A method and system for high temperature continuous casting steel billet profile measurement

Abstract

The application provides a high-temperature continuous casting steel billet profile measurement method and system, and relates to the technical field of machine vision detection. The method comprises the following steps: collecting target steel billet surface images from different angles by multiple 3D cameras, and combining laser line dislocation distance measurement technology to calculate the depth value between the steel billet and the camera, and generating depth value data; based on the depth value data, determining the coordinates of the steel billet in each 3D camera coordinate system, and calculating the local curvature of the side surface and the upper and lower surfaces; by analyzing the curvature change difference value, identifying and removing the overlapping area, forming optimized depth value data; using the optimized depth value data, calculating the width of each section of the target steel billet, and combining the section width to generate depth value data; according to the depth value data, correcting the corrected section width by the inclination angle, and further determining the section thickness; combining the optimized depth value data, the corrected section width and the section thickness, the accurate section profile of the target steel billet is obtained.

Description

Technical Field

[0001] This invention relates to the field of machine vision inspection technology, and in particular to a method and system for measuring the contour of high-temperature continuous casting steel billets. Background Technology

[0002] Billet production is a crucial step in steel manufacturing. The size, surface quality, and internal structure of the billet directly affect subsequent rolling and the performance of the final product. The surface profile of the billet, including its thickness, width, T-value (the temperature difference between the width range and the center of the billet), and slenderness (the width-to-length ratio of the billet's shape), must meet strict quality standards to ensure the quality of the final product.

[0003] Currently, in the billet production process, the main methods for inspecting the billet's dimensions and surface quality are manual visual inspection, manual measurement, and some simple automated equipment. Manual visual inspection is usually performed by experienced operators who judge whether the billet meets specifications by observing its surface condition and dimensions; while manual measurement relies on tools such as calipers and measuring rods to periodically measure key dimensions of the billet such as width and thickness.

[0004] However, manual visual inspection relies on the experience and judgment of workers and is easily affected by the subjective factors of operators, resulting in low inspection efficiency. At the same time, traditional manual measurement relies on simple measuring tools and cannot achieve real-time and continuous accurate measurement of steel billets in production. Especially when the size of steel billets changes rapidly, manual measurement is difficult to provide sufficient accuracy. Summary of the Invention

[0005] To address the issues that manual visual inspection relies on workers' experience and judgment, which is easily affected by the operator's subjective factors, resulting in low inspection efficiency; and that traditional manual measurement relies on simple measuring tools, which cannot achieve real-time and continuous accurate measurement of steel billets during production, especially when the billet size changes rapidly, manual measurement cannot provide sufficient accuracy, this invention provides a method and system for measuring the contour of high-temperature continuous casting steel billets.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] First aspect:

[0008] This invention provides a method for measuring the profile of a high-temperature continuously cast steel billet, comprising:

[0009] S1: Use multiple 3D cameras to acquire multiple surface images of the target steel billet from multiple angles;

[0010] S2: Calculate the depth value between the target steel billet and the corresponding 3D camera zero point using laser line misalignment distance measurement technology to form depth value data;

[0011] S3: Based on the depth data, determine the coordinates of the target billet in each 3D camera coordinate system;

[0012] S4: Based on the depth data, calculate the local curvature of the side surface and the local curvature of the upper and lower surfaces of the target steel billet;

[0013] S5: Based on the local curvature of the side surface and the local curvature of the upper and lower surfaces, determine the curvature change difference. If the curvature change value is less than the preset curvature change difference, determine the overlapping area and remove the depth value data of the overlapping area to form optimized depth value data.

[0014] S6: Based on the depth values ​​relative to the camera in the optimized depth value data, calculate the cross-sectional width of each cross-section of the target steel billet at different positions, and combine the cross-sectional width to form the depth value data on each cross-section;

[0015] S7: Based on the depth data on each cut surface, determine the corrected cut surface width by adjusting the tilt angle, and determine the cut surface thickness of the corresponding cut surface based on the corrected cut surface width.

[0016] S8: Based on the optimized depth value data, the corrected section width, and the section thickness, determine the section profile of the target steel billet.

[0017] The second aspect:

[0018] This invention provides a high-temperature continuous casting billet profile measurement system, comprising:

[0019] processor;

[0020] A memory storing computer-readable instructions, which, when executed by the processor, implement the high-temperature continuous casting billet contour measurement method as described in the first aspect.

[0021] Third aspect:

[0022] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the high-temperature continuous casting billet contour measurement method as described in the first aspect.

[0023] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0024] (1) In this invention, multiple 3D cameras are used to collect multiple surface images of the target steel billet from multiple directions. The depth value between the target steel billet and the corresponding 3D camera zero point is calculated by laser line misalignment distance measurement technology to form depth value data. Through automated acquisition and calculation, the dependence of manual visual inspection on workers' experience and judgment is eliminated, the influence of subjective factors of operators is effectively reduced, and the inspection efficiency is greatly improved.

[0025] (2) In this invention, the local curvature of the side and top surfaces of the target billet is calculated, and the overlapping area is identified by combining the curvature change difference. Redundant data points are eliminated to form optimized depth value data. The optimized depth value data is further used to calculate the cross-sectional width of each cross-section of the billet at different positions. Combined with the tilt angle correction method, the corrected cross-sectional width and thickness are obtained, and finally the cross-sectional profile of the billet is formed. This enables real-time, continuous and high-precision measurement of the billet in production, effectively avoiding the limitations of traditional manual measurement that relies on simple measuring tools and is difficult to achieve accurate measurement, and improving the accuracy of measurement. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A schematic flowchart of a high-temperature continuous casting steel billet contour measurement method provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a high-temperature continuous casting billet contour measurement system provided in an embodiment of the present invention. Detailed Implementation

[0029] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0030] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0031] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0032] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0033] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0034] Reference manual attached Figure 1 The diagram shows a flowchart of a high-temperature continuous casting billet contour measurement method provided by an embodiment of the present invention.

[0035] This invention provides a method for measuring the profile of a high-temperature continuously cast steel billet. This method can be implemented using a high-temperature continuously cast steel billet profile measuring device, which can be a terminal or a server. The processing flow of the high-temperature continuously cast steel billet profile measurement method may include the following steps:

[0036] S1: Use multiple 3D cameras to acquire multiple surface images of the target steel billet from multiple angles.

[0037] S2: Using laser line misalignment distance measurement technology, the depth value between the target steel billet and the corresponding 3D camera zero point is calculated to form depth value data.

[0038] Among them, laser line misalignment distance measurement technology is a non-contact measurement technology based on the principle of laser triangulation, which is widely used for the detection of object depth, surface contour, and size. By analyzing the light deflection formed after the laser is projected onto the target surface, the distance between the object and the sensor is calculated.

[0039] Depth data is a type of digital information that describes the shape or position of an object's surface, representing the distance from a reference point (usually a reference point for devices such as 3D cameras or laser rangefinders) to various points on the object's surface.

[0040] In this invention, depth data is obtained by laser line misalignment distance measurement technology, providing a non-contact, high-precision, real-time, and comprehensive surface inspection method. This not only improves inspection efficiency and safety but also lays a solid foundation for subsequent data analysis, automated control, and shape optimization.

[0041] S3: Based on depth data, determine the coordinates of the target billet in each 3D camera coordinate system.

[0042] Optionally, the X-axis of the camera data acquisition is the horizontal cross-sectional direction of the billet, the right side of the billet's forward direction is the positive X-axis direction of the vertical camera, the left and right cameras are the positive X-axis direction of the top view direction, the Y-axis is the billet's movement direction, the billet's movement direction is defined as the positive Y-axis direction, and the Z-axis is the perpendicular direction between the billet and the camera, the direction in which the camera faces the billet is the positive Z-axis direction.

[0043] In this invention, a unified coordinate system helps to accurately map the depth data of the steel billet to its actual spatial location, ensuring more efficient fusion and alignment of multi-view data. This explicit spatial definition reduces geometric errors in data processing.

[0044] It should be noted that when analyzing data collected by an industrial camera along the Y-axis, when the y-value is fixed, the corresponding ( In the case of depth values, the camera captures both the image of the steel billet and the background image during acquisition. The difference between these two types of images (depth values) is significant, therefore, according to... Values ​​to filter out background areas corresponding to ( In addition, the four corners of the billet may be repeatedly captured by the cameras on both sides and the top and bottom, so it is necessary to collect depth data to remove overlapping areas.

[0045] S4: Based on the depth data and the coordinates of the target billet in each 3D camera coordinate system, calculate the local curvature of the side surface and the local curvature of the upper and lower surfaces of the target billet.

[0046] Local curvature is a geometric quantity used to describe the degree of curvature of a curve or surface near a certain point. It usually represents the curvature characteristics and trend of change of the shape near that point.

[0047] In one possible implementation, S4 specifically includes:

[0048] S401: Set the sequence of depth values ​​of the left side surface of the target steel billet to be acquired by the side 3D camera as follows:

[0049]

[0050] in, Z l This represents the sequence of depth values ​​on the left surface. The first section of the left surface is represented by the first section. a One depth value data, a =[1, n ], n This represents the total number of depth values ​​for the cross-section on the left side of the surface.

[0051] The sequence of cut depth values ​​on the upper surface of the target steel billet acquired by the 3D camera is as follows:

[0052]

[0053] in, Z u This represents the sequence of depth values ​​of the upper surface section. The first section of the upper surface sectional plane c One depth value data, c =[1, p ], p This represents the total number of depth data for the upper surface cross section.

[0054] S402: Based on the side surface depth value sequence and the coordinates of the target billet in each 3D camera coordinate system, the local curvature of the measured surface is calculated using the finite difference method. :

[0055] Among them, the finite difference method is a numerical method that approximates the derivative of a function by discretization, and it is widely used in numerical computation, data processing and physical simulation.

[0056]

[0057]

[0058]

[0059] in, Indicates the first on the left side surface section i Local curvature at a depth value data point Indicates the first i +2 depth data points and the first i The difference in depth values ​​between +1 depth value data points. Indicates the first i +1 depth data point and the first i The difference in depth values ​​between depth data points Indicates the first on the left side surface section i+ One depth data point, Indicates the left surface number i One depth value data point, Indicates the first on the left side surface section i+ Two depth data points, This indicates the spacing between adjacent depth data points.

[0060] S403: Calculate the local curvature of the upper surface using the same method as calculating the local curvature of the left surface. .

[0061] In this invention, by calculating the local curvature of the side and top surfaces, the geometric characteristics of the billet surface can be accurately evaluated, and overlapping areas can be quickly identified.

[0062] S5: Based on the local curvature of the side surface and the local curvature of the upper and lower surfaces, determine the curvature change difference. If the curvature change value is less than the preset curvature change difference, determine the overlapping area and remove the depth value data of the overlapping area to form optimized depth value data.

[0063] In one possible implementation, S5 specifically includes:

[0064] S501: Calculate the difference in curvature variation:

[0065]

[0066] in, Indicates the difference in curvature. Indicates the local curvature of the upper surface section. This indicates the local curvature of the left side surface.

[0067] S502: When the curvature change value is less than the preset curvature change difference value, the regions with similar curvature change trends are identified as overlapping regions.

[0068] It should be noted that similar curvature change trends mean that the two sets of curvature data have similar rates and directions of change in space.

[0069] S503: Retain the depth data of the side surface and remove the data points of the overlapping areas in the upper surface.

[0070] S504: Using the same elimination method as the data set of the upper left side section, if the data set of the lower right side section is less than the preset curvature change difference, the data is eliminated, and the remaining depth value data is integrated to form the optimized depth value data.

[0071] In this invention, by calculating the curvature variation difference and eliminating overlapping regions with similar curvature variation trends, redundant data can be effectively reduced, ensuring data accuracy and avoiding deviations caused by overlapping regions. Simultaneously, eliminating overlapping regions can effectively reduce errors caused by repeated measurements in the same area, ensuring that the optimized depth values ​​more accurately reflect the actual geometry of the target billet.

[0072] S6: Based on the depth values ​​relative to the camera in the optimized depth value data, calculate the width of each cut surface of the target steel billet at different positions, and combine the width of the cut surface to form the depth value data of each cut surface.

[0073] For example, the width of the cross-section at different locations can be the width dimensions at the top, middle, and bottom.

[0074] Among them, the cross-sectional width refers to the width of an object measured along a horizontal or other specified direction on a certain cross-section of the object. It is an important parameter for describing the shape and size of the object's cross-section.

[0075] In one possible implementation, S6 specifically includes:

[0076] S601: The depth value data set of the left-side cross section in the optimized depth value data is represented as:

[0077]

[0078] in, L This represents the set of depth values ​​for the left-side cross-section. The left-side section represents the first... a One depth value data, a ∈[1, n ], n This represents the total number of depth values ​​for the left-side cut surface.

[0079] The depth value data set of the right-side cross section in the optimized depth value data is represented as:

[0080]

[0081] in, R This represents the set of depth values ​​for the right-side cross-section. The right-side section represents the first... β One depth value data, β ∈[1, m ], m This represents the total number of depth values ​​for the right-side section.

[0082] S602: Camera group on the left Take the center depth data at both ends. Each depth value is a data point.

[0083] S603: Calculate the mean and standard deviation of the depth values ​​in the depth data set of the left-side section:

[0084]

[0085]

[0086] in, m This represents the mean, 2 w This represents the total number of depth value data. Indicates the left-side section Depth value at location i ∈[- w ,w ], s It represents the standard deviation.

[0087] S604: Remove depth value data points that meet preset conditions from the depth value data set of the left side section; and remove area data that meet preset conditions from the data set of the right side section using the same removal method as the data set of the left side section.

[0088] The specific preset conditions are as follows:

[0089]

[0090] in, k Represents a constant.

[0091] S605: Calculate the 2 of the left side section. w Depth variation for each data point in a depth value dataset:

[0092]

[0093] in, This represents the set of absolute values ​​of the depth changes between adjacent data points in the left-side section depth data set.

[0094] S606: Based on the depth change of each data point in the depth value dataset of the left-side cross-section, calculate the cumulative sum sequence of the absolute differences within a preset window size:

[0095]

[0096]

[0097] in, S This represents the sequence formed by the cumulative sum of the absolute differences of each data point within a preset window size in the left-side section depth value dataset. S i Indicates the first i Data points in length oh The cumulative sum of the absolute values ​​of the depth changes within the interval. i =[1,2 w - oh +1],2 w - oh +1 indicates the cumulative sum sequence. S Length, This represents a sequence of depth changes. j This indicates the index position of the absolute difference sequence within the sliding window. i + oh -1 indicates the end position of the sliding window.

[0098] S607: Calculate the standard deviation of the cumulative sum sequence. In the data set of the left-side section Regional data was removed.

[0099] S608: Using the same elimination method as the data set on the left side, in the data set on the right side... Regional data was removed.

[0100] In this invention, statistical methods such as standard deviation and cumulative sum are used to process depth data and remove outliers, ensuring smoother and more reliable data. Simultaneously, optimization is achieved by removing noise and outliers, enabling the optimized data to more accurately reflect the true shape of objects.

[0101] S609: Based on the depth data after the rejection process, determine the width dimensions at different positions on each cut surface of the target steel billet:

[0102]

[0103]

[0104] in, W Indicates 2 w The average distance between each sampling point This represents the difference between the distance between the zero points of the left and right cameras and the sum of the data points collected from the left and right cameras. Indicates the zero-point distance between the left and right cameras. Indicated in the left-side section Depth value at location Indicates the right-side section Depth value at location i ∈[- w , w ];

[0105] S610: Calculate the width dimensions at different positions on each cross-section of the upper and lower surfaces using the same calculation method as for calculating the side surface dimensions;

[0106] S611: Combine the dimensions at different positions on the left and right camera cut surfaces and the width dimensions at different positions on the upper and lower surface cut surfaces to form the measurement data on the cut surface of the target steel billet.

[0107] In this invention, by calculating the width of each cut surface at different positions based on the optimized depth value data, and combining these widths to generate more accurate depth data, the quality inspection, size control and production optimization capabilities of steel billets can be comprehensively improved.

[0108] S7: Based on the depth data on each cut surface, determine the corrected cut surface width by adjusting the tilt angle, and determine the cut surface thickness of the corresponding cut surface based on the corrected cut surface width.

[0109] Tilt angle correction is a technique commonly used in industrial inspection, robot path planning, and 3D modeling. It aims to correct tilt errors caused by objects from different viewpoints or between sensors.

[0110] In one possible implementation, S7 specifically includes:

[0111] S701: Along the billet's movement direction, depth data of the first and second cross-sections are acquired using the left-side camera. The depth data of the first and second cross-sections are acquired at adjacent discrete time points.

[0112]

[0113]

[0114] in, Indicates the first cross-section. This represents the depth data of the first left-side section. p ∈[1, n ], n This represents the total number of depth values ​​for the first left-side section. Indicates the second sectional surface. This represents the depth data of the second left-side section. q ∈[1, s ], s This represents the total number of depth values ​​for the second left-side cut surface.

[0115] S702: Extract depth data points from the middle of the two cross-sections respectively. and Calculate the tilt angle of the mid-depth data points corresponding to the two cross-sections:

[0116]

[0117] in, i i Indicates the location of the mid-depth data point. i The tilt angle at that location, This indicates the longitudinal position coordinates when the left camera captures the second cross-section. This represents the longitudinal position coordinates when the left camera captures the first cross-section. It indicates the distance between two cut surfaces.

[0118] S703: Calculate the tilt angle of each depth data point in the two sections using the same method as the tilt angle used to calculate the position of the depth data point in the middle section.

[0119] S704: Determine the average tilt angle of adjacent cut surfaces in the left 3D camera based on the tilt angles of w depth data points taken at both ends of the midpoint of the two cut surfaces.

[0120]

[0121] in, i 1 represents the average tilt angle of adjacent cut surfaces in the left 3D camera, 2 w This indicates the number of individual tilt angles.

[0122] S705: Determine the average tilt angle of the adjacent cut plane of the right 3D camera in the same manner as determining the average tilt angle of the adjacent cut plane of the left 3D camera.

[0123] S706: Subtract the average tilt angle of the adjacent cut surfaces of the left 3D camera and the average tilt angle of the adjacent cut surfaces of the right 3D camera to determine the tilt angle difference.

[0124] S707: Correct the cross-sectional width if the tilt angle difference is less than the preset tilt angle difference.

[0125]

[0126] in, W A This represents the width of the cut surface after tilt angle correction. W This represents the average width of the cut surface. i 1 represents the average tilt angle of adjacent cut surfaces in the left 3D camera. i 2 represents the average tilt angle of adjacent cut surfaces in the 3D camera on the right.

[0127] S708: Coordinate position for acquiring depth data from the camera on the first cross-section. Based on the coordinate position and the corrected cross-sectional width, the thickness acquisition position for tilt correction is determined:

[0128]

[0129]

[0130]

[0131] in, Indicates the first surface of the first cross-section i The three-dimensional coordinates of a depth value data point i∈[1, p ], This indicates that a width value is obtained at the junction of the top and side surfaces on the cross-section. Indicates the scaling factor. This indicates the location where the corrected section thickness was collected.

[0132] S709: Based on the updated tilt-corrected thickness acquisition position, correct the coordinate point position acquired on the upper surface of the first cross-section:

[0133]

[0134] in, This indicates the first surface of the corrected first cross-section. i The three-dimensional coordinates of the depth data points.

[0135] S710: Correct the position of the coordinate points collected on the lower surface of the first cut surface in the same manner as adjusting the position of the coordinate points collected on the upper surface of the first cut surface.

[0136] S711: Determine the thickness corresponding to the width section based on the corrected coordinates of the upper and lower cameras.

[0137]

[0138] in, L A This indicates the thickness corresponding to the width of the cross section. This indicates the corrected cross-sectional thickness.

[0139] In this invention, by correcting multiple cross-sections, the consistency of measurement data for the steel billet at different locations is ensured, thus improving the overall measurement accuracy. Simultaneously, by correcting the tilt angle, a more precise cross-sectional width can be obtained, thereby providing data support for the quality control, processing adjustment, and shape optimization of the steel billet.

[0140] Furthermore, by ensuring the accurate dimensions of each cross-section, the final generated model can more realistically reflect the three-dimensional shape of the steel billet.

[0141] S8: Determine the cross-sectional profile of the target billet based on the optimized depth data, the corrected cross-sectional width, and the cross-sectional thickness.

[0142] In one possible implementation, S8 specifically includes:

[0143] S801: Collect corrected depth data from four directions: left, right, top, and bottom.

[0144]

[0145]

[0146]

[0147]

[0148] in, l 1 represents the set of two-dimensional coordinates of the left camera on the same sectional plane. This indicates the first data acquired by the left camera in the horizontal direction of the measured section. a The coordinate values ​​of each location data point. This indicates the number of images acquired by the left camera in the depth direction of the measured section. a The depth value of the data at each location. a ∈1,2,… n , where n represents the total number of camera positions on the left. r 1 represents the set of two-dimensional coordinates of the right-side camera on the same sectional plane. This indicates the first data collected by the right-hand camera in the horizontal direction of the measured section. t The coordinate values ​​of each location data point. This indicates the number of images acquired by the right-hand camera in the depth direction of the measured section. t The depth value of the data at each location. t ∈1,2,… m , m This indicates the total number of camera positions on the right. u 1 represents the set of two-dimensional coordinates of the upper camera on the same sectional plane. This indicates the first data collected by the upper camera in the horizontal direction of the measured section. c The coordinate values ​​of each location data point. This indicates the number of images acquired by the upper camera in the depth direction of the measured section. c The depth value of the data at each location. c ∈1,2,… p , p This indicates the total number of positions of the top-side cameras. b 1 represents the set of two-dimensional coordinates of the lower camera on the same sectional plane. This indicates the first data collected by the lower camera in the horizontal direction of the measured section. d The coordinate values ​​of each location data point. This indicates the first data acquired by the lower camera in the depth direction of the measured section. d The depth value of the data at each location. d ∈1,2,… q , q This indicates the total number of camera positions on the top side.

[0149] S802: In the set of camera points on the left, determine the point with the closest Euclidean distance to the camera point on the right. In the same manner, within the lower camera point set, determine the point with the closest Euclidean distance to the upper camera point. :

[0150]

[0151] in, This represents the index of the data point in the left-hand camera point set. n This indicates the total number of data points in the left-hand camera point set. x ri Indicates the first point in the right-side camera point set. r The horizontal coordinates of the points x lj Indicates the first point in the left camera point set. j The horizontal coordinates of the points.

[0152] S803 based on point Depth value at and The depth value at that location is then converted from the depth values ​​on the top and right sides to obtain the converted depth value data:

[0153]

[0154]

[0155] in, Indicates the position of the upper and lower cameras on the cross-section. Distance between data points of steel billet Indicates the side above i The depth value of the nearest Euclidean distance to the data point. Indicates the left and right cameras on the cross-section. Distance between data points of steel billet Indicates the right side i The depth value of the nearest Euclidean distance of the data point.

[0156] S804: Based on the converted depth data, calculate the true distance represented by a single pixel in the horizontal cross-section direction for each 3D camera.

[0157]

[0158]

[0159]

[0160]

[0161] in, p l This represents the actual distance of each pixel on the left-side camera slice in the horizontal slice direction.p r This represents the actual distance represented by each pixel on the right-side camera slice in the horizontal slice direction. p u This represents the actual distance of each pixel on the upper camera slice in the horizontal slice direction. p b This represents the actual distance represented by each pixel on the lower camera slice in the horizontal slice direction.

[0162] S805: Based on the real distance represented by a single pixel in the horizontal cross-section direction of 3D cameras in various orientations, the data acquired by the left 3D camera is transformed as follows:

[0163] .

[0164] The data acquired by the 3D camera on the left is transformed as follows:

[0165] .

[0166] The data collected by the upper 3D camera is transformed into:

[0167] .

[0168] The data collected by the lower 3D camera is transformed as follows:

[0169] .

[0170] S806: Based on the transformed data, determine the values ​​in the horizontal cross-section direction of each orientation through coordinate transformation.

[0171] S807: Rotate the left and right camera data 90 degrees clockwise around the origin and determine the offset of the left, right, top, and bottom cameras:

[0172]

[0173]

[0174]

[0175]

[0176] in, This indicates the offset of the left camera relative to the top camera. This indicates the offset of the right-side camera relative to the top-side camera. This indicates the offset of the upper camera relative to the left camera. This indicates the offset of the lower camera relative to the left camera;

[0177] S808: Based on the values ​​in each horizontal sectional direction and the offset, transform the left and right camera data to the same coordinate system, and determine the transformed left and right camera data:

[0178] ;

[0179] ;

[0180] ;

[0181] .

[0182] S809: Based on the converted left and right camera data, combined with the upper and lower camera data, the data are aligned according to the same coordinate system and stitched together to form the cross-sectional profile of the target steel billet.

[0183] In this invention, by stitching together corrected data from different directions (left, right, top, and bottom), a complete cross-sectional profile of the target steel billet can be generated. The depth values ​​from each direction, after correction and transformation, can accurately reflect the three-dimensional shape of the billet. Simultaneously, by converting data collected by different cameras to a unified coordinate system, errors caused by different measurement angles are reduced, thus improving data accuracy.

[0184] In one possible implementation, the process after S8 includes:

[0185] The T-value and strand length are calculated using data from the cross-section of the steel billet.

[0186] The T-value (also known as the size difference or shape difference) is an indicator used to measure the maximum and minimum size difference of an object or component in a certain dimension. It is usually used to describe the size stability or shape change of a target object.

[0187] Among them, width difference (or width variation) is an indicator used to measure the width variation of different parts of an object. It is usually used to describe the dimensional changes of an object at different locations, especially for the dimensional inspection of metal materials such as steel billets.

[0188] The formula for calculating the T-value is:

[0189]

[0190]

[0191] in, T This represents the difference between the maximum and minimum target billet dimensions. max Indicates the maximum value. minutes This represents the minimum value. WThis represents the set of widths of all cross-sections of the target steel billet. l wq Indicates the billet number q The width measured on each cross-section q ∈[1, m ], m This indicates the total number of width values.

[0192] The formula for calculating the number of shares is:

[0193]

[0194] in, rad Indicates stock degree, Indicates the width at the center of the cross-section. This indicates the width of the upper part of the cut surface.

[0195] In this invention, by calculating the T-value and the length, the dimensional stability and shape consistency of the billet during the production process can be comprehensively evaluated, providing strong data support for production process optimization, quality control, shape analysis and subsequent processing. This not only improves product quality and reduces production errors, but also enhances the level of automation control and intelligent production, ultimately achieving more efficient and precise production management.

[0196] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0197] (1) In this invention, multiple 3D cameras are used to collect multiple surface images of the target steel billet from multiple directions. The depth value between the target steel billet and the corresponding 3D camera zero point is calculated by laser line misalignment distance measurement technology to form depth value data. Through automated acquisition and calculation, the dependence of manual visual inspection on workers' experience and judgment is eliminated, the influence of subjective factors of operators is effectively reduced, and the inspection efficiency is greatly improved.

[0198] (2) In this invention, the local curvature of the side and top surfaces of the target billet is calculated, and the overlapping area is identified by combining the curvature change difference. Redundant data points are eliminated to form optimized depth value data. The optimized depth value data is further used to calculate the cross-sectional width of each cross-section of the billet at different positions. Combined with the tilt angle correction method, the corrected cross-sectional width and thickness are obtained, and finally the cross-sectional profile of the billet is formed. This enables real-time, continuous and high-precision measurement of the billet in production, effectively avoiding the limitations of traditional manual measurement that relies on simple measuring tools and is difficult to achieve accurate measurement, and improving the accuracy of measurement.

[0199] Reference manual attached Figure 2 The diagram shows a structural schematic of a high-temperature continuous casting billet contour measurement system provided by the present invention.

[0200] The present invention also provides a high-temperature continuous casting billet contour measurement system 20, applied to the above-mentioned high-temperature continuous casting billet contour measurement method, comprising:

[0201] Processor 201.

[0202] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, they implement the high-temperature continuous casting billet contour measurement method as described in the method embodiment.

[0203] The high-temperature continuous casting billet contour measurement system 20 provided by the present invention can perform the above-mentioned high-temperature continuous casting billet contour measurement method and achieve the same or similar technical effects. To avoid repetition, the present invention will not elaborate further.

[0204] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0205] (1) In this invention, multiple 3D cameras are used to collect multiple surface images of the target steel billet from multiple directions. The depth value between the target steel billet and the corresponding 3D camera zero point is calculated by laser line misalignment distance measurement technology to form depth value data. Through automated acquisition and calculation, the dependence of manual visual inspection on workers' experience and judgment is eliminated, the influence of subjective factors of operators is effectively reduced, and the inspection efficiency is greatly improved.

[0206] (2) In this invention, the local curvature of the side and top surfaces of the target billet is calculated, and the overlapping area is identified by combining the curvature change difference. Redundant data points are eliminated to form optimized depth value data. The optimized depth value data is further used to calculate the cross-sectional width of each cross-section of the billet at different positions. Combined with the tilt angle correction method, the corrected cross-sectional width and thickness are obtained, and finally the cross-sectional profile of the billet is formed. This enables real-time, continuous and high-precision measurement of the billet in production, effectively avoiding the limitations of traditional manual measurement that relies on simple measuring tools and is difficult to achieve accurate measurement, and improving the accuracy of measurement.

[0207] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0208] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0209] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0210] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0211] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0212] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0213] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0214] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0215] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0216] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0217] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0218] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0219] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the high-temperature continuous casting billet contour measurement method as described in the method embodiment.

[0220] The present invention provides a computer-readable storage medium that can implement the steps and effects of the high-temperature continuous casting billet contour measurement method in the above-described method embodiments. To avoid repetition, the present invention will not repeat the details.

[0221] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0222] (1) In this invention, multiple 3D cameras are used to collect multiple surface images of the target steel billet from multiple directions. The depth value between the target steel billet and the corresponding 3D camera zero point is calculated by laser line misalignment distance measurement technology to form depth value data. Through automated acquisition and calculation, the dependence of manual visual inspection on workers' experience and judgment is eliminated, the influence of subjective factors of operators is effectively reduced, and the inspection efficiency is greatly improved.

[0223] (2) In this invention, the local curvature of the side and top surfaces of the target billet is calculated, and the overlapping area is identified by combining the curvature change difference. Redundant data points are eliminated to form optimized depth value data. The optimized depth value data is further used to calculate the cross-sectional width of each cross-section of the billet at different positions. Combined with the tilt angle correction method, the corrected cross-sectional width and thickness are obtained, and finally the cross-sectional profile of the billet is formed. This enables real-time, continuous and high-precision measurement of the billet in production, effectively avoiding the limitations of traditional manual measurement that relies on simple measuring tools and is difficult to achieve accurate measurement, and improving the accuracy of measurement.

[0224] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0225] The following points need to be explained:

[0226] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0227] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0228] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0229] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for measuring the profile of a high-temperature continuously cast steel billet, characterized in that, include: S1: Use multiple 3D cameras to acquire multiple surface images of the target steel billet from multiple angles; S2: Calculate the depth value between the target steel billet and the corresponding 3D camera zero point using laser line misalignment distance measurement technology to form depth value data; S3: Based on the depth data, determine the coordinates of the target billet in each 3D camera coordinate system; S4: Based on the depth data and the coordinates of the target billet in each 3D camera coordinate system, calculate the local curvature of the side surface and the local curvature of the upper and lower surfaces of the target billet. S5: Based on the local curvature of the side surface and the local curvature of the upper and lower surfaces, determine the curvature change difference. If the curvature change difference is less than the preset curvature change difference, determine the overlapping area and remove the depth value data of the overlapping area to form optimized depth value data. S6: Based on the depth values ​​relative to the camera in the optimized depth value data, calculate the cross-sectional width of each cross-section of the target steel billet at different positions, and combine the cross-sectional width to form the depth value data on each cross-section; S7: Based on the depth data on each cut surface, determine the corrected cut surface width by adjusting the tilt angle, and determine the cut surface thickness of the corresponding cut surface based on the corrected cut surface width. S8: Based on the depth data, the cross-sectional width, and the cross-sectional thickness, determine the cross-sectional profile of the target steel billet; Specifically, S4 includes: S401: Set the sequence of cross-sectional depth values ​​of the left side surface of the target steel billet to be acquired by the side 3D camera as follows: ； in, Z l This represents the sequence of depth values ​​on the left surface. The first section of the left surface is represented by the first section. a One depth value data, a =[1, n ], n This represents the total number of depth data for the cross-section on the left side of the surface; The sequence of cut depth values ​​of the upper surface of the target steel billet acquired by the 3D camera above is as follows: ； in, Z u This represents the sequence of depth values ​​of the upper surface section. The first section of the upper surface sectional plane c One depth value data, c =[1, p ], p This represents the total number of depth data for the upper surface; S402: Based on the left surface depth value sequence and the coordinates of the target billet in each 3D camera coordinate system, calculate the local curvature of the left surface section using the difference method. : ； ； ； in, Indicates the first on the left side surface section i Local curvature at a depth value data point Indicates the first i +1 depth data point and the first i The difference in depth values ​​between depth data points Indicates the first i +2 depth data points and the first i The difference in depth values ​​between +1 depth value data points. Indicates the first on the left side surface section i+ One depth data point, Indicates the left surface number i One depth value data point, Indicates the first on the left side surface section i+ Two depth data points, This indicates the spacing between adjacent depth data points; S403: Calculate the local curvature of the upper surface using the same method as calculating the local curvature of the left surface. .

2. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 1, characterized in that, S5 specifically includes: S501: Calculate the difference in curvature variation: ； in, Indicates the difference in curvature. Indicates the local curvature of the upper surface section. Indicates the local curvature of the cross-section on the left side; S502: When the curvature change value is less than the preset curvature change difference value, the regions with similar curvature change trends are determined as overlapping regions; S503: Retain the depth data of the side surface and remove the data points in the overlapping areas of the upper and lower surfaces; S504: Integrate the retained depth data to form optimized depth data.

3. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 1, characterized in that, S6 specifically includes: S601: The set of depth value data of the left cross-section in the optimized depth value data is represented as: ； in, L This represents the set of depth values ​​for the left-side cross-section. The left-side section represents the first... a One depth value data, a ∈[1, n ], n This represents the total number of depth values ​​for the left-side cut surface. The set of depth value data for the right-side section in the optimized depth value data is represented as: ； in, R This represents the set of depth values ​​for the right-side cross-section. The right-side section represents the first... β One depth value data, β ∈[1, m ], m This represents the total number of depth values ​​for the right-side section. S602: Camera group on the left Take the center depth value data from both ends One depth value data; S603: Calculate the mean and standard deviation of the depth values ​​in the depth data set of the left-side section: ； ； in, μ This represents the mean, 2 w This represents the total number of depth value data. Indicates the left-side section Depth value at location i ∈[- w , w ], σ Indicates standard deviation; S604: Remove depth value data points that meet preset conditions from the depth value data set of the left side section; and remove area data that meet preset conditions from the data set of the right side section using the same removal method as the data set of the left side section. The preset conditions are specifically as follows: ； in, k Represents a constant; S605: Calculate the 2 of the left side section. w Depth variation for each data point in a depth value dataset: ； in, This represents the set of absolute values ​​of the depth changes between adjacent data points in the left-side section depth data set; S606: Based on the depth change of each data point in the depth value dataset of the left-side cross-section, calculate the cumulative sum sequence of the absolute differences within a preset window size: ； ； in, S This represents the sequence formed by the cumulative sum of the absolute differences of each data point within a preset window size in the left-side section depth value dataset. S i Indicates the first i Data points in length ω The cumulative sum of the absolute values ​​of the depth changes within the interval. i =[1,2 w - ω +1],2 w - ω +1 indicates the cumulative sum sequence. S Length, This represents a sequence of depth changes. j This indicates the index position of the absolute difference sequence within the sliding window. i + ω -1 indicates the end position of the sliding window; S607: Calculate the standard deviation of the cumulative sum sequence. In the data set of the left-side section Regional data was removed. S608: Using the same elimination method as the data set on the left side, in the data set on the right side... Regional data was removed. S609: Based on the depth data after the rejection process, determine the width dimensions at different positions on each cut surface of the target steel billet: ； ； in, W Indicates 2 w The average distance between each sampling point This represents the difference between the distance between the zero points of the left and right cameras and the sum of the data points collected from the left and right cameras. Indicates the zero-point distance between the left and right cameras. Indicated in the left-side section Depth value at location Indicates the right-side section Depth value at location i ∈[- w , w ]; S610: Calculate the width dimensions at different positions on each cross-section of the upper and lower surfaces using the same calculation method as for calculating the side surface dimensions; S611: Combine the dimensions at different positions on the left and right camera cut surfaces and the width dimensions at different positions on the upper and lower surface cut surfaces to form the measurement data on the cut surface of the target steel billet.

4. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 1, characterized in that, Specifically, S7 includes: S701: Along the billet's movement direction, depth data of the first and second cross-sections are acquired using the left-side camera, wherein the depth data of the first and second cross-sections are acquired at adjacent discrete time points. ； ； in, Indicates the first cross-section. This represents the depth data of the first left-side cut surface. p ∈[1, n ], n This represents the total number of depth values ​​for the first left-side cut surface; Indicates the second sectional surface. This represents the depth data of the second left-side section. q ∈[1, s ], s This represents the total number of depth values ​​for the second left-side section. S702: Extract depth data points from the middle of the two cross-sections respectively. and Calculate the tilt angle of the mid-depth data points corresponding to the two cross-sections: ； in, θ i Indicates the location of the mid-depth data point. i The tilt angle at that location, This indicates the longitudinal position coordinates when the left camera captures the second cross-section. This represents the longitudinal position coordinates when the left camera captures the first cross-section. Indicates the distance between two cut surfaces; S703: Calculate the tilt angle of each depth value data point position in the two cross planes using the same calculation method as that used to calculate the tilt angle of the position of the central depth value data point; S704: Take the two ends of the midpoint of the two cut planes. The tilt angle of each depth data point is used to determine the average tilt angle of adjacent cut surfaces in the left 3D camera: ； in, θ 1 represents the average tilt angle of adjacent cut surfaces in the left 3D camera, 2 w Indicates the number of individual tilt angles; S705: Determine the average tilt angle of the adjacent cut plane of the right 3D camera in the same manner as determining the average tilt angle of the adjacent cut plane of the left 3D camera. S706: Subtract the average tilt angle of the adjacent cut surfaces of the left 3D camera and the average tilt angle of the adjacent cut surfaces of the right 3D camera to determine the tilt angle difference. S707: If the tilt angle difference is less than a preset tilt angle difference, the cross-sectional width is corrected. ； in, This represents the width of the cut surface after tilt angle correction. W This represents the average width of the cut surface. θ 1 represents the average tilt angle of adjacent cut surfaces in the left 3D camera. θ 2 represents the average tilt angle of adjacent cut surfaces in the 3D camera on the right; S708: Coordinate position for acquiring depth data from the camera on the first cross-section. Based on the coordinate position and the corrected cross-sectional width, the thickness acquisition position for tilt correction is determined: ； ； ； in, Indicates the first surface of the first cross-section i The three-dimensional coordinates of a depth value data point i ∈[1, p ], This indicates that a width value is obtained at the junction of the top and side surfaces on the cross-section. Indicates the scaling factor. Indicates the location where the corrected section thickness was collected; S709: Based on the updated tilt-corrected thickness acquisition position, correct the coordinate point position acquired on the upper surface of the first cross-section: ； in, This indicates the first surface of the corrected first cross-section. i The three-dimensional coordinates of a depth value data point; S710: Correct the position of the coordinate points collected on the lower surface of the first cut surface in the same manner as adjusting the position of the coordinate points collected on the upper surface of the first cut surface; S711: Determine the thickness corresponding to the width section based on the corrected coordinates of the upper and lower cameras. ； in, L A This indicates the thickness corresponding to the width of the cross section. This indicates the corrected cross-sectional thickness.

5. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 1, characterized in that, S8 specifically includes: S801: Collect coordinate data from the same cross-section from four directions: left, right, top, and bottom. ； ； ； ； in, l 1 represents the set of two-dimensional coordinates of the left camera on the same sectional plane. This indicates the first data acquired by the left camera in the horizontal direction of the measured section. a The coordinate values ​​of each location data point. This indicates the number of images acquired by the left camera in the depth direction of the measured section. a The depth value of the data at each location. a ∈1,2,… n , n This indicates the total number of camera positions on the left. r 1 represents the set of two-dimensional coordinates of the right-side camera on the same sectional plane. This indicates the first data collected by the right-hand camera in the horizontal direction of the measured section. t The coordinate values ​​of each location data point. This indicates the number of images acquired by the right-hand camera in the depth direction of the measured section. t The depth value of the data at each location. t ∈1,2,… m , m This indicates the total number of camera positions on the right. u 1 represents the set of two-dimensional coordinates of the upper camera on the same sectional plane. This indicates the first data collected by the upper camera in the horizontal direction of the measured section. c The coordinate values ​​of each location data point. This indicates the number of images acquired by the upper camera in the depth direction of the measured section. c The depth value of the data at each location. c ∈1,2,… p , p This indicates the total number of positions of the top-side cameras. b 1 represents the set of two-dimensional coordinates of the lower camera on the same sectional plane. This indicates the first data collected by the lower camera in the horizontal direction of the measured section. d The coordinate values ​​of each location data point. This indicates the first data acquired by the lower camera in the depth direction of the measured section. d The depth value of the data at each location. d ∈1,2,… q , q This indicates the total number of camera positions on the top side; S802: In the set of camera points on the left, determine the point with the closest Euclidean distance to the camera point on the right. In the same manner, within the lower camera point set, determine the point with the closest Euclidean distance to the upper camera point. : ； in, This represents the index of the data point in the left-hand camera point set. n This indicates the total number of data points in the left-hand camera point set. x ri Indicates the first point in the right-side camera point set. i The horizontal coordinates of the points x lj Indicates the first point in the left camera point set. j The horizontal coordinates of each point; S803: Point-based Depth value at and The depth value at that location is then converted from the depth values ​​on the top and right sides to obtain the converted depth value data: ； ； in, Indicates the position of the upper and lower cameras on the cross-section. Distance between data points of steel billet Indicates the side above i The depth value of the nearest Euclidean distance to the data point. Indicates the left and right cameras on the cross-section. Distance between data points of steel billet Indicates the right side i The depth value of the nearest Euclidean distance to the data point; S804: Based on the converted depth data, calculate the true distance represented by a single pixel in the horizontal cross-section direction for each 3D camera. ； ； ； ； in, p l This represents the actual distance of each pixel on the left-side camera slice in the horizontal slice direction. p r This represents the actual distance represented by each pixel on the right-side camera slice in the horizontal slice direction. p u This represents the actual distance of each pixel on the upper camera slice in the horizontal slice direction. p b This represents the actual distance represented by each pixel on the lower camera slice in the horizontal slice direction; S805: Based on the real distance represented by a single pixel in the horizontal cross-section direction of 3D cameras in various orientations, the data acquired by the left 3D camera is transformed as follows: ； The data collected by the 3D camera on the right is transformed as follows: ； The data collected by the upper 3D camera is transformed into: ； The data collected by the lower 3D camera is transformed as follows: ； S806: Based on the transformed data, determine the values ​​in the horizontal sectional direction of each orientation through coordinate transformation; S807: Rotate the left and right camera data 90 degrees clockwise around the origin and determine the offset of the left, right, top, and bottom cameras: ； ； ； ； in, This indicates the offset of the left camera relative to the top camera. This indicates the offset of the right camera relative to the top camera. This indicates the offset of the upper camera relative to the left camera. This indicates the offset of the lower camera relative to the left camera; S808: Based on the values ​​in each horizontal sectional direction and the offset, transform the left and right camera data to the same coordinate system, and determine the transformed left and right camera data: ； ； ； ； S809: Based on the converted left and right camera data, combined with the upper and lower camera data, the cross-sectional profile of the target steel billet can be obtained by stitching together the same coordinate system.

6. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 1, characterized in that, Following S8, the following is also included: The T-value and strand length are calculated using data from the cross-section of the steel billet.

7. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 6, characterized in that, The formula for calculating the T value is: ； ； in, T This represents the difference between the maximum and minimum target billet dimensions. max Indicates the maximum value. min This represents the minimum value. W This represents the set of widths of all cross-sections of the target steel billet. l wq Indicates the billet number q The width measured on each cross-section q ∈[1, m ], m This indicates the total number of cross-sections.

8. The method for measuring the profile of a high-temperature continuously cast steel billet according to claim 6, characterized in that, The formula for calculating the number of shares is: ； in, rad Indicates stock degree, Indicates the width at the center of the cross-section. This indicates the width of the upper part of the cut surface.

9. A high-temperature continuous casting steel billet contour measurement system, characterized in that, include: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the high-temperature continuous casting billet contour measurement method as described in any one of claims 1 to 8.

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