An automated in-situ measurement and calibration method and system for thin-walled rotating workpieces

Abstract

This invention discloses an automated in-situ measurement and calibration method for thin-walled rotating workpieces. The method includes: constructing a reference coordinate system in the robot's machining space; acquiring a point cloud model of the turntable in the scanner coordinate system to construct a corresponding turntable coordinate system; establishing transformation relationships between multiple coordinate systems, including all reference coordinate systems and the turntable coordinate system; determining the calibration range of the shot peening gun using two singular configuration points of the robot; using the point deviation between corresponding points in the workpiece's point cloud data and the reference point cloud data as the calibration quantity for each point on the workpiece; generating a normal vector for each point on the workpiece's generatrix based on the workpiece's point cloud data; and generating the machining path of the shot peening gun based on the obtained point cloud data, the corresponding calibration quantity, and the normal vector to complete the calibration task. This invention also provides an automated in-situ measurement and calibration system. The method provided by this invention can solve the problem of robots being unable to reach specific positions due to singular configurations.

Description

Technical Field

[0001] This invention belongs to the field of intelligent manufacturing technology, and in particular relates to an automated in-situ measurement and calibration method and system for thin-walled rotating workpieces. Background Technology

[0002] In aerospace, automotive, and machining industries, thin-walled metal rotating parts are indispensable components, such as rocket propellant tanks and automobile wheel hubs. During the forming process, these parts often experience roundness deformation due to factors such as complex structural shapes, numerous thin-walled sections, low rigidity, and uneven heating and cooling during heat treatment. This severely impacts the quality of the parts, reducing their pressure resistance and performance. Therefore, it is essential to correct deformed parts to ensure product performance indicators, appearance quality, and improve stability and safety. However, before correcting a workpiece, the location of the correction point and the amount of deformation at that location must be known. This requires three-dimensional morphological measurement of the workpiece followed by correction processing. However, current methods for measuring and correcting rotating workpieces still have some limitations.

[0003] Patent document CN115585750A discloses an automated wheel rim roundness detection system and method. First, a device consisting of a wheel hub clamping turntable and a laser lifting slide is constructed, and the external parameters of the measurement system are calibrated using a laser tracker. Second, the position of the laser line is changed according to the slide to achieve multiple segmented measurements of the wheel rim. Based on mechanical constraints, the data from these multiple measurements are stitched together to obtain a complete wheel rim measurement point cloud model. The three-dimensional point cloud data of the measured wheel rim is then converted from the measurement coordinate system to the turntable coordinate system based on the external calibration results. Finally, an improved ICP algorithm based on k-dtree is used to match the measurement model with the CAD model. The wheel rim roundness deformation is calculated based on the matching results, thereby achieving the detection of wheel rim roundness.

[0004] Patent document CN117324751A discloses a composite shaping method and system based on laser and ultrasonic shot peening technology. The method includes: S1: heating the part of the target component to be shaped to a preset temperature using a laser heating device; S2: using a preset configuration as the shaping target, impact shaping the part to be shaped at the preset temperature using an ultrasonic shot peening device; S3: acquiring the real-time deformation and real-time temperature of the part to be shaped during the impact shaping process; S4: retrieving corresponding process parameters from a process parameter library based on the real-time deformation and real-time temperature; S5: adjusting the position and moving speed of the ultrasonic shot peening device and the laser heating device according to the retrieved process parameters; S6: determining whether the part to be shaped to the preset configuration. If yes, the shaping is completed; otherwise, returning to step S3.

[0005] Existing 3D scanning solutions suffer from complex platform structures, cumbersome scanning processes, low levels of automation, and some platforms require multiple scans of the workpiece followed by data stitching, resulting in low efficiency. Summary of the Invention

[0006] The purpose of this invention is to provide an automated in-situ measurement and alignment method and system for thin-walled rotating workpieces. This method can solve the problem that robots cannot reach specific positions due to unusual configurations, thereby improving alignment efficiency and enabling alignment programmability.

[0007] To achieve the first objective of this invention, the following technical solution is provided: an automated in-situ measurement and calibration method for a thin-walled rotating workpiece, wherein the thin-walled rotating workpiece is placed on a turntable, and the automated in-situ measurement and calibration method includes the following steps:

[0008] Construct a reference coordinate system in the robot processing space. The reference coordinate system includes a robot base coordinate system with the center of the robot base as the origin, a robot end flange coordinate system with the center of the robot end as the origin, a shot peening gun tool coordinate system with the geometric center of the shot peening gun surface as the origin when the robot end is equipped with a shot peening gun, and a three-dimensional scanner coordinate system when the robot end is equipped with a three-dimensional scanner.

[0009] Obtain the point cloud model of the turntable in the scanner coordinate system to construct the corresponding turntable coordinate system;

[0010] For all reference coordinate systems and the turntable coordinate system, establish transformation relationships between multiple coordinate systems;

[0011] By having the robot drive the shot peening gun to contact the surface contour of the turntable, two singular configuration points of the robot are determined, and the correction range of the shot peening gun is determined in the turntable coordinate system corresponding to the two singular configuration points.

[0012] The robot drives a 3D scanner to acquire point cloud data of the thin-walled rotating workpiece on the turntable in the turntable coordinate system. The point cloud data is then registered with the reference point cloud data of the qualified workpiece. The point deviation between the corresponding points of the point cloud data and the reference point cloud data is used as the shape correction quantity corresponding to each point on the thin-walled rotating workpiece.

[0013] Based on the point cloud data of the thin-walled rotating workpiece, the generatrix equation of the thin-walled rotating workpiece is solved in the turntable coordinate system to obtain the normal vector of each point on the generatrix.

[0014] Based on the obtained point cloud data and the corresponding quantities to be calibrated and normal vectors, a processing path for the shot peening gun within the calibration range is generated to complete the calibration task.

[0015] This invention performs two stages of coarse and fine registration on the point cloud data of the workpiece, and simultaneously introduces the normal vector of each point in the workpiece to adjust the fixed angle describing the attitude of the shot peening gun, thereby ensuring that the shot peening pin is always vertically aligned with the calibration point.

[0016] Specifically, the shot peening gun coordinate system is generated by calibration using a six-point method based on the robot base coordinate system.

[0017] Specifically, the transformation relationship between the 3D scanner coordinate system and the robot end flange coordinate system is established as follows:

[0018] The target ball is scanned by a 3D scanner carried by the robot end effector during axial movement to obtain the rotation matrix between the 3D scanner and the robot end effector flange.

[0019] The tracking device located on one side of the robot is used as a relay coordinate system to obtain the translation vector corresponding to the 3D scanner and the end flange of the robot.

[0020] The corresponding transformation relationship is constructed based on the rotation matrix and translation vector.

[0021] Specifically, the process of constructing the turntable coordinate system is as follows:

[0022] By obtaining n points on the circumference of the turntable's point cloud model and substituting them into the preset center equation, the corresponding center coordinates are solved using the least squares method. The center coordinates are then used as the origin to construct the coordinate system.

[0023] Specifically, the expression for the transformation relationship is as follows:

[0024]

[0025] in, S O A This represents the coordinates of the origin in the turntable coordinate system. This represents the unit vector along the x-axis in the turntable coordinate system. This represents the unit vector along the y-axis in the turntable coordinate system. This represents the unit vector of the z-axis in the turntable coordinate system.

[0026] Specifically, the process for obtaining the calibration range is as follows:

[0027] The robot drives the shot peening gun to make the origin of the shot peening gun tool coordinate system contact the contour of the turntable surface, so as to obtain the Cartesian coordinates when it is at two singular configuration points in the turntable coordinate system, and then convert the Cartesian coordinates into the corresponding cylindrical coordinates.

[0028] The angle parameters in the two cylindrical coordinate systems are subtracted to obtain the corresponding angle range, which is then used as the calibration range.

[0029] Specifically, the expression for converting Cartesian coordinates to cylindrical coordinates is as follows:

[0030] P n =(ρ n ,θ n ,z n )in, θ n =atan2(x i ,y i ), z n =z i ;

[0031] Among them, (x i ,y i ,z i ) represents Cartesian coordinates, (ρ) n ,θ n ,z n ) represents cylindrical coordinates.

[0032] In both cylindrical coordinate system representation and Cartesian representation, the z component remains constant, representing the coordinate value along the central axis of the workpiece.

[0033] To achieve the second objective of this invention, the following technical solution is provided: an automated in-situ measurement and calibration system, which is implemented by the above-mentioned automated in-situ measurement and calibration method for thin-walled rotating workpieces, comprising an industrial control computer module, a workpiece placement module, a three-dimensional shape scanning module, and a calibration processing module.

[0034] The industrial control computer module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and to control the robot to complete the processing task according to the generated processing path.

[0035] The workpiece placement module is used to place the thin-walled rotating workpiece to be corrected;

[0036] The three-dimensional topography scanning module is used to acquire point cloud data of thin-walled rotating workpieces;

[0037] The calibration and machining module calibrates the initial machining path based on the acquired point cloud data and reference point cloud data, so as to output the optimal machining path to the industrial control computer module.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0039] The ICP registration algorithm based on the PCA algorithm completes point cloud registration and can output the shape to be corrected, which greatly reduces the registration time and improves the registration efficiency and accuracy.

[0040] By solving the generatrix equation of the workpiece in the turntable coordinate system, the normal vector of each point on the generatrix is ​​obtained. By adjusting the fixed angle describing the attitude of the shot peening gun, the x-axis of the shot peening gun coordinate system is kept parallel to and opposite to the normal vector, ensuring that the shot peening pin is always vertically aligned with the alignment point. Attached Figure Description

[0041] Figure 1 This is a flowchart of the automated in-situ measurement and calibration method for thin-walled rotating workpieces provided in this embodiment;

[0042] Figure 2 This is a schematic diagram of the automated in-situ measurement and calibration method for thin-walled rotating workpieces provided in this embodiment;

[0043] Figure 3 This is a schematic diagram of solving the rotation matrix provided in this embodiment;

[0044] Figure 4 This is a schematic diagram illustrating the solution of the translation vector provided in this embodiment;

[0045] Figure 5 This is a schematic diagram of the turntable calibration provided in this embodiment;

[0046] Figure 6 This is a framework diagram of the automated in-situ measurement and calibration system provided in this embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0048] like Figure 1 The figure shows the automated in-situ measurement and calibration method for thin-walled rotating workpieces provided in this embodiment. The specific steps are as follows:

[0049] A reference coordinate system is constructed in the robot processing space. The reference coordinate system includes a robot base coordinate system with the center of the robot base as the origin, a robot end flange coordinate system with the center of the robot end as the origin, a shot peening gun tool coordinate system with the geometric center of the shot peening gun surface as the origin when the robot end is equipped with a shot peening gun, and a 3D scanner coordinate system when the robot end is equipped with a 3D scanner.

[0050] More specifically, based on the 3D model of the handheld 3D scanner device and the characteristics of the 3D scanner surface, a gripper for securing the handheld 3D scanner device to the end of a robot is designed.

[0051] like Figure 2 As shown, the six-point method in the robot system is first used to calibrate the coordinate system {F} of the shot peening gun center. The calibration result is...

[0052] Based on the robot's axial movement and with the aid of a Leica tracker, the transformation relationship between the 3D scanner coordinate system {S} and the robot's end flange coordinate system {Tool} is solved.

[0053] like Figure 3 The diagram illustrates the rotation matrix calibration process provided in this embodiment. {B} represents the robot base coordinate system, {Tool} represents the robot end-effector coordinate system, and {S} represents the scanner coordinate system. In the robot end-effector coordinate system, the scanner is moved along the coordinate axis -x... Tool , -y Tool -z Tool The target ball is moved in the direction of [tool], and the coordinates of the center point (TCP) of {Tool} are recorded at different positions using a scanner. The motion matrix of TCP in the robot's base coordinate system {B} is then fitted using these coordinates.

[0054] B H=[λ1,λ2,λ3] (1)

[0055] Where λ1, λ2, and λ3 are the unit translation vectors of TCP in {B}. Based on relative motion, TCP moves along the negative direction of the coordinate axis of {Tool}, which can be considered as the target ball moving along the positive direction of the coordinate axis of {Tool}. Therefore:

[0056]

[0057] The coordinates of the center of the target sphere are obtained by fitting the point cloud surface of the scanned standard target sphere, and the motion matrix of the target sphere in {S} is obtained as follows:

[0058] S H=[β1,β2,β3] (3)

[0059] Where β1, β2, and β3 are the unit translation vectors of the sphere's center in {S}. Let... To obtain the required rotation matrix for hand-eye calibration, we have:

[0060]

[0061] Combining (2), (3), and (4), we get

[0062]

[0063] Obtain the point cloud model of the turntable in the scanner coordinate system to construct the corresponding turntable coordinate system.

[0064] like Figure 4 The diagram illustrates the process of solving the translation vector in this embodiment. The coordinate system {L} is the coordinate system of the Leica tracker. First, the tracker measures the target ball at three positions, obtaining three coordinates in {L}. L P1 = (x1, y1, z1), L P2 = (x2, y2, z2) L P3 = (x3, y3, z3). The coordinates of the three spheres in the robot's base coordinate system {B} are measured using the shot peening center point at the robot's end effector. B P1 = (a1, b1, c1), B P2 = (a2, b2, c2) B P3 = (a3, b3, c3). A coordinate system can be established using vector methods for these three points, defined as {M}. With P1 as the origin of {M}, the formula is used:

[0065]

[0066] Therefore, the transformation matrix between {M} and {L} is:

[0067]

[0068] Similarly, from the formula:

[0069]

[0070] The transformation matrix between {M} and {B} can be obtained as follows:

[0071]

[0072] Then from the formula Obtain the transformation matrix with {B}.

[0073] Furthermore, the transformation relationship between {B} and {Tool} can be derived from the robot's forward kinematics. Therefore, the conversion relationship between {L} and {Tool} is as follows:

[0074] Replace the shot peening gun at the robot's end effector with a 3D scanner, and simultaneously use a Leica tracker and the 3D scanner to measure a target ball at the same location, obtaining the target ball's coordinates in the Leica tracker's coordinate system {L}. L P4 = (x4, y4, z4), the coordinates of P4 in the scanner coordinate system {S} S P4 = (a4, b4, c4).

[0075] From the formula:

[0076]

[0077] The coordinates of the target ball in the tool coordinate system {Tool} can be obtained.

[0078] Then from the formula:

[0079]

[0080] By combining the formulas, we can obtain

[0081] This completes the conversion relationship between {B} and {S}. Solve for it.

[0082] From (5) and (11), we can obtain the hand-eye matrix:

[0083]

[0084] Furthermore, the relationship between the robot's base coordinate system {B} and {Tool} can be obtained from the robot's kinematics. Therefore, the transformation relationship between {B} and {S} is:

[0085] Obtain the point cloud model of the turntable in the scanner coordinate system to construct the corresponding turntable coordinate system. For all reference coordinate systems and the turntable coordinate system, construct the transformation relationship between multiple coordinate systems.

[0086] More specifically, such as Figure 5 The diagram illustrates the calibration process of the turntable coordinate system provided in this embodiment. To establish the turntable coordinate system {A}, it is necessary to determine the center of the turntable. First, the turntable is scanned with a scanner to obtain a point cloud model of the turntable in the scanner coordinate system. Then, n points P on the circumference of the turntable are selected. n =(x n ,y n ,z n Let the coordinates of the center of the circle be... S O A= (x0, y0, z0), with the formula:

[0087] (x-x0) 2 +(y-y0) 2 +(z-z0) 2 =r 2 (13)

[0088] Substituting the n points into (13), the coordinates of the center of the circle can be obtained from the matrix form of the least squares method. S O A =(x0,y0,z0), with S Let OA be the origin of the turntable coordinate system {A}, and take a point on the plane on the circumference of the turntable. S O1 = (x1, y1, z1), take a point on the axis of rotation. S O2 = (x2, y2, z2), and based on these three points, establish the coordinate system {A} of the turntable coordinate system. These are the unit vectors along the three coordinate axes of {A}. From the vector method formula, we can obtain:

[0089]

[0090] Therefore, the transformation relationship between {S} and {A} is:

[0091]

[0092] Through the above steps, we can obtain the key coordinate systems in the entire measurement-calibration system, which are the robot base coordinate system {B}, the 3D scanner coordinate system {S}, the shot peening gun coordinate system {F}, and the turntable coordinate system {A}. We also obtain the transformation relationships between these coordinate systems, which enables the conversion of the scanner's measurement data.

[0093] By having the robot drive the shot peening gun to contact the surface contour of the turntable, two singular configuration points of the robot are determined, and the calibration range of the shot peening gun is determined in the turntable coordinate system corresponding to the two singular configuration points.

[0094] The shot peening gun's center contacts the contour of the turntable surface, and the shot peening gun moves along the contour of the turntable. When the shot peening gun reaches... B Q1 point and B At point Q2, the robot is unable to continue moving due to a singular configuration. Transform these two points into the turntable coordinate system {A} as follows: A Q1 = (x1, y1, z1), A Q2 = (x2, y2, z2), then convert from Cartesian coordinates to cylindrical coordinates. A Q1 = (ρ1, θ1, z1), AQ2 = (ρ2, θ2, z2), and the robot's calibration range is α = θ2 - θ1. To make angle calculation convenient and intuitive, in the calibration of the S300 turntable coordinate system {A}, the following is used... A Q1 = (x1, y1, z1) Replace S The x-axis of {A} is determined by O1 = (x1, y1, z1). therefore A The Cartesian coordinates of Q1 = (x1, y1, z1) in {A} A Q1 = (ρ1, θ1, z1) has θ1 = 0. Therefore, the robot's calibration range is α = θ2.

[0095] The expression for converting Cartesian coordinates to cylindrical coordinates is as follows:

[0096] P n =(ρ n ,θ n ,z n )in, θ n =atan2(x i ,y i ), z n =z i .

[0097] A robot drives a 3D scanner to acquire point cloud data of a thin-walled rotating workpiece on a turntable in the turntable coordinate system. The point cloud data is then registered with the reference point cloud data of a qualified workpiece. The point deviation between the corresponding points of the point cloud data and the reference point cloud data is used as the calibration quantity for each point on the thin-walled rotating workpiece.

[0098] More specifically, the above calibration can obtain the point cloud data of the rotating workpiece in the turntable coordinate system obtained by the scanner, perform point cloud registration between the source point cloud of the workpiece and the target point cloud of the qualified workpiece, and obtain the deviation between each point in the source point cloud and the corresponding point in the target point cloud. This deviation is the amount to be corrected for that point.

[0099] Point cloud registration is divided into two stages: coarse registration and fine registration. The purpose of coarse registration is to provide good initial conditions for fine registration when the initial positions of the two point clouds are poor. In coarse registration, the PCA algorithm can quickly find the rotation axis of the rotating workpiece, and then the rotation axes of the two point clouds are aligned to quickly complete the coarse registration. Based on this, ICP fine registration is performed. Let the source point cloud P = {P1, P2, P3, ... P...} n}, the target point cloud Q = {q1,q2,q3,…q} n In this process, an optimal transformation matrix is ​​obtained. Make the objective function Registration is completed at the minimum.

[0100] The point cloud registration process is as follows:

[0101] 1. Determine the principal axis direction U of the source point cloud. P The principal axis direction U of the target point cloud Q ;

[0102] 2. Align the principal axes of the two point clouds to complete the coarse registration of the point clouds and obtain the transformation matrix of the coarse registration. Applying R1 and t1 to the source point cloud yields P. i =R1·P i +t1.

[0103] 3. Set ICP registration parameters, including the distance threshold d between corresponding points within different curvature ranges. max Maximum number of iterations K, average distance For points with greater curvature, set a smaller distance threshold;

[0104] 4. For each point P in the source point cloud i First, calculate the curvature of each point, then perform a traversal search in the target point cloud to find the nearest corresponding point Q. i ;

[0105] 5. Calculate the transformation matrix Make the error function Minimum;

[0106] 6. Calculate P i With corresponding point Q i The average distance d;

[0107] 7. If d is less than the given value If the number of iterations exceeds the preset maximum number of iterations K, then stop the iteration calculation. Otherwise, return to step 4 until the convergence condition is met. The optimal registration transformation matrix is ​​obtained.

[0108] Based on the obtained Point P in the source point cloud i Corresponding point Q of the target point cloud i There is a deviation value:

[0109] Δ i =(R k P i +t k )-Q i (19)

[0110] Deviation value Δ i This refers to the quantity to be calibrated, which provides guidance for the calibration of the shot peening gun.

[0111] More specifically, in the turntable coordinate system, for any point to be corrected, its Cartesian coordinate representation is... A P i =(x i ,y i ,z i Transformation into cylindrical coordinate system representation A P n =(ρ n ,θ n ,z n ), where θ n =atan2(x i ,y i ), compare θ n With respect to the magnitude of α, if θ n If θ < α, then the correction point is within the correction range, and the robot only needs to be controlled to identify the position of the point; if θ < α, then the correction point is within the correction range. n If the value is greater than α, then the turntable needs to be rotated by at least θ. n -α is used to ensure that the correction point is within the correction range, and then the robot is controlled to identify the position of the point.

[0112] Based on the point cloud data of the thin-walled rotating workpiece, the generatrix equation of the thin-walled rotating workpiece is solved in the turntable coordinate system to obtain the normal vector of each point on the generatrix.

[0113] More specifically, in this embodiment, the three coordinate axes of the shot peening gun's central coordinate system {F} are collinear with and in the same direction as the three coordinate axes of the robot's base coordinate system. The z-axis of {F} and {A} are also collinear and in the same direction. Therefore, when adjusting the shot peening gun's attitude for calibration, only the x-axis of the shot peening gun is adjusted. F The axis should coincide with the normal vector of the point cloud, but in the opposite direction. Therefore, to achieve this, the normal vector of the point cloud needs to be calculated. First, in the turntable coordinate system, the equation of the generatrix of the workpiece surface is obtained. Then, the normal vector of each point on the generatrix can be obtained from the generatrix equation. Finally, the normal vector is transformed into the robot base coordinate system. When the robot is in its initial position, the axes of the shot peening gun coordinate system coincide with and are in the same direction as the axes of the robot's base coordinate system. To ensure the x-axis of the shot peening gun... F shaft and Coincident and opposite directions, calculate the axis of rotation and the rotation angle. Initial x F axis The target vector is The axis of rotation is:

[0114]

[0115] The rotation angle is:

[0116]

[0117] Therefore, the rotation matrix can be obtained from the rotation axis and rotation angle:

[0118] R=I+sin(θ)+(1-cos(θ))K 2

[0119] Where I is the identity matrix and K is the antisymmetric matrix of the rotation axis. Finally, the rotation matrix R represents the rotation of the shot peening gun coordinate system relative to the base coordinate system, satisfying the conditions. The fixed angle of the shot peening gun about the base coordinate system can then be calculated from R. in For the z B The rotation angle of the axis, φ, is about the y-axis. B The rotation angle of the axis, ψ, is about x. B The rotation angle of the axis.

[0120] At this point, the workpiece deformation, the location of the alignment points, and the fixed angle corresponding to the shot peening gun's alignment posture have been determined. These three data points can accurately and efficiently guide the shot peening gun in alignment. In the LabVIEW robot control program within the industrial control computer module, because the 3D scanner can automatically stitch together the scanned data, the scanning process only requires the turntable to rotate while the robot moves up and down to drive the scanner, thus automating the scanning process. Therefore, a control program for the fixed 3D shape scanning module is written based on a state machine. Finally, the position information of each point is calculated... B P = (x, y, z), deformation Δ i And the fixed angle that shot peening needs to be perpendicular to the calibration point. Output in CSV table format. It enables the control of robots in LabVIEW, thereby automating the shaping of shot peening guns.

[0121] This embodiment also provides an automated in-situ measurement and calibration system, which is implemented through the automated in-situ measurement and calibration method for thin-walled rotating workpieces provided in the above embodiment.

[0122] like Figure 6 As shown, it includes an industrial control computer module, a workpiece placement module, a three-dimensional shape scanning module, and a shape correction and processing module.

[0123] The industrial control computer module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and to control the robot to complete the processing task according to the generated processing path.

[0124] The workpiece placement module is used to place the thin-walled rotating workpiece to be corrected;

[0125] The three-dimensional topography scanning module is used to acquire point cloud data of thin-walled rotating workpieces;

[0126] The calibration and machining module calibrates the initial machining path based on the acquired point cloud data and reference point cloud data, so as to output the optimal machining path to the industrial control computer module.

[0127] More specifically, the system's functional modules mainly consist of four parts: an industrial computer control module, a workpiece placement module, a 3D topography scanning module, and a calibration and machining module. The industrial computer control module comprises an industrial computer and a Compact RIO module. The industrial computer is a human-machine interface terminal, and the Compact RIO module is a product of NI (National Instruments). Through the Compact RIO module, the industrial computer can simultaneously control mobile devices in both the automatic calibration and machining module and the workpiece placement module, such as the workpiece clamping turntable. Furthermore, the industrial computer controls the scanner via TCP communication established with the scanner using LabVIEW. The workpiece placement module is the turntable used to clamp the workpiece during in-situ measurement and shot peening calibration. The 3D topography automatic scanning module mainly includes a handheld scanner, scanner fixture, and scanner communication technology. The scanner is mounted on the robot's end effector via the fixture, and the robot is controlled to move the scanner, achieving automated scanning. The automatic calibration and machining module includes point cloud data processing and a turntable-robot linkage calibration solution. The industrial computer control module, in cooperation with other modules, can realize a complete series of functions such as automatic workpiece scanning, point cloud data processing, and automatic shape correction processing, thereby achieving automated measurement and correction of workpieces.

[0128] Furthermore, the terms "upper," "lower," "inner," "outer," "front," and "rear" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Unless otherwise specifically stated, the relative steps, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0129] Of course, the above description is only a specific embodiment of the present invention and is not intended to limit the scope of the present invention. All equivalent changes or modifications made to the structure, features and principles described in the claims of the present invention should be included in the scope of the claims of the present invention.

[0130] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An automated in-situ measurement and calibration method for a thin-walled rotating workpiece, wherein the thin-walled rotating workpiece is placed on a turntable, characterized in that, The automated in-situ measurement and calibration method includes the following steps: Construct a reference coordinate system in the robot processing space. The reference coordinate system includes a robot base coordinate system with the center of the robot base as the origin, a robot end flange coordinate system with the center of the robot end as the origin, a shot peening gun tool coordinate system with the geometric center of the shot peening gun surface as the origin when the robot end is equipped with a shot peening gun, and a three-dimensional scanner coordinate system when the robot end is equipped with a three-dimensional scanner. Obtain the point cloud model of the turntable in the scanner coordinate system to construct the corresponding turntable coordinate system; For all reference coordinate systems and the turntable coordinate system, establish transformation relationships between multiple coordinate systems; By having the robot drive the shot peening gun to contact the surface contour of the turntable, two singular configuration points of the robot are determined, and the correction range of the shot peening gun is determined in the turntable coordinate system corresponding to the two singular configuration points. The robot drives a 3D scanner to acquire point cloud data of the thin-walled rotating workpiece on the turntable in the turntable coordinate system. The point cloud data is then registered with the reference point cloud data of the qualified workpiece. The point deviation between the corresponding points of the point cloud data and the reference point cloud data is used as the shape correction quantity corresponding to each point on the thin-walled rotating workpiece. Based on the point cloud data of the thin-walled rotating workpiece, the generatrix equation of the thin-walled rotating workpiece is solved in the turntable coordinate system to obtain the normal vector of each point on the generatrix. Based on the obtained point cloud data and the corresponding quantities to be calibrated and normal vectors, a processing path for the shot peening gun within the calibration range is generated to complete the calibration task.

2. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 1, characterized in that, The shot peening gun coordinate system is generated by calibration using a six-point method based on the robot base coordinate system.

3. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 1, characterized in that, The process of establishing the transformation relationship between the 3D scanner coordinate system and the robot end-effector coordinate system is as follows: The target ball is scanned by a 3D scanner carried by the robot end effector during axial movement to obtain the rotation matrix between the 3D scanner and the robot end effector flange. The tracking device located on one side of the robot is used as a relay coordinate system to obtain the translation vector corresponding to the 3D scanner and the end flange of the robot. The corresponding transformation relationship is constructed based on the rotation matrix and translation vector.

4. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 1, characterized in that, The process of constructing the turntable coordinate system is as follows: By obtaining n points on the circumference of the turntable's point cloud model and substituting them into the preset center equation, the corresponding center coordinates are solved using the least squares method. The center coordinates are then used as the origin to construct the coordinate system.

5. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 1, characterized in that, The expression for the transformation relationship is as follows: in, S O A This represents the coordinates of the origin in the turntable coordinate system. This represents the unit vector along the x-axis in the turntable coordinate system. This represents the unit vector along the y-axis in the turntable coordinate system. This represents the unit vector of the z-axis in the turntable coordinate system.

6. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 1, characterized in that, The process for obtaining the correction range is as follows: The robot drives the shot peening gun to make the origin of the shot peening gun tool coordinate system contact the contour of the turntable surface, so as to obtain the Cartesian coordinates when it is at two singular configuration points in the turntable coordinate system, and then convert the Cartesian coordinates into the corresponding cylindrical coordinates. The angle parameters in the two cylindrical coordinate systems are subtracted to obtain the corresponding angle range, which is then used as the calibration range.

7. The automated in-situ measurement and calibration method for thin-walled rotating workpieces according to claim 6, characterized in that, The expression for converting Cartesian coordinates to cylindrical coordinates is as follows: P n =(ρ n ,i n ,z n ) among them, θ n =here2(x i ,y i ),z n =z i 4 Among them, (x i ,y i ,z i ) represents Cartesian coordinates, (ρ) n ,θ n ,z n ) represents cylindrical coordinates.

8. An automated in-situ measurement and calibration system, characterized in that, The method is implemented by the automated in-situ measurement and correction method for thin-walled rotating workpieces as described in any one of claims 1 to 7, including an industrial control computer control module, a workpiece placement module, a three-dimensional shape scanning module, and a correction processing module. The industrial control computer module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and to control the robot to complete the processing task according to the generated processing path. The workpiece placement module is used to place the thin-walled rotating workpiece to be corrected; The three-dimensional topography scanning module is used to acquire point cloud data of thin-walled rotating workpieces; The calibration and machining module calibrates the initial machining path based on the acquired point cloud data and reference point cloud data, so as to output the optimal machining path to the industrial control computer module.

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