Corrosion steel bar morphological feature extraction device and non-uniform corrosion analysis method

Abstract

The invention particularly relates to a corroded steel bar morphology feature extraction device and a non-uniform corrosion analysis method.The corroded steel bar morphology feature extraction device comprises a base and a three-dimensional scanner, a steel bar fixing mechanism is assembled on the upper side of the base and comprises a sliding rail, the sliding rail is fixedly assembled at the upper end of the base, and supports are assembled on the left side and the right side of the upper end of the base; the left support is fixedly connected with the base, the lower side of the right support is provided with a wheel set, the sliding rail is provided with a plurality of evenly-distributed hole sites, the right side of the upper end of the base is fixedly provided with rivets, the steel bar driving assembly comprises a hand rocker, the hand rocker is rotationally assembled on the upper side of the support, and a closed wheel disc is rotationally assembled on the upper side of the support. The rocker is fixedly connected with the closed wheel disc, the supports are inserted with bolts, the closed wheel disc is provided with pin holes, the closed wheel disc is fixedly provided with identification fan blades along the circular contour, the closed wheel disc is fixedly provided with self-centering vises, and an experimental steel bar is assembled between the self-centering vises of the left and right supports.

Description

Technical Field

[0001] The invention belongs to the technical field of steel bar corrosion data analysis, and in particular relates to a device for extracting morphological features of corroded steel bars and a method for analyzing uneven corrosion. Background Art

[0002] Steel bar corrosion is the main cause of durability degradation of existing concrete structures. In the current research field of steel bar corrosion, most scholars have conducted mechanical property degradation analysis of corroded steel bars and structural bearing capacity and ductility degradation based on the assumption of uniform steel bar corrosion, ignoring the stress concentration caused by uneven steel bar corrosion, which will exaggerate the assessment of structural durability and affect the scientificity and accuracy of concrete structure maintenance decision-making. Therefore, understanding the uneven distribution characteristics of steel bar corrosion is helpful to evaluate the actual degradation of mechanical properties of concrete structures in actual projects.

[0003] The primary task in exploring the uneven corrosion of steel bars in service environments is to obtain the morphological characteristics of the corroded steel bars. However, it is very difficult to obtain the morphological characteristics of corroded steel bars at all angles, which leads to relatively few studies on the unevenness of corroded steel bars. In previous studies, researchers mostly used vernier caliper method, weighing method, drainage method, image method, XCT method, etc. to extract the corrosion of steel bars, and used parameters such as mass corrosion rate and volume corrosion rate to reflect the overall corrosion degree of steel bars. However, the accuracy of the vernier caliper method is easily affected by the conversion method, resulting in inconsistent measurement results. The weighing method and drainage method can only obtain the average The degree of corrosion; the imaging method has very high requirements on pixels, and it only takes pictures to record the morphological characteristics of the corroded steel bars, and it is difficult to obtain data support; the XCT method is complex and costly to operate and is not suitable for general experiments; compared with the above methods, 3D scanning technology can accurately capture the morphological characteristics of the corroded steel bars and form point cloud data, which is helpful for the study of uneven corrosion, but this method also has many problems such as difficulty in scanning the steel bars at all angles and redundant point cloud data; therefore, it is very necessary to invent a device for extracting the morphological characteristics of corroded steel bars and a method for studying uneven corrosion with 3D scanning as the technical support. Summary of the invention

[0004] The purpose of the present invention is to provide a device for extracting the morphological features of corroded steel bars and a method for analyzing uneven corrosion, so as to solve the problems existing in the background technology.

[0005] In order to achieve the above technical objectives, the technical solution adopted by the present invention is as follows:

[0006] A device for extracting morphological features of corroded steel bars, comprising a base and a three-dimensional scanner, wherein a steel bar fixing mechanism is installed on the upper side of the base, wherein the steel bar fixing mechanism comprises a slide rail, wherein the slide rail is fixedly installed on the upper end of the base, wherein supports are installed on both the left and right sides of the upper end of the base, wherein the supports are equipped with steel bar driving components, wherein the support on the left side is fixedly connected to the base, and the support on the right side is slidably connected to the slide rail left and right, wherein a wheel group is installed on the lower side of the support on the right side, wherein a plurality of evenly distributed holes are provided on the slide rail, wherein the support on the right side is fixedly connected to the slide rail by bolts, and wherein a rivet is fixedly provided on the right side of the upper end of the base;

[0007] The steel bar driving assembly includes a hand crank, which is rotatably assembled on the upper side of the support, and a closed disc is rotatably assembled on the upper side of the support. The hand crank is fixedly connected to the closed disc, and a pin is inserted into the support. The closed disc is provided with a plurality of pin holes matching the pin, and an identification fan is fixedly assembled on the closed disc along a circular contour. A self-centering vise is fixedly assembled on the closed disc, and experimental steel bars are assembled between the automatic centering vises of the left and right supports.

[0008] Preferably, the base, slide rail, support, wheel set, rivet, hand crank, latch, automatic core vise, test steel bar, identification fan and closed wheel disc are all sprayed with black paint.

[0009] Preferably, the length of the slide rail is 300 mm, the interval between adjacent holes is 20 mm, and the interval between the slide rail and the front and rear ends of the base is 10 mm.

[0010] Preferably, the length of the test steel bar is between 100 mm and 400 mm.

[0011] Preferably, the measuring range of the three-dimensional scanner is 100 mm×300 mm, and the reference working distance between the three-dimensional scanner lens and the test steel bar is 620 mm to 720 mm.

[0012] Preferably, the experimental steel bars are all sprayed with a developer.

[0013] Preferably, the marking sector is paved with a plurality of marking points.

[0014] A method for analyzing uneven corrosion of corroded steel bars, based on a device for extracting morphological features of corroded steel bars, comprises the following steps:

[0015] S1: Establishing coordinate axes and format conversion processing for the extracted steel bar morphology feature image: Importing the extracted scan file into Geomagic Studio software for data optimization, setting the steel bar coordinates, and storing it as a .STL file;

[0016] S2: Use Matlab program to read the .STL file, select the Z-axis section, and vertex ≤ΔZ filter local point cloud, where Z vertex represents the vertex coordinates, and ΔZ is the tolerance range, which stipulates that the selected cross-sectional figures are within the steel bar range;

[0017] S3: According to the establishment of the Z axis, the steel bar section is intercepted at intervals of 1mm, and the point cloud data with Z axis coordinates of Z±ΔZ is retained; the integrity of the circular figure of the cross section formed by the point cloud data is screened, and the point cloud data with local defects is processed by adding points, that is, Delaunay triangulation is performed on the XY plane to generate a triangular mesh, and each triangle is traversed. New points are added on each edge by linear interpolation to generate a supplemented point cloud. The formula for linear interpolation is:

[0018]

[0019] Where v1 and v2 are the two vertices of the triangle, k is the interpolation point index, and N is the number of points inserted on each edge;

[0020] S4: Use the alpha shape algorithm to reconstruct the shape of the cross-section circular point cloud data and extract the outer contour curve. The parameter α of the alpha shape algorithm is used to control the compactness of the shape;

[0021] S5: After extracting the outer contour, the cross-sectional area A of the corroded steel bar is obtained based on the calculation formula of the polygon area:

[0022]

[0023] Where (x i y i ) are the coordinates of the vertices on the outer contour, and n is the number of vertices.

[0024] The invention satisfies the basic function of acquiring the characteristic morphological image of corrosion within the range. The scanning range of the steel bar is 100-400mm. The simple and fast device method can efficiently obtain point cloud data, and quickly obtain the cross-sectional information of the corroded steel bar through Matlab programming. The cross-sectional corrosion rate and uneven corrosion of the steel bar are studied based on the statistical analysis method.

[0025] Compared with the prior art, the advantages of the steel bar morphology feature extraction of the present invention are: compared with the known auxiliary three-dimensional scanning steel bar clamp, the present invention can be adjusted according to the size and length of the steel bar, and the applicable steel bar length range is wider; and the steel bar can be rotated 360° throughout the range through the joystick to avoid missing surfaces, broken surfaces, etc. during three-dimensional scanning; the marking surface covered with marking points in the clamp device helps the three-dimensional scanner to position the steel bar; the clamp end is fixed by a self-centering vise to always ensure that the steel bar and the marking points on the marking surface remain relatively still; in summary, the device of the present invention effectively solves the problems of holes, misalignment, missing scans, and inability to sew in the scanning results, is easy to operate, has a simple process, is ready to use after installation, occupies a very small area, and is very suitable for the extraction of surface morphology features of rusted steel bars. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention is further illustrated by means of the non-limiting examples given in the accompanying drawings.

[0027] Figure 1 It is a structural schematic diagram of a device for extracting morphological features of corroded steel bars according to the present invention;

[0028] Figure 2 It is a partial structural schematic diagram of a device for extracting the morphological features of corroded steel bars according to the present invention;

[0029] Figure 3 This is a full-body real shot of the steel bars in the embodiment of the present invention;

[0030] Figure 4 A point cloud diagram of a three-dimensional scan of a steel bar according to an embodiment of the present invention;

[0031] Figure 5 It is a cross-sectional profile diagram identified by Matlab program according to an example of the present invention;

[0032] Figure 6 This is a cross-sectional profile diagram after point filling based on Matlab program in the example of the present invention;

[0033] Figure 7 The outer contour of the cross section of the corroded steel bar extracted by the Matlab program according to the example of the present invention;

[0034] Figure 8 This is a comparison diagram of the cross-sectional area results of steel bars ① obtained by commercial software and self-programming in an example of the present invention;

[0035] Fig. 9 It is a statistical diagram of the residual cross-sectional area of ​​the steel bar ① of the present invention;

[0036] Fig.10 The cross-sectional area distribution of the corroded steel bar ② along the longitudinal length of the present invention;

[0037] Fig.11It is a statistical diagram of the cross-sectional area of ​​the corroded steel bar ② of the example of the present invention;

[0038] Fig.12 The cross-sectional area of ​​the steel bar① measured by vernier caliper;

[0039] Fig.13 It is a flow chart of the present invention.

[0040] The main component symbols are described as follows:

[0041] Base 1, slide rail 2, support 3, wheel set 4, rivet 5, hand crank 6, latch 7, self-centering vise 8, experimental steel bar 9, identification fan 10, closed wheel disc 11. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0043] like Figure 1-2 As shown, a device for extracting morphological features of corroded steel bars of the present invention comprises a base 1 and a three-dimensional scanner, a steel bar fixing mechanism is mounted on the upper side of the base 1, the steel bar fixing mechanism comprises a slide rail 2, the slide rail 2 is fixedly mounted on the upper end of the base 1, supports 3 are mounted on both the left and right sides of the upper end of the base 1, the supports 3 are mounted with a steel bar driving assembly, the left support 3 is fixedly connected to the base 1, the right support 3 is slidably connected to the slide rail 2 left and right, a wheel set 4 is mounted on the lower side of the right support 3, the slide rail 2 is provided with a plurality of evenly distributed holes, the right support 3 is fixedly connected to the slide rail 2 by bolts, and a rivet 5 is fixedly mounted on the right side of the upper end of the base 1;

[0044] The steel bar driving assembly includes a hand crank 6, which is rotatably mounted on the upper side of the support 3, and a closed wheel disc 11 is rotatably mounted on the upper side of the support 3. The hand crank 6 is fixedly connected to the closed wheel disc 11, and the support 3 is plugged with a latch 7. The closed wheel disc 11 is provided with a plurality of pin holes matching the latch 7. The closed wheel disc 11 is fixedly mounted with an identification fan 10 along a circular contour, and a self-centering vise 8 is fixedly mounted on the closed wheel disc 11. A test steel bar 9 is mounted between the automatic centering vises 8 of the left and right side supports 3. The closed wheel disc 11 and the test steel bar 9 are driven to rotate by the hand crank 6 to perform full-angle scanning, and the latch 7 is inserted into the closed wheel disc 11 and the support 3 every time the rotation is 90°; wherein the test steel bar 9 can be fixed at the center of the closed wheel disc 11 by the self-centering vise 8, so that the test steel bar 9 and the central axis of the hand crank 6 are kept in the same straight line;

[0045] The base 1, slide rail 2, support 3, wheel set 4, rivet 5, hand crank 6, pin 7, automatic core vise 8, experimental steel bar 9, identification fan 10 and closed wheel 11 are all sprayed with black paint. The length of the slide rail 2 is 300mm, the interval between adjacent holes is 20mm, the interval between the slide rail 2 and the front and rear ends of the base 1 is 10mm, the length of the experimental steel bar 9 is between 100mm and 400mm, the measurement range of the 3D scanner is 100mm×300mm, the reference working distance between the 3D scanner lens and the experimental steel bar 9 is 620mm~720mm, the experimental steel bars 9 are all sprayed with imaging agent, and the identification fan 10 is paved with several identification points.

[0046] A method for analyzing uneven corrosion of corroded steel bars, based on a device for extracting morphological features of corroded steel bars, comprises the following steps:

[0047] S1: Establishing coordinate axes and format conversion processing for the extracted steel bar morphology feature image: Importing the extracted scan file into Geomagic Studio software for data optimization, setting the steel bar coordinates, and storing it as a .STL file;

[0048] S2: Use Matlab program to read the .STL file, select the Z-axis section, and vertex ≤ΔZ filter local point cloud, where Z vertex represents the vertex coordinates, and ΔZ is the tolerance range, which stipulates that the selected cross-sectional figures are within the steel bar range;

[0049] S3: According to the establishment of the Z axis, the steel bar section is intercepted at intervals of 1mm, and the point cloud data with Z axis coordinates of Z±ΔZ is retained; the integrity of the circular figure of the cross section formed by the point cloud data is screened, and the point cloud data with local defects is processed by adding points, that is, Delaunay triangulation is performed on the XY plane to generate a triangular mesh, and each triangle is traversed. New points are added on each edge by linear interpolation to generate a supplemented point cloud. The formula for linear interpolation is:

[0050]

[0051] Where v1 and v2 are the two vertices of the triangle, k is the interpolation point index, and N is the number of points inserted on each edge;

[0052] The number of points N inserted on each edge can be adjusted as needed to reduce or increase the density of supplementary points;

[0053] S4: Use the alpha shape algorithm to reconstruct the shape of the cross-section circular point cloud data and extract the outer contour curve. The parameter α of the alpha shape algorithm is used to control the compactness of the shape;

[0054] The parameter α of the alpha shape algorithm is selected according to the required shape compactness. The larger the α value, the tighter the shape. Specifically, different α values ​​are applicable to different diameters of steel bars. For example, for a steel bar with a diameter of 6.5 mm, the parameter α can be set to 1.5 or 2.0.

[0055] S5: After extracting the outer contour, the cross-sectional area A of the corroded steel bar is obtained based on the calculation formula of the polygon area:

[0056]

[0057] Where (x i y i ) are the coordinates of the vertices on the outer contour, and n is the number of vertices;

[0058] With regard to the corrosion parameter analysis of the present invention, compared with the prior art, the corrosion parameters studied in the prior art generally revolve around parameters such as mass corrosion rate and maximum corrosion pit depth. The present invention chooses to study the cross-sectional corrosion rate, which can more intuitively reflect the spatial distribution characteristics of uneven corrosion of steel bars. In addition, the present invention uses an independent program based on Matlab software in the research process, which is more efficient than the data processing method of commercial software. The present invention selects two groups of experimental steel bars as examples for verification according to the mass corrosion rate, in which steel bar ① is uncorroded steel bar and steel bar ② has a mass corrosion rate of 10.6%. It is worth mentioning that the corroded steel bars come from the simulated natural corrosion environment. The corroded beam component is more in line with the corrosion of steel bars in actual engineering. Secondly, when writing the program, the present invention takes into account the irregularity of the cross-sectional curve and selects the α-shape method, which has the following three main advantages: first, the method has strong applicability and flexibility, and the accuracy and complexity of the generated shape can be controlled by adjusting the α parameter to achieve the user's ideal result; second, the method can handle concave hulls, and can outline multiple boundary lines for multiple point clouds, which is particularly important when processing complex shapes; third, its powerful computing performance, the optimized α-shape algorithm can also efficiently cope with large point cloud data sets with huge data volumes, significantly improving the computing efficiency;

[0059] Example:

[0060] In this example, two round steel bars with a length of about 370 mm and a maximum diameter of 6 mm are selected according to the degree of corrosion of the steel bars, namely steel bar ① (no corrosion) and steel bar ② (slightly corroded). The corroded steel bars are extracted from concrete beam components simulating natural corrosion. By measuring the quality of the corroded steel bars, it can be concluded that the quality corrosion rate of steel bar ② is 10.6%;

[0061] Before performing 3D scanning to extract the steel bar morphology features, spray a layer of developer evenly on the surface of the rust-removed steel bar, such as Figure 3As shown; after drying and forming a film, fix it to the self-centering vise 8, operate the steel bar fixing mechanism and the steel bar driving assembly, and after completing the above preparations, place the auxiliary three-dimensional scanning device in front of the three-dimensional scanner lens to gradually scan and obtain the point cloud data of the steel bar; Figure 4 The point cloud data of the steel bars obtained based on 3D scanning is displayed. The steel bar ① has a smooth surface without bumps and is cylindrical in shape with uniform thickness. The surface of the steel bar ② is covered with rust pits of varying depths and dense rust marks, and is of varying thickness.

[0062] The scanned file is imported into Geomagic Studio software to check for broken surfaces, missing surfaces, misalignment, etc., and the point cloud data is optimized. Then, the coordinate axis is established with the center axis of the steel bar as the Z axis, and the .STL file is exported. The optimized .STL file is imported into the program independently written by the present invention, and the point cloud data of the outer contour of the cross section can be effectively obtained, such as Figure 5 As shown; at the same time, the point cloud defect position is supplemented, such as Figure 6 As shown; finally, the cross-sectional area of ​​the steel bar is accurately extracted using the shape parameter a, as shown Figure 7 As shown;

[0063] The distribution of the cross-sectional area of ​​the non-corroded steel bars along the longitudinal direction was extracted using a vernier caliper, commercial software, and a self-written program. First, the maximum diameter of the steel bar ① was measured using a vernier caliper and the corresponding cross-sectional area was calculated. The measurement results are shown in Figure 2. Fig.12 As shown; secondly, commercial software and self-written programs were used to extract the distribution of the cross-sectional area of ​​non-corroded steel bars along the longitudinal length, as shown in Figure 8 As shown in Table 1 and Figure 8 It can be seen that the residual cross-sectional areas of corroded steel bars obtained by the three different methods are relatively consistent, and the cross-sectional information of steel bars can be extracted along the longitudinal length using commercial software and self-written programs, which is more conducive to the analysis of uneven corrosion of steel bars; however, in terms of computational efficiency, since commercial software needs to select and calculate the cross-sectional area for each cross section, it takes a long time to extract information. For example, it takes about half an hour to obtain the information of a steel bar with a length of 370 mm. However, under the same computational requirements, it only takes about 10 seconds from reading the steel bar point cloud data to outputting the residual cross-sectional area results of the corroded steel bars based on the self-written program; in summary, the use of the self-written program to extract the cross-sectional area of ​​steel bars is accurate and efficient;

[0064] Through data processing, we can get the area distribution of steel bar ①, such as Fig. 9 As shown in the figure, the cross-sectional area of ​​steel bar ① is concentrated, and the cross-sectional area is mostly 35mm 2 Around, the minimum cross-sectional area is 34mm 2 , the maximum cross-sectional area is 36mm 2 , the fluctuation range is 2mm2 within;

[0065] Fig.10 and 11 The distribution of the cross-sectional area of ​​steel bar ② along the longitudinal length and its statistical diagram are shown respectively; it can be seen from the figure that the maximum and minimum cross-sectional areas of steel bar ② are 36mm 2 With 27.5mm 2 , difference 8.5mm 2 , indicating that the cross-sectional area distribution of the steel bars is relatively discrete; connecting the residual cross-sectional area counts of the corroded steel bars can find three maximum values, which are 29.5mm 2 、32mm 2 With 34mm 2 , indicating that the frequency of its fluctuation is very large, and the steel bar ② has obvious uneven corrosion, which is consistent with the point cloud of steel bar ②; in addition, the residual cross-sectional area of ​​the steel bars at the lengths of 50mm, 200mm, and 340mm is a small value, indicating that obvious corrosion reaction has occurred there, resulting in cross-sectional area loss. The difference between the three is about 150mm, which shows that the corrosion of the steel bars at the stirrup distribution is better, and the cross-sectional area loss of the steel bars at the position where the protective layer of the corroded steel bars is thinner is greater;

[0066] The point cloud data extracted by the device of the present invention obtains the geometric morphology image of the corroded steel bars, and can further extract many corrosion parameters for measuring the corrosion degree of the corroded steel bars, such as the depth and position distribution of rust pits of the corroded steel bars, the circumference of the cross section of the corroded steel bars, the residual volume of the corroded steel bars and other characteristic parameters, which is of great significance for studying the uneven corrosion of the corroded steel bars.

[0067] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A device for extracting the morphological features of corroded steel bars, comprising a base and a three-dimensional scanner, characterized in that: A steel bar fixing mechanism is installed on the upper side of the base, and the steel bar fixing mechanism includes a slide rail, and the slide rail is fixedly installed on the upper end of the base, and supports are installed on the left and right sides of the upper end of the base, and the supports are equipped with a steel bar driving assembly, the left support is fixedly connected to the base, and the right support is slidably connected to the slide rail left and right, and a wheel group is installed on the lower side of the right support, and the slide rail is provided with a plurality of evenly distributed holes, and the right support and the slide rail are fixedly connected by bolts, and a rivet is fixedly provided on the right side of the upper end of the base; The steel bar driving assembly includes a hand crank, which is rotatably assembled on the upper side of the support, and a closed disc is rotatably assembled on the upper side of the support. The hand crank is fixedly connected to the closed disc, and a pin is inserted into the support. The closed disc is provided with a plurality of pin holes matching the pin, and an identification fan is fixedly assembled on the closed disc along a circular contour. A self-centering vise is fixedly assembled on the closed disc, and experimental steel bars are assembled between the automatic centering vises of the left and right supports.

2. The device for extracting the morphological features of corroded steel bars according to claim 1, characterized in that: The base, slide rail, support, wheel set, rivet, hand crank, latch, automatic core vise, experimental steel bar, identification fan and closed wheel are all sprayed with black paint.

3. The device for extracting the morphological features of corroded steel bars according to claim 1, characterized in that: The length of the slide rail is 300 mm, the interval between adjacent holes is 20 mm, and the interval between the slide rail and the front and rear ends of the base is 10 mm.

4. The device for extracting the morphological features of corroded steel bars according to claim 3, characterized in that: The length of the experimental steel bar is between 100 mm and 400 mm.

5. The device for extracting the morphological features of corroded steel bars according to claim 1, characterized in that: The measuring range of the three-dimensional scanner is 100 mm×300 mm, and the reference working distance between the three-dimensional scanner lens and the experimental steel bar is 620 mm to 720 mm.

6. The device for extracting the morphological features of corroded steel bars according to claim 1, characterized in that: The experimental steel bars were all sprayed with a developer.

7. The device for extracting the morphological features of corroded steel bars according to claim 1, characterized in that: The marking sector is provided with a plurality of marking points.

8. A method for analyzing uneven corrosion of corroded steel bars, based on a device for extracting morphological features of corroded steel bars according to claims 1-7, characterized in that: The following steps are involved: S1: Establishing coordinate axes and format conversion processing for the extracted steel bar morphology feature image: Importing the extracted scan file into Geomagic Studio software for data optimization, setting the steel bar coordinates, and storing it as a .STL file; S2: Use Matlab program to read the .STL file, select the Z-axis section, and vertex ≤ΔZ filter local point cloud, where Z vertex represents the vertex coordinates, and ΔZ is the tolerance range, which stipulates that the selected cross-sectional figures are within the steel bar range; S3: According to the establishment of the Z axis, the steel bar section is intercepted at intervals of 1mm, and the point cloud data with Z axis coordinates of Z±ΔZ is retained; the integrity of the circular figure of the cross section formed by the point cloud data is screened, and the point cloud data with local defects is processed by adding points, that is, Delaunay triangulation is performed on the XY plane to generate a triangular mesh, and each triangle is traversed. New points are added on each edge by linear interpolation to generate a supplemented point cloud. The formula for linear interpolation is: Where v1 and v2 are the two vertices of the triangle, k is the interpolation point index, and N is the number of points inserted on each edge; S4: Use the alpha shape algorithm to reconstruct the shape of the cross-section circular point cloud data and extract the outer contour curve. The parameter α of the alpha shape algorithm is used to control the compactness of the shape; S5: After extracting the outer contour, the cross-sectional area A of the corroded steel bar is obtained based on the calculation formula of the polygon area: Where (x i y i ) are the coordinates of the vertices on the outer contour, and n is the number of vertices.

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