A method for calibrating a rotating structured light three-dimensional measurement system

Abstract

A kind of rotary structured light three-dimensional measurement system calibration method, comprising the following steps: building rotary structured light three-dimensional measurement system;Camera calibration;Obtain the coordinate conversion relationship between camera coordinate system and pixel coordinate system;Structured light calibration;Vertical rotation axis calibration;Solve the coordinate conversion relationship between camera coordinate system and rotation axis coordinate system when vertical rotation axis rotates;Horizontal rotation axis calibration;Solve the coordinate conversion relationship between camera coordinate system and rotation axis coordinate system when horizontal rotation axis rotates;This kind of calibration method is applied to rotary structured light three-dimensional measurement system;With vertical rotation axis and horizontal rotation axis, its measurement range is expanded, and effective measurement of large-size object can be realized;Through rotation axis calibration, the installation position of camera and rotation axis is accurately calculated, the influence of system installation error on calibration accuracy is avoided, the accuracy and stability of three-dimensional reconstruction are effectively improved, and reliable technical support is provided for industrial automation detection, reverse engineering and other fields.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quantitative detection of defects of hydroelectric generating set equipment, and particularly relates to a calibration method of a rotating structured light three-dimensional measurement system. BACKGROUND

[0002] As an important part of the power system, the structural integrity of the hydroelectric generating set is directly related to the safety and stability of energy supply. In the long-term operation process, the flow components such as blades and runners in the hydroelectric generating set often have defects such as wear and tear and cracks due to the effects of natural factors such as water erosion, cavitation and corrosion. If these defects are not discovered and repaired in time, they will pose a serious threat to the performance and safe operation of the generating set, and even cause major accidents. Therefore, realizing the quantitative detection of defects of the hydroelectric generating set equipment is of great significance to ensure the safe operation of the generating set.

[0003] The rotating structured light three-dimensional measurement technology, as a non-contact and high-precision measurement method, has unique advantages in the detection of complex curved surfaces and large structures. This technology projects structured light onto the surface of the measured object, uses a camera to capture the deformation image of the structured light on the object surface, and through image processing and algorithm analysis, the three-dimensional topography information of the object can be restored with high precision. However, most existing rotating structured light three-dimensional measurement systems use single-axis rotation design, which limits the measurement range and flexibility, making it difficult to meet the high-precision measurement needs of large-size and complex-shaped objects.

[0004] For example, CN112179291A discloses a self-rotating scanning line structured light three-dimensional measurement device calibration method, which belongs to the technical field of three-dimensional measurement. The self-rotating scanning line structured light three-dimensional measurement device is mainly composed of a line structured light profile measurement instrument and a high-precision rotary table. The coordinate system of the self-rotating scanning line structured light three-dimensional measurement device is usually established based on the rotation axis of the high-precision rotary table, and does not coincide with the coordinate system of the line structured light profile measurement instrument. The positional relationship between the two cannot be accurately determined through mechanical installation. The calibration method of the present application uses a plane target to calibrate the positional parameters between the coordinate system of the line structured light profile measurement instrument and the coordinate system of the self-rotating scanning line structured light three-dimensional measurement device. This method uses a line structured light profile measurement instrument and a high-precision rotary table to form a measurement device, and completes calibration through a plane target. Although this technical solution achieves a certain degree of measurement accuracy, it can only realize single-axis rotation and calibration, and cannot realize full-range measurement of large-size targets.

[0005] Furthermore, Cui Yi from Harbin Engineering University proposed a rotating structured light 3D measurement system in his master's thesis, "Research on 3D Vision Measurement Method Based on Line Laser Rotation Scanning." This system uses a dual-axis turntable to rotate the system, enabling the measurement of large objects. However, this technical solution has shortcomings in the precise calculation of the camera and axis mounting positions, and the system's measurement accuracy is easily affected by installation errors.

[0006] Given the limitations of the existing technologies, there is an urgent need for a more accurate and reliable calibration method for rotating structured light 3D measurement systems to achieve high-precision 3D measurement of large objects. This invention is proposed against this backdrop, aiming to accurately calculate the installation positions of the camera and the rotating shaft through an innovative calibration method, thereby expanding the measurement range and improving measurement accuracy, and ultimately meeting the practical needs of quantitative detection of defects in hydroelectric generator sets. Summary of the Invention

[0007] The technical problem to be solved by this invention is to provide a calibration method for a rotating structured light three-dimensional measurement system, which solves a key problem in the field of quantitative detection of defects in hydro-generator equipment, especially addressing the limitations of existing rotating structured light three-dimensional measurement systems in the process of measuring large-size targets, such as limited measurement range and the impact of system assembly and adjustment errors on calibration accuracy.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a calibration method for a rotating structured light three-dimensional measurement system, comprising the following steps:

[0009] Step 1: Construct a rotating structured light 3D measurement system, which includes a camera, laser, horizontal axis, vertical axis, crossbeam and base;

[0010] Step 2: Perform camera calibration to obtain the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system. The coordinate transformation relationship between the camera coordinate system and the pixel coordinate system is described by the intrinsic parameter matrix.

[0011] Step 3: Perform structural cursor calibration to obtain the light plane equation in the camera coordinate system;

[0012] Step 4: Perform vertical axis calibration. By changing the position of the vertical axis and acquiring images, the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when the vertical axis rotates is obtained.

[0013] Step 5: Perform horizontal axis calibration. By changing the position of the horizontal axis and acquiring images, solve for the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when the horizontal axis rotates.

[0014] In the preferred embodiment, camera calibration in Step 2 obtains the camera coordinate system. With pixel coordinate system The coordinate transformation relationship between them; and the camera coordinate system With pixel coordinate system The coordinate transformation relationship between them satisfies:

[0015] (1)

[0016] in, This represents the intrinsic parameter matrix.

[0017] In the preferred embodiment, the specific process of camera calibration in Step 2 includes: placing the chessboard within the camera's field of view, changing its position and orientation, acquiring a series of chessboard images, and calculating the intrinsic parameter matrix and distortion parameters, wherein the camera imaging model satisfies a preset formula relationship:

[0018] (2)

[0019] in, Indicates the scale factor. Indicates focal length. This represents the coordinates of the principal point in the image captured by the camera. The corner points of the chessboard in the camera coordinate system The three-dimensional coordinates below Represents the pixel coordinates of the corner points of the chessboard grid.

[0020] In the preferred embodiment, the specific process of structural beam calibration in Step 3 includes: keeping the rotating structured light 3D measurement system stationary, allowing its emitted line structured light to illuminate the checkerboard, changing the pose of the checkerboard, acquiring at least two checkerboard images, extracting the pixel coordinates of the line structured light centerline using the gray-scale centroid method, and obtaining the light plane equation.

[0021] In the preferred embodiment, the pixel coordinates of the center line of the structured light extracted using the gray-scale centroid method are: The center line of the line structured light was calculated in the camera coordinate system. The coordinates below are used to fit the camera coordinate system. The light plane equation below, which satisfies:

[0022] (3)

[0023] Where A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is any point on the plane, and D is a constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0024] In the preferred embodiment, the camera coordinate system is obtained in Step 4 when the vertical axis rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using the rotation matrix and translation matrix, calculating the distance between the camera optical center and the vertical rotation axis by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship.

[0025] In a preferred embodiment, the solution obtains the camera coordinate system during vertical rotation. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0026] In three-dimensional space, the coordinate system along The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0027] (4)

[0028] (5)

[0029] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0030] Assuming camera coordinate system of The axis is parallel to the vertical rotation axis, and the camera coordinate system of Plane and Rotational Coordinate Systems of If the planes are in the same plane, then the translation matrix can be rewritten as:

[0031] (6)

[0032] in, This indicates that after the vertical axis of rotation, the crossbeam and... The angle formed by the axis, This indicates the distance between the camera's optical center and the vertical axis of rotation;

[0033] Rotation coordinate system The origin is defined in the camera coordinate system. The origin is along For positions where the displacement difference in the direction is 0, the translation matrix of the initial position can be rewritten as:

[0034] (7)

[0035] The coordinate transformation relationship before and after the camera rotation satisfies:

[0036] (8)

[0037] in, Camera coordinate system before and after vertical rotation axis , The coordinate transformation matrix between them Camera coordinate system before and after vertical rotation axis , Rotation matrix between Camera coordinate system before and after vertical rotation axis , Translation matrix between them;

[0038] Introducing a rotation coordinate system Finally, the overall transformation relation satisfies:

[0039] (9)

[0040] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, Camera coordinate system With rotation coordinate system Translation matrix between them Camera coordinate system With rotation coordinate system Translation matrix between them;

[0041] When calibrating the vertical axis, the crossbeam and... Angle between the axes Given that the chessboard is fixed, images of the chessboard are captured by a camera before and after rotation along the vertical axis. Two different coordinate transformation matrices are obtained through camera calibration:

[0042] (10)

[0043] (11)

[0044] in, and The camera coordinate systems before and after the vertical axis rotation are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0045] By combining equations (8), (10), and (11), the distance between the camera's optical center and the vertical rotation axis can be calculated. ,satisfy:

[0046] (12)

[0047] Among them, the distance between the camera's optical center and the vertical rotation axis Used to mark the camera's mounting position, and from this, the camera coordinate system is further solved for rotation of the vertical axis. With rotation coordinate system The coordinate transformation relationship between them.

[0048] In the preferred embodiment, the camera coordinate system is obtained in Step 5 when the horizontal axis rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using the rotation matrix and translation matrix, calculating the distance between the horizontal rotation axis and the origin of the rotation axis coordinate system by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship.

[0049] In a preferred embodiment, the solution obtains the camera coordinate system when the horizontal axis rotates. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0050] In three-dimensional space, the coordinate system along The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0051] (13)

[0052] (14)

[0053] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0054] The coordinate system of the rotating axis when the horizontal axis rotates origin exist The translation in the direction is , The translation in the direction is Then the translation matrix can be rewritten as:

[0055] (15)

[0056] in, This indicates that after the horizontal axis rotates, the crossbeam and... The angle between planes This represents the distance between the horizontal axis of rotation and the origin of the coordinate system.

[0057] Due to the horizontal rotating shaft During rotation, the axis of rotation coordinate system The axis will rotate accordingly, therefore the coordinate system of the axis of rotation before and after the horizontal axis of rotation. and ,satisfy:

[0058] (16)

[0059] in, The coordinate system representing the axis of rotation before and after the horizontal axis of rotation. and Coordinate transformation matrix between;

[0060] Due to the rotation of the horizontal axis, the camera coordinate system With rotation coordinate system Synchronous changes, therefore the camera coordinate system Coordinate transformation matrix before and after rotation If they are the same, then the camera coordinate system before and after rotation is the same. , ,satisfy:

[0061] (17)

[0062] in, The coordinate system representing the axis of rotation before and after the horizontal axis of rotation. and Rotation matrix between The coordinate system representing the axis of rotation before and after the horizontal axis of rotation. and Translation matrix between them;

[0063] When calibrating the horizontal axis, the crossbeam and... Angle between planes Given that the chessboard is fixed, images of the chessboard are captured by a camera before and after rotation along the horizontal axis. Two different coordinate transformation matrices are obtained through camera calibration:

[0064] (18)

[0065] (19)

[0066] in, and The camera coordinate systems before and after the horizontal axis rotation are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0067] By combining equations (17), (18), and (19), we can calculate the following:

[0068] (20)

[0069] Let the camera coordinate system be before the horizontal axis rotates. The origin position is Rotated camera coordinate system The origin position is After performing a position transformation between the two coordinate systems, the following calculations were obtained:

[0070] (twenty one)

[0071] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, The coordinate system of the rotation axis (3) before and after rotation. and Translation matrix between them;

[0072] From equation (20), the camera coordinate system before and after the horizontal axis rotation is obtained. , coordinate transformation matrix between From equation (21), the horizontal axis of rotation and the coordinate system of the axis of rotation are obtained. Distance between origins Furthermore, the camera coordinate system during horizontal axis rotation can be obtained by solving the problem. With rotation coordinate system The coordinate transformation relationship between them satisfies:

[0073] (twenty two).

[0074] In the preferred embodiment, the camera uses a lens with a frame rate of 30fps and a resolution of 1280×1024 pixels, and the laser is a line structured light laser with a wavelength of 450nm, a power of 10mW, and a linewidth of a preset value.

[0075] In a preferred embodiment, the checkerboard used in the calibration process is 200mm×200mm in size, with checkerboard squares of 10mm×10mm distributed on it. By moving the checkerboard multiple times to change its position and orientation in the camera's field of view, a series of calibration images are collected for camera calibration.

[0076] The calibration method for a rotating structured light three-dimensional measurement system provided by this invention has the following beneficial effects:

[0077] 1. This invention solves a key problem in the field of quantitative detection of defects in hydro-generator equipment, especially addressing the limitations of existing rotating structured light three-dimensional measurement systems in the measurement of large-size targets, such as limited measurement range and the impact of system assembly and adjustment errors on calibration accuracy;

[0078] 2. This invention provides an innovative calibration method for a rotating structured light three-dimensional measurement system, overcoming the shortcomings of existing technologies, achieving effective measurement of large-sized objects, and significantly improving measurement accuracy;

[0079] 3. Compared with the traditional single-axis rotating structure light three-dimensional measurement system, the dual-axis rotating structure of the present invention introduces a vertical axis and a horizontal axis, realizing the dual-axis rotation function of the measurement system, thereby significantly expanding the measurement range and enabling it to measure large-sized objects more effectively.

[0080] 4. The precise axis calibration method of this invention, through precise calibration of the vertical and horizontal axes, can accurately calculate the installation position between the camera and the axis, avoiding the impact of system assembly and adjustment errors on calibration accuracy. This precise calibration method is not available in traditional methods.

[0081] 5. This invention provides a comprehensive system calibration process. This scheme not only includes camera calibration and structural cursor calibration, but also details the calibration processes for the vertical and horizontal rotation axes, forming a comprehensive system calibration process. This comprehensive calibration process helps improve the overall measurement accuracy of the system.

[0082] 6. This invention innovatively solves the coordinate transformation relationship by introducing a rotation axis coordinate system during the calibration of the vertical and horizontal rotation axes. Using rotation and translation matrices, it innovatively solves the coordinate transformation relationship between the camera coordinate system and the rotation axis coordinate system. This method improves the accuracy and reliability of coordinate transformation.

[0083] 7. This invention, combined with practical application needs, addresses the actual need for quantitative detection of defects in hydro-generator unit equipment. By optimizing the structure and calibration method of the measurement system, this solution improves measurement accuracy and efficiency, demonstrating the creativity of applying advanced technology to practical engineering problems.

[0084] 8. This invention solves the technical bottlenecks of existing rotating structured light 3D measurement systems in the process of measuring large-size targets, such as the limitations of single-axis rotation and the influence of installation errors. By introducing dual-axis rotation and precise calibration methods, it achieves effective measurement of large-size objects.

[0085] 9. This invention demonstrates high novelty and inventiveness in both the structural design and calibration method of the rotating structured light three-dimensional measurement system, providing a new technical means for the quantitative detection of defects in hydro-generator equipment;

[0086] 10. This invention not only improves the accuracy and efficiency of measurement, but also reduces the dependence on the operating environment, enabling accurate three-dimensional scanning and defect identification even in complex industrial sites, bringing significant innovation and progress to the field of industrial inspection. Attached Figure Description

[0087] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0088] Figure 1 This is a flowchart illustrating the calibration method of the rotating structured light three-dimensional measurement system of the present invention;

[0089] Figure 2 This is a schematic diagram of the structure of the rotating structured light three-dimensional measurement system of the present invention;

[0090] Figure 3 This is a schematic diagram of the reference relationships between various coordinate systems during the vertical axis calibration process of this invention;

[0091] Figure 4 This is a schematic diagram of the reference relationships between various coordinate systems during the horizontal axis calibration process of this invention;

[0092] Figure 5 This is a schematic diagram illustrating the implementation process of the calibration method in Embodiment 2 of the present invention;

[0093] In the diagram: Camera 1, Laser 2, Horizontal pivot 3, Vertical pivot 4, Crossbeam 5, Base 6. Detailed Implementation

[0094] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments:

[0095] Example 1

[0096] like Figures 1-4 As shown, a calibration method for a rotating structured light three-dimensional measurement system includes the following steps:

[0097] Step 1: Construct a rotating structured light 3D measurement system, which includes a camera 1, a laser 2, a horizontal rotating axis 3, a vertical rotating axis 4, a crossbeam 5, and a base 6;

[0098] Step 2: Perform camera 1 calibration to obtain the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system. The coordinate transformation relationship between the camera coordinate system and the pixel coordinate system is described by the intrinsic parameter matrix.

[0099] Step 3: Perform structural cursor calibration to obtain the light plane equation in the camera coordinate system;

[0100] Step 4: Perform vertical axis 4 calibration. By changing the position of vertical axis 4 and acquiring images, solve for the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when vertical axis 4 rotates.

[0101] Step 5: Perform horizontal axis 3 calibration. By changing the position of horizontal axis 3 and acquiring images, solve for the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when horizontal axis 3 rotates.

[0102] In this embodiment, in Step 2, camera 1 is calibrated to obtain the camera coordinate system. With pixel coordinate system The coordinate transformation relationship between them; and the camera coordinate system With pixel coordinate system The coordinate transformation relationship between them satisfies:

[0103] (1)

[0104] in, This represents the intrinsic parameter matrix.

[0105] Furthermore, the specific process of calibrating camera 1 in Step 2 includes: placing the chessboard within the field of view of camera 1, changing its position and orientation, acquiring a series of chessboard images, and calculating the intrinsic parameter matrix and distortion parameters, wherein the imaging model of camera 1 satisfies a preset formula relationship:

[0106] (2)

[0107] in, Indicates the scale factor. Indicates focal length. This indicates the coordinates of the principal point in the image captured by camera 1. The corner points of the chessboard in the camera coordinate system The three-dimensional coordinates below Represents the pixel coordinates of the corner points of the chessboard grid.

[0108] Furthermore, the specific process of structural beam calibration in Step 3 includes: keeping the rotating structured light 3D measurement system stationary, illuminating the line structured light emitted by it onto the checkerboard, changing the pose of the checkerboard, acquiring at least two checkerboard images, extracting the pixel coordinates of the center line of the line structured light using the gray-scale centroid method, and obtaining the light plane equation.

[0109] Furthermore, the pixel coordinates of the center line of the structured light extracted using the gray-scale centroid method are: The center line of the line structured light was calculated in the camera coordinate system. The coordinates below are used to fit the camera coordinate system. The light plane equation below, which satisfies:

[0110] (3)

[0111] Where A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is any point on the plane, and D is a constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0112] Furthermore, in Step 4, the camera coordinate system is obtained when the vertical rotation axis 4 rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using the rotation matrix and translation matrix, calculating the distance between the optical center of camera 1 and the vertical rotation axis 4 by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship.

[0113] Furthermore, the solution yields the camera coordinate system when the vertical rotation axis 4 rotates. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0114] In three-dimensional space, the coordinate system along The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0115] (4)

[0116] (5)

[0117] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0118] Assuming camera coordinate system of The axis is parallel to the vertical rotation axis 4, and the camera coordinate system of Plane and Rotational Coordinate Systems of If the planes are in the same plane, then the translation matrix can be rewritten as:

[0119] (6)

[0120] in, This indicates that after the vertical axis 4 rotates, the crossbeam 5 and... The angle formed by the axis, This indicates the distance between the optical center of camera 1 and the vertical rotation axis 4;

[0121] Rotation coordinate system The origin is defined in the camera coordinate system. The origin is along For positions where the displacement difference in the direction is 0, the translation matrix of the initial position can be rewritten as:

[0122] (7)

[0123] The coordinate transformation relationship before and after camera 1 rotates satisfies:

[0124] (8)

[0125] in, Camera coordinate system before and after rotation along vertical axis 4 , The coordinate transformation matrix between them Camera coordinate system before and after rotation along vertical axis 4 , Rotation matrix between Camera coordinate system before and after rotation along vertical axis 4 , Translation matrix between them;

[0126] Introducing a rotation coordinate system Finally, the overall transformation relation satisfies:

[0127] (9)

[0128] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, Camera coordinate system With rotation coordinate system Translation matrix between them Camera coordinate system With rotation coordinate system Translation matrix between them;

[0129] When calibrating the vertical axis 4, because the crossbeam 5 is parallel to the vertical axis 4 after rotation... Angle between the axes Given that the chessboard is fixed, images of the chessboard are captured by camera 1 before and after rotation along the vertical axis 4. Two different coordinate transformation matrices are obtained through camera 1 calibration:

[0130] (10)

[0131] (11)

[0132] in, and The camera coordinate system before and after rotation along the vertical axis 4 are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0133] By combining equations (8), (10), and (11), the distance between the optical center of camera 1 and the vertical rotation axis 4 is calculated. ,satisfy:

[0134] (12)

[0135] Among them, the distance between the optical center of camera 1 and the vertical rotation axis 4 The mounting position of camera 1 is used to further solve for the camera coordinate system when the vertical axis 4 rotates. With rotation coordinate system The coordinate transformation relationship between them.

[0136] Furthermore, in Step 5, the camera coordinate system is obtained when the horizontal axis 3 rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using the rotation matrix and translation matrix, calculating the distance between the horizontal rotation axis 3 and the origin of the rotation axis coordinate system by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship.

[0137] Furthermore, the solution yields the camera coordinate system when the horizontal axis 3 rotates. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0138] In three-dimensional space, the coordinate system along The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0139] (13)

[0140] (14)

[0141] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0142] The coordinate system of the rotation axis when the horizontal axis 3 rotates origin exist The translation in the direction is , The translation in the direction is Then the translation matrix can be rewritten as:

[0143] (15)

[0144] in, This indicates that after the horizontal shaft 3 rotates, the crossbeam 5 and... The angle between planes Indicates the horizontal rotation axis 3 and the rotation axis coordinate system The distance between the origins;

[0145] Because when the horizontal axis 3 rotates, the axis coordinate system It will rotate accordingly, therefore the coordinate system of the rotation axis before and after the horizontal rotation axis 3 rotates. and ,satisfy:

[0146] (16)

[0147] in, The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and Coordinate transformation matrix between;

[0148] Due to the rotation of the horizontal axis 3, the camera coordinate system With rotation coordinate system Synchronous changes, therefore the camera coordinate system Coordinate transformation matrix before and after rotation If they are the same, then the camera coordinate system before and after rotation is the same. , ,satisfy:

[0149] (17)

[0150] in, The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and Rotation matrix between The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and Translation matrix between them;

[0151] When calibrating the horizontal rotating shaft 3, because the horizontal rotating shaft 3 rotates, the crossbeam 5 and... Angle between planes Given that the chessboard is fixed, images of the chessboard are captured by camera 1 before and after rotation along the horizontal axis 3. Two different coordinate transformation matrices are obtained through camera 1 calibration:

[0152] (18)

[0153] (19)

[0154] in, and The camera coordinate systems before and after rotation of the horizontal axis 3 are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0155] By combining equations (17), (18), and (19), we can calculate the following:

[0156] (20)

[0157] Let the camera coordinate system be before the horizontal axis 3 rotates. The origin position is Rotated camera coordinate system The origin position is After performing a position transformation between the two coordinate systems, the following calculations were obtained:

[0158] (twenty one)

[0159] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, The coordinate system of the rotation axis before and after the horizontal rotation axis 3. and Translation matrix between them;

[0160] From equation (20), the camera coordinate system before and after the horizontal axis 3 is rotated is obtained. , coordinate transformation matrix between From equation (21), the coordinate system of the horizontal rotation axis 3 and the rotation axis is obtained. Distance between origins Furthermore, the camera coordinate system is obtained when the horizontal axis 3 rotates. With rotation coordinate system The coordinate transformation relationship between them satisfies:

[0161] (twenty two).

[0162] Furthermore, the camera 1 uses a lens with a frame rate of 30fps and a resolution of 1280×1024 pixels, and the laser 2 uses a line structured light laser with a wavelength of 450nm, a power of 10mW, and a line width of a preset value.

[0163] Furthermore, the checkerboard used in the calibration process is 200mm×200mm in size, with checkerboard squares of 10mm×10mm distributed on it. By moving the checkerboard multiple times to change its position and orientation in the field of view of camera 1, a series of calibration images are collected for camera 1 calibration.

[0164] Example 2

[0165] In another preferred embodiment, based on Embodiment 1 above, an implementation method for a calibration method of a rotating structured light three-dimensional measurement system is provided, as follows: Figure 5 As shown, it includes the following steps:

[0166] Step (1): Build a rotating structured light 3D measurement system. It is worth noting that, for example... Figure 2 As shown, the rotating structured light 3D measurement system specifically consists of a camera 1, a laser 22, a horizontal rotating axis 3, a vertical rotating axis 4, a crossbeam 5, and a base 6. The camera 1 has a frame rate of 30fps, a resolution of 1280×1024 pixels, and a lens focal length of 12mm. The laser 22 is a line structured light laser 2 with a wavelength of 450nm, a power of 10mW, and a linewidth of [missing information]. A high-precision standard sphere is selected for the target being measured.

[0167] After the setup is complete, when performing measurements using the rotating structured light 3D measurement system, first rotate perpendicularly along axis 4, and then rotate laser 22 along... The axis scans the object being measured; then the horizontal axis 3 rotates to change the relationship between the crossbeam 5 and the object being measured. The angle between planes; the rotating structured light 3D measurement system again along The axis is scanned until the scan of the object being measured is completed.

[0168] Step (2): Camera 1 calibration.

[0169] Obtain the camera coordinate system With pixel coordinate system Coordinate transformation relationships between them; where the camera coordinate system With pixel coordinate system The coordinate transformation relationship between them satisfies:

[0170] (1)

[0171] in, This represents the intrinsic parameter matrix.

[0172] As a preferred embodiment of the present invention, the specific process of camera 1 calibration in step (2) can be described as follows: placing the chessboard within the field of view of camera 1, changing its position and orientation, acquiring a series of chessboard images, and calculating the intrinsic parameter matrix and distortion parameters.

[0173] Camera 1 imaging model satisfies:

[0174] (2)

[0175] in, Indicates the scale factor. Indicates focal length. This indicates the coordinates of the principal point in the image captured by camera 1. The corner points of the chessboard in the camera coordinate system The three-dimensional coordinates below Represents the pixel coordinates of the corner points of the chessboard grid.

[0176] It should be noted that the Zhang calibration method used in step (2) combined with a high-precision checkerboard is used to calibrate camera 1 (including the calibration of intrinsic parameter matrices). and distortion parameters (including radial distortion coefficients) , and tangential distortion parameters , (Calibration of camera 1). The checkerboard used in this process is 200×200mm in size, with 10×10mm checkerboard squares distributed on its surface. During calibration, the checkerboard is moved multiple times, changing its position and orientation within the field of view of camera 1 (e.g., 15 times), and a series of calibration images are acquired to calibrate the imaging model of camera 1. Based on the aforementioned imaging model formula for camera 1, the intrinsic parameter matrix of camera 1 is obtained. And distortion parameters, please refer to Table 1 below for details:

[0177] Table 1

[0178]

[0179] Step (3): Determine the structural cursor.

[0180] As a preferred embodiment of the present invention, the specific process of structural cursor determination in step (3) can be described as follows:

[0181] Keep the rotating structured light 3D measurement system stationary and let its emitted line structured light illuminate the chessboard; change the pose of the chessboard and acquire at least two images of the chessboard.

[0182] The pixel coordinates of the center line of the line structured light are extracted using the gray-scale centroid method. The center line of the line structured light was calculated in the camera coordinate system. The coordinates below;

[0183] Based on the coordinates of each point, the camera coordinate system is obtained by fitting. The equation of the light plane is as follows; the equation of the light plane satisfies:

[0184] (3)

[0185] Where A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is any point on the plane, and D is a constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0186] Specifically, first, an image of a chessboard is acquired. Laser 2 emits line structured light onto the chessboard, and camera 1 acquires an image of the chessboard. Then, the line structured light emitted by the rotating structured light 3D measurement system is directed onto the chessboard and kept fixed. The pose of the chessboard is changed, and the above steps are repeated to acquire another image of the chessboard. Finally, at least two sets of images are obtained.

[0187] Then, the pixel coordinates of the center line of the line structured light were extracted using the gray-scale centroid method, and the coordinates of each point on the center line of the line structured light in the camera coordinate system were calculated. The coordinates below are used to fit the equation of the light plane based on the coordinates of each point. The equation of the light plane is as follows: .

[0188] Step (4): Vertical axis calibration;

[0189] The camera coordinate system is obtained when the vertical rotation axis 4 is rotated. With rotation coordinate system The coordinate transformation relationship between them.

[0190] In a preferred embodiment of the present invention, the camera coordinate system is obtained in step (4) when the vertical rotation axis 4 rotates. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0191] like Figure 3 As shown, in three-dimensional space, the coordinate system along... The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0192] (4)

[0193] (5)

[0194] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0195] Assuming camera coordinate system of The axis is parallel to the vertical rotation axis 4, and the camera coordinate system of Plane and Rotational Coordinate Systems of If the planes are in the same plane, then the translation matrix can be rewritten as:

[0196] (6)

[0197] in, This indicates that after the vertical axis 4 rotates, the crossbeam 5 and... The angle formed by the axis, This indicates the distance between the optical center of camera 1 and the vertical rotation axis 4;

[0198] Rotation coordinate system The origin is defined in the camera coordinate system. The origin is along For positions where the displacement difference in the direction is 0, the translation matrix of the initial position can be rewritten as:

[0199] (7)

[0200] The coordinate transformation relationship before and after camera 1 rotates satisfies:

[0201] (8)

[0202] in, Camera coordinate system before and after rotation along vertical axis 4 , The coordinate transformation matrix between them Camera coordinate system before and after rotation along vertical axis 4 , Rotation matrix between Camera coordinate system before and after rotation along vertical axis 4 , Translation matrix between them;

[0203] Introducing a rotation coordinate system Finally, the overall transformation relation satisfies:

[0204] (9)

[0205] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, Camera coordinate system With rotation coordinate system Translation matrix between them Camera coordinate system With rotation coordinate system Translation matrix between them;

[0206] like Figure 3 As shown, during the calibration of the vertical axis 4, because the vertical axis 4 rotates, the crossbeam 5 and... Angle between the axes Given that the chessboard is fixed, images of the chessboard are captured by camera 1 before and after rotation along the vertical axis 4. Two different coordinate transformation matrices are obtained through camera 1 calibration:

[0207] (10)

[0208] (11)

[0209] in, and The camera coordinate system before and after rotation along the vertical axis 4 are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0210] By combining equations (8), (10), and (11), the distance between the optical center of camera 1 and the vertical rotation axis 4 is calculated. ,satisfy:

[0211] (12)

[0212] Among them, the distance between the optical center of camera 1 and the vertical rotation axis 4 The mounting position of camera 1 is used to determine the camera coordinate system when the vertical axis 4 rotates. With rotation coordinate system The coordinate transformation relationship between them.

[0213] It is worth noting that, such as Figure 3 As shown, during the calibration of the vertical axis 4, the chessboard is first fixed, and an image of the chessboard is acquired by camera 1 before the vertical axis 4 is rotated; then the vertical axis 4 is rotated (here, a rotation of 2.5 degrees is chosen), while ensuring that the image of the chessboard is within the field of view of camera 1. Throughout this process, the pose of the chessboard is kept fixed, and then another image of the chessboard is acquired. From equations (10) and (11), the extrinsic parameter matrix of camera 1 before the vertical axis 4 is rotated is as follows:

[0214] .

[0215] The extrinsic parameter matrix of camera 1 after rotation along vertical axis 4 is as follows:

[0216] .

[0217] From the above calculation process, we can obtain the distance from the optical center of camera 1 to the rotation axis coordinate system. Distance from the origin .

[0218] After rotating around the vertical axis 4, the crossbeam 5 and Angle between the axes Taking 10 degrees as an example, calculate the camera coordinate system. With rotation coordinate system The coordinate transformation matrix is ​​as follows:

[0219] .

[0220] Step (5): Calibrate the horizontal axis 3.

[0221] The camera coordinate system is obtained by solving the problem when the horizontal axis 3 rotates. With rotation coordinate system The coordinate transformation relationship between them.

[0222] In a preferred embodiment of the present invention, the camera coordinate system is obtained in step (5) when the horizontal axis 3 rotates. With rotation coordinate system The specific process of coordinate transformation between them can be described as follows:

[0223] like Figure 4 As shown, in three-dimensional space, the coordinate system along... The rotation matrix for axis rotation and the translation matrix for overall coordinate system translation satisfy the following:

[0224] (13)

[0225] (14)

[0226] in, This represents the angle of rotation of the coordinate system around the y-axis in three-dimensional space.

[0227] The coordinate system of the rotation axis when the horizontal axis 3 rotates origin exist The translation in the direction is , The translation in the direction is Then the translation matrix can be rewritten as:

[0228] (15)

[0229] in, This indicates that after the horizontal shaft 3 rotates, the crossbeam 5 and... The angle between planes Indicates the horizontal rotation axis 3 and the rotation axis coordinate system The distance between the origins;

[0230] Because when the horizontal axis 3 rotates, the axis coordinate system It will rotate accordingly, therefore the coordinate system of the rotation axis before and after the horizontal rotation axis 3 rotates. and ,satisfy:

[0231] (16)

[0232] in, The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and Coordinate transformation matrix between;

[0233] Due to the rotation of the horizontal axis 3, the camera coordinate system With rotation coordinate system Synchronous changes, therefore the camera coordinate system Coordinate transformation matrix before and after rotation If they are the same, then the camera coordinate system before and after rotation is the same. , ,satisfy:

[0234] (17)

[0235] in, The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and Rotation matrix between The coordinate system representing the axis of rotation before and after the horizontal axis 3 is rotated. and The translation matrix between them.

[0236] like Figure 4 As shown, during the calibration of the horizontal rotating shaft 3, due to the rotation of the horizontal rotating shaft 3, the crossbeam 5 and... Angle between planes Given that the chessboard is fixed, images of the chessboard are captured by camera 1 before and after rotation along the horizontal axis 3. Two different coordinate transformation matrices are obtained through camera 1 calibration:

[0237] (18)

[0238] (19)

[0239] in, and The camera coordinate systems before and after rotation of the horizontal axis 3 are respectively. , Relative to the world coordinate system The coordinate transformation matrix;

[0240] By combining equations (17), (18), and (19), we can calculate the following:

[0241] (20)

[0242] Let the camera coordinate system be before the horizontal axis 3 rotates. The origin position is Rotated camera coordinate system The origin position is After performing a position transformation between the two coordinate systems, the following calculations were obtained:

[0243] (twenty one)

[0244] in, Rotational coordinate system Around Axis rotation Rotation matrix of angle, The coordinate system of the rotation axis before and after the horizontal rotation axis 3. and Translation matrix between them;

[0245] From equation (20), the camera coordinate system before and after the horizontal axis 3 is rotated is obtained. , coordinate transformation matrix between From equation (21), the coordinate system of the horizontal rotation axis 3 and the rotation axis is obtained. Distance between origins Furthermore, the camera coordinate system is obtained when the horizontal axis 3 rotates. With rotation coordinate system The coordinate transformation relationship between them satisfies:

[0246] (twenty two).

[0247] It is worth noting that, such as Figure 4As shown, during the calibration of the horizontal axis 3, the chessboard is first fixed. Before the horizontal axis 3 rotates, the camera 1 captures an image of the chessboard. Then, the horizontal axis 3 is rotated (here, a 5-degree rotation is chosen), while ensuring that the image of the chessboard is within the field of view of the camera 1. Throughout this process, the pose of the chessboard is kept fixed, and then another image of the chessboard is captured.

[0248] From equations (18) and (19), the extrinsic parameter matrix of camera 1 before the horizontal axis 3 rotates is as follows:

[0249] .

[0250] The extrinsic parameter matrix of camera 1 after rotation along horizontal axis 3 is as follows:

[0251] .

[0252] By combining equations (20) and (22), we can obtain the horizontal rotation axis 3 and the rotation axis coordinate system. Distance from the origin .

[0253] After rotating around the horizontal axis 3, the crossbeam 5 and Angle between planes Taking 8 degrees as an example, calculate the camera coordinate system. With rotation coordinate system Coordinate transformation matrix:

[0254] .

[0255] Combining equations (1), (3), (12), and (22), we know that when the pixel coordinates of the line structured light are... At that time, the corresponding rotation axis coordinate system The coordinates below are After the line structured light has completed its rotational scanning of the object being measured, the three-dimensional coordinates of the entire surface of the target object can be obtained.

[0256] Thus, the calibration method for the rotating structured light three-dimensional measurement system provided by this invention realizes three-dimensional measurement of the target object and has a vertical rotation axis 4 and a horizontal rotation axis 3, which expands the measurement range and enables effective measurement of large-sized objects. The calibration method for the rotating structured light three-dimensional measurement system of this invention not only expands the measurement range and improves the measurement accuracy, but also avoids the influence of system assembly and adjustment errors on the calibration accuracy through precise rotation axis calibration, which has significant technical progress and practical value.

[0257] In the preferred embodiment, the specific process of structured light calibration in Step 3 includes: keeping the rotating structured light 3D measurement system stationary, allowing its emitted line structured light to illuminate the checkerboard, changing the pose of the checkerboard, acquiring at least two checkerboard images, extracting the pixel coordinates of the line structured light centerline using the gray-scale centroid method, and obtaining the light plane equation. These settings ensure that the system can accurately capture changes in the light spot after each pose adjustment, and then fit all pixel coordinate points using the least squares method to optimize and solve for the light plane model that best matches the actual scene, providing a solid foundation for subsequent 3D reconstruction.

[0258] In the preferred embodiment, the camera coordinate system is obtained in Step 4 when the vertical axis rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using the rotation matrix and translation matrix, calculating the distance between the optical center of camera 1 and the vertical rotation axis 4 by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship; the above settings ensure that the camera can accurately transform the captured image information into a unified rotation axis coordinate system under different rotation angles, providing a solid foundation for subsequent image processing and data analysis.

[0259] In the preferred embodiment, the camera coordinate system is obtained in Step 5 when the horizontal axis rotates. With rotation coordinate system The specific process of coordinate transformation between them includes: using rotation and translation matrices, calculating the distance between the horizontal rotation axis 3 and the origin of the rotation axis coordinate system by solving a system of simultaneous equations, and further solving for the coordinate transformation relationship; the above settings, combined with real-time sensor data, ensure the transformation accuracy; in software implementation, an efficient matrix operation library is used to optimize computation efficiency, while an error detection mechanism is introduced to ensure the accuracy and robustness of coordinate transformation.

[0260] In the preferred embodiment, the camera uses a lens with a frame rate of 30fps and a resolution of 1280×1024 pixels, and the laser is a line structured light laser with a wavelength of 450nm, a power of 10mW, and a preset linewidth. These settings ensure that clear and high-precision image data is obtained during the scanning process. At the same time, with the addition of a high-performance data processing unit, rapid capture and accurate analysis of three-dimensional spatial information are achieved, meeting the high-precision measurement requirements in complex environments.

[0261] In the preferred embodiment, the checkerboard used in the calibration process is 200mm×200mm in size, with 10mm×10mm checkerboard squares distributed on it. By repeatedly moving the checkerboard square to change its position and orientation in the field of view of camera 1, a series of calibration images are acquired for camera 1 calibration. The above settings ensure the accuracy and stability of the calibration process. In addition, the use of high-precision algorithms to process these calibration images further improves the accuracy of solving the intrinsic and extrinsic parameters of camera 1, laying a solid foundation for subsequent 3D reconstruction and visual measurement.

[0262] In summary, this invention provides a calibration method for a rotating structured light 3D measurement system, solving key problems in the field of quantitative detection of defects in hydro-generator equipment, particularly addressing the limitations of existing rotating structured light 3D measurement systems in measuring large targets, such as limited measurement range and the impact of system assembly and adjustment errors on calibration accuracy. By employing an innovative calibration method, this invention overcomes the shortcomings of existing technologies, achieving effective measurement of large objects and significantly improving measurement accuracy. The invention introduces vertical and horizontal rotating axes, realizing a dual-axis rotation function for the measurement system, thereby significantly expanding the measurement range and enabling more effective measurement of large objects. Through precise calibration of the vertical and horizontal rotating axes, this invention accurately calculates the installation position between the camera and the axes, avoiding the impact of system assembly and adjustment errors on calibration accuracy—a precision not found in traditional methods. This invention includes not only camera and structured light calibration but also details the calibration process for the vertical and horizontal rotating axes, forming a comprehensive system calibration workflow. This comprehensive calibration process helps improve the overall measurement accuracy of the system. By introducing a rotation axis coordinate system and utilizing rotation and translation matrices, this invention innovatively solves the coordinate transformation relationship between the camera coordinate system and the rotation axis coordinate system, improving the accuracy and reliability of coordinate transformation. Addressing the practical needs of quantitative detection of defects in hydro-generator equipment, this invention improves measurement accuracy and efficiency by optimizing the structure and calibration method of the measurement system, demonstrating the creativity of applying advanced technology to practical engineering problems. This invention exhibits high novelty and creativity in both the structural design and calibration method of the rotating structured light 3D measurement system, providing a new technical means for quantitative detection of defects in hydro-generator equipment. This invention achieves high-precision and rapid 3D measurement system calibration. By calibrating the camera 1, structured light plane, and vertical and horizontal rotation axes 3 step-by-step, it effectively improves the accuracy and stability of 3D reconstruction, providing reliable technical support for industrial automation inspection, reverse engineering, and other fields. Furthermore, the modular design of this invention facilitates maintenance and upgrades, adapts to different inspection scenarios, and demonstrates good flexibility and scalability, injecting new vitality into the continuous development of the industrial measurement field.

Claims

1. A calibration method for a rotating structured light three-dimensional measurement system, characterized in that, The method comprises the following steps: Step 1: a rotating structured light three-dimensional measurement system is built, the system comprising a camera (1), a laser (2), a horizontal rotating shaft (3), a vertical rotating shaft (4), a crossbeam (5) and a base (6); Step 2: camera (1) calibration is performed to obtain the coordinate conversion relationship between the camera coordinate system and the pixel coordinate system, wherein the coordinate conversion relationship between the camera coordinate system and the pixel coordinate system is described by an intrinsic matrix; Step 3: structured light calibration is performed to obtain the light plane equation in the camera coordinate system; Step 4: vertical rotating shaft (4) calibration is performed, the position of the vertical rotating shaft (4) is changed and an image is collected, a rotation matrix and a translation matrix are used, the distance between the camera (1) light center and the vertical rotating shaft (4) is calculated by solving the equation set, and the coordinate conversion relationship between the camera coordinate system and the rotating shaft coordinate system during the rotation of the vertical rotating shaft (4) is further solved, the specific process being as follows: In three-dimensional space, the rotation matrix when the coordinate system rotates along the x-axis, the y-axis, and the z-axis, respectively, is The translation matrix when the coordinate system translates as a whole The translation matrix when the coordinate system translates as a whole respectively. （4）； （5）； wherein, denotes the angle of rotation of the coordinate system around the axis in the three-dimensional space; is the arbitrary point in the plane, , , are the coordinates of the , , axis, respectively. Assume the camera coordinate system The axis is parallel to the vertical rotation axis (4), and the The plane of the camera coordinate system The plane of the rotation axis coordinate system is in the same plane, then the translation matrix is rewritten as: （6）； wherein, represents the angle between the horizontal beam (5) and the vertical rotation axis (4) after the rotation of the vertical rotation axis (4), represents the angle between the horizontal beam (5) and the vertical rotation axis (4) after the rotation of the vertical rotation axis (4), represents the distance between the optical center of the camera (1) and the vertical rotation axis (4); The rotation axis coordinate system The origin is defined at the same position as the camera coordinate system The origin is at the same position as the camera coordinate system The translation matrix of the initial position is rewritten as: （7）； The coordinate conversion relationship of the camera (1) before and after rotation satisfies: （8）； wherein, is the coordinate transformation matrix between the camera coordinate systems before and after rotation of the vertical rotation axis (4), , is the rotation matrix between the camera coordinate systems before and after rotation of the vertical rotation axis (4), , is the translation matrix between the camera coordinate systems before and after rotation of the vertical rotation axis (4), , is the translation matrix between the camera coordinate systems before and after rotation of the vertical rotation axis (4), , is the translation matrix between the camera coordinate systems before and after rotation of the vertical rotation axis (4). Introducing the body-fixed coordinate system After the total conversion relationship, meet: （9）； wherein, is a rotation matrix for rotating the camera coordinate system about the rotation axis by an angle, is a translation matrix between the camera coordinate system and the rotation axis coordinate system , is a translation matrix between the camera coordinate system and the rotation axis coordinate system . When calibrating the vertical axis (4), the crossbeam (5) and the vertical axis (4) rotate after the vertical axis (4) are calibrated. Angle between the axes Given that the chessboard is fixed, images of the chessboard are captured by camera (1) before and after rotation along the vertical axis (4). Two different coordinate transformation matrices are obtained through camera (1) calibration, namely: （10）； （11）； wherein, and are the coordinate transformation matrices of the camera coordinate system , with respect to the world coordinate system before and after rotation of the vertical rotation axis (4). By combining equations (8), (10) and (11), the distance between the optical center of the camera (1) and the vertical rotation shaft (4) is calculated , which satisfies: （12）； Wherein the distance between the camera (1) optical center and the vertical rotation axis (4) For marking the installation position of the camera (1), and further solving the coordinate conversion relationship between the camera coordinate system and the rotation axis coordinate system when the vertical rotation axis (4) rotates With the rotation axis coordinate system ​ Step 5: Perform horizontal rotating shaft (3) calibration. Change the position of the horizontal rotating shaft (3) and collect images. Use rotation matrix and translation matrix. Solve the equation set to obtain the distance between the horizontal rotating shaft (3) and the rotating shaft coordinate system origin. Further solve to obtain the coordinate conversion relationship between the camera coordinate system and the rotating shaft coordinate system when the horizontal rotating shaft (3) rotates.

2. The method of claim 1, wherein The camera (1) in Step 2 is calibrated to obtain the coordinate conversion relationship between the camera coordinate system and the pixel coordinate system ; and the coordinate conversion relationship between the camera coordinate system and the pixel coordinate system satisfies: （1）； wherein, represents an intrinsic matrix, is a three-dimensional coordinate of the chessboard corner point in the camera coordinate system under the camera coordinate system, represents a pixel coordinate of the chessboard corner point.

3. The method of claim 2, wherein The specific process of the camera (1) calibration in the Step 2 comprises placing a checkerboard in the field of view of the camera (1), changing the position and attitude thereof, collecting a series of checkerboard images, and calculating the intrinsic matrix and distortion parameters, wherein the imaging model of the camera (1) satisfies a preset formula relationship: （2）； wherein, denotes a scale factor, denotes a focal length, denotes a principal point coordinate at which the camera (1) captures an image.

4. The method of claim 3, wherein The specific process of the structured light calibration in the Step 3 comprises keeping the rotating structured light three-dimensional measurement system stationary, making the linear structured light emitted thereby irradiate onto the checkerboard, changing the attitude of the checkerboard, collecting at least two checkerboard images, and using the gray centroid method to extract the pixel coordinates of the linear structured light center line to obtain the light plane equation.

5. The method of claim 4, wherein: The checkerboard has a size of 200mm*200mm, and the checkerboard is provided with checkerboards with a size of 10mm*10mm, the position and attitude of the checkerboard in the field of view of the camera (1) are changed by moving the checkerboard multiple times, and a series of calibration images are collected for camera (1) calibration.

6. The calibration method of a rotating structured light three-dimensional measurement system according to claim 4, wherein: The pixel coordinates of the line structured light center line extracted by the gray gravity center method are , the coordinates of each point of the line structured light center line in the camera coordinate system are calculated, and the light plane equation in the camera coordinate system is fitted according to the coordinates of each point, and the light plane equation satisfies: （3）； Wherein, A, B and C are the components of the normal vector of the light plane on the respective coordinate axes, (x, y, z) is an arbitrary point on the plane, and D is a constant term in the plane equation, which is related to the distance of the plane from the origin.

7. The method of claim 1, wherein The specific process of solving the coordinate conversion relationship between the horizontal rotating shaft (3) and the camera coordinate system in Step 5 is as follows: and the rotating shaft coordinate system are as follows: In three-dimensional space, the rotation matrix when the coordinate system rotates along The translation matrix when the coordinate system as a whole translates satisfies: （13）； （14）； wherein denotes the angle of rotation of the coordinate system about the y-axis in three-dimensional space; horizontal rotation axis (3) rotates, the rotation axis coordinate system origin in the translation amount in the direction is , the translation amount in the direction is the translation matrix can be rewritten as: （15）； wherein denotes the angle between the horizontal rotation axis (3) and the plane of the cross member (5) after rotation of the horizontal rotation axis (3), denotes the angle between the horizontal rotation axis (3) and the plane of the cross member (5) after rotation of the horizontal rotation axis (3), denotes the distance between the horizontal rotation axis (3) and the origin of the rotation axis coordinate system, denotes the distance between the horizontal rotation axis (3) and the origin of the rotation axis coordinate system, Since the horizontal rotating shaft (3) rotates, the rotating shaft coordinate system will rotate accordingly, so the rotating shaft coordinate system before and after the rotation of the horizontal rotating shaft (3) satisfies: , （16）； wherein represents the coordinate transformation matrix between the coordinate systems of the horizontal rotation axis (3) before and after rotation and and Since the camera coordinate system changes synchronously with the rotation of the horizontal rotation axis (3) , the camera coordinate system before and after rotation has the same coordinate transformation matrix ; therefore, the camera coordinate system , before and after rotation satisfies: （17）； in, The coordinate system representing the horizontal axis of rotation (3) before and after rotation. and Rotation matrix between The coordinate system representing the horizontal axis of rotation (3) before and after rotation. and Translation matrix between them; When calibrating the horizontal rotating shaft (3), the crossbeam (5) and the horizontal rotating shaft (3) rotate after the horizontal rotating shaft (3) are calibrated. Angle between planes Given that the chessboard is fixed, images of the chessboard are captured by camera (1) before and after rotation along the horizontal axis (3). Two different coordinate transformation matrices are obtained through camera (1) calibration, namely: （18）； （19）； wherein, and are the coordinate transformation matrices of the camera coordinate system , with respect to the world coordinate system before and after the horizontal rotation axis (3) rotates. The equations (17), (18) and (19) are solved to obtain: （20）； Camera coordinate system before rotation of horizontal rotation shaft (3) Origin position is Camera coordinate system after rotation Origin position is Position conversion of two coordinate systems is performed, and the following is calculated: （21）； wherein, is the rotation matrix for rotating the axis of rotation about the axis of rotation by an angle of is the translation matrix between the horizontal axis of rotation (3) before and after rotation and the axis of rotation. From equation (20), the camera coordinate system before and after the horizontal axis (3) is rotated is obtained. , coordinate transformation matrix between From equation (21), the horizontal rotation axis (3) and the rotation axis coordinate system are obtained. Distance between origins Furthermore, the camera coordinate system when the horizontal axis (3) rotates is obtained by solving the problem. With rotation coordinate system The coordinate transformation relationship between them satisfies: （22）。 8. The method of claim 1, wherein: The camera (1) uses a lens with a frame frequency of 30fps and a resolution of 1280*1024 pixels, the laser (2) uses a linear structured light laser with a wavelength of 450nm, a power of 10mW and a preset line width.

Images