Method and system for measuring road core sample size based on line laser scanning

Abstract

The present invention discloses a method and system for measuring the size of a road core sample based on line laser scanning, comprising the following steps: S1: setting the rotation speed of a rotating platform of a laser generator; S2: clarifying the coordinate relationship between the coordinate systems of a line laser scanning system based on a direct laser triangulation method, and calculating the camera internal parameter matrix A and the external parameter matrix [R, t]; S3: acquiring images with timestamps and grouping the images according to the timestamps; S4: converting two images in each group of images into two-dimensional images for splicing, and determining the standard diameter and height of the core sample to be measured according to the physical coordinate points of each group of spliced ​​images; S5: performing surface reconstruction on each group of spliced ​​images, and obtaining the diameters of each level of the core sample to be measured according to the surface reconstruction and the standard diameter of the core sample to be measured; the advantages of the present invention are: combining two-dimensional and three-dimensional models to effectively observe the diameters of irregular cylinders on the side at different heights.

Description

Technical Field

[0001] The invention relates to the field of measurement, and in particular to a method and a system for measuring the size of a road core sample based on line laser scanning. Background Art

[0002] In the current daily inspection process, the coring method is used to measure the thickness of the road structure layer. A coring machine takes out a cylindrical core sample from the structure layer and then uses a steel tape measure to manually measure its diameter and height.

[0003] Due to the special material of the road core sample, there is a big difference between the sampling side and the ideal cylindrical side, and most of the sampling side is irregular and broken; and the road core sample has obvious multi-level stratification due to the multi-layer paving of the road construction. In the case of relying only on the tape measure, the division of each level of the road core sample and the diameter of each level are determined by the subjective judgment of the inspection personnel. The greater subjectivity determines the objective facts, which is prone to large errors and is not conducive to subsequent quality, durability, compressive strength and other inspections.

[0004] For example, the published patent application document (CN114812413A) "A method and system for measuring the diameter of a cylinder" proposes a method for measuring the diameter of a standard cylinder. The bottom surface is placed on a rotating platform, one axis is scanned, and then the diameter of the measured cylinder is calculated. The main method is to establish a polar coordinate system with the rotation center of the rotating platform as the origin, and calculate the diameter of a regular cylinder by combining the collection of multiple diameter points and the calibration distance from the camera to the rotation center. There is a lack of diameter calculations for each level of irregular cylinders. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a method and system for measuring the size of road core samples based on line laser scanning, which is used to solve the technical problem that the prior art lacks the calculation of the diameters of each layer of irregular cylinders.

[0006] To achieve the above object, the present invention provides a method for measuring the size of a road core sample based on line laser scanning, comprising the following steps:

[0007] S1: Set the rotation speed of the laser generator rotating platform to a multiple of the camera shooting frequency;

[0008] S2: Based on the direct laser triangulation method, the coordinate relationship between the coordinate systems of the line laser scanning system is clarified, and the camera internal parameter matrix A and external parameter matrix [R, t] are calculated to ensure that the camera accurately captures the projection position of the laser line on the surface of the core sample to be measured;

[0009] S3: Obtain images with timestamps and group the images according to the timestamps, each group of images contains two images;

[0010] S4: converting two images in each set of images into two-dimensional images for splicing, and determining the standard diameter and height of the core sample to be tested according to the physical coordinate points of each set of spliced ​​images;

[0011] S5: Perform surface reconstruction on each group of spliced ​​images based on Voronoi Thiessen polygon two-dimensional scatter plot and greedy projection algorithm, and obtain the diameter of each layer of the core sample to be tested according to the surface reconstruction and the standard diameter of the core sample to be tested;

[0012] In S1, the rotation speed of the rotating platform is a multiple of the shooting frequency of the camera. The rotation speed of the rotating platform and the shooting frequency of the camera are adjusted to make a multiple relationship between the two, thereby achieving efficient and accurate image capture.

[0013] Further: The specific method of S2 is as follows:

[0014] Establish a pixel coordinate system with pixels as units (u, v, 1), the camera coordinate system with the camera lens as the origin (Xc, Yc, Zc) and the world coordinate system that describes the actual position of the camera in three-dimensional space ( Xw , Yw , Zw );

[0015] Based on the principles of coordinate system transformation and camera projection model, the camera intrinsic parameter matrix A and extrinsic parameter matrix [R, t] are obtained;

[0016] The coordinate system transformation includes: transformation between world coordinate system and camera coordinate system, transformation between pixel coordinate system and physical coordinate system;

[0017] The conversion relationship between the camera coordinate system and the world coordinate system is shown in the following formula:

[0018] ;

[0019] in, is the rotation matrix between the camera coordinate system and the world coordinate system, and its size is ;

[0020] is the translation vector between the camera coordinate system and the world coordinate system;

[0021] 0 is one The all-zero matrix of

[0022] 1 for one The all-one matrix of ;

[0023] The conversion relationship between the pixel coordinate system and the physical coordinate system can be expressed as:

[0024] ;

[0025] Where dx and dy are the physical lengths of a single pixel in the x-axis and y-axis directions respectively;

[0026] is the coordinate of any point on the imaging plane in the pixel coordinate system;

[0027] is the coordinate of the origin of the physical coordinate system in the pixel coordinate system;

[0028] The coordinates of any point on the imaging plane in the pixel coordinate system correspond to the coordinates in the physical coordinate system;

[0029] Then, according to the camera projection model principle, the coordinate relationship is established as follows:

[0030] ;

[0031] Thus, we get the camera internal parameter matrix A and external parameter matrix [R, t];

[0032] Among them, the world coordinate system and the camera coordinate system are both coordinate systems in three-dimensional space, and the two coordinate systems can be converted to each other through rigid transformation, that is, the camera coordinate system and the world coordinate system can be transformed to each other through translation and rotation;

[0033] The pixel coordinate system takes the pixel starting position as the origin and the pixel direction as the coordinate direction. Let the pixel row direction be the u axis and the pixel column direction be the v axis. That is, the coordinates of any point on the imaging plane can be written as (u, v) in the pixel coordinate system. The physical coordinate system takes the intersection of the camera lens main axis and the imaging plane as the origin. Its coordinate axis direction is parallel to the pixel coordinate system direction, that is, the x-axis is consistent with the u-axis direction, and the y-axis is consistent with the v-axis direction. Let the coordinates of the origin of the physical coordinate system in the pixel coordinate system be (u0, v0). The physical lengths of a single pixel in the x-axis and y-axis directions are dx and dy respectively.

[0034] Further: the specific method of S3 is:

[0035] The core sample to be tested is placed on the rotating platform of the laser generator, and the camera collects data with a time stamp. The images are grouped according to the following rules: and The images are grouped into one;

[0036] in, , ;

[0037] All timestamps corresponding to the images captured by the camera when the laser generator rotating platform rotates one circle;

[0038] n is the number of times the camera takes pictures, divided into Group;

[0039] This ensures that each set of images is a complete image of the core sample to be tested after one rotation.

[0040] Further: The specific method of S4 is:

[0041] The two images in each group of images are converted into two-dimensional images and stitched together. The pixel coordinates in the stitched two-dimensional images are converted into physical coordinates. ; where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image; j is the j-th column of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image;

[0042] Traverse each row and column of the row and column structure composed of physical coordinate points in each group of images, and obtain the maximum row length of each group of images and the maximum length of the column ; Create a row length array and an array of column lengths ; Treat all the data in the row length array and column length array as normal distribution and assign weights; determine the standard diameter and height of the core sample to be tested based on the weighted average method, as shown in the following formula:

[0043] ;

[0044] ;

[0045] Among them, R is the standard diameter of the core sample to be tested, and H is the height of the core sample to be tested;

[0046] is the weight of the maximum value of the length of the k-th group of image rows;

[0047] π is the ratio of a circle to a circle;

[0048] is the weight of the maximum value of the length of the k-th group of image columns;

[0049] The purpose is to directly convert the side faces of several core samples to be tested into a two-dimensional image, which is represented on the horizontal axis as the circumference of the cylinder and on the vertical axis as the height of the cylinder, and the standard diameter and height of the core sample to be tested are calculated in a weighted average manner.

[0050] Further: The specific method of performing normal distribution processing and assigning weights is:

[0051] Process row length arrays separately and an array of column lengths ; Calculate the mean and standard deviation of an array of row lengths and the mean and standard deviation of an array of column lengths;

[0052] Among them, the row length array Middle: Located The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.1;

[0053] Column length array Middle: Located The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data with the highest value is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.1.

[0054] Further: the specific method of S5 is:

[0055] For each physical coordinate in each group of spliced ​​images in S4 Standardization processing, unify the number of rows i and columns j of physical coordinate points to ensure that the rows and columns of coordinate points in each spliced ​​image are the same, where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, ; j is the jth column of the row and column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, ;

[0056] Based on the triangulation principle, each physical coordinate in each group of stitched images The lines form a non-overlapping triangle combination, which is the dual graph of the Voronoi Thiessen polygon two-dimensional scatter graph;

[0057] The dual graph is reconstructed based on the greedy projection algorithm: each point in the dual graph and its neighboring points are mapped to the tangent plane of the point, and all the coordinate points contained in the two-dimensional plane are triangular meshed in a unidirectional growth manner on the two-dimensional plane. Finally, the association of the projection points in the three-dimensional space is directly determined based on the mapping relationship and topological relationship, thereby generating a spatial triangular mesh to obtain a surface model;

[0058] According to the surface tangent point of the surface model The Y-axis coordinate, Z-axis coordinate and standard diameter of the core sample to be measured in the spatial coordinate system are used to determine the diameters of each level of the core sample to be measured, that is, the diameters corresponding to different heights of the core sample to be measured;

[0059] The Y-axis coordinate actually corresponds to the Y-coordinate value of the side unfolded diagram of the core sample to be tested. After unidirectional growth, the Z coordinates of all points corresponding to the same Y-coordinate are the depressions and protrusions of all points contained in this level of the core sample to be tested.

[0060] Further: the specific method for determining the diameter of each layer of the core sample to be tested is as follows:

[0061] Each level of the core sample to be tested is divided into i layers;

[0062] The diameter corresponding to each level is the standard diameter of the core sample to be tested plus the following formula:

[0063] ;

[0064] Wherein, R is the standard diameter of the core sample to be tested;

[0065] The growth heights of all points on a certain level i are accumulated, and the approximate growth height is calculated using a completely average method as the growth height on the standard diameter, which is the true diameter of the level i.

[0066] The present invention also provides a system for measuring the size of a road core sample based on line laser scanning, comprising: a laser generator rotating platform;

[0067] The laser generator rotating platform is electrically connected to the PC device;

[0068] The PC device includes: a memory, a processor, and a program stored in the memory and executable on the processor;

[0069] The PC device is also electrically connected to at least one camera;

[0070] When the processor executes the program, the method for measuring the size of a road core sample based on line laser scanning as described above is implemented.

[0071] The present invention has the following effects:

[0072] There is no need to measure the camera parameters in advance, such as installation angle and installation distance; the laser triangulation method is used to directly clarify the coordinate relationship between the coordinate systems.

[0073] The core sample to be tested is converted into a two-dimensional image to directly obtain the core sample height, and the two-dimensional image is reconstructed by combining the Voronoi Thiessen polygon two-dimensional scatter diagram and the greedy projection algorithm to measure the diameter of the core sample to be tested at different heights. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention and the technical solutions in the prior art, the drawings required for use in the embodiments and the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some implementation methods recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 is a system flow chart of the present invention;

[0076] Figure 2 This is a schematic diagram of the camera of the present invention observing the core sample to be tested;

[0077] Figure 3 It is a system schematic diagram of the present invention. DETAILED DESCRIPTION

[0078] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0079] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can be applied to other similar scenarios based on these drawings without any creative work.

[0080] In addition, it can be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in this application, some design, manufacturing or production changes based on the technical contents disclosed in this application are just conventional technical means and should not be understood as the contents disclosed in this application are insufficient.

[0081] Unless otherwise specified, all embodiments and optional embodiments of the present application can be combined with each other to form a new technical solution.

[0082] See also Figure 1 , the system flow chart of the present invention comprises the following steps:

[0083] S1: Set the rotation speed of the laser generator rotating platform to a multiple of the camera shooting frequency;

[0084] S2: Based on the direct laser triangulation method, the coordinate relationship between the coordinate systems of the line laser scanning system is clarified, and the camera internal parameter matrix A and external parameter matrix [R, t] are calculated to ensure that the camera accurately captures the projection position of the laser line on the surface of the core sample to be measured. The capture status is as follows: Figure 2 As shown, the B axis is a polar line projected by the laser generator onto the side of the core sample to be measured and can be received by the camera;

[0085] S3: Obtain images with timestamps and group the images according to the timestamps, each group of images contains two images;

[0086] S4: converting two images in each set of images into two-dimensional images for splicing, and determining the standard diameter and height of the core sample to be tested according to the physical coordinate points of each set of spliced ​​images;

[0087] S5: Surface reconstruction is performed on each group of spliced ​​images based on the Voronoi Thiessen polygon two-dimensional scatter plot and the greedy projection algorithm, and the diameters of each layer of the core sample to be tested are obtained according to the surface reconstruction and the standard diameter of the core sample to be tested.

[0088] Specifically:

[0089] In S1, in order to ensure the quality of imaging, the rotation speed of the rotating platform is controlled to be a multiple of the camera shooting frequency. This is done by adjusting the rotation speed of the rotating platform and the camera shooting frequency to make a multiple relationship between the two, thereby achieving efficient and accurate image capture.

[0090] In S2, if you want to obtain the contour information on the measured object, you must clarify the transformation relationship between different coordinate systems and coordinate systems;

[0091] First, establish a pixel coordinate system with pixels as units (u, v, 1), the camera coordinate system with the camera lens as the origin (Xc, Yc, Zc) and the world coordinate system that describes the actual position of the camera in three-dimensional space ( Xw , Yw , Zw );

[0092] Based on the principles of coordinate system transformation and camera projection model, the camera intrinsic parameter matrix A and extrinsic parameter matrix [R, t] are obtained;

[0093] Coordinate system transformation includes: world coordinate system and camera coordinate system transformation, pixel coordinate system and physical coordinate system transformation;

[0094] Among them, the world coordinate system and the camera coordinate system are both coordinate systems in three-dimensional space, and the two coordinate systems can be converted to each other through rigid transformation, that is, the camera coordinate system and the world coordinate system can be transformed to each other through translation and rotation. The conversion relationship between the camera coordinate system and the world coordinate system is shown in the following formula:

[0095] ;

[0096] in, is the rotation matrix between the camera coordinate system and the world coordinate system, and its size is ;

[0097] is the translation vector between the camera coordinate system and the world coordinate system;

[0098] 0 is one The all-zero matrix of

[0099] 1 for one The all-one matrix of ;

[0100] M represents the total homogeneous transformation matrix between the two coordinate systems;

[0101] The transformation between the pixel coordinate system and the physical coordinate system is based on the image coordinate system. The image coordinate system is a coordinate system established on the imaging plane, including a pixel coordinate system in pixels and a physical coordinate system in physical length (in mm). The pixel coordinate system takes the pixel starting position as the origin and the pixel direction as the coordinate direction. Let the pixel row direction be the u axis and the pixel column direction be the v axis. That is, the coordinates of any point on the imaging plane can be written as (u, v) in the pixel coordinate system. The physical coordinate system takes the intersection of the camera lens principal axis and the imaging plane as the origin. The direction of its coordinate axis is parallel to the direction of the pixel coordinate system, that is, the x-axis is consistent with the u-axis direction, and the y-axis is consistent with the v-axis direction. Let the coordinates of the origin of the physical coordinate system in the pixel coordinate system be (u0, v0). The physical lengths of a single pixel in the x-axis and y-axis directions are dx and dy respectively. Then the transformation relationship between the pixel coordinate system and the physical coordinate system can be expressed as:

[0102] ;

[0103] Where dx and dy are the physical lengths of a single pixel in the x-axis and y-axis directions respectively;

[0104] is the coordinate of any point on the imaging plane in the pixel coordinate system;

[0105] is the coordinate of the origin of the physical coordinate system in the pixel coordinate system;

[0106] The coordinates of any point on the imaging plane in the pixel coordinate system correspond to the coordinates in the physical coordinate system;

[0107] Then, according to the principle of camera projection model, the coordinate relationship is established as follows:

[0108] ;

[0109] This results in the camera's intrinsic parameter matrix A and extrinsic parameter matrix [R, t].

[0110] In S3, in order to obtain multiple complete images of the side of the core sample to be tested, the core sample to be tested is placed on the rotating platform of the laser generator, and the camera collects images with timestamps. The images are grouped according to the following rules: and The images are grouped into one;

[0111] in, , ;

[0112] All timestamps corresponding to the images captured by the camera when the laser generator rotating platform rotates one circle;

[0113] n is the number of times the camera takes pictures, divided into Group;

[0114] This ensures that each set of images is a complete image of the core sample to be tested after one rotation.

[0115] In S4, in order to preliminarily obtain the standard diameter and height of the core sample to be tested, the two images in each group of images are converted into two-dimensional images for stitching, and the pixel coordinates in the stitched two-dimensional images are converted into physical coordinates. ; where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image; j is the j-th column of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image;

[0116] Traverse each row and column of the row and column structure composed of physical coordinate points in each group of images, and obtain the maximum row length of each group of images and the maximum length of the column ; Create a row length array and an array of column lengths ; Treat all the data in the row length array and column length array as normal distribution and assign weights; determine the standard diameter and height of the core sample to be tested based on the weighted average method, as shown in the following formula:

[0117] ;

[0118] ;

[0119] Among them, R is the standard diameter of the core sample to be tested, and H is the height of the core sample to be tested;

[0120] is the weight of the maximum value of the length of the k-th group of image rows;

[0121] π is the ratio of a circle to a circle;

[0122] is the weight of the maximum value of the length of the k-th group of image columns;

[0123] Among them, the specific method of normal distribution processing and weighting is:

[0124] Process row length arrays separately and an array of column lengths ; Calculate the mean and standard deviation of an array of row lengths and the mean and standard deviation of an array of column lengths;

[0125] Among them, the row length array Middle: Located The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.1;

[0126] Column length array Middle: Located The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data with the highest value is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.1.

[0127] In S5, since the core sample to be measured is a cylinder with an uneven side surface, in order to measure its true diameter, the side surface of the core sample to be measured is firstly two-dimensionalized using the method of S4, and is divided into β layers according to its coordinates on the Y axis, and the diameter of each layer is corrected respectively, as follows:

[0128] For each physical coordinate in each group of spliced ​​images in S4 Standardization processing, unify the number of rows i and columns j of physical coordinate points to ensure that the rows and columns of coordinate points in each spliced ​​image are the same, where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, ; j is the jth column of the row and column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, ;

[0129] Based on the triangulation principle, each physical coordinate in each group of stitched images The lines form a non-overlapping triangle combination, which is the dual graph of the Voronoi Thiessen polygon two-dimensional scatter graph;

[0130] The dual graph is reconstructed based on the greedy projection algorithm: each point in the dual graph and its neighboring points are mapped to the tangent plane of the point, and all the coordinate points contained in the two-dimensional plane are triangular meshed in a unidirectional growth manner on the two-dimensional plane. Finally, the association of the projection points in the three-dimensional space is directly determined based on the mapping relationship and topological relationship, thereby generating a spatial triangular mesh to obtain a surface model;

[0131] According to the surface tangent point of the surface model The Y-axis coordinate, Z-axis coordinate and standard diameter of the core sample to be tested in the spatial coordinate system are used to determine the diameter of each layer of the core sample to be tested. The specific method is as follows:

[0132] Each level of the core sample to be tested is divided into i layers;

[0133] The diameter corresponding to each level is the standard diameter of the core sample to be tested plus the following formula:

[0134] ;

[0135] Where R is the standard diameter of the core sample to be tested.

[0136] The invention has the advantages of combining two-dimensional and three-dimensional models to effectively observe the diameters of the side irregular cylinder at different heights.

[0137] The above is a very detailed description of one or more embodiments of the present invention, but the content is only a specific example of the present invention and cannot be considered to limit the scope of application of the present invention. Any other methods and changes proposed based on the content of the present invention should fall within the scope of patent protection of the present invention.

Claims

1. A method for measuring the size of a road core sample based on line laser scanning, characterized in that: The steps include: S1: Set the rotation speed of the laser generator rotating platform to a multiple of the camera shooting frequency; S2: Based on the direct laser triangulation method, the coordinate relationship between the coordinate systems of the line laser scanning system is clarified, and the camera internal parameter matrix A and external parameter matrix [R, t] are calculated to ensure that the camera accurately captures the projection position of the laser line on the surface of the core sample to be measured; S3: Obtain images with timestamps and group the images according to the timestamps, each group of images contains two images; S4: converting two images in each set of images into two-dimensional images for splicing, and determining the standard diameter and height of the core sample to be tested according to the physical coordinate points of each set of spliced ​​images; S5: Perform surface reconstruction on each group of spliced ​​images based on Voronoi Thiessen polygon two-dimensional scatter plot and greedy projection algorithm, and obtain the diameter of each layer of the core sample to be tested according to the surface reconstruction and the standard diameter of the core sample to be tested; The specific method of S5 is: respectively calculate each physical coordinate in each group of spliced ​​images in S4 Standardization processing, unify the number of rows i and columns j of physical coordinate points to ensure that the rows and columns of coordinate points in each spliced ​​image are the same, where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, i∈(1,α), α is the total number of rows of the two-dimensional image containing physical coordinate points, that is, the total level of the core sample to be tested; j is the j-th column of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image, j∈(1,β), β is the total number of columns of the two-dimensional image containing physical coordinate points; Based on the triangulation principle, each physical coordinate in each group of stitched images The lines form a non-overlapping triangle combination, which is the dual graph of the Voronoi Thiessen polygon two-dimensional scatter graph; The dual graph is reconstructed based on the greedy projection algorithm: each point in the dual graph and its neighboring points are mapped to the tangent plane of the point, and all the coordinate points contained in the two-dimensional plane are processed in a unidirectional growth manner to generate a triangular mesh. Finally, the association of the projection points in the three-dimensional space is directly determined according to the mapping relationship and topological relationship, thereby generating a spatial triangular mesh to obtain a surface model. According to the surface tangent point of the surface model The Y-axis coordinate, Z-axis coordinate and standard diameter of the core sample to be tested in the spatial coordinate system are used to determine the diameters of each level of the core sample to be tested, that is, the diameters corresponding to different heights of the core sample to be tested. The specific method for determining the diameter of each layer of the core sample to be tested is as follows: Each level of the core sample to be tested is divided into α layers; The diameter corresponding to the i-th level is shown in the following formula: ； Where R is the standard diameter of the core sample to be tested.

2. The method for measuring the size of a road core sample based on line laser scanning according to claim 1, characterized in that: The specific method of S2 is as follows: Establish a pixel coordinate system with pixels as units (u, v, 1), the camera coordinate system with the camera lens as the origin (Xc, Yc, Zc) and the world coordinate system that describes the actual position of the camera in three-dimensional space ( Xw , Yw , Zw ); Based on the principles of coordinate system transformation and camera projection model, the camera intrinsic parameter matrix A and extrinsic parameter matrix [R, t] are obtained; The coordinate system transformation includes: transformation between world coordinate system and camera coordinate system, transformation between pixel coordinate system and physical coordinate system; The conversion relationship between the camera coordinate system and the world coordinate system is shown in the following formula: ； in, It is the rotation matrix between the camera coordinate system and the world coordinate system, with a size of 3*3; is the translation vector between the camera coordinate system and the world coordinate system; 0 is a 1*3 all-zero matrix; 1 is a 1*3 all-one matrix; The conversion relationship between the pixel coordinate system and the physical coordinate system can be expressed as: ； Where dx and dy are the physical lengths of a single pixel in the x-axis and y-axis directions respectively; is the coordinate of any point on the imaging plane in the pixel coordinate system; is the coordinate of the origin of the physical coordinate system in the pixel coordinate system; The coordinates of any point on the imaging plane in the pixel coordinate system correspond to the coordinates in the physical coordinate system; Then, according to the camera projection model principle, the coordinate relationship is established as follows: ； This results in the camera's intrinsic parameter matrix A and extrinsic parameter matrix [R, t].

3. The method for measuring the size of a road core sample based on line laser scanning according to claim 1, characterized in that: The specific method of S3 is: The core sample to be tested is placed on the rotating platform of the laser generator, and the camera collects data with a time stamp. The images are grouped according to the following rules: and The images are grouped into one; in, , ; All timestamps corresponding to the images captured by the camera when the laser generator rotating platform rotates one circle; n is the number of times the camera takes pictures, divided into Group.

4. The method for measuring the size of a road core sample based on line laser scanning according to claim 1, characterized in that: The specific method of S4 is: The two images in each group of images are converted into two-dimensional images and stitched together. The pixel coordinates in the stitched two-dimensional images are converted into physical coordinates. ; where k is the kth group of images, , is the total number of image groups; i is the i-th row of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image; j is the j-th column of the row-column structure composed of the physical coordinate points in each spliced ​​two-dimensional image; Traverse each row and column of the row and column structure composed of physical coordinate points in each group of images, and obtain the maximum row length of each group of images and the maximum length of the column ; Create a row length array ( , ,……, ) and an array of column lengths ( , ,……, ); treat all the data in the row length array and column length array as normal distribution and assign weights; determine the standard diameter and height of the core sample to be tested based on the weighted average method, as shown in the following formula: ; ； Among them, R is the standard diameter of the core sample to be tested, and H is the height of the core sample to be tested; is the weight of the maximum value of the length of the k-th group of image rows; π is the ratio of a circle to a circle; is the weight of the maximum value of the length of the k-th group of image columns.

5. The method for measuring the size of a road core sample based on line laser scanning according to claim 4, characterized in that: The specific method of performing normal distribution processing and assigning weights is: Process the row length array separately ( , ,……, ) and an array of column lengths ( , ,……, ; Calculate the mean and standard deviation of an array of row lengths and the mean and standard deviation of an array of column lengths; Among them, the row length array ( , ,……, ) in: The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.1; Column length array ( , ,……, ) in: The data is given a weight of 0.4 and is located at and The data is given a weight of 0.3, located and The data with the highest value is assigned a weight of 0.2, and the rest of the data is assigned a weight of 0.

1.

6. A system for measuring the size of road core samples based on line laser scanning, characterized in that: include: Laser generator rotating platform; The laser generator rotating platform is electrically connected to the PC device; The PC device includes: a memory, a processor, and a program stored in the memory and executable on the processor; The PC device is also electrically connected to at least one camera; When the processor executes the program, the method for measuring the size of a road core sample based on line laser scanning as described in any one of claims 1 to 5 is implemented.

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