Calibration method of rotating structured light three-dimensional measurement system

Abstract

The invention relates to a calibration method for a rotating structured light three-dimensional measurement system. The method comprises the following steps: building the rotating structured light three-dimensional measurement system; calibrating a camera; obtaining a coordinate conversion relation between a camera coordinate system and a pixel coordinate system; performing structure cursor calibration; calibrating a vertical rotating shaft; solving to obtain a coordinate conversion relation between a camera coordinate system and a rotating shaft coordinate system when the vertical rotating shaft rotates; calibrating a horizontal rotating shaft; solving to obtain a coordinate conversion relation between a camera coordinate system and a rotating shaft coordinate system when the horizontal rotating shaft rotates; the calibration method is applied to the rotating structured light three-dimensional measurement system. The vertical rotating shaft and the horizontal rotating shaft are arranged, so that the measurement range is expanded, and effective measurement of large-size objects can be realized; the installation positions of the camera and the rotating shaft are obtained through rotating shaft calibration and accurate calculation, the influence of system installation and adjustment errors on calibration precision is avoided, the precision and stability of three-dimensional reconstruction are effectively improved, and reliable technical support is provided for the fields of industrial automatic detection, reverse engineering and the like.

Description

Technical Field

[0001] The invention relates to the technical field of quantitative detection of defects in hydro-generator equipment, and in particular to a calibration method for a rotating structured light three-dimensional measurement system. Background Art

[0002] As an important part of the power system, the structural integrity of the hydro-turbine generator set is directly related to the safety and stability of energy supply. During long-term operation, the flow-through components in the hydro-turbine generator set, such as blades and impellers, often suffer from defects such as wear and cracks due to natural factors such as water scouring, 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 generator set, and even cause major accidents. Therefore, achieving quantitative detection of defects in hydro-turbine generator set equipment is of great significance to ensure the safe operation of the generator set.

[0003] As a non-contact, high-precision measurement method, rotational structured light 3D measurement technology has shown unique advantages in the detection of complex curved surfaces and large structures. This technology projects structured light onto the surface of the object to be measured, uses a camera to capture the deformed image of the structured light on the surface of the object, and through image processing and algorithm analysis, it can restore the 3D shape information of the object with high precision. However, most of the existing rotational structured light 3D measurement systems adopt a single-axis rotation design, which limits their measurement range and flexibility, making it difficult to meet the high-precision measurement requirements of large-sized and complex-shaped objects.

[0004] For example, CN112179291A discloses a calibration method for a self-rotating scanning type line structured light three-dimensional measuring device, which belongs to the field of three-dimensional measurement technology; the self-rotating scanning type line structured light three-dimensional measuring device is mainly composed of a line structured light profile measuring instrument and a high-precision turntable. Usually, the coordinate system of the self-rotating scanning type line structured light three-dimensional measuring device is established based on the rotation axis of the high-precision turntable, and does not coincide with the coordinate system of the line structured light profile measuring instrument, and the positional relationship between the two cannot be accurately determined by mechanical installation. The calibration method of the present invention uses a plane target to calibrate the position parameters between the coordinate system of the line structured light profile measuring instrument and the coordinate system of the self-rotating scanning type line structured light three-dimensional measuring device; the method uses a line structured light profile measuring instrument and a high-precision turntable to form a measuring device, and completes the calibration through a plane target; although the technical solution achieves a certain degree of measurement accuracy, it can only achieve single-axis rotation and its calibration, and cannot achieve all-round measurement of large-size targets.

[0005] In addition, Cui Yi from Harbin Engineering University proposed a rotating structured light 3D measurement system in his master's thesis "Research on 3D visual measurement method based on line laser rotation scanning". The system rotates the system through a dual-axis turntable to achieve measurement of large-sized objects. However, this technical solution has shortcomings in the accurate calculation of the installation position of the camera and the shaft, and the system measurement accuracy is easily affected by installation errors.

[0006] In view of the limitations of the above-mentioned prior art, a more accurate and reliable calibration method for the rotating structured light 3D measurement system is urgently needed to achieve high-precision 3D measurement of large-sized objects. The present invention is proposed in this context, aiming to accurately calculate the installation position of the camera and the rotating shaft through an innovative calibration method, expand the measurement range, and improve the measurement accuracy, thereby meeting the actual needs of quantitative detection of defects in hydro-turbine generator equipment. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a calibration method for a rotational structured light three-dimensional measurement system to solve the key problems in the technical field of quantitative detection of defects in hydro-turbine generator sets, especially the limitations of existing rotational structured light three-dimensional measurement systems in the process of measuring large-size targets, such as limited measurement range and the influence of system installation errors on calibration accuracy.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: a rotation structured light three-dimensional measurement system calibration method, comprising the following steps: Step 1: Build a rotating structured light 3D measurement system, which includes a camera, a laser, a horizontal axis, a vertical axis, a beam and a base; Step 2: Perform camera calibration to obtain the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system, where the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system is described by the intrinsic parameter matrix; Step 3: Perform structured light calibration to obtain the light plane equation in the camera coordinate system; Step 4: Calibrate the vertical axis. By changing the position of the vertical axis and collecting images, the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when the vertical axis rotates is solved. Step 5: Calibrate the horizontal axis. By changing the position of the horizontal axis and collecting images, the coordinate transformation relationship between the camera coordinate system and the axis coordinate system is obtained when the horizontal axis rotates.

[0009] In the preferred solution, the camera is calibrated in Step 2 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: (1) in, represents the internal parameter matrix.

[0010] In a preferred solution, the specific process of camera calibration in Step 2 includes: placing a checkerboard in the camera field of view, changing its position and posture, collecting a series of checkerboard images, and obtaining an intrinsic parameter matrix and distortion parameters by calculation, wherein the camera imaging model satisfies a preset formula relationship: (2) in, represents the scale factor, represents the focal length, Indicates the coordinates of the principal point of the image captured by the camera, The corner points of the chessboard are in the camera coordinate system The three-dimensional coordinates of Represents the pixel coordinates of the corner points of the checkerboard.

[0011] In a preferred solution, the specific process of structured light measurement in Step 3 includes: keeping the rotating structured light three-dimensional measurement system stationary, irradiating the line structured light emitted by it onto the checkerboard, changing the posture of the checkerboard, collecting at least two checkerboard images, and using the grayscale centroid method to extract the pixel coordinates of the center line of the line structured light to obtain the light plane equation.

[0012] In a preferred embodiment, the pixel coordinates of the center line of the line structured light extracted by using the grayscale centroid method are: , calculate the center line of the line structured light in the camera coordinate system According to the coordinates of each point, the camera coordinate system is fitted The light plane equation satisfies: (3) Among them, A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is an arbitrary point on the plane, and D is the constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0013] In the preferred solution, the camera coordinate system obtained in Step 4 when the vertical axis rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the camera optical center and the vertical rotation axis through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

[0014] In the preferred solution, the camera coordinate system is obtained when the vertical axis rotates With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (4) (5) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Assume the camera coordinate system of The axis is parallel to the vertical axis of rotation, and the camera coordinate system of Plane and axis coordinate system of If the planes are in the same plane, the translation matrix can be rewritten as: (6) in, Indicates that the beam and The angle between the axes, Indicates the distance between the camera's optical center and the vertical axis of rotation; The axis coordinate system The origin is defined in the camera coordinate system The origin is along If the displacement difference in the direction is 0, the translation matrix of the initial position is rewritten as: (7) Then the coordinate transformation relationship before and after the camera rotates satisfies: (8) in, The camera coordinate system before and after the vertical axis rotation , The coordinate transformation matrix between The camera coordinate system before and after the vertical axis rotation , The rotation matrix between The camera coordinate system before and after the vertical axis rotation , The translation matrix between Introducing the axis coordinate system After that, the total conversion relationship satisfies: (9) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the camera coordinate system With the axis coordinate system The translation matrix between is the camera coordinate system With the axis coordinate system The translation matrix between When calibrating the vertical axis, the crossbeam and Angle between axes It is known that, therefore, the checkerboard is fixed, and the camera is used to collect images of the checkerboard before and after the vertical axis rotation. Two different coordinate transformation matrices are obtained through camera calibration, which are: (10) (11) in, and They are the camera coordinate systems before and after the vertical axis rotation. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (8), (10) and (11), we can calculate the distance between the camera optical center and the vertical axis of rotation. ,satisfy: (12) Among them, the distance between the camera optical center and the vertical axis of rotation is Used to mark the installation position of the camera, and further solve the camera coordinate system when the vertical axis rotates With the axis coordinate system The coordinate transformation relationship between them.

[0015] In the preferred solution, the camera coordinate system obtained in Step 5 when the horizontal axis rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the horizontal axis and the origin of the axis coordinate system through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

[0016] In the preferred solution, the camera coordinate system is obtained by solving the horizontal axis rotation With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (13) (14) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Axis coordinate system when the horizontal axis rotates origin exist The translation amount in the direction is , The translation amount in the direction is , then the translation matrix can be rewritten as: (15) in, Indicates that the horizontal axis rotates and the beam The angle between the planes, Indicates the distance between the horizontal axis and the origin of the axis coordinate system; Due to the horizontal axis When rotating, the axis coordinate system Will rotate accordingly, so the axis coordinate system before and after the horizontal axis rotation and ,satisfy: (16) in, Represents the axis coordinate system before and after the horizontal axis rotates and The coordinate transformation matrix between Since the camera coordinate system rotates along the horizontal axis With the axis coordinate system Synchronously change, so the camera coordinate system The coordinate transformation matrix before and after rotation is The same; then the camera coordinate system before and after rotation , ,satisfy: (17) in, Represents the axis coordinate system before and after the horizontal axis rotates and The rotation matrix between Represents the axis coordinate system before and after the horizontal axis rotates and The translation matrix between When calibrating the horizontal axis, the horizontal axis rotates and the crossbeam Angle between planes It is known that, therefore, the checkerboard is fixed, and the camera is used to collect images of the checkerboard before and after the horizontal axis is rotated. Two different coordinate transformation matrices are obtained through camera calibration, which are: (18) (19) in, and They are the camera coordinate systems before and after the horizontal axis rotation. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (17), (18) and (19), we can get: (20) Set the camera coordinate system before horizontal axis rotation The origin position is , the rotated camera coordinate system The origin position is , perform the position conversion of the two coordinate systems and calculate: (twenty one) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the axis coordinate system before and after the horizontal axis (3) rotates and The translation matrix between From formula (20), we can find the camera coordinate system before and after the horizontal axis rotation: , The coordinate transformation matrix between ; From formula (21), find the horizontal axis and the axis coordinate system The distance between the origins ; Then solve the camera coordinate system when the horizontal axis rotates With the axis coordinate system The coordinate transformation relationship between them satisfies: (twenty two).

[0017] In a preferred solution, the camera uses a lens with a frame rate of 30fps and a resolution of 1280×1024 pixels, and the laser uses a line structured light laser with a wavelength of 450nm, a power of 10mW, and a line width of a preset value.

[0018] In a preferred solution, the size of the checkerboard used in the calibration process is 200mm×200mm, and checkerboards of size 10mm×10mm are distributed on the checkerboard. The position and posture of the checkerboard in the camera field of view are changed by moving the checkerboard multiple times, and a series of calibration images are collected for camera calibration.

[0019] The present invention provides a method for calibrating a rotating structured light three-dimensional measurement system, which has the following beneficial effects: 1. The present invention solves the key problems in the technical field of quantitative detection of defects in hydro-turbine generator sets, especially 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 influence of system adjustment errors on calibration accuracy. 2. The present invention overcomes the shortcomings of the prior art by providing an innovative calibration method for a rotating structured light three-dimensional measurement system, realizes effective measurement of large-sized objects, and significantly improves measurement accuracy; 3. Compared with the traditional single-axis rotation structured light 3D measurement system, the dual-axis rotation structure of the present invention introduces a vertical rotation axis and a horizontal rotation axis, realizing the dual-axis rotation function of the measurement system, thereby significantly expanding the measurement range, enabling it to more effectively measure large-sized objects; 4. The precise rotation axis calibration method of the present invention can accurately calculate the installation position between the camera and the rotation axis by accurately calibrating the vertical rotation axis and the horizontal rotation axis, thus avoiding the influence of the system adjustment error on the calibration accuracy. This precise calibration method is not available in traditional methods; 5. The comprehensive system calibration process of the present invention not only includes camera calibration and structural light calibration, but also describes in detail the calibration process of the vertical axis and the horizontal axis, forming a comprehensive system calibration process. This comprehensive calibration process helps to improve the overall measurement accuracy of the system; 6. The invention innovatively solves the coordinate transformation relationship. In the calibration process of the vertical axis and the horizontal axis, the solution introduces the axis coordinate system and uses the rotation matrix and the translation matrix to innovatively solve the coordinate transformation relationship between the camera coordinate system and the axis coordinate system. This method improves the accuracy and reliability of coordinate transformation; 7. The present invention combines practical application needs and targets the actual needs of quantitative detection of defects in hydro-generator equipment. The solution 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. 8. The present invention solves the bottleneck of the existing technology and solves the technical bottleneck of the existing rotating structured light 3D measurement system in the process of measuring large-sized targets, such as single-axis rotation limitation and installation error influence, etc. By introducing dual-axis rotation and precise calibration method, the effective measurement of large-sized objects is realized; 9. The present invention shows high novelty and creativity in the structural design and calibration method of the rotating structured light three-dimensional measurement system, and provides a new technical means for quantitative detection of defects in hydro-turbine generator sets; 10. The present invention not only improves the accuracy and efficiency of measurement, but also reduces the dependence on the operating environment, so that accurate three-dimensional scanning and defect identification can be achieved in complex industrial sites, bringing significant innovation and progress to the field of industrial inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below in conjunction with the accompanying drawings and implementation examples: Figure 1 It is a schematic flow chart of the calibration method of the rotating structured light three-dimensional measurement system of the present invention; Figure 2 A schematic diagram of the structure of the rotating structured light three-dimensional measurement system built for the present invention; Figure 3 A schematic diagram of the reference relationship of each coordinate system during the vertical axis calibration process of the present invention; Figure 4 A schematic diagram of the reference relationship of various coordinate systems during the horizontal axis calibration process of the present invention; Figure 5 Schematic diagram of the implementation process of the calibration method of Example 2 of the present invention; In the figure: camera 1, laser 2, horizontal rotation axis 3, vertical rotation axis 4, beam 5, base 6. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments: Example 1 like Figures 1 to 4 As shown, a rotation structured light three-dimensional measurement system calibration method includes the following steps: Step 1: Build a rotating structured light 3D measurement system, which includes a camera 1, a laser 2, a horizontal rotation axis 3, a vertical rotation axis 4, a beam 5 and a base 6; Step 2: Calibrate camera 1 to obtain the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system, where the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system is described by the intrinsic parameter matrix; Step 3: Perform structured light calibration to obtain the light plane equation in the camera coordinate system; Step 4: Calibrate the vertical axis 4. By changing the position of the vertical axis 4 and collecting images, the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when the vertical axis 4 rotates is solved. Step 5: Calibrate the horizontal axis 3. By changing the position of the horizontal axis 3 and collecting images, the coordinate transformation relationship between the camera coordinate system and the axis coordinate system when the horizontal axis 3 rotates is solved.

[0022] In this embodiment, the camera 1 is calibrated in Step 2 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: (1) in, represents the internal parameter matrix.

[0023] Furthermore, the specific process of camera 1 calibration in Step 2 includes: placing a checkerboard in the field of view of camera 1, changing its position and posture, collecting a series of checkerboard images, and obtaining an intrinsic parameter matrix and distortion parameters by calculation, wherein the imaging model of camera 1 satisfies a preset formula relationship: (2) in, represents the scale factor, represents the focal length, Indicates the coordinates of the principal point of the image captured by camera 1, The corner points of the chessboard are in the camera coordinate system The three-dimensional coordinates of Represents the pixel coordinates of the corner points of the checkerboard.

[0024] Furthermore, the specific process of structured light measurement in Step 3 includes: keeping the rotating structured light three-dimensional measurement system stationary, so that the line structured light emitted by it is irradiated onto the checkerboard, changing the posture of the checkerboard, collecting at least two checkerboard images, and using the grayscale centroid method to extract the pixel coordinates of the center line of the line structured light to obtain the light plane equation.

[0025] Furthermore, the pixel coordinates of the center line of the line structured light extracted by using the grayscale centroid method are: , calculate the center line of the line structured light in the camera coordinate system According to the coordinates of each point, the camera coordinate system is fitted The light plane equation satisfies: (3) Among them, A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is an arbitrary point on the plane, and D is the constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0026] Furthermore, the camera coordinate system obtained in Step 4 when the vertical axis 4 rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the optical center of the camera 1 and the vertical rotation axis 4 through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

[0027] Furthermore, the camera coordinate system obtained by the solution when the vertical axis 4 rotates is With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (4) (5) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Assume the camera coordinate system of The axis is parallel to the vertical axis 4, and the camera coordinate system of Plane and axis coordinate system of If the planes are in the same plane, the translation matrix can be rewritten as: (6) in, It means that after the vertical shaft 4 rotates, the cross beam 5 and The angle between the axes, represents the distance between the optical center of the camera 1 and the vertical rotation axis 4; The axis coordinate system The origin is defined in the camera coordinate system The origin is along If the displacement difference in the direction is 0, the translation matrix of the initial position is rewritten as: (7) Then the coordinate transformation relationship of camera 1 before and after rotation satisfies: (8) in, The camera coordinate system before and after the vertical axis 4 rotation , The coordinate transformation matrix between The camera coordinate system before and after the vertical axis 4 rotation , The rotation matrix between The camera coordinate system before and after the vertical axis 4 rotation , The translation matrix between Introducing the axis coordinate system After that, the total conversion relationship satisfies: (9) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the camera coordinate system With the axis coordinate system The translation matrix between is the camera coordinate system With the axis coordinate system The translation matrix between When calibrating the vertical axis 4, the cross beam 5 and the vertical axis 4 rotate. Angle between axes It is known that, therefore, the checkerboard is fixed, and the camera 1 is used to collect the checkerboard image before and after the vertical axis 4 rotates. Two different coordinate transformation matrices are obtained by calibration of the camera 1, which are: (10) (11) in, and They are the camera coordinate systems before and after the vertical axis 4 rotates. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (8), (10) and (11), we can calculate the distance between the optical center of camera 1 and the vertical axis 4. ,satisfy: (12) Among them, the distance between the optical center of the camera 1 and the vertical axis 4 Used to mark the installation position of camera 1, and further solve the camera coordinate system when the vertical axis 4 rotates With the axis coordinate system The coordinate transformation relationship between them.

[0028] Furthermore, the camera coordinate system obtained in Step 5 when the horizontal axis 3 rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the horizontal rotation axis 3 and the origin of the rotation axis coordinate system through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

[0029] Furthermore, the camera coordinate system obtained by solving the horizontal axis 3 rotation is With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (13) (14) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Axis coordinate system when horizontal axis 3 rotates origin exist The translation amount in the direction is , The translation amount in the direction is , then the translation matrix can be rewritten as: (15) in, It means that after the horizontal shaft 3 rotates, the cross beam 5 and The angle between the planes, Represents the horizontal axis 3 and the axis coordinate system The distance between the origins; When the horizontal axis 3 rotates, the axis coordinate system Will rotate accordingly, so the axis coordinate system before and after the horizontal axis 3 rotates and ,satisfy: (16) in, Represents the axis coordinate system before and after the horizontal axis 3 rotates and The coordinate transformation matrix between Since the camera coordinate system rotates along the horizontal axis 3 With the axis coordinate system Synchronously change, so the camera coordinate system The coordinate transformation matrix before and after rotation is The same; then the camera coordinate system before and after rotation , ,satisfy: (17) in, Represents the axis coordinate system before and after the horizontal axis 3 rotates and The rotation matrix between Represents the axis coordinate system before and after the horizontal axis 3 rotates and The translation matrix between When calibrating the horizontal axis 3, the horizontal axis 3 rotates and the cross beam 5 is aligned with the horizontal axis 3. Angle between planes It is known that, therefore, the checkerboard is fixed, and the camera 1 is used to collect the checkerboard image before and after the horizontal axis 3 rotates. Two different coordinate transformation matrices are obtained by calibration of the camera 1, which are: (18) (19) in, and They are the camera coordinate systems before and after the horizontal axis 3 rotates. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (17), (18) and (19), we can get: (20) Assume the camera coordinate system before the horizontal axis 3 rotation The origin position is , the rotated camera coordinate system The origin position is , perform the position conversion of the two coordinate systems and calculate: (twenty one) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, The axis coordinate system before and after the horizontal axis 3 rotates and The translation matrix between From equation (20), we can find the camera coordinate system before and after the horizontal axis 3 rotates: , The coordinate transformation matrix between ; From formula (21), find the horizontal axis 3 and the axis coordinate system The distance between the origins ; Then solve the camera coordinate system when the horizontal axis 3 rotates With the axis coordinate system The coordinate transformation relationship between them satisfies: (twenty two).

[0030] 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.

[0031] Furthermore, the size of the checkerboard used in the calibration process is 200mm×200mm, and the checkerboard is distributed with checkerboards of size 10mm×10mm. The checkerboard is moved multiple times to change its position and posture in the field of view of camera 1, and a series of calibration images are collected to calibrate camera 1.

[0032] Example 2 In another preferred embodiment, based on the above embodiment 1, a method for implementing a calibration method of a rotating structured light three-dimensional measurement system is as follows: Figure 5 As shown, the following steps are included: Step (1): Build a rotating structured light 3D measurement system. It is worth noting that Figure 2 As shown in FIG. 1 , the rotating structured light 3D measurement system is specifically composed of a camera 1, a laser 22, a horizontal axis 3, a vertical axis 4, a beam 5, and a base 6. The frame rate of the camera 1 is 30fps, the resolution is 1280×1024 pixels, and the focal length of the lens is 12mm; the laser 22 is a linear structured light laser 2, with a wavelength of 450nm, a power of 10mW, and a line width of ; A high-precision standard ball is used as the target to be measured.

[0033] After the installation is completed, when the rotating structured light 3D measurement system is used for measurement, the vertical axis 4 is rotated first, and the laser 22 is rotated along The axis scans the object to be measured; then the horizontal axis 3 rotates to change the crossbeam 5 and The angle between the planes; the rotating structured light 3D measurement system is again along The axis is scanned until the object is scanned.

[0034] Step (2): Camera 1 calibration.

[0035] Get the camera coordinate system With pixel coordinate system The coordinate transformation relationship between them; among them, the camera coordinate system With pixel coordinate system The coordinate transformation relationship between them satisfies: (1) in, represents the internal parameter matrix.

[0036] As a preferred embodiment of the present invention, the specific process of calibrating the camera 1 in step (2) can be described as follows: placing a checkerboard in the field of view of the camera 1, changing its position and posture, collecting a series of checkerboard images, and calculating the intrinsic parameter matrix and distortion parameters; The imaging model of camera 1 satisfies: (2) in, represents the scale factor, represents the focal length, Indicates the coordinates of the principal point of the image captured by camera 1, The corner points of the chessboard are in the camera coordinate system The three-dimensional coordinates of Represents the pixel coordinates of the corner points of the checkerboard.

[0037] It should be noted that the Zhang calibration method used in step (2) is combined with a high-precision checkerboard to calibrate the camera 1 (including the internal parameter matrix and distortion parameters (including radial distortion coefficient , And the tangential distortion parameters , ) calibration). In this process, the size of the checkerboard used is 200×200mm, and the size of the checkerboard is 10×10mm. During calibration, the checkerboard is moved multiple times to change its position and posture in the field of view of camera 1 (for example, 15 times), and a series of calibration images are collected to calibrate the imaging model of camera 1. According to the above imaging model formula of camera 1, the intrinsic parameter matrix of camera 1 is obtained. And distortion parameters, please refer to the following Table 1: Table 1

[0038] Step (3): Structural cursor positioning.

[0039] As a preferred embodiment of the present invention, the specific process of structural light determination in step (3) can be described as follows: Keep the rotating structured light 3D measurement system stationary so that the line structured light emitted by it is irradiated onto the checkerboard; change the posture of the checkerboard to acquire at least two images of the checkerboard; Use the grayscale centroid method to extract the pixel coordinates of the center line of the line structured light , calculate the center line of the line structured light in the camera coordinate system The coordinates below; According to the coordinates of each point, the camera coordinate system is fitted The light plane equation under the condition: The light plane equation satisfies: (3) Among them, A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is an arbitrary point on the plane, and D is the constant term in the plane equation, which is related to the distance of the plane relative to the origin.

[0040] Specifically, first, a checkerboard image is acquired, laser 2 is used to emit line structured light to illuminate the checkerboard, and camera 1 is used to acquire an image of the checkerboard. Then, the line structured light emitted by the rotating structured light 3D measurement system is illuminated onto the checkerboard and kept fixed, the posture of the checkerboard is changed, and the above steps are repeated to acquire an image of the checkerboard again, and finally at least two sets of images are obtained.

[0041] Then, the grayscale centroid method is used to extract the pixel coordinates of the center line of the line structured light, and the pixel coordinates of each point on the center line of the line structured light in the camera coordinate system are calculated. The light plane equation is fitted according to the coordinates of each point. The light plane equation is: .

[0042] Step (4): calibrate the vertical axis 4; Solve to get the camera coordinate system when the vertical axis 4 rotates With the axis coordinate system The coordinate transformation relationship between them.

[0043] As a preferred embodiment of the present invention, the camera coordinate system obtained by solving the vertical axis 4 when rotating in step (4) is With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: like Figure 3 As shown, in three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (4) (5) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Assume the camera coordinate system of The axis is parallel to the vertical axis 4, and the camera coordinate system of Plane and axis coordinate system of If the planes are in the same plane, the translation matrix can be rewritten as: (6) in, It means that after the vertical shaft 4 rotates, the cross beam 5 and The angle between the axes, represents the distance between the optical center of the camera 1 and the vertical rotation axis 4; The axis coordinate system The origin is defined in the camera coordinate system The origin is along If the displacement difference in the direction is 0, the translation matrix of the initial position is rewritten as: (7) Then the coordinate transformation relationship of camera 1 before and after rotation satisfies: (8) in, The camera coordinate system before and after the vertical axis 4 rotation , The coordinate transformation matrix between The camera coordinate system before and after the vertical axis 4 rotation , The rotation matrix between The camera coordinate system before and after the vertical axis 4 rotation , The translation matrix between Introducing the axis coordinate system After that, the total conversion relationship satisfies: (9) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the camera coordinate system With the axis coordinate system The translation matrix between is the camera coordinate system With the axis coordinate system The translation matrix between like Figure 3 As shown, when the vertical shaft 4 is calibrated, the cross beam 5 and the vertical shaft 4 rotate. Angle between axes It is known that, therefore, the checkerboard is fixed, and the camera 1 is used to collect the checkerboard image before and after the vertical axis 4 rotates. Two different coordinate transformation matrices are obtained by calibration of the camera 1, which are: (10) (11) in, and They are the camera coordinate systems before and after the vertical axis 4 rotates. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (8), (10) and (11), we can calculate the distance between the optical center of camera 1 and the vertical axis 4. ,satisfy: (12) Among them, the distance between the optical center of the camera 1 and the vertical axis 4 Used to mark the installation position of camera 1, and thus solve the camera coordinate system when the vertical axis 4 rotates With the axis coordinate system The coordinate transformation relationship between them.

[0044] It is worth noting that Figure 3 As shown, when calibrating the vertical axis 4, the checkerboard is first fixed, and the camera 1 is used to collect the checkerboard image before the vertical axis 4 rotates; then the vertical axis 4 is rotated (here, 2.5 degrees is selected), while ensuring that the checkerboard image is within the field of view of the camera 1. In this process, the posture of the checkerboard is always kept fixed, and then another checkerboard image is collected. From equations (10) and (11), the external parameter matrix of camera 1 before the vertical axis 4 rotates is: .

[0045] The external parameter matrix of camera 1 after the vertical axis 4 rotates is: .

[0046] From the above calculation process, we can get the coordinate system from the optical center of camera 1 to the rotation axis Distance from origin .

[0047] The rear beam 5 rotates with the vertical axis 4 Angle between axes Taking 10 degrees as an example, calculate the camera coordinate system With the axis coordinate system The coordinate transformation matrix is: .

[0048] Step (5): Calibrate the horizontal axis 3.

[0049] Solve to get the camera coordinate system when the horizontal axis 3 rotates With the axis coordinate system The coordinate transformation relationship between them.

[0050] As a preferred embodiment of the present invention, the camera coordinate system obtained by solving the horizontal axis 3 rotation in step (5) is With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: like Figure 4 As shown, in three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: (13) (14) in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Axis coordinate system when horizontal axis 3 rotates origin exist The translation amount in the direction is , The translation amount in the direction is , then the translation matrix can be rewritten as: (15) in, It means that after the horizontal shaft 3 rotates, the cross beam 5 and The angle between the planes, Represents the horizontal axis 3 and the axis coordinate system The distance between the origins; When the horizontal axis 3 rotates, the axis coordinate system Will rotate accordingly, so the axis coordinate system before and after the horizontal axis 3 rotates and ,satisfy: (16) in, Represents the axis coordinate system before and after the horizontal axis 3 rotates and The coordinate transformation matrix between Since the camera coordinate system rotates along the horizontal axis 3 With the axis coordinate system Synchronously change, so the camera coordinate system The coordinate transformation matrix before and after rotation is The same; then the camera coordinate system before and after rotation , ,satisfy: (17) in, Represents the axis coordinate system before and after the horizontal axis 3 rotates and The rotation matrix between Represents the axis coordinate system before and after the horizontal axis 3 rotates and The translation matrix between .

[0051] like Figure 4 As shown, when calibrating the horizontal axis 3, the horizontal axis 3 rotates and the cross beam 5 is aligned with the horizontal axis 3. Angle between planes It is known that, therefore, the checkerboard is fixed, and the camera 1 is used to collect the checkerboard image before and after the horizontal axis 3 rotates. Two different coordinate transformation matrices are obtained by calibration of the camera 1, which are: (18) (19) in, and They are the camera coordinate systems before and after the horizontal axis 3 rotates. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (17), (18) and (19), we can get: (20) Assume the camera coordinate system before the horizontal axis 3 rotation The origin position is , the rotated camera coordinate system The origin position is , perform the position conversion of the two coordinate systems and calculate: (twenty one) in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, The axis coordinate system before and after the horizontal axis 3 rotates and The translation matrix between From equation (20), we can find the camera coordinate system before and after the horizontal axis 3 rotates: , The coordinate transformation matrix between ; From formula (21), find the horizontal axis 3 and the axis coordinate system The distance between the origins ; Then solve the camera coordinate system when the horizontal axis 3 rotates With the axis coordinate system The coordinate transformation relationship between them satisfies: (twenty two).

[0052] It is worth noting that Figure 4 As shown, when calibrating the horizontal axis 3, the checkerboard is first fixed, and the camera 1 is used to capture the checkerboard image before the horizontal axis 3 rotates, and then the horizontal axis 3 is rotated (here, 5 degrees are selected), while ensuring that the checkerboard image is within the field of view of the camera 1. In this process, the posture of the checkerboard is always kept fixed, and then another checkerboard image is captured.

[0053] From equations (18) and (19), we can get the external parameter matrix of camera 1 before the horizontal axis 3 rotates: .

[0054] The external parameter matrix of camera 1 after the horizontal axis 3 rotates is: .

[0055] By combining equation (20) and equation (22), we can get the horizontal axis 3 and the axis coordinate system Distance from origin .

[0056] The rear beam 5 rotates with the horizontal axis 3 Angle between planes Taking 8 degrees as an example, calculate the camera coordinate system With the axis coordinate system The coordinate transformation matrix: .

[0057] Combining equations (1), (3), (12) and (22), we know that when the pixel coordinates of the line structured light are When the corresponding axis coordinate system The coordinates below are When the line structured light rotates and scans the object to be measured, the three-dimensional coordinates of the entire surface of the target can be obtained.

[0058] Thus, the calibration method of the rotating structured light three-dimensional measurement system provided by the present invention realizes the three-dimensional measurement of the measured target, and has a vertical rotation axis 4 and a horizontal rotation axis 3, and its measurement range is expanded, which can realize the effective measurement of large-size objects; the calibration method of the rotating structured light three-dimensional measurement system of the present invention not only expands the measurement range and improves the measurement accuracy, but also avoids the influence of the system installation error on the calibration accuracy through precise rotation axis calibration, and has significant technical progress and practical value.

[0059] In the preferred solution, the specific process of structured light measurement in Step 3 includes: keeping the rotating structured light 3D measurement system stationary so that the line structured light it emits is irradiated onto the checkerboard, changing the posture of the checkerboard, collecting at least two checkerboard images, and using the grayscale centroid method to extract the pixel coordinates of the center line of the line structured light to obtain the light plane equation; the above settings ensure that after each posture adjustment, the system can accurately capture the changes in the light spot, and then fit all pixel coordinate points through the least squares method, optimize and solve the light plane model that best fits the actual scene, and provide a solid foundation for subsequent 3D reconstruction.

[0060] In the preferred solution, the camera coordinate system obtained in Step 4 when the vertical axis rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix to calculate the distance between the optical center of the camera 1 and the vertical axis 4 through a set of simultaneous equations, and further solving the coordinate transformation relationship; the above settings ensure that the camera can accurately convert the captured image information into a unified axis coordinate system at different rotation angles, providing a solid foundation for subsequent image processing and data analysis.

[0061] In the preferred solution, the camera coordinate system obtained in Step 5 when the horizontal axis rotates is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the horizontal axis 3 and the origin of the axis coordinate system through a set of simultaneous equations, and further solving the coordinate transformation relationship; the above settings, combined with real-time sensor data, ensure the conversion accuracy; in software implementation, an efficient matrix operation library is used to optimize the calculation efficiency, and an error detection mechanism is introduced to ensure the accuracy and robustness of the coordinate transformation.

[0062] In the preferred solution, the camera uses a lens with a frame rate of 30fps and a resolution of 1280×1024 pixels, and the laser uses a line structured light laser with a wavelength of 450nm, a power of 10mW, and a line width of a preset value; the above settings can ensure that clear and high-precision image data is obtained during the scanning process; at the same time, in combination with a high-performance data processing unit, it realizes the rapid capture and accurate analysis of three-dimensional spatial information, meeting the high-precision measurement requirements in complex environments.

[0063] In the preferred solution, the size of the checkerboard used in the calibration process is 200mm×200mm, and the checkerboard is distributed with checkerboards of size 10mm×10mm. The checkerboard is moved multiple times to change its position and posture in the field of view of camera 1, and a series of calibration images are collected to calibrate camera 1. The above settings ensure the accuracy and stability of the calibration process. In addition, the high-precision algorithm is used to process these calibration images, which further improves the accuracy of solving the internal and external parameters of camera 1, laying a solid foundation for subsequent three-dimensional reconstruction and visual measurement.

[0064] In summary, the present invention provides a calibration method for a rotating structured light three-dimensional measurement system, which solves the key problems in the technical field of quantitative detection of defects of hydro-turbine generator sets in the prior art, especially the limitations of the existing rotating structured light three-dimensional measurement system in the process of measuring large-size targets, such as limited measurement range and influence of system adjustment error on calibration accuracy. By adopting an innovative calibration method for a rotating structured light three-dimensional measurement system, the shortcomings of the prior art are overcome, the effective measurement of large-size objects is achieved, and the measurement accuracy is significantly improved. The present invention introduces a vertical rotation axis and a horizontal rotation axis to achieve a dual-axis rotation function of the measurement system, thereby significantly expanding the measurement range, so that it can more effectively measure large-size objects. The present invention accurately calculates the installation position between the camera and the rotation axis by accurately calibrating the vertical rotation axis and the horizontal rotation axis, thereby avoiding the influence of the system adjustment error on the calibration accuracy. This precise calibration method is not available in traditional methods. The present invention not only includes camera calibration and structured light calibration, but also describes in detail the calibration process of the vertical rotation axis and the horizontal rotation axis, forming a comprehensive system calibration process. This comprehensive calibration process helps to improve the overall measurement accuracy of the system; the present invention introduces the axis coordinate system and uses the rotation matrix and translation matrix to innovatively solve the coordinate transformation relationship between the camera coordinate system and the axis coordinate system, which improves the accuracy and reliability of coordinate transformation; the present invention aims at the actual needs of quantitative detection of defects in hydro-turbine generator set equipment, improves the measurement accuracy and efficiency by optimizing the structure and calibration method of the measurement system, and demonstrates the creativity of applying advanced technology to practical engineering problems; the present invention shows high novelty and creativity in both the structural design and calibration method of the rotating structured light three-dimensional measurement system, and provides a new technical means for quantitative detection of defects in hydro-turbine generator set equipment; the present invention realizes high-precision and rapid calibration of the three-dimensional measurement system, and effectively improves the accuracy and stability of three-dimensional reconstruction by calibrating the camera 1, the structured light plane, and the vertical and horizontal axes 3 in steps, providing reliable technical support for the fields of industrial automation detection, reverse engineering, etc.; in addition, the modular design of the present invention is easy to maintain and upgrade, adapts to the needs of different detection scenarios, shows good flexibility and scalability, and injects new vitality into the sustainable development of the industrial measurement field.

Claims

1. A method for calibrating a rotating structured light three-dimensional measurement system, characterized in that: The method comprises the following steps: Step 1: construct a rotating structured light three-dimensional measurement system, the system comprising a camera (1), a laser (2), a horizontal rotation axis (3), a vertical rotation axis (4), a beam (5) and a base (6); Step 2: Calibrate the camera (1) to obtain the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system, where the coordinate transformation relationship between the camera coordinate system and the pixel coordinate system is described by the intrinsic parameter matrix; Step 3: Perform structured light calibration to obtain the light plane equation in the camera coordinate system; Step 4: Calibrate the vertical rotation axis (4). By changing the position of the vertical rotation axis (4) and collecting images, the coordinate transformation relationship between the camera coordinate system and the rotation axis coordinate system when the vertical rotation axis (4) rotates is obtained. Step 5: Calibrate the horizontal rotation axis (3). By changing the position of the horizontal rotation axis (3) and collecting images, the coordinate transformation relationship between the camera coordinate system and the rotation axis coordinate system when the horizontal rotation axis (3) rotates is obtained.

2. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 1, characterized in that: In Step 2, the 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: （1） in, represents the internal parameter matrix.

3. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 2, characterized in that: The specific process of calibrating the camera (1) in Step 2 includes: placing a checkerboard in the field of view of the camera (1), changing its position and posture, collecting a series of checkerboard images, and obtaining an internal parameter matrix and distortion parameters by calculation, wherein the imaging model of the camera (1) satisfies a preset formula relationship: （2） in, represents the scale factor, represents the focal length, represents the coordinates of the principal point of the image captured by camera (1), The corner points of the chessboard are in the camera coordinate system The three-dimensional coordinates of Represents the pixel coordinates of the corner points of the checkerboard.

4. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 3, characterized in that: The specific process of structured light measurement in Step 3 includes: keeping the rotating structured light 3D measurement system stationary, irradiating the line structured light emitted by it onto the checkerboard, changing the posture of the checkerboard, collecting at least two checkerboard images, extracting the pixel coordinates of the center line of the line structured light by using the grayscale centroid method, and obtaining the light plane equation.

5. The method for calibrating a rotational structured light 3D measurement system according to claim 4, characterized in that: The pixel coordinates of the center line of the line structured light extracted by using the grayscale centroid method are: , calculate the center line of the line structured light in the camera coordinate system According to the coordinates of each point, the camera coordinate system is fitted The light plane equation satisfies: （3） Among them, A, B, and C are the components of the light plane normal vector on each coordinate axis, (x, y, z) is an arbitrary point on the plane, and D is the constant term in the plane equation, which is related to the distance of the plane relative to the origin.

6. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 5, characterized in that: The camera coordinate system obtained by solving the vertical axis (4) rotation in Step 4 is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the optical center of the camera (1) and the vertical rotation axis (4) through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

7. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 6, characterized in that: The solution obtains the camera coordinate system when the vertical axis (4) rotates With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: （4） （5） in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Assume the camera coordinate system of The axis is parallel to the vertical axis (4), and the camera coordinate system of Plane and axis coordinate system of If the planes are in the same plane, the translation matrix can be rewritten as: （6） in, It indicates that the cross beam (5) and the vertical shaft (4) rotate after rotation. The angle between the axes, represents the distance between the optical center of the camera (1) and the vertical rotation axis (4); The axis coordinate system The origin is defined in the camera coordinate system The origin is along If the displacement difference in the direction is 0, the translation matrix of the initial position is rewritten as: （7） Then the coordinate transformation relationship of the camera (1) before and after rotation satisfies: （8） in, The camera coordinate system before and after rotation about the vertical axis (4) , The coordinate transformation matrix between The camera coordinate system before and after rotation about the vertical axis (4) , The rotation matrix between The camera coordinate system before and after rotation about the vertical axis (4) , The translation matrix between Introducing the axis coordinate system After that, the total conversion relationship satisfies: （9） in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the camera coordinate system With the axis coordinate system The translation matrix between is the camera coordinate system With the axis coordinate system The translation matrix between When calibrating the vertical shaft (4), the cross beam (5) and the vertical shaft (4) rotate. Angle between axes It is known that, therefore, the checkerboard is fixed, and the checkerboard image is collected by camera (1) before and after the vertical axis (4) is rotated. Two different coordinate transformation matrices are obtained by calibration of camera (1), which are: （10） （11） in, and They are the camera coordinate systems before and after the vertical axis (4) is rotated. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (8), (10) and (11), we can calculate the distance between the optical center of the camera (1) and the vertical axis (4): ,satisfy: （12） The distance between the optical center of the camera (1) and the vertical axis (4) is It is used to mark the installation position of the camera (1), and further solve the camera coordinate system when the vertical axis (4) rotates. With the axis coordinate system The coordinate transformation relationship between them.

8. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 7, characterized in that: The camera coordinate system obtained by solving the horizontal axis (3) rotation in Step 5 is With the axis coordinate system The specific process of the coordinate transformation relationship between them includes: using the rotation matrix and the translation matrix, calculating the distance between the horizontal axis (3) and the origin of the axis coordinate system through a set of simultaneous equations, and further solving to obtain the coordinate transformation relationship.

9. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 8, characterized in that: The solution obtains the camera coordinate system when the horizontal axis (3) rotates With the axis coordinate system The specific process of coordinate transformation relationship between can be described as: In three-dimensional space, the coordinate system is along The rotation matrix when the axis rotates and the translation matrix when the coordinate system translates as a whole satisfy: （13） （14） in, Indicates the angle of rotation of the coordinate system around the y-axis in three-dimensional space; Axis coordinate system when the horizontal axis (3) rotates origin exist The translation amount in the direction is , The translation amount in the direction is , then the translation matrix can be rewritten as: （15） in, It indicates that after the horizontal shaft (3) rotates, the crossbeam (5) and The angle between the planes, Represents the horizontal axis (3) and the axis coordinate system The distance between the origins; As the horizontal axis (3) rotates, the axis coordinate system will rotate accordingly, so the axis coordinate system before and after the horizontal axis (3) rotates and ,satisfy: （16） in, Represents the axis coordinate system before and after the horizontal axis (3) rotates and The coordinate transformation matrix between Since the camera coordinate system rotates along the horizontal axis (3) With the axis coordinate system Synchronously change, so the camera coordinate system The coordinate transformation matrix before and after rotation is The same; then the camera coordinate system before and after rotation , ,satisfy: （17） in, Represents the axis coordinate system before and after the horizontal axis (3) rotates and The rotation matrix between Represents the axis coordinate system before and after the horizontal axis (3) rotates and The translation matrix between When calibrating the horizontal shaft (3), the horizontal shaft (3) rotates and the cross beam (5) is aligned with the horizontal shaft (3). Angle between planes It is known that, therefore, the checkerboard is fixed, and the checkerboard image is collected by camera (1) before and after the horizontal axis (3) is rotated. Two different coordinate transformation matrices are obtained by calibration of camera (1), which are: （18） （19） in, and They are the camera coordinate systems before and after the horizontal axis (3) is rotated. , Relative to the world coordinate system The coordinate transformation matrix of Combining equations (17), (18) and (19), we can get: （20） Assume the camera coordinate system before the horizontal axis (3) rotation The origin position is , the rotated camera coordinate system The origin position is , perform the position conversion of the two coordinate systems and calculate: （21） in, The axis coordinate system Around Axis rotation The rotation matrix of the angle, is the axis coordinate system before and after the horizontal axis (3) rotates and The translation matrix between From equation (20), we can find the camera coordinate system before and after the horizontal axis (3) is rotated: , The coordinate transformation matrix between ; From formula (21), find the horizontal axis (3) and the axis coordinate system The distance between the origins ; Then solve the camera coordinate system when the horizontal axis (3) rotates With the axis coordinate system The coordinate transformation relationship between them satisfies: （22）。 10. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 9, characterized in that: 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.

11. The method for calibrating a rotational structured light three-dimensional measurement system according to claim 10, characterized in that: The size of the checkerboard used in the calibration process is 200 mm×200 mm, and checkerboards of size 10 mm×10 mm are distributed on the checkerboard. The position and posture 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 to calibrate the camera (1).

Images