bending test to carry out beam body cracking crack width and crack image gray value test; S3, crack position sealing layer thickness judgment: processing the image of S2 step test, and combining the corresponding relationship of sealing layer thickness and crack image gray value established in S1 step, obtaining sealing layer thickness of crack area. The method collects high-resolution images of the beam surface, accurately analyzes the gray value change in the image, and quickly detects the thickness of the residual sealing layer at the beam crack by using the relationship between the gray value in the image and the sealing layer thickness, thereby providing support for bridge waterproof layer design.

Description

Technical Field

[0001] This invention relates to the fields of bridge engineering, tunnel engineering, and road engineering, and more specifically, to the fields of bridge deck waterproofing, tunnel waterproofing, and road sealing layer design and manufacturing (including modified asphalt waterproof coatings, polyurethane waterproof coatings, and waterproof membranes), and particularly to a method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition. Background Technology

[0002] Waterproofing layers or sealing layers are an indispensable and important component of bridge, tunnel, and road structures. Their main function is to prevent external moisture such as rainwater, snowmelt, and de-icing salt from seeping into the bridge deck structure, effectively avoiding problems such as concrete carbonation and steel corrosion, thereby improving the durability and service life of roads, bridges, and tunnels. Simultaneously, waterproofing layers or sealing layers also prevent surface peeling, voids, freeze-thaw damage, and other defects, improving the adhesion between the pavement layer and the bridge / tunnel concrete slab or semi-rigid road base layer, ensuring the overall stability and safety of the bridge deck structure. As a crucial measure for the maintenance and long-life design of infrastructure such as roads, bridges, and tunnels, sealing layers play a key role throughout the entire life cycle of infrastructure.

[0003] However, existing thickness measurement methods often struggle to accurately measure the thickness of the sealing layer, especially after cracks appear in the bridge deck. Traditional methods often fail to accurately reflect the remaining thickness of the sealing layer (for example, vernier calipers, while accurate enough, can get stuck in narrow cracks; when the crack widens, the calipers may reach in and get stuck, but because the sealing layer is relatively soft, it easily deforms under the caliper's grip, rendering it unsuitable). This not only affects the assessment of bridge health but also fails to provide a scientific basis for bridge maintenance and repair.

[0004] Therefore, there is an urgent need for a method to measure the thickness of the sealing layer at the crack in the bridge deck in a timely manner after cracking, so as to accurately assess the health status of the bridge and provide a scientific basis for bridge maintenance and repair. Summary of the Invention

[0005] This invention provides a method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition. It involves conducting axial tensile tests on pre-reserved gaps in concrete specimens to record grayscale values. The method then uses the grayscale value changes to establish a correlation between the sealing layer thickness and the image grayscale values ​​at the crack location. This relationship is applied to the sealing layer design of actual bridges to quickly detect the thickness of the sealing layer at bridge deck cracks. Especially in cases where bridge deck cracks appear, this image grayscale recognition-based method overcomes the limitations of traditional methods. By accurately measuring grayscale values, it assesses the thickness of the sealing layer around the crack, thereby determining the relationship between the crack width and the residual waterproof coating, providing support for subsequent waterproof layer design.

[0006] The technical solution adopted by this invention to solve its technical problem is a method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition. This method is used to predict the remaining thickness of the sealing layer after cracks appear in a concrete structure. The method for predicting the thickness of the sealing layer based on image grayscale recognition includes the following steps:

[0007] S1. Obtain the measured data fitting curve of image grayscale and cover thickness: Prepare two cubic test blocks, with a width of W between the cubic test blocks. ys A pre-set seam is provided, and a sealing layer of thickness t0 is provided on the top surface of the cube specimen and the top surface of the pre-set seam. A tensile test is performed on the cube specimen until the pre-set seam reaches its maximum value W. ys,max Take photos of the stretching process of the sealing layer and process them into grayscale images. Obtain the average grayscale value of each grayscale image at the preset seam. Measure and record the sealing layer thickness value at the time corresponding to each grayscale value. Plot the fitting curve between the sealing layer thickness value and the grayscale value.

[0008] S2. Establish a measured database with a one-to-one correspondence between image grayscale and crack width: Fabricate concrete structure specimens, apply a sealing layer of thickness t0 to the tension surface of the concrete structure specimens, conduct loading tests on the concrete structure specimens, and measure the crack width W of the concrete structure specimens during the loading process. cr Take photographs of the sealing layer at the location of the crack until the crack width of the concrete structure specimen reaches its maximum value W. cr,max Stop loading and shooting;

[0009] S3. Identify the grayscale of the crack area image of the concrete structure and predict the sealing layer thickness: Process the sealing layer photos taken in step S2 into grayscale images, divide the grayscale images into crack areas and non-crack areas according to the grayscale differences, calculate the average grayscale value of the crack area, substitute the average grayscale value into the fitting curve in step S1 to obtain the corresponding sealing layer thickness prediction value, and plot the sealing layer thickness prediction value corresponding to each sealing layer photo with the crack width value in S2 to draw a second fitting curve. The second fitting curve can be used to predict the sealing layer thickness corresponding to any crack width value.

[0010] Preferably, the surface of the concrete specimen is provided with an initial thickness of The sealing layer, the volume of which changes due to Poisson's ratio during stretching, is such that the Poisson's ratio of the sealing layer material is... The thickness of the sealing layer in the crack area during loading is then... .

[0011] Preferably, the step S1, establishing the correspondence between the sealing layer thickness and the image grayscale value at the crack, includes the following steps:

[0012] S101. Concrete Specimen Preparation: Prepare paired concrete specimens, and place a layer of material with a thickness of [thickness missing] between the paired specimens. After the steel plates are aligned and fixed in pairs, the concrete specimens are then surfaced with a thickness of [missing information]. The amount of waterproof coating used at the steel plate is, in the case of the sealing layer, the amount of waterproof coating used is. After the seal layer has solidified and stabilized, the steel plate is removed to obtain a width between the paired concrete specimens. Artificial crack areas;

[0013] S102, Image Gray-Sealing Thickness Curve: One of the concrete specimens is placed on a fixed base, and the other concrete specimen is placed on a movable base. The movable base is stretched slowly in stages, and the change in the total width of the artificial crack is recorded after each stretch. The thickness of the sealing layer in the artificial crack area can be calculated as follows: Furthermore, the sealing layer of the artificial crack is photographed and image processed to obtain the grayscale value of the sealing layer at the artificial crack;

[0014] S103. Establish the gray-thickness relationship model of the sealing layer: Assume the length of the concrete specimen is... ,width The amount of sealing layer used in the concrete specimen is... ,in Given the asphalt density, the stretching distance decreases by a certain amount for each stage, and the seal layer thickness is calculated. and the corresponding stretching distance .

[0015] Preferably, in step S102, an image grayscale-sealing thickness curve is obtained by drawing the sealing layer thickness in the artificial crack area and the grayscale value of the sealing layer at the artificial crack.

[0016] Preferably, in step S102, the sealing layer is photographed using a high-resolution camera and an LED light source box. The LED light source box and the high-resolution camera are fixedly mounted on the base, and the high-resolution camera is parallel to the concrete specimen.

[0017] Preferably, in step S103, the grayscale value of the sealing layer photograph is recorded at each level of crack, and the grayscale value of the sealing layer is compared with the tensile distance of the crack area one by one. Perform fitting and prediction to obtain ,in, It is the thickness The grayscale value at that time; This represents the initial grayscale attenuation amplitude. The attenuation coefficient; The saturated grayscale value refers to the grayscale value of the cover image when the thickness is sufficiently large. .

[0018] Preferably, the method for loading the reinforced concrete beam specimen in step S2 is a graded loading method: after each load increment of 5kN is applied to the reinforced concrete beam specimen, a photograph is taken; when the reinforced concrete beam specimen enters the plastic stage, a displacement loading method is adopted, and the actuator of the loading device increases the displacement by 1mm at each stage, and a photograph is taken; loading is stopped when the crack width of the beam body of the reinforced concrete beam specimen reaches 1.5mm.

[0019] Preferably, in step S2, when the reinforced concrete beam specimen is subjected to a loading test, the reinforced concrete beam specimen is loaded with 5kN each time or the actuator of the loading device increases the displacement by 1mm at each stage, and the load is sustained for 1 minute before the crack width and the gray value of the sealing layer are recorded.

[0020] Preferably, the loading device includes a distribution beam and an actuator; the output end of the actuator is connected to the distribution beam, and the distribution beam is connected to the reinforced concrete beam specimen.

[0021] Preferably, the reinforced concrete beam specimen includes a notch and a water storage tank at the mid-span position; the water storage tank is located at the mid-span position to keep the sealing layer at a constant temperature, and the outer wall of the water storage tank is provided with a waterproof sealing coating.

[0022] Preferably, the image processing method in step S3 includes image denoising, image grayscale value analysis, image thresholding, and image region analysis to calculate the average grayscale value of the crack region of the sealing layer.

[0023] This invention also provides a structural sealing toughness design method based on image grayscale recognition. The toughness design method is implemented according to the above-described prediction method and includes the following steps:

[0024] S11. Assuming the initial thickness of the concrete sealing layer is t0, calculate the crack width W based on the design load of the concrete structure and the relevant industry standards. cr,t ;

[0025] S12. Based on the crack width value W cr,c Substitute the second fitted curve in S3 to obtain the corresponding predicted value t of the sealing layer thickness. c ;

[0026] S13. If t c <t min , t min If the minimum sealing layer thickness is required by the relevant industry standard, then the sealing layer thickness of the concrete structure is increased to t0+f(t). min -t c If f > 1, terminate the capping design; otherwise, terminate the capping design.

[0027] The beneficial effects of this invention are as follows:

[0028] This invention discloses a method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition. By acquiring high-resolution images of the bridge deck surface and utilizing image processing technology, it can accurately analyze changes in grayscale values ​​within the images. The relationship between grayscale values ​​and sealing layer thickness is then used to quickly detect the thickness of the sealing layer at the crack in the bridge deck. Especially when cracks appear in the bridge deck, the image grayscale analysis method overcomes the limitations of traditional methods. By accurately measuring grayscale values, it assesses the thickness of the sealing layer around the crack, thereby determining the relationship between the crack width and the remaining waterproof coating, providing support for the design of subsequent waterproof layers. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the fabrication and tensile testing of a concrete specimen for the method of predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition, as described in this invention.

[0030] Figure 2 This is a schematic diagram of the sealing layer thickness monitoring and crack resistance test in step S2 of the structural sealing layer thickness prediction method based on image grayscale recognition of the present invention.

[0031] Figure 3 This is a schematic diagram showing the changes in crack location and seal thickness after cracking of a reinforced concrete beam in step S2 of the structural cracking seal thickness prediction method based on image grayscale recognition of the present invention.

[0032] Figure 4 This is a photograph of a concrete specimen in step S1 of the method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition, as described in this invention.

[0033] Figure 5 These are sample photos taken at the crack location in the structural cracking prevention method based on image grayscale recognition, as described in this invention.

[0034] Figure 6 This is a photograph of a reinforced concrete beam specimen in step S2 of the structural crack sealing layer thickness prediction method based on image grayscale recognition of the present invention.

[0035] Figure 7 These are photographs of the sealing layer thickness monitoring and crack resistance performance test in step S2 of the structural cracking sealing layer thickness prediction method based on image grayscale recognition of the present invention. Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0037] Numerous specific details are set forth in the following description to enable those skilled in the art to fully understand the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0038] In the description of the embodiments of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0040] like Figures 1-3As shown, a method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition is used to quickly detect the remaining thickness of the sealing layer after cracks appear in a bridge deck. The method includes the following steps:

[0041] S1. Obtain the measured data fitting curve of image grayscale and cover thickness: Prepare two cubic test blocks, with a width of W between the cubic test blocks. ys A pre-set seam is provided, and a sealing layer of thickness t0 is provided on the top surface of the cube specimen and the top surface of the pre-set seam. A tensile test is performed on the cube specimen until the pre-set seam reaches its maximum value W. ys,max Furthermore, the minimum distance between two adjacent cubic test blocks is ≥2mm. The photos of the sealing layer stretching process are taken and processed into grayscale images. The average grayscale value of each grayscale image at the preset seam is obtained. The sealing layer thickness value at the time corresponding to each grayscale value is measured and recorded. The fitting curve between the sealing layer thickness value and the grayscale value is plotted.

[0042] In this step, the sealing layer initially exhibits a relatively low grayscale (darker color) after construction. However, under load, it is continuously stretched. As the stretching rate increases, the distance between sealing layer molecules increases, and the grayscale value of the sealing layer gradually increases, meaning the color gradually lightens. This means the grayscale value and thickness of the sealing layer typically exhibit a non-linear negative correlation. Based on this principle and combined with practical application scenarios, the sealing layer thickness and grayscale value are calibrated. Furthermore, methods for obtaining the sealing layer thickness include direct measurement using high-precision optical measuring equipment, such as microscopes. However, this measurement process typically requires high precision from the measuring equipment and skilled operators, and is time-consuming. Therefore, directly measuring the sealing layer thickness using high-precision optical measuring equipment often requires significant manpower and resources. To facilitate obtaining the sealing layer thickness value, this image-based grayscale recognition-based method for predicting the sealing layer thickness after structural cracking also provides a method for calculating the sealing layer thickness. When the surface of the concrete specimen is set with an initial thickness of... During the sealing process, the volume of the sealing layer changes due to Poisson's ratio during stretching, so the Poisson's ratio of the sealing layer material is set to... The thickness of the sealing layer in the crack area during loading is then... .

[0043] S2. Establish a measured database with a one-to-one correspondence between image grayscale and crack width: Fabricate concrete structure specimens, apply a sealing layer of thickness t0 to the tension surface of the concrete structure specimens, conduct loading tests on the concrete structure specimens, and measure the crack width W of the concrete structure specimens during the loading process. crTake photographs of the sealing layer at the location of the crack until the crack width of the concrete structure specimen reaches its maximum value W. cr,max Stop loading and shooting.

[0044] In this step, since the bridge deck cracking occurs after the sealing layer, the sealing layer will crack to a certain height along with the crack. Therefore, the thickness of the sealing layer can be determined by the grayscale of the photograph, thus achieving accurate determination of the sealing layer thickness for different crack widths and providing a reference for assessing the health status of the bridge. Furthermore, as... Figure 2 As shown, in the loading test of this step, a notch is made at the mid-span of the reinforced concrete beam specimen to allow the specimen to crack along the notch under load. After the concrete beam cracks at the mid-span, the waterproof coating at the crack will thin as the crack expands, thus changing the grayscale of the image. The maximum crack width Wcr,max of the concrete structure specimen is generally taken as 1.5 mm.

[0045] S3. Determination of seal layer thickness at crack location: The images of the reinforced concrete beam specimens taken in step S2 are processed using image processing methods to locate the crack area of ​​the reinforced concrete beam specimens and calculate the average gray value of the seal layer in the crack area. Combined with the correspondence between the seal layer thickness and the image gray value at the crack established in step S1, the seal layer thickness in the crack area is obtained.

[0046] In this embodiment, high-resolution images of the bridge deck surface are acquired, and image processing technology is used to accurately analyze the changes in grayscale values ​​in the images. The relationship between the grayscale values ​​in the images and the thickness of the sealing layer is used to quickly detect the thickness of the sealing layer at the cracks in the bridge deck. Especially when cracks appear in the bridge deck, the image grayscale analysis method can overcome the limitations of traditional methods. By accurately measuring the grayscale values, the thickness of the sealing layer around the crack can be evaluated, thereby achieving non-destructive testing and real-time monitoring.

[0047] Furthermore, in step S1, during the stretching process, the volume of the sealing layer changes due to Poisson's ratio, resulting in a Poisson's ratio of the sealing layer material being... During the loading process, the thickness of the sealing layer in the crack area is... The formula derivation is as follows:

[0048] (1) Three-dimensional stress-strain relationship

[0049] According to Hooke's Law, the relationship between stress and strain is as follows:

[0050]

[0051] in , , These are the normal stresses in the length, width, and thickness directions;

[0052] , , Engineering strain in the length, width, and thickness directions;

[0053] The elastic modulus of the material; Let be the Poisson's ratio of the material.

[0054] (2) Engineering strain

[0055] The strain in the width direction remains constant, while the stress in the thickness direction is 0. , ,have to

[0056] Get adaptable ,

[0057] (3) Realistic response

[0058] strain ,

[0059] achievable .

[0060] Furthermore, such as Figure 1 As shown, the steps in step S1 to establish the correspondence between the sealing layer thickness and the grayscale values ​​of the image at the crack include the following steps:

[0061] S101. Concrete Specimen Preparation: Prepare paired concrete specimens, and place a layer of material with a thickness of [thickness missing] between the paired specimens. After the steel plates and pairs of concrete specimens are aligned and fixed, a layer with a thickness of [thickness missing] is set on the surface of the concrete specimens. For the sealing layer, the amount of waterproof coating used at the steel plate is... After the seal layer has solidified and stabilized, the steel plate is removed to obtain a width between the paired concrete specimens. Artificial crack areas;

[0062] S102, Image Gray-Sealing Thickness Curve: One concrete specimen was placed on a fixed base, and the other on a movable base. The movable base was stretched slowly in stages, and the width change of the artificial crack was recorded after each stretch. The thickness of the sealing layer in the artificial crack area can be calculated as follows: Furthermore, the grayscale value of the seal layer at the artificial crack is obtained by photographing the seal layer in the artificial crack area, and the seal layer thickness in the artificial crack area is determined accordingly. The grayscale value of the sealing layer at the artificial crack is compared with the grayscale value of the sealing layer to obtain the image grayscale-sealing layer thickness curve; in step S102, the sealing layer is photographed by a high-resolution camera and an LED light source box. The LED light source box and the high-resolution camera are fixedly set on the base, and the high-resolution camera is parallel to the concrete specimen.

[0063] S103. Establish the gray-thickness relationship model of the sealing layer: Assume the length of the concrete specimen is... ,width The amount of sealant used in the concrete specimen is then... ,in Given the asphalt density, the stretching distance decreases by a certain amount for each stage, and the seal layer thickness is calculated. and the corresponding stretching distance Furthermore, based on the grayscale values ​​of the sealing layer photographs recorded at each level of crack, the grayscale value of the sealing layer and the stretching distance of the crack area were compared. By performing a fitting prediction, we can obtain ,in, It is the thickness The grayscale value at that time; This represents the initial grayscale attenuation amplitude. The attenuation coefficient is... To control the rate of grayscale change; This is the saturated grayscale value, which is the grayscale value that tends to be when the thickness is large enough.

[0064] Further, see Figure 2 and Figure 3 In step S2, the loading test method for the reinforced concrete beam specimen is a graded loading method: the load increment of each loading on the reinforced concrete beam specimen is 5kN and then photographed. When the reinforced concrete beam specimen enters the plastic stage, displacement loading is adopted. The actuator of the loading device increases the displacement by 1mm for each stage and then photographs are taken. Loading is stopped when the crack width of the reinforced concrete beam specimen reaches 1.5mm.

[0065] In step S2, when performing loading tests on reinforced concrete beam specimens, the specimens are loaded with 5 kN each time, or the actuator of the loading device increases the displacement by 1 mm per stage. After continuous loading for 1 minute, the crack width and the gray value of the sealing layer are recorded. The loading device includes a distribution beam and an actuator; the output end of the actuator is connected to the distribution beam, which is connected to the reinforced concrete beam specimen.

[0066] like Figure 4As shown, the reinforced concrete beam specimen includes a notch at the mid-span and a water storage tank. The water storage tank is located at the mid-span to maintain a constant temperature for the sealing layer, and a waterproof sealing coating is applied to the outer wall of the water storage tank. The waterproof sealing coating includes a high-toughness waterproof sealant of a certain thickness to prevent water from seeping out of the water storage tank after the beam cracks, thus affecting the performance of the sealing layer and the pixel grayscale of the sealing layer image.

[0067] In a preferred embodiment, the image processing method in step S3 includes image denoising, image grayscale analysis, image thresholding, and image region analysis to calculate the average grayscale value of the crack region of the sealing layer.

[0068] Furthermore, the present invention also provides an embodiment, which is based on a 2mm thick bridge deck seal layer, and the specific steps are as follows:

[0069] First, prepare two standard concrete specimens in pairs, each measuring 10cm x 10cm x 10cm. Place a calibrated thickness between the two specimens. The steel plate is coated with a release oil or wrapped with a thin layer of silicone paper for later demolding. After aligning and fixing two specimens, a sealing layer is evenly applied to the surface of the concrete specimen. The thickness of the waterproof coating is calculated based on the amount of sealing layer used and the area covered. At the same time, the amount of waterproof coating required within the area of ​​the steel plate can be calculated. After the sealant has dried, the insulating steel plate between the specimens is removed from the mold to obtain artificial cracks of different widths, forming a sealant of known width and thickness.

[0070] One concrete specimen was placed on a fixed base, and the other on a movable base. During tensile testing, the sliding end specimen was stretched slowly in stages, and the stretching distance (i.e., the crack width) was recorded using a dial indicator. Simultaneously, a camera was used to photograph the seal layer in the artificial crack area, extracting the grayscale values ​​of the seal layer at the artificial crack locations for later grayscale calibration. The entire process used the same camera and maintained a constant lighting source to minimize interference from other factors. The thickness of the seal layer was then calculated. To obtain the image grayscale-capping thickness curve.

[0071] The commonly used bridge deck seal thickness is 2mm. This embodiment uses a 2mm thick bridge deck seal as the benchmark for research, and the stretching speed is set to 0.5mm per minute for better process control. Each stretching is paused at a certain distance, and images are taken to record the thickness of the sample after stretching. ) and grayscale value ( To eliminate dispersion and ensure the accuracy of the experiment, the grayscale value here ( The grayscale value is the average grayscale value within the crack area. Image processing tools (such as OpenCV) are used to extract the grayscale value of each image, i.e., to extract the average grayscale value of the crack region (region of interest). The grayscale value of each stretched image is then matched with the corresponding thickness data.

[0072] Furthermore, a gray-scale-thickness relationship model was established, and the length of the concrete specimens used in this experiment was determined. ,width Given a preset crack width of 2mm and an asphalt thickness of 2mm, the asphalt usage is: ,in This represents the density of asphalt.

[0073] To facilitate data recording, the stretching distance is paused each time to ensure a 0.2mm reduction in the seal layer thickness for each level, i.e., 1.8mm, 1.6mm, ... 0.4mm, depending on the seal layer thickness. Calculations were performed to determine the seal thickness. and the corresponding stretching distance (Displacement gauge readings). Simultaneously, the grayscale values ​​of the sealing layer photographs at each crack level were recorded according to this rule, as shown in the table below:

[0074] Table 1 Comparison of Seal Thickness and Tension Distance

[0075]

[0076] As shown in Table 1, with the decrease of the sealing layer thickness, the grayscale values ​​of the sealing layer image at the crack exhibit a trend of first slow, then fast, and then slowing down again. This can be predicted by fitting the data using an exponential decay function with a constant term. For the experimental data in this study... That is, the correspondence between the grayscale value of the initial 2mm thick seal layer and its thickness is as follows: .

[0077] Further, in step S2, reinforced concrete beam specimens are fabricated, sealed at a constant temperature, and then subjected to loading tests. The loading test method for the reinforced concrete beam specimens is a graded loading method: the load increment for each loading of the reinforced concrete beam specimen is 5kN (approximately 1 / 10 of the ultimate bearing capacity of the concrete beam), and then photographs are taken. When the reinforced concrete beam specimen enters the plastic stage (the plastic stage is determined by the load and displacement curves displayed on the actuator; the point where the displacement increases but the load no longer increases is the starting point of the plastic stage, and thereafter the plasticity increases slowly with the increase of displacement), displacement loading is adopted. The actuator of the loading device increases the displacement by 1mm per stage (approximately 1 / 1000 of the beam span), and then photographs are taken. Loading is stopped when the crack width of the reinforced concrete beam specimen reaches 1.5mm.

[0078] When conducting loading tests on reinforced concrete beam specimens, the specimens were loaded with 5 kN each time, or the actuator of the loading device increased the displacement by 1 mm per increment. After maintaining the load for 1 minute, the crack width and the grayscale value of the sealing layer were recorded. Furthermore, after the beam cracked, the crack width and the grayscale of the sealing layer image pixels were recorded again. As the crack developed, the sealing layer at the crack became thinner and thinner. Crack development was monitored using a crack observation instrument or DIC (Diverterless Indicator) method. After each load or displacement reached the preset value, the crack width was recorded and a high-definition camera was used to take pictures after maintaining the load for 1 minute.

[0079] After loading stops, the captured images are processed through steps such as noise reduction, grayscale analysis, threshold segmentation, contour detection, and region analysis to detect the location of cracks in the asphalt seal layer in a non-contact manner and estimate the thickness of the seal layer.

[0080] Image denoising: Using filtering techniques (such as Gaussian filtering) to smooth the image and reduce interference from device or environmental noise, making cracks and grayscale changes in the image more obvious.

[0081] Gray-scale value analysis: Tensile tests show that the gray-scale value in the image is negatively correlated with the thickness of the asphalt layer; thinner seal layers (such as those at crack locations) will exhibit larger gray-scale values. Statistical analysis of the image gray-scale values ​​reveals the gray-scale changes in each region, which can help locate crack areas.

[0082] Threshold-based segmentation: The image is binarized through adaptive thresholding to highlight crack areas.

[0083] Crack region analysis: All obvious structural regions are identified through contour detection algorithms, distinguishing crack regions from areas with thicker sealing layers.

[0084] Output results: Output the average gray value of the crack area. Combined with the calibration relationship between the gray value and the sealing layer thickness in step S1, the thickness of the sealing layer in the crack area can be obtained, thus realizing the non-contact accurate measurement of the sealing layer thickness.

[0085] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition, the method being used to predict the remaining thickness of the sealing layer after cracks appear in a concrete structure, characterized in that... The method for predicting the cover thickness based on image grayscale recognition includes the following steps: S1. Obtain the measured data fitting curve of image grayscale and cover thickness: Prepare two cubic test blocks, with a width of W between the cubic test blocks. ys A pre-set seam is provided, and a sealing layer of thickness t0 is provided on the top surface of the cube specimen and the top surface of the pre-set seam. A tensile test is performed on the cube specimen until the pre-set seam reaches its maximum value W. ys,max Take photos of the stretching process of the sealing layer and process them into grayscale images to obtain the average grayscale value of each grayscale image at the preset seam. Measure and record the sealing layer thickness value at the time corresponding to each average grayscale value, and draw a fitting curve between the sealing layer thickness value and the average grayscale value. S2. Establish a measured database with a one-to-one correspondence between image grayscale and crack width: Fabricate concrete structure specimens, apply a sealing layer of thickness t0 to the tension surface of the concrete structure specimens, conduct loading tests on the concrete structure specimens, and measure the crack width W of the concrete structure specimens during the loading process. cr Take photographs of the sealing layer at the location of the crack until the crack width of the concrete structure specimen reaches its maximum value W. cr,max Stop loading and shooting; S3. Identify the grayscale of the crack area image of the concrete structure and predict the sealing layer thickness: Process the sealing layer photos taken in step S2 into grayscale images, divide the grayscale images into crack areas and non-crack areas according to the grayscale differences, calculate the average grayscale value of the crack area, substitute the average grayscale value into the fitting curve in step S1 to obtain the corresponding sealing layer thickness prediction value, and plot the sealing layer thickness prediction value corresponding to each sealing layer photo with the crack width value in S2 to draw a second fitting curve. The second fitting curve can be used to predict the sealing layer thickness corresponding to any crack width value.

2. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 1, characterized in that, The surface of the concrete structure specimen is provided with an initial thickness of The sealing layer, the volume of which changes due to Poisson's ratio during stretching, is such that the Poisson's ratio of the sealing layer material is... The thickness of the sealing layer in the crack area during loading is then... .

3. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 1, characterized in that, Establishing the correspondence between the sealing layer thickness and the image grayscale value at the crack in step S1 includes the following steps: S101. Concrete Specimen Preparation: Prepare paired concrete specimens, and place a layer of material with a thickness of [thickness missing] between the paired specimens. After the steel plates are aligned and fixed in pairs, the concrete specimens are then surfaced with a thickness of [missing information]. The amount of waterproof coating used at the steel plate is, in the case of the sealing layer, the amount of waterproof coating used is. After the seal layer has solidified and stabilized, the steel plate is removed to obtain a width between the paired concrete specimens. Artificial crack areas; S102, Image Gray-Sealing Thickness Curve: One of the concrete specimens is placed on a fixed base, and the other concrete specimen is placed on a movable base. The movable base is stretched slowly in stages, and the change in the total width of the artificial crack is recorded after each stretch. The thickness of the sealing layer in the artificial crack area can be calculated as follows: Furthermore, the sealing layer of the artificial crack is photographed and image processed to obtain the grayscale value of the sealing layer at the artificial crack; S103. Establish the gray-thickness relationship model of the sealing layer: Assume the length of the concrete specimen is... ,width The amount of sealing layer used in the concrete specimen is... ,in Given the asphalt density, the stretching distance decreases by a certain amount for each stage, and the seal layer thickness is calculated. and the corresponding stretching distance .

4. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 3, characterized in that, In step S102, an image grayscale-sealing thickness curve is obtained by drawing the sealing layer thickness of the artificial crack area and the grayscale value of the sealing layer at the artificial crack.

5. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 3, characterized in that, In step S102, the sealing layer is photographed using a high-resolution camera and an LED light source box. The LED light source box and the high-resolution camera are fixedly mounted on the base, and the high-resolution camera is parallel to the concrete specimen.

6. The method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition according to claim 3, characterized in that, In step S103, the grayscale value of the sealing layer photograph is recorded at each level of crack, and the grayscale value of the sealing layer is compared with the tensile distance of the crack area one by one. Perform fitting and prediction to obtain ,in, It is the thickness The grayscale value at that time; This represents the initial grayscale attenuation amplitude. The attenuation coefficient; The saturated grayscale value refers to the grayscale value of the cover image when the thickness is sufficiently large. .

7. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 1, characterized in that, The method for loading the concrete structure specimen in step S2 is a graded loading method: the load increment of the concrete structure specimen is 5kN each time, and then the specimen is photographed. When the concrete structure specimen enters the plastic stage, displacement loading is adopted. The actuator of the loading device increases the displacement by 1mm at each stage, and then the specimen is photographed. Loading is stopped when the crack width of the beam of the concrete structure specimen reaches 1.5mm.

8. The method for predicting the thickness of the sealing layer after structural cracking based on image grayscale recognition according to claim 7, characterized in that, In step S2, when the concrete structure specimen is subjected to a loading test, the concrete structure specimen is loaded with 5kN each time or the actuator of the loading device increases the displacement by 1mm at each stage, and the load is continued for 1 minute before the crack width and the gray value of the sealing layer are recorded.

9. The method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition according to claim 8, characterized in that, The loading device includes a distribution beam and an actuator; the output end of the actuator is connected to the distribution beam, and the distribution beam is connected to the concrete structure specimen.

10. The method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition according to claim 1, characterized in that, The concrete structure specimen includes a notch and a water storage tank at the mid-span position; the water storage tank is located at the mid-span position to keep the sealing layer at a constant temperature, and the outer wall of the water storage tank is provided with a waterproof sealing coating.

11. The method for predicting the thickness of a sealing layer after structural cracking based on image grayscale recognition according to claim 10, characterized in that, The image processing method in step S3, which processes the sealing layer photo taken in step S2 into a grayscale image, includes image denoising, image grayscale value analysis, image thresholding, and image region analysis to calculate the average grayscale value of the crack region of the sealing layer.

12. A structural sealing toughness design method based on image grayscale recognition, wherein the toughness design method is implemented based on the prediction method according to any one of claims 1-11, characterized in that, The toughness design method includes the following steps: S11. Assuming the initial thickness of the concrete sealing layer is t0, calculate the crack width W based on the design load of the concrete structure and the relevant industry standards. cr,t ; S12. Based on the crack width value W cr,c Substitute the second fitted curve in S3 to obtain the corresponding predicted value t of the sealing layer thickness. c ; S13. If t c <t min , t min If the minimum sealing layer thickness is required by the relevant industry standard, then the sealing layer thickness of the concrete structure is increased to t0+f(t). min -t c If f > 1, terminate the capping design; otherwise, terminate the capping design.

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