A method and system for automatic calibration of coordinate systems for ultrasound detection of end effectors

Abstract

The application discloses a kind of coordinate system automatic calibration method and system for ultrasonic detection terminal executor, it is related to executor calibration technical field, including replacing the nozzle of ultrasonic detection terminal executor with vector target seat, and robot is installed on pedestal;The ultrasonic detection terminal executor is driven by robot, and is moved in the measurement space of laser tracker with multiple different postures;The joint angle vector of robot and the three-dimensional coordinates of two target points under each posture are synchronously acquired;The three-dimensional coordinates of two target points are converted to robot flange coordinate system;Based on the two target point coordinates under robot flange coordinate system, the rough estimate of the pose transformation matrix of ultrasonic detection terminal executor to flange is constructed;Based on the rough estimate of pose transformation matrix under all robot postures, the accurate estimate of pose transformation matrix is calculated using data fusion algorithm;It is used to solve the problem of low precision and poor robustness of traditional calibration method.

Description

Technical Field

[0001] This invention relates to the field of actuator calibration technology, and more specifically to an automatic coordinate system calibration method and system for ultrasonic testing terminal actuators. Background Technology

[0002] In the field of robotic ultrasonic nondestructive testing, the tool center point (TCP) calibration accuracy of the ultrasonic end effector is a core prerequisite for determining the reliability and consistency of the test results. A single-arm ultrasonic end effector typically consists of a complex structure including a quick-change disc, anti-collision device, water chamber, and nozzle. Its TCP coordinate system is defined as the center position of the nozzle outlet, and its coordinate axes (X, Y, Z axes) should be strictly aligned with the robot's end flange coordinate system. However, in the multiple stages of machining, component assembly, and on-site installation, dimensional tolerances, form and position errors, and assembly clearances are inevitably introduced, resulting in a small but not negligible deviation between the actual physical pose of the TCP coordinate system and its theoretical design pose relative to the flange. If this deviation is not accurately measured and compensated, it will directly lead to incorrect ultrasonic beam pointing, severely reducing the positioning accuracy of defect detection and the accuracy of quantitative assessment. Therefore, high-precision calibration must be performed before the actuator is put into use.

[0003] Traditional mainstream calibration methods heavily rely on manual operation and contact-based measuring tools. Technicians typically use calipers, height gauges, dial indicators, or even coordinate measuring machines to directly measure the external geometric features of the actuator nozzle, attempting to deduce the TCP position from a physical reference. This approach reveals a series of systemic flaws in practice: First, the actuator end, especially the nozzle area, is often compact and space-constrained, with internal channels intersecting with external installation features, making it difficult for the measuring probe to approach the true TCP physical reference point (i.e., the nozzle center). This forces operators to perform indirect measurements and geometric conversions, introducing multiple error accumulations. Second, the entire process heavily depends on the operator's personal experience, skills, and even subjective judgment. From the selection of the measurement reference and the operation of the tools to the reading and recording of data, random errors caused by human intervention exist at every stage, resulting in poor repeatability and reproducibility of calibration results, failing to meet the requirements of standardized, large-scale production for process consistency.

[0004] More importantly, traditional methods typically perform calibration when the robot is in a single or very few static poses. This "single-point calibration" mode has inherent limitations: it cannot effectively separate and identify the influence of different error sources. The measurement results are mixed with various systematic errors such as the robot's positioning error, joint backlash, link flexibility deformation, and flange mounting surface error. These errors manifest differently under different robot poses and loads. Therefore, the TCP accuracy of calibration parameters obtained based on a few poses often decreases significantly when the robot moves to other positions or poses in the workspace, resulting in insufficient robustness.

[0005] Furthermore, traditional contact calibration methods lack an effective and independent in-process verification mechanism. The calibration process itself cannot provide closed-loop verification of the accuracy of the results, and the operator can only choose to "trust" the measurement. Once a deviation is found in the subsequent inspection process, it is difficult to trace back and distinguish whether it is caused by calibration error, robot trajectory error or workpiece positioning error, which brings great difficulties to process debugging and problem tracing.

[0006] Therefore, we propose a calibration method that can improve calibration accuracy and ensure robustness. Summary of the Invention

[0007] The purpose of this invention is to provide an automatic coordinate system calibration method and system for ultrasonic testing terminal actuators, which solves the problems of low accuracy and poor robustness of traditional calibration methods.

[0008] This invention is achieved through the following technical solution:

[0009] An automatic coordinate system calibration method for an ultrasonic testing terminal actuator, specifically comprising:

[0010] Replace the nozzle of the ultrasonic testing terminal actuator with a vector target, and mount the robot on the base;

[0011] The ultrasonic testing terminal actuator, driven by a robot, moves in multiple different postures within the measurement space of the laser tracker.

[0012] Simultaneously acquire the robot's joint angle vectors for each posture, as well as the three-dimensional coordinates of the two target points on the vector target base in the base coordinate system measured by the laser tracker;

[0013] Based on the pose transformation matrix of the robot base coordinate system relative to the base coordinate system, and the robot's posture, calculate the pose transformation matrix of the robot flange coordinate system relative to the base coordinate system under each posture.

[0014] Using the pose transformation matrix, the three-dimensional coordinates of the two target points are transformed into the robot flange coordinate system;

[0015] Based on the coordinates of two target points in the robot flange coordinate system, a rough estimate of the pose transformation matrix of the vector target actuator coordinate system relative to the robot flange coordinate system is constructed.

[0016] Based on a rough estimate of the pose transformation matrix under all robot postures, a data fusion algorithm is used to calculate a precise estimate of the pose transformation matrix.

[0017] Furthermore, the pose transformation matrix based on the robot's base coordinate system relative to the base coordinate system... Calculate the pose transformation matrix of the robot flange coordinate system relative to the base coordinate system in each pose. The specific calculation formula is as follows:

[0018] ;

[0019] In the formula, Joint angle vector The pose of the flange coordinate system is obtained through forward kinematics calculation.

[0020] Furthermore, the pose transformation matrix is ​​used to transform the three-dimensional coordinates of the two target points to the robot flange coordinate system. The specific calculation formula is as follows:

[0021] ;

[0022] ;

[0023] In the formula, The three-dimensional coordinates of the first target point. The coordinates of the second target point are shown in the three-dimensional coordinates.

[0024] Furthermore, the rough estimation of the pose transformation matrix of the vector target actuator coordinate system relative to the robot flange coordinate system based on the coordinates of the two target points in the robot flange coordinate system specifically includes:

[0025] The z-axis direction of the vector target actuator coordinate system is determined by the coordinates of two collinear target points;

[0026] Along the z-axis, the point offset from the first target point by the designed distance d is defined as the origin;

[0027] Project the x-axis direction vector in the flange coordinate system onto a plane perpendicular to the z-axis direction and normalize it to determine the x-axis direction of the vector target actuator coordinate system;

[0028] The y-axis direction of the vector target actuator coordinate system is determined according to the right-hand Cartesian coordinate system rule;

[0029] Based on the z-axis direction, origin coordinates, x-axis direction, and y-axis direction, a rough estimate of the pose transformation matrix of the vector target actuator coordinate system relative to the robot flange coordinate system is constructed.

[0030] Furthermore, the data fusion algorithm is a mean-based method, including:

[0031] right The coordinates of the origin Take the average value to obtain the translation vector. ;

[0032] ;

[0033] right Rotation matrices Perform a rotational average, and calculate it using either the quaternion average method or the Lie algebra average method, to obtain the average rotation matrix. ;

[0034] Combine the averaged translation vector with the averaged rotation matrix This is the accurate estimate of the pose transformation matrix:

[0035] .

[0036] Furthermore, the data fusion algorithm is a nonlinear optimization method, including:

[0037] Using the results obtained by the mean method as initial values, a nonlinear least squares optimization problem is constructed, the objective function of which is:

[0038] ;

[0039] In the formula, Let be the rotation matrix to be optimized. Let be the translation vector to be optimized. and These are the fixed coordinates of the first and second target points in the target coordinate system, respectively.

[0040] The objective function is solved using the Levenberg-Marquardt algorithm or the Gauss-Newton algorithm to obtain the optimal solution. and This constitutes an accurate estimate of the pose transformation matrix.

[0041] An automatic coordinate system calibration system for an ultrasonic testing terminal actuator, comprising:

[0042] A robot with known kinematic parameters;

[0043] A vector target mount, detachably mounted at the nozzle of the ultrasonic end effector to be calibrated, has two collinear targets with a center-to-center distance of [missing information]. spherical reflection target point;

[0044] A laser tracker is used to capture the three-dimensional coordinates of the spherical reflective target point within the measurement space;

[0045] The computing and control unit, which is communicatively connected to both the robot's controller and the laser tracker, is configured to perform the following operations:

[0046] The robot is controlled to move the ultrasonic testing terminal actuator to multiple preset postures, and the robot's posture data and target coordinate data are collected simultaneously.

[0047] Perform coordinate system transformations and calculations;

[0048] Based on the above-mentioned automatic coordinate system calibration method for ultrasonic testing terminal actuators, a rough estimate of the pose transformation matrix under each attitude is constructed;

[0049] The data fusion algorithm is executed to calculate and output a precise estimate of the final pose transformation matrix.

[0050] Furthermore, the calculation and control unit also pre-stores the pose transformation matrix of the robot's base coordinate system relative to the base coordinate system, as well as the design distance.

[0051] Furthermore, the vector target holder is installed in conjunction with the nozzle mounting position center of the ultrasonic terminal actuator via its base, ensuring that the line connecting the two target points is collinear with the central axis of the nozzle.

[0052] Furthermore, the computing and control unit is a separate computer or a data processing module integrated into the robot controller.

[0053] The technical solution of the present invention has at least the following advantages and beneficial effects:

[0054] This invention discloses an automatic coordinate system calibration method and system for ultrasonic testing terminal actuators. By using a laser tracker for non-contact optical measurement, errors caused by the contact pressure and alignment deviation of the measuring probe are fundamentally eliminated. On the other hand, by measuring the standard spherical reflection target point installed on the vector target base, spatial coordinate data with a resolution far exceeding that of manual measurement are obtained, laying a data foundation for high-precision calibration.

[0055] Furthermore, this method transforms the operator's role from "measurement executor and judge" to "process initiator and monitor," eliminating random errors introduced by personal skills and subjective judgment, and ensuring that calibration results from different personnel and at different times are highly consistent and reproducible.

[0056] In addition, by fusing multiple sets of spatially distributed data and using the mean method or nonlinear optimization algorithm for overall solution, random noise in a single measurement can be effectively averaged, and the fluctuation of systematic errors such as robot positioning error and joint clearance under different poses can be significantly suppressed. As a result, the final calibrated TCP parameters maintain high accuracy throughout the robot's workspace, greatly improving the robustness of the calibration results.

[0057] Furthermore, by employing two data fusion algorithms—the mean method and the nonlinear optimization method—the mean method is computationally efficient and can quickly obtain stable estimates. The nonlinear optimization method, on the other hand, uses the former as an initial value and solves the optimal transformation by minimizing the reprojection error of all measurement points, further squeezing the potential of the data. This results in calibration results with higher theoretical accuracy and less sensitivity to noise, making it suitable for applications requiring higher precision.

[0058] It should be noted that the vector target holder designed in this invention is detachably installed at the actuator nozzle, and the two collinear target points on it accurately simulate the nozzle axis. This "plug and play" design allows the same target holder to be adapted to multiple actuators of the same model, which is highly versatile. At the same time, the target holder installation requirements are clear (ensuring collinearity), which reduces the difficulty of installation and adjustment. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of an automatic coordinate system calibration method for an ultrasonic testing terminal actuator according to the present invention;

[0060] Figure 2 This is a schematic diagram of an automatic coordinate system calibration system for an ultrasonic testing terminal actuator according to the present invention.

[0061] Figure 3 This is a schematic diagram of the electronic device in this invention.

[0062] Reference numerals: 1. Base; 2. Robot; 3. Vector target; 4. Target point; 5. Laser tracker. Detailed Implementation

[0063] 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.

[0064] Example 1

[0065] like Figures 1-2 The method for automatic coordinate system calibration of an ultrasonic testing terminal actuator, as shown, specifically includes:

[0066] Replace the nozzle of the ultrasonic testing terminal actuator with a vector target 3, and mount the robot 2 on the base 1;

[0067] The designed vector target holder 3 includes a base on which two spherical reflective target points 4 are fixedly mounted. The head end of the base has a connecting post with the same diameter as the nozzle, which is connected to the ultrasonic testing terminal actuator. In addition, the spherical reflective target point 4 includes a spherical shell with an observation window on the top. A reflector is fixedly mounted at the center of the sphere inside the shell. It should be noted that the line connecting the centers of the two spherical reflective target points 4 is mechanically designed to strictly coincide with the theoretical central axis of the nozzle. Therefore, this spatial straight line formed by the two target centers accurately represents the nozzle axis that cannot be directly measured.

[0068] This allows the laser tracker 5 to measure the three-dimensional coordinates of the center of target point 4 with extremely high precision by receiving the light emitted from the inner mirror of target point 4; thus, by measuring the three-dimensional coordinates of the centers of these two target points 4, the direction of the straight line they define can be calculated and deduced based on the known design distance. That is, the mechanical offset distance from the target point 4 on the vector target 3, which is close to the connecting column, to the theoretical outlet of the nozzle, and the position of the theoretical outlet of the nozzle on this straight line is accurately calculated.

[0069] Furthermore, base 1 and robot 2 base are rigidly connected; the pose transformation matrix of the robot's base coordinate system relative to the base coordinate system can be accurately calibrated offline and used as a known constant. Specifically, this pose transformation matrix... The determination method is as follows: After robot 2 grasps the calibration tool, a target ball is fixedly placed at its end; by controlling robot 2 to move the tool in various postures, the joint data of robot 2 in each posture are recorded simultaneously, and the position of the target ball on the tool relative to the coordinate system of base 1 is measured using laser tracker 5. Finally, based on the collected data, the kinematic parameters of robot 2, the transformation relationship between the tool coordinate system and the end flange coordinate system of robot 2, and the pose relationship between the base coordinate system of robot 2 and the coordinate system of base 1 are simultaneously determined through a joint optimization method, i.e., the pose transformation matrix. .

[0070] In summary, the vector target 3 provides standard feature points that can be measured with extreme precision by the laser tracker 5; the base 1 scheme ensures that the pose data of the robot 2 and the measurement data of the tracker can be correlated with high precision under a unified reference system. The combination of the two provides a high-quality data input source for the entire algorithm; moreover, the target is a detachable calibration tool and the base 1 is a preset platform, which makes the entire calibration process programmable and controllable. The robot 2 can automatically drive the target to move to multiple preset postures, and the system collects data synchronously, realizing a fundamental transformation from "manual operation" to "automatic program execution".

[0071] Furthermore, the expanded measurement range provided by the base 1 enables the system to collect more spatially distributed and diverse robot 2 posture data. By using this data for fusion calculation, random errors can be more fully averaged and systematic errors can be compensated, so that the final calibration result does not depend on a specific location, thus maintaining stability and reliability throughout the entire workspace.

[0072] The ultrasonic testing terminal actuator, driven by robot 2, moves in multiple different postures within the measurement space of laser tracker 5.

[0073] Since the positioning error and link flexibility deformation of robot 2 change with the posture and are not fixed deviations, after multi-posture data fusion using this method, these changing errors tend to cancel each other out statistically, rather than all accumulating in the calibration results. This makes the calibrated TCP parameters more accurate and stable throughout the entire workspace of robot 2, rather than only accurate under the calibration posture.

[0074] Furthermore, after nonlinear optimization, the reprojection error of the measurement points under each posture can be analyzed. If the residual of a certain posture is unusually large, it may indicate that the robot 2 is moving abnormally under that posture, the tracker measurement is blocked, or there is a gross error. This provides a basis for data quality inspection and process diagnosis.

[0075] Synchronously acquire the joint angle vector of robot 2 under each posture, and the three-dimensional coordinates of two target points 4 on the vector target 3 in the base coordinate system measured by laser tracker 5;

[0076] The joint angle vector of robot 2 The joint angles are the minimum complete input set for the robot's kinematic model. Compared to directly reading the flange pose calculated by the robot's controller, the joint angles are more original and reliable underlying data, and the pose is calculated through forward kinematics. This ensures the consistency of the kinematic model;

[0077] The first target point is target point 4 on the base, which is close to the connecting column. The second target point is another target point 4. The coordinates of the two target points 4 originally output by the laser tracker 5 are in the coordinate system of the laser tracker itself. Through the transformation relationship of "laser tracker coordinate system - base coordinate system" obtained by pre-calibration, the measured values ​​are converted to the base coordinate system in real time. This operation can complete the coordinate system transformations that are frequently needed in subsequent calculations in advance. In the base coordinate system, the relationship between all data and the robot base coordinate system is described by known constants, and the calculation chain is clearer. If the laser tracker 5 has a slight drift in its world coordinate system due to thermal deformation or slight disturbance during the calibration process, as long as its relative relationship with the base 1 is accurate after recalibration by fixing the target point 4, then all measured values ​​are stable in the base coordinate system.

[0078] Furthermore, synchronous acquisition ensures the inherent consistency of each set of data, eliminating any "stitching" caused by asynchrony, thus providing a rigorous mathematical foundation for subsequent calculations based on rigid body transformation.

[0079] Based on the pose transformation matrix of the robot's base coordinate system relative to the base coordinate system Calculate the pose transformation matrix of the robot flange coordinate system relative to the base coordinate system in each pose. The specific calculation formula is as follows:

[0080] ;

[0081] In the formula, Joint angle vector Flange coordinate system pose obtained through forward kinematics calculation;

[0082] This is used to reliably correlate high-precision external measurements with the imperfect internal model of robot 2, where the pose transformation matrix of the robot's base coordinate system relative to the base coordinate system is used. It is a constant transformation matrix obtained through offline precision calibration; it accurately describes the rigid connection between the two physical entities, robot 2 (Base) and base 1 (world). Because its calibration process can be carried out independently of the production cycle and repeatedly measured and optimized using high-precision methods, the accuracy and reliability of this matrix are far higher than any pose data reported online in real time by robot 2.

[0083] It is the real-time output of the robot 2's forward kinematics model, which is based on the current joint angles. The theoretical flange pose is calculated. This calculation is based on the design parameters (DH parameters) of robot 2, but it is affected by all internal errors such as robot 2 positioning error, gear backlash, and linkage flexibility. Therefore, the relationship between the flange and the base described by this calculation has a certain degree of uncertainty.

[0084] Furthermore, this step breaks down the complex "robot 2-tracker" system calibration problem into two simpler and more independent sub-problems.

[0085] Using the pose transformation matrix, the three-dimensional coordinates of the two target points 4 are transformed to the robot flange coordinate system. The specific calculation formula is as follows:

[0086] ;

[0087] ;

[0088] In the formula, The three-dimensional coordinates of the first target point. The three-dimensional coordinates of the second target point;

[0089] Based on the coordinates of the two target points 4 in the robot flange coordinate system, a rough estimate of the pose transformation matrix of the vector target holder 3 actuator coordinate system relative to the robot flange coordinate system is constructed. This is mainly used to unambiguously define a coordinate system based on the measurement data of the target holder with two collinear target points 4, according to the general rules of three-dimensional rigid body kinematics and the right-hand Cartesian coordinate system. Specifically, this includes:

[0090] The z-axis direction of the actuator coordinate system of the vector target 3 is determined by the coordinates of two collinear target points 4, and the calculation formula is as follows:

[0091] ;

[0092] Along the z-axis, the point after the first target point is offset by the designed distance is defined as the origin, and the calculation formula is:

[0093] ;

[0094] The x-axis direction vector in the flange coordinate system Project the vector onto a plane perpendicular to the z-axis and normalize it to determine the x-axis direction of the actuator coordinate system of vector target 3. The calculation formula is as follows:

[0095] ;

[0096] The y-axis direction of the actuator coordinate system of vector target 3 is determined according to the rules of the right-hand Cartesian coordinate system. The calculation formula is as follows:

[0097]

[0098] Based on the z-axis direction, origin coordinates, x-axis direction, and y-axis direction, a rough estimate of the pose transformation matrix of the actuator coordinate system of vector target 3 relative to the robot flange coordinate system is constructed. The calculation formula is as follows:

[0099] ;

[0100] This model connects imperfect, discrete external measurement data with an ideal, desired tool coordinate system parameter. Its effectiveness lies in successfully decomposing a complex 6-DOF spatial calibration problem into a series of executable, verifiable deterministic computational steps and producing high-quality, structured intermediate results, thus laying a solid foundation for achieving high-precision, highly robust optimal estimation.

[0101] Based on a rough estimate of the pose transformation matrix under all robot postures, a data fusion algorithm is used to calculate a precise estimate of the pose transformation matrix.

[0102] Specifically, the data fusion algorithm is the mean method, including:

[0103] right The coordinates of the origin Take the average value;

[0104] ;

[0105] right Rotation matrices A rotation average is performed, but since the rotation matrix belongs to the special orthogonal group SO(3), the arithmetic average cannot be directly performed in Euclidean space. Therefore, the quaternion average method or the Lie algebra average method is used for calculation.

[0106] The quaternion averaging method converts each rotation matrix into a unit quaternion. The average quaternion is obtained on a unit quaternion manifold using either spherical average or weighted average methods. Then convert back to the average rotation matrix ;

[0107] The Lie algebra averaging method transforms each rotation matrix to its Lie algebra through a logarithmic mapping. Calculate the arithmetic mean in the tangent space Then through exponential mapping Obtain the average rotation matrix .

[0108] All of the above methods can guarantee the average rotation matrix Satisfying the orthogonality constraint of the rotation matrix ,in It is an identity matrix, and .

[0109] Combine the averaged translation vector with the rotation matrix This is the accurate estimate of the pose transformation matrix:

[0110] .

[0111] Furthermore, the data fusion algorithm can be a nonlinear optimization method, which optimizes the results based on the mean method, specifically including:

[0112] Using the results obtained by the mean method as initial values, a nonlinear least squares optimization problem is constructed, the objective function of which is:

[0113] ;

[0114] In the formula, Let be the rotation matrix to be optimized. Let be the translation vector to be optimized. and These are the fixed coordinates of the first and second target points in the target coordinate system, respectively.

[0115] The objective function is solved using the Levenberg-Marquardt algorithm or the Gauss-Newton algorithm to obtain the optimal solution. and The accurate estimate of the optimized pose transformation matrix is ​​the pose of the calibrated vector target coordinate system, with its origin at... The z-axis direction of the actuator coordinate system of the vector target (3) is the position of the ultrasonic terminal actuator outlet TCP and the main direction of the ultrasonic beam.

[0116] Example 2

[0117] An automatic coordinate system calibration system for an ultrasonic testing terminal actuator, comprising:

[0118] Robot 2, which has known kinematic parameters;

[0119] Vector target 3, detachably mounted at the nozzle of the ultrasonic terminal actuator to be calibrated, has two collinear targets with a center distance of [missing information]. 4. Spherical reflective target point;

[0120] Laser tracker 5 is used to capture the three-dimensional coordinates of the spherical reflective target point 4 within the measurement space;

[0121] The computing and control unit, which is communicatively connected to the controller of robot 2 and the laser tracker 5 respectively, is configured to perform the following operations:

[0122] The robot 2 is controlled to move the ultrasonic testing terminal actuator to multiple preset postures, and the robot 2's posture data and target point 4's coordinate data are collected simultaneously.

[0123] Perform coordinate system transformations and calculations;

[0124] Based on the above-mentioned automatic coordinate system calibration method for ultrasonic testing terminal actuators, a rough estimate of the pose transformation matrix under each attitude is constructed;

[0125] The data fusion algorithm is executed to calculate and output a precise estimate of the final pose transformation matrix.

[0126] In addition, the calculation and control unit also pre-stores the pose transformation matrix of the robot base coordinate system relative to the base coordinate system, as well as the design distance.

[0127] Furthermore, the vector target 3 is installed by its base in conjunction with the center of the nozzle mounting position of the ultrasonic terminal actuator, ensuring that the line connecting the two target points 4 is collinear with the central axis of the nozzle.

[0128] Depending on the requirements, the computing and control unit may be a standalone computer or a data processing module integrated into the controller of the robot 2.

[0129] Example 3

[0130] As attached Figure 3 An electronic device shown includes:

[0131] Processor, memory, communication interface;

[0132] The memory is used to store the executable instructions of the processor;

[0133] The processor is configured to execute the above-described automatic coordinate system calibration method for an ultrasonic testing terminal actuator by executing the executable instructions.

[0134] A readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described automatic coordinate system calibration method for an ultrasonic testing terminal actuator.

[0135] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for automatic coordinate system calibration of an ultrasonic testing terminal actuator, characterized in that, Specifically, it includes: Replace the nozzle of the ultrasonic testing terminal actuator with a vector target (3), and mount the robot (2) on the base (1); The ultrasonic testing terminal actuator is driven by the robot (2) and moves in multiple different postures within the measurement space of the laser tracker (5); Synchronously acquire the joint angle vector of the robot (2) under each posture, and the three-dimensional coordinates of the two target points (4) on the vector target (3) in the base coordinate system measured by the laser tracker (5). The direction of the line connecting the two target points (4) is collinear with the central axis of the nozzle. Based on the pose transformation matrix of the robot base coordinate system relative to the base coordinate system, and the robot's posture, calculate the pose transformation matrix of the robot flange coordinate system relative to the base coordinate system under each posture. Using the pose transformation matrix, the three-dimensional coordinates of the two target points (4) are transformed to the robot flange coordinate system; Based on the coordinates of the two target points (4) in the robot flange coordinate system, a rough estimate of the pose transformation matrix of the vector target holder (3) actuator coordinate system relative to the robot flange coordinate system is obtained, specifically including: The z-axis direction of the vector target holder (3) actuator coordinate system is determined by the coordinates of two collinear target points (4); Define the design distance of the first target point offset along the z-axis. The point after that is the origin; Project the x-axis direction vector in the flange coordinate system onto a plane perpendicular to the z-axis direction and normalize it to determine the x-axis direction of the vector target (3) actuator coordinate system; The y-axis direction of the vector target (3) actuator coordinate system is determined according to the right-hand Cartesian coordinate system rule; Based on the z-axis direction, origin coordinates, x-axis direction and y-axis direction, a rough estimate of the pose transformation matrix of the vector target (3) actuator coordinate system relative to the robot flange coordinate system is constructed; Based on a coarse estimate of the pose transformation matrix under all robot postures, a data fusion algorithm is used to calculate a precise estimate of the pose transformation matrix. The data fusion algorithm is a mean-based method, which includes: right The coordinates of the origin Take the average value to obtain the translation vector. ; ； right Rotation matrices Perform a rotational average, and calculate it using either the quaternion average method or the Lie algebra average method, to obtain the average rotation matrix. ; Combine the averaged translation vector with the averaged rotation matrix This is the accurate estimate of the pose transformation matrix: 。 2. The automatic coordinate system calibration method for an ultrasonic testing terminal actuator according to claim 1, characterized in that: The pose transformation matrix based on the robot's base coordinate system relative to the base coordinate system Calculate the pose transformation matrix of the robot flange coordinate system relative to the base coordinate system in each pose. The specific calculation formula is as follows: ； In the formula, Joint angle vector The pose of the flange coordinate system is obtained through forward kinematics calculation.

3. The automatic coordinate system calibration method for an ultrasonic testing terminal actuator according to claim 2, characterized in that: The pose transformation matrix is ​​used to transform the three-dimensional coordinates of the two target points (4) to the robot flange coordinate system. The specific calculation formula is as follows: ； ； In the formula, The three-dimensional coordinates of the first target point. The coordinates of the second target point are shown in the three-dimensional coordinates.

4. The automatic coordinate system calibration method for an ultrasonic testing terminal actuator according to claim 1, characterized in that: The data fusion algorithm, based on the mean method, uses a nonlinear optimization method to calculate an accurate estimate of the optimized pose transformation matrix, including: Using the results obtained by the mean method as initial values, a nonlinear least squares optimization problem is constructed, the objective function of which is: ； In the formula, Let be the rotation matrix to be optimized. Let be the translation vector to be optimized. and These are the fixed coordinates of the first and second target points in the target coordinate system, respectively. The objective function is solved using the Levenberg-Marquardt algorithm or the Gauss-Newton algorithm to obtain the optimal solution. and This constitutes an accurate estimate of the optimized pose transformation matrix.

5. An automatic coordinate system calibration system for implementing the automatic coordinate system calibration method for an ultrasonic testing terminal actuator as described in any one of claims 1-4, characterized in that, include: Robot (2), which has known kinematic parameters; The vector target holder (3) is detachably mounted at the nozzle of the ultrasonic terminal actuator to be calibrated, and has two collinear targets with a center distance of [missing information]. spherical reflective target point (4); A laser tracker (5) is used to capture the three-dimensional coordinates of the spherical reflective target point (4) within the measurement space; The computing and control unit, which is communicatively connected to the controller of the robot (2) and the laser tracker (5), is configured to perform the following operations: The robot (2) is controlled to move the ultrasonic detection terminal actuator to multiple preset postures, and the robot (2) posture data and target point (4) coordinate data are collected simultaneously. Perform coordinate system transformations and calculations; Based on the above-mentioned automatic coordinate system calibration method for ultrasonic testing terminal actuators, a rough estimate of the pose transformation matrix under each attitude is constructed; The data fusion algorithm is executed to calculate and output a precise estimate of the final pose transformation matrix.

6. The automatic coordinate system calibration system according to claim 5, characterized in that: The calculation and control unit also pre-stores the pose transformation matrix of the robot's base coordinate system relative to the base coordinate system, as well as the design distance.

7. The automatic coordinate system calibration system according to claim 6, characterized in that: The vector target (3) is installed by its base in conjunction with the center of the nozzle mounting position of the ultrasonic terminal actuator, ensuring that the line connecting the two target points (4) is collinear with the central axis of the nozzle.

8. The automatic coordinate system calibration system according to claim 5, characterized in that: The computing and control unit is a separate computer or a data processing module integrated into the robot (2) controller.

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