Automatic in-situ measurement-shape correction method and system for thin-wall revolving body workpiece

Abstract

The invention discloses an automatic in-situ measurement-shape correction method for a thin-wall revolving body workpiece. The method comprises the following steps: constructing a reference coordinate system in a robot processing space; obtaining a point cloud model of the rotary table under the scanner coordinate system to construct a corresponding rotary table coordinate system; aiming at all the reference coordinate systems and the rotary table coordinate system, constructing a conversion relation among a plurality of coordinate systems; the shape correction range of the shot blasting gun is determined according to the two singular configuration points of the robot; the point deviation of the corresponding points between the point cloud data of the workpiece and the reference point cloud data is used as the to-be-corrected size corresponding to each point on the workpiece; generating a normal vector of each point on a workpiece bus based on the point cloud data of the workpiece; and on the basis of the obtained point cloud data and the corresponding to-be-corrected shape quantity and the normal vector, a machining path of the shot blasting gun is generated to complete a shape correction task. The invention further provides an automatic in-situ measurement-shape correction system. The method provided by the invention can solve the problem that the robot cannot reach the specific position due to the singular configuration.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent manufacturing technology, and in particular relates to an automated in-situ measurement-correction method and system for a thin-walled rotating workpiece. Background Art

[0002] In the fields of aerospace, automobile industry, and mechanical processing, thin-walled metal rotating workpieces are an indispensable part, such as the tank barrel section of a rocket, the wheel hub of a car, etc. During the forming process, parts often cause roundness deformation due to factors such as complex structural shapes, many thin-walled parts, low rigidity, and uneven heating and cooling of heat treatment, which will seriously affect the quality of the parts, reduce their ability to withstand pressure, and affect their performance. Therefore, it is necessary to calibrate the deformed parts to ensure the performance indicators and appearance quality of the product and improve stability and safety. However, before calibrating the workpiece, the position of the workpiece to be calibrated and the deformation at that position must be known. Therefore, it is necessary to measure the three-dimensional shape of the workpiece and then perform calibration processing on it. However, the current measurement and calibration methods for rotating workpieces are still somewhat insufficient.

[0003] Patent document CN115585750A discloses a rim roundness automatic detection system and method. First, a device of a wheel hub clamping turntable and a laser lifting slide is built, and the external parameter calibration of the measurement system is completed with the help of a laser tracker; secondly, the rim is measured in sections multiple times according to the position of the linear laser changed by the slide, and the multiple measurement data are spliced ​​based on mechanical constraints to obtain a complete rim measurement point cloud model; the three-dimensional point cloud data of the measured rim is converted from the measurement coordinate system to the turntable coordinate system according to the external calibration result; finally, the measurement model and the CAD model are matched based on the improved ICP algorithm based on k-dtree, and the rim roundness deformation is calculated according to the matching result to realize the rim roundness detection.

[0004] Patent document CN117324751A discloses a composite shaping method and system based on laser and ultrasonic shot peening technology, and the method includes: S1: heating the part to be shaped of the target component to a preset temperature through a laser heating device; S2: taking the preset configuration as the shaping target, the part to be shaped that reaches the preset temperature is impact shaped by an ultrasonic shot peening device; S3: obtaining the real-time deformation amount and real-time temperature of the part to be shaped during the impact shaping process; S4: according to the real-time deformation amount and real-time temperature, retrieving corresponding process parameters from a process parameter library; S5: regulating the position and moving speed of the ultrasonic shot peening device and the laser heating device according to the retrieved process parameters; S6: judging whether the part to be shaped is shaped to the preset configuration, if so, completing the shaping, if not, returning to step S3.

[0005] In the existing 3D scanning solutions, the 3D scanning platform has a complex structure, the scanning process is relatively cumbersome, the degree of automation is low, and some platforms need to scan the workpiece in multiple times and then splice the data from multiple scans, which is inefficient. Summary of the invention

[0006] The purpose of the present invention is to provide an automated in-situ measurement-correction method and system for thin-walled rotating workpieces, which can solve the problem that the robot cannot reach a specific position due to its singular configuration, thereby improving the correction efficiency and realizing the programmability of correction.

[0007] In order to achieve the first object of the present invention, the following technical solution is provided: an automated in-situ measurement-alignment method for a thin-walled rotating workpiece, wherein the thin-walled rotating workpiece is placed on a turntable, and the automated in-situ measurement-alignment method comprises the following steps:

[0008] Constructing a reference coordinate system in the robot processing space, the reference coordinate system includes a robot base coordinate system constructed with the center of the robot base as the origin, a robot end flange coordinate system constructed with the center of the robot end as the origin, and a shot peening gun tool coordinate system constructed 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;

[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 turntable coordinate systems, to establish the transformation relationship between multiple coordinate systems;

[0011] The robot drives the shot peening gun to contact the surface contour of the turntable to respectively determine two singular configuration points of the robot, and the calibration 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 three-dimensional scanner to obtain point cloud data of the thin-walled rotating workpiece on the turntable in the turntable coordinate system, and the point cloud data is aligned with the reference point cloud data of the qualified workpiece, and the point deviation of the corresponding point between the point cloud data and the reference point cloud data is used as the shape correction amount 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 amount to be calibrated and the normal vector, a processing path of the shot peening gun within the calibration range is generated to complete the calibration task.

[0015] The present invention performs two stages of coarse registration 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 posture of the shot peening gun, thereby ensuring that the shot peening needle is always vertically aligned with the correction 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 conversion relationship between the three-dimensional scanner coordinate system and the robot end flange coordinate system is constructed as follows:

[0018] The target ball is scanned by carrying a three-dimensional scanner at the end of the robot during axial movement to obtain a rotation matrix between the three-dimensional scanner and the flange at the end of the robot;

[0019] The tracker 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] A corresponding transformation relationship is constructed based on the rotation matrix and the translation vector.

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

[0022] By obtaining n points on the circumference of the turntable in the point cloud model, substituting them into the preset circle center equation and using the least square method to solve the corresponding circle center coordinates, the circle center coordinates are used as the coordinate origin for coordinate construction.

[0023] Specifically, the expression of the conversion relationship is as follows:

[0024]

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

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

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

[0028] The angle parameters in the two cylindrical coordinates are processed by difference to obtain the corresponding angle range as the correction range.

[0029] Specifically, the expression for converting the 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 the cylindrical coordinate system representation and the Cartesian representation, the z component is unchanged, and both represent the coordinate value in the direction of the center axis of the workpiece.

[0033] In order to achieve the second purpose of the present invention, the following technical solution is provided: an automated in-situ measurement-correction system, which is implemented by the above-mentioned automated in-situ measurement-correction method of thin-walled rotating workpieces, and includes an industrial computer control module, a workpiece placement module, a three-dimensional shape scanning module and a correction processing module.

[0034] The industrial computer control module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and 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 body workpiece to be corrected;

[0036] The three-dimensional shape scanning module is used to obtain point cloud data of the thin-walled rotating workpiece;

[0037] The shape correction processing module corrects the initial processing path according to the acquired point cloud data and the reference point cloud data, so as to output the best processing path to the industrial computer control module.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

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

[0040] The normal vector of each point on the generatrix is ​​obtained by solving the generatrix equation of the workpiece in the turntable coordinate system. The x-axis of the shot peening gun coordinate system is kept parallel and opposite to the normal vector by adjusting the fixed angle describing the posture of the shot peening gun, ensuring that the shot peening needle is always vertically aligned with the correction point. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of the automated in-situ measurement and shape correction method for a thin-walled rotating workpiece provided in this embodiment;

[0042] Figure 2 Schematic diagram of the automated in-situ measurement and shape correction method for thin-walled rotating workpieces provided in this embodiment;

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

[0044] Figure 4 A schematic diagram of solving the translation vector provided in this embodiment;

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

[0046] Figure 6 A framework diagram of the automated in-situ measurement-alignment system provided for this embodiment. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0048] like Figure 1 As shown, the automated in-situ measurement and shape correction method for a thin-walled rotating workpiece provided in this embodiment has the following specific steps:

[0049] A reference coordinate system is constructed in the robot processing space, wherein the reference coordinate system includes a robot base coordinate system constructed with the center of the robot base as the origin, a robot end flange coordinate system constructed with the center of the robot end as the origin, a shot peening gun tool coordinate system constructed 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.

[0050] More specifically, a clamp for fixing the handheld 3D scanner device at the end of the robot is designed based on the 3D model of the handheld 3D scanner device and the features of the 3D scanner surface.

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

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

[0053] like Figure 3 The figure shows the rotation matrix calibration process provided in this embodiment, where {B} represents the robot base coordinate system, {Tool} represents the robot end flange coordinate system, and {S} represents the scanner coordinate system. In the robot end flange 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 the robot, and the scanner is used to scan the target ball at different positions and record the coordinates of the center point (TCP) of {Tool}. Through these coordinates, the motion matrix of TCP in the robot base coordinate system {B} is fitted as follows:

[0054] B H=[λ1,λ2,λ3] (1)

[0055] Among them, λ1, λ2, λ3 are the unit translation vectors of TCP in {B}. According to the relative motion, TCP moves along the negative direction of the coordinate axis of {Tool}, which can be regarded as the target ball moving along the positive direction of the coordinate axis of {Tool}, so:

[0056]

[0057] The point cloud surface of the scanned standard target ball is fitted to obtain the coordinates of the center of the ball, and the motion matrix of the target ball in {S} is obtained as follows:

[0058] S H=[β1,β2,β3] (3)

[0059] Among them, β1, β2, β3 are the unit translation vectors of the sphere center in {S}. For the required hand-eye calibration rotation matrix, 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 As shown in FIG. 1 , the translation vector solution process provided in this embodiment is shown in FIG. 1 . The coordinate system {L} is the coordinate system of the Leica tracker. First, the tracker is used to measure the target ball at three positions to obtain three coordinates under {L}. L P1=(x1,y1,z1), L P2=(x2,y2,z2), L P3=(x3,y3,z3). The coordinates of the three balls in the robot base coordinate system {B} are measured using the shot peening center point at the end of the robot. B P1=(a1,b1,c1), B P2=(a2,b2,c2), B P3=(a3,b3,c3). From these three points, we can establish a coordinate system through the vector method, and define this coordinate as {M}. Take P1 as the origin of the coordinates of {M}, and use the formula:

[0065]

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

[0067]

[0068] Similarly, according to the formula:

[0069]

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

[0071]

[0072] Then by the formula Get the transformation matrix with {B}.

[0073] In addition, 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

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

[0075] By the formula:

[0076]

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

[0078] Then by the formula:

[0079]

[0080] The combined formulas give

[0081] At this point, the conversion relationship between {B} and {S} is completed The solution.

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

[0083]

[0084] In addition, the relationship between the robot base coordinate system {B} and {Tool} can be obtained from the robot kinematics: Therefore, the conversion relationship between {B} and {S} is

[0085] The point cloud model of the turntable in the scanner coordinate system is obtained to construct the corresponding turntable coordinate system, and the conversion relationship between multiple coordinate systems is constructed for all reference coordinate systems and the turntable coordinate system.

[0086] More specifically, if Figure 5 The figure shows the calibration process of the turntable coordinate system provided in this embodiment. In order to establish the turntable coordinate system {A}, it is necessary to solve the center of the turntable. First, scan the turntable with a scanner to obtain a point cloud model of the turntable in the scanner coordinate system. Take n points P on the circumference of the turntable. n =(x n ,y n ,z n ). Let the coordinates of the circle center be S O A=(x0,y0,z0), there is a formula:

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

[0088] Substituting n points into (13), the coordinates of the circle center can be obtained by the matrix form of the least squares method: S O A =(x0,y0,z0), with S OA is the origin of the turntable coordinate system {A}, and a point is taken on the plane on the turntable circumference S O1=(x1,y1,z1), take a point on the rotation axis S O2=(x2,y2,z2), based on these three points, the coordinate system {A} of the turntable coordinate system is established. They are the unit vectors in the three coordinate axis directions of {A}. According to the vector method formula, we can get:

[0089]

[0090] So the conversion 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 conversion relationship between these coordinate systems, which can realize the conversion of the scanner's measurement data.

[0093] The robot drives the shot peening gun to contact the surface contour of the turntable to respectively determine two singular configuration points of the robot, and the calibration range of the shot peening gun is determined in the turntable coordinate system corresponding to the two singular configuration points.

[0094] Use the center of the shot peening gun to contact the surface contour of the turntable, 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 cannot continue to move due to the singular configuration. Convert these two points to the turntable coordinate system {A} 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), the robot calibration range is α=θ2-θ1. In order to make the angle calculation convenient and intuitive, in the calibration of the S300 turntable coordinate system {A}, A Q1=(x1,y1,z1) Replace S O1=(x1,y1,z1) determines the x-axis of {A} therefore A Q1=(x1,y1,z1) corresponds to the Cartesian coordinates in {A} A Q1=(ρ1,θ1,z1)θ1=0. Therefore, the robot calibration range α=θ2.

[0095] That is, 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] The robot drives the three-dimensional scanner to obtain the point cloud data of the thin-walled rotating workpiece on the turntable in the turntable coordinate system, and the point cloud data is aligned with the reference point cloud data of the qualified workpiece. The point deviation of the corresponding points between the point cloud data and the reference point cloud data is used as the amount to be corrected corresponding to each point on the thin-walled rotating workpiece.

[0098] More specifically, the above calibration can obtain the point cloud data of the rotating workpiece scanned by the scanner in the turntable coordinate system, and perform point cloud registration on the source point cloud of the workpiece and the target point cloud of the qualified workpiece to 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 of correction to be made for the 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, and then fine registration is performed. In coarse registration, the PCA algorithm can quickly find the main axis of rotation of the rotating workpiece, and then coincide the main axes of the two point clouds, which can quickly complete the coarse registration of the point cloud. On this basis, ICP fine registration is performed. Suppose the source point cloud P = {P1, P2, P3, ... P n}, target point cloud Q = {q1,q2,q3,…q n}, we get an optimal transformation matrix Make the objective function The minimum value completes the registration.

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

[0101] 1. Find the main axis direction U of the source point cloud P , the main axis direction U of the target point cloud Q ;

[0102] 2. Align the main axis directions of the two point clouds to complete the rough registration of the point clouds and obtain the transformation matrix of the rough registration Apply R1 and t1 to the source point cloud to get P i =R1·P i +t1.

[0103] 3. Set the ICP registration parameters, including the distance threshold d for corresponding points in 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 traverse and search in the target point cloud to find the nearest corresponding point Q i ;

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

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

[0107] 7. If d is less than the given Or if the number of iterations is greater than the preset maximum number of iterations K, the iterative calculation is stopped. Otherwise, return to step 4 until the convergence condition is met. The transformation matrix of the optimal registration is obtained

[0108] Based on the obtained Point P in the source point cloud i The corresponding point Q with the target point cloud i There is a bias value:

[0109] Δ i =(R k P i +t k )-Q i (19)

[0110] Deviation value Δ i That is, the amount 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 calibrated, its Cartesian coordinate representation is A P i =(x i ,y i ,z i ) is converted 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 and the size of α, if θ n <α, then the calibration point is within the calibration range, and the robot only needs to be controlled to identify the position of the point; if θ n >α, then the turntable needs to be rotated at least by θ n -α, so that the calibration point is within the calibration 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, the three coordinate axes of the shot peening gun center coordinate system {F} in this embodiment are collinear and in the same direction with the three coordinate axes of the robot base coordinate system, and the z axes of {F} and {A} are also collinear and in the same direction. Therefore, when adjusting the posture of the shot peening gun for calibration, only the x axis of the shot peening gun is adjusted. F The axis and the normal vector of the point cloud coincide but are in opposite directions. Therefore, to achieve this, it is necessary to calculate the normal vector of the point cloud. First, in the turntable coordinate system, find the generatrix equation of the workpiece surface, and then use the generatrix equation to get the normal vector of each point on the generatrix. Then convert the normal vector to the robot base coordinate system: When the robot is in the initial position, the axes of the shot peening gun coordinate system coincide with the axes of the robot base coordinate system and are in the same direction. F Axis and Overlap and reverse, calculate the rotation axis and rotation angle. F axis The target vector is The rotation axis is then:

[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] Among them, I is the unit matrix, K is the antisymmetric matrix of the rotation axis. Finally, the rotation matrix R is used to represent the rotation matrix of the shot peening gun coordinate system relative to the base coordinate system. The fixed angle of the shot peening gun around the base coordinate system is obtained by inverse calculation. in For z B The rotation angle of the axis, φ is the rotation angle around the y axis. B The rotation angle of the axis, ψ is the rotation angle around the x axis. B The rotation angle of the axis.

[0120] So far, the deformation of the workpiece, the position of the correction point and the fixed angle corresponding to the correction posture of the shot peening gun have been solved. These three data can accurately and efficiently guide the shot peening gun to correct the shape. In the LabVIEW robot control program in the industrial computer module, because the three-dimensional scanner can automatically complete the splicing of the scan data, the scanning work only needs the turntable to rotate while the robot moves up and down to drive the scanner to complete the automatic scanning work. Therefore, the control program of the fixed three-dimensional shape scanning module is written based on the state machine. Finally, the position information of each point is calculated. B P = (x, y, z), deformation Δ i , and the fixed angle at which the shot peening needs to be vertically aligned with the correction point Output in csv format. The robot can be controlled in LabVIEW, thereby realizing the automatic shape correction of the shot peening gun.

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

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

[0123] The industrial computer control module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and 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 body workpiece to be corrected;

[0125] The three-dimensional shape scanning module is used to obtain point cloud data of the thin-walled rotating workpiece;

[0126] The shape correction processing module corrects the initial processing path according to the acquired point cloud data and the reference point cloud data, so as to output the best processing path to the industrial computer control module.

[0127] More specifically, the functional modules of the system are mainly composed of four parts: industrial computer control module, workpiece placement module, 3D shape scanning module, and shape correction processing module. The industrial computer control module mainly includes industrial computer and Compact RIO module, among which the industrial computer is a human-computer interaction terminal device, and the Compact RIO control module is a product of NI. The industrial computer can control the automatic shape correction processing module and the mobile devices in the workpiece placement module at the same time through the Compact RIO module, such as the workpiece clamping turntable. In addition, the industrial computer can control the scanner through the TCP communication established between LabVIEW and the scanner; the workpiece placement module is the turntable for clamping the workpiece during in-situ measurement and shot peening correction; the 3D shape automatic scanning module mainly includes handheld scanner equipment, scanner fixture, and scanner communication technology. The scanner is mounted on the end of the robot through the fixture, and the robot is controlled to drive the scanner to move to realize automatic scanning; the automatic shape correction processing module includes point cloud data processing, and the shape correction scheme of the turntable and robot linkage. The industrial computer control module cooperates with other modules to realize a series of complete functions such as automatic scanning of workpieces, point cloud data processing, and automatic shape correction processing, thereby realizing automatic measurement and correction of workpieces.

[0128] In addition, the terms "upper", "lower", "inner", "outer", "front", "rear" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps described in these embodiments do not limit the scope of the present 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 implementation of the present invention. All equivalent changes or modifications made according to the structure, characteristics and principles described in the patent application scope of the present invention should be included in the patent application scope of the present invention.

[0130] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An automated in-situ measurement and shape correction 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-calibration method comprises the following steps: Constructing a reference coordinate system in the robot processing space, the reference coordinate system includes a robot base coordinate system constructed with the center of the robot base as the origin, a robot end flange coordinate system constructed with the center of the robot end as the origin, and a shot peening gun tool coordinate system constructed 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 turntable coordinate systems, to establish the transformation relationship between multiple coordinate systems; The robot drives the shot peening gun to contact the surface contour of the turntable to respectively determine two singular configuration points of the robot, and the calibration range of the shot peening gun is determined in the turntable coordinate system corresponding to the two singular configuration points; The robot drives a three-dimensional scanner to obtain point cloud data of the thin-walled rotating workpiece on the turntable in the turntable coordinate system, and the point cloud data is aligned with the reference point cloud data of the qualified workpiece, and the point deviation of the corresponding point between the point cloud data and the reference point cloud data is used as the shape correction amount 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 amount to be calibrated and the normal vector, a processing path of the shot peening gun within the calibration range is generated to complete the calibration task.

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

3. The automated in-situ measurement and shape correction method for thin-walled rotating workpiece according to claim 1, characterized in that: The conversion relationship between the three-dimensional scanner coordinate system and the robot end flange coordinate system is constructed as follows: The target ball is scanned by carrying a three-dimensional scanner at the end of the robot during axial movement to obtain a rotation matrix between the three-dimensional scanner and the flange at the end of the robot; The tracker 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; A corresponding transformation relationship is constructed based on the rotation matrix and the translation vector.

4. The automated in-situ measurement and shape correction method for thin-walled rotating workpiece according to claim 1, characterized in that: The construction process of the turntable coordinate system is as follows: By obtaining n points on the circumference of the turntable in the point cloud model, substituting them into the preset circle center equation and using the least squares method to solve the corresponding circle center coordinates, the circle center coordinates are used as the coordinate origin for coordinate construction.

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

6. The automated in-situ measurement and shape correction method for thin-walled rotating workpiece according to claim 1, characterized in that: The process of obtaining the calibration range is as follows: The robot drives the shot peening gun to make the origin of the tool coordinate system of the shot peening gun contact with the contour of the turntable surface, so as to obtain the Cartesian coordinates of the two singular configuration points in the turntable coordinate system, and convert the Cartesian coordinates into corresponding cylindrical coordinates; The angle parameters in the two cylindrical coordinates are processed by difference to obtain the corresponding angle range as the correction range.

7. The automated in-situ measurement and shape correction method for thin-walled rotating workpiece according to claim 6, characterized in that: The expression for converting the 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-calibration system, characterized in that: It is achieved by the automated in-situ measurement-alignment method of a thin-walled rotating body workpiece as claimed in any one of claims 1 to 7, comprising an industrial computer control module, a workpiece placement module, a three-dimensional shape scanning module and a alignment processing module; The industrial computer control module is used to control the corresponding functions of the scanner, the movement of the robot and the rotation of the turntable, and 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 body workpiece to be corrected; The three-dimensional shape scanning module is used to obtain point cloud data of the thin-walled rotating workpiece; The shape correction processing module corrects the initial processing path according to the acquired point cloud data and the reference point cloud data, so as to output the best processing path to the industrial computer control module.

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