Nine-axis linkage robot welding system and welding point posture adjustment method

Abstract

The application provides a nine-axis linkage robot welding system and a welding point posture adjustment method, and relates to the technical field of industrial robot welding. The system comprises a welding device, a U-shaped double-axis turntable, a visual sensing device and a control computer; the welding device comprises a welding robot, an automatic welding main machine and an L-shaped sliding table; the method first carries out hand-eye calibration on a weld seam tracker, obtains a hand-eye calibration matrix, and transforms measurement points collected by the weld seam tracker to a robot base coordinate system in real time; then, based on the three-dimensional coordinates of the measurement points in the base coordinate system, target joint angles of the U-shaped double-axis turntable are determined; finally, the weld seam is leveled, optimal postures of each layer of weld seam are calculated according to the thick plate bevel state, and the corresponding U-shaped double-axis turntable pose angles of each layer of weld seam are determined. The method can reduce the influence of installation errors of the nine-axis linkage robot welding system and improve the weld seam feature positioning accuracy.

Description

Technical Field

[0001] This invention relates to the field of industrial robot welding technology, and in particular to a nine-axis linkage robot welding system and a method for adjusting the posture of weld points. Background Technology

[0002] In the field of compressor large component manufacturing, the extra-large air duct, as a core component of the compressor housing, directly determines the compressor's operational stability and service life through its structural dimensions and welding quality. This type of extra-large air duct measures 2500×3000mm, has a turning radius of 1500mm, and a plate thickness ranging from 16mm to 40mm. It is a typical thick-plate, large curved surface component. The welding process between the compressor housing and the inlet / outlet air duct faces numerous insurmountable technical bottlenecks due to the component's structural characteristics, welding process requirements, and current technological limitations, severely restricting production efficiency, welding quality, and product consistency.

[0003] During the welding process, three major technical bottlenecks are faced: (1) thermal deformation of components leads to failure of offline programming paths; (2) multi-layer and multi-pass welding parameters need to be adjusted manually based on experience; (3) the traditional welding gun posture adjustment is limited in a narrow space, and the processing process is mainly taught by humans to edit the robot's program, making it difficult to guarantee product consistency and welding quality. The welding process requires welding process parameters to be adjusted in real time and smoothly according to the weld shape.

[0004] To address the aforementioned welding challenges, existing technologies have proposed several improvements, but all have significant limitations and cannot meet the welding requirements of ultra-large compressor ducts. Patent CN202311491135.8 proposes a real-time adaptive weld seam tracking device and method based on laser vision. While it can instantly correct the welding path and welding torch posture based on real-time feedback from the laser vision sensor, it completely abandons offline pre-programming, lacks prior knowledge of the overall characteristics of the workpiece and the global distribution of the weld seam, and faces initial positioning difficulties. For long-distance, high-curvature weld seams in ultra-large compressor ducts, it can only rely on local sensing fields for segment-by-segment tracking, resulting in low operational efficiency and an inability to achieve autonomous identification of workpiece features and welding trajectories. Furthermore, the positioning method used in ship assembly welding (CN202410163271.2) is ill-suited to the continuously varying curvature characteristics of the compressor duct. It is evident that existing technologies either rely on one-time pre-welding planning and lack real-time process correction and compensation, or rely on pure real-time tracking and lack global trajectory priors. Neither has achieved the integration of pre-programming and real-time sensing data, making it difficult to support the robot's autonomous planning of welding paths for large and complex curved surface welds.

[0005] In summary, existing welding technologies and related improvement schemes cannot effectively solve the core technical problems in the welding process of ultra-large compressor casing and housing. There is an urgent need for a welding technology solution that can be adapted to such large variable curvature thick plate components to break through the existing technical bottlenecks, improve welding quality and production efficiency, and meet the needs of industrial-scale production. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a nine-axis linkage robot welding system and a welding point posture adjustment method, which is suitable for welding large variable curvature thick plate components.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: On one hand, the present invention provides a nine-axis linkage robot welding system, including a welding device, a U-shaped dual-axis turntable, a vision sensing device, and a control computer; The welding device includes a welding robot, an automated welding host, and an L-shaped slide table; The welding robot is a six-axis industrial robot with a vision sensor integrated at its end flange and a welding torch as the end effector, responsible for scanning the weld seam and performing welding tasks. The automated welding host provides a stable arc with deep penetration / high-speed pulses and controls welding parameters for the welding torch. The vision sensor uses a weld seam tracker to scan the weld seam of the workpiece in real time and transmits the real-time scanned weld seam image to the control computer. The welding robot is mounted on an L-shaped slide, which serves as the external linear axis of the welding robot, expanding its workspace. The U-shaped dual-axis rotary table fixes the workpiece to be processed by the clamping fixture set above. The welding robot, the L-shaped slide table and the U-shaped dual-axis rotary table move together to complete the workpiece scanning and processing motion process. The control computer is equipped with a processing monitoring system, which generates weld seam scans and welding process trajectories, and realizes the coordinated control of the welding robot, U-shaped dual-axis turntable, vision sensing device, and welding torch, as well as the coordinate transformation of the measurement points collected by the vision sensing device from the sensor coordinate system to the base coordinate system, thus completing the automated welding process of the robot.

[0008] Furthermore, the system also includes a fume extraction and dust removal system located above the welding point of the workpiece, used to absorb and remove fumes and dust generated during the welding process.

[0009] Furthermore, the welding device also includes an automatic torch cleaner located at the end flange of the welding robot. The automatic torch cleaner automatically cleans the welding torch under the control of the welding host.

[0010] On the other hand, the present invention also provides a method for adjusting the posture of solder joints, comprising the following steps: Step 1: Perform hand-eye calibration on the weld seam tracker to obtain the hand-eye calibration matrix; Step 2: Based on the hand-eye calibration matrix, transform the measurement points collected by the weld seam tracker to the robot base coordinate system in real time; Step 3: Based on the three-dimensional coordinates of the measurement points in the base coordinate system, determine the target joint angles of the U-shaped dual-axis turntable, including the target tilt joint angles and the target rotation joint angles; Step 4: Level the weld seam, calculate the optimal posture for each layer of weld seam according to the bevel condition of the thick plate, and then determine the U-shaped dual-axis turntable posture angle corresponding to each layer of weld seam.

[0011] Furthermore, the specific method for performing hand-eye calibration on the weld seam tracker in step 1 to obtain the hand-eye calibration matrix is ​​as follows: Step 1.1: Data Acquisition; A cylindrical workpiece is fixed on a U-shaped dual-axis turntable. The end effector of the welding robot is controlled to weld the workpiece along a fixed straight line. At N different positions and postures, the weld seam tracker scans the cylindrical workpiece, collects 2D cross-sectional point cloud data, and simultaneously records the pose matrix set of the end flange in the base coordinate system at each moment. , Indicates the position number. ; Step 1.2: Determine the initial set of center points in the sensor coordinate system based on 2D cross-sectional point cloud data; For the 2D cross-sectional point cloud data at each location, the Y and Z coordinates of the point cloud are extracted. The coordinates of the center of the cross-sectional ellipse where the laser intersects the cylinder at each location are obtained using a direct ellipse fitting algorithm based on least squares. This yields the initial set of center points in the sensor coordinate system. ; Step 1.3: Determine the set of center points of the cylindrical section in the robot base coordinate system based on the initial set of center points in the sensor coordinate system; Set up the hand-eye calibration matrix The initial estimate is obtained by estimating the hand-eye calibration matrix of the initial center points in the sensor coordinate system. The corresponding pose matrix is ​​mapped to the base coordinate system to obtain the set of center points in the base coordinate system. ; Step 1.4: Perform three-dimensional spatial straight line fitting and error calculation on the set of center points of the cylindrical section in the base coordinate system of the robot base; Pair set Calculate the centroid And construct the covariance matrix : ; Perform eigenvalue decomposition on the covariance matrix and take the eigenvector corresponding to the largest eigenvalue as the direction vector of the spatial line. Then calculate the point set. The average Euclidean distance from all the center points of the circle to the fitted line is used as the objective function value, i.e., the error value. Step 1.5: Perform nonlinear optimization iterative solution on the objective function and output the final hand-eye calibration matrix; Using the average Euclidean distance from each center point in the set of center points in the base coordinate system to the fitted line as the objective function, the hand-eye calibration matrix is ​​iteratively solved using a simplex nonlinear optimization algorithm. The parameters are calculated until convergence, and the final hand-eye calibration matrix is ​​output.

[0012] Furthermore, the specific method for step 2, which transforms the measurement points collected by the weld seam tracker to the robot base coordinate system in real time based on the hand-eye calibration matrix, is as follows: (1) Read the current virtual tool pose matrix from the robot controller Transformation matrix of the preset nominal tool After inverting the equation and multiplying it on the right, the nominal tool offset is removed to obtain the true physical pose of the flange in the base coordinate system. ; Inverting the preset nominal tool transformation matrix yields the inverse transformation matrix. And multiply it by the currently read virtual tool pose matrix. This allows us to extract the pure physical pose matrix of the robot flange in the base coordinate system. ; (2) Determine the actual physical pose of the flange in the base coordinate system. With hand-eye calibration matrix Multiplying these values ​​yields the precise pose of the optical origin of the weld seam tracker in the base coordinate system. : ; (3) Precise pose of the optical origin of the weld seam tracker in the base coordinate system The coordinates of the measurement points collected by the weld seam tracker Perform a homogeneous coordinate transformation and output the three-dimensional coordinates of the measured points in the base coordinate system. : .

[0013] Furthermore, the specific method for determining the target joint angle of the U-shaped dual-axis turntable based on the three-dimensional coordinates of the measurement points in the base coordinate system in step 3 is as follows: Establish a description from the world coordinate system Welding points on the workpiece The complete coordinate transformation chain of the normal vector, which sequentially contains the turntable transformation matrix. and workpiece installation transformation matrix And it acts on the solder joint normal vector. ; The zero-position convention for the nine-axis linkage robot welding system is set as follows: the tilt axis E2 is parallel to the world axis X, the rotation axis E3 is parallel to the world axis Z, and the workpiece installation rotation angle is... The two transformation matrices are: (The matrix is ​​not provided in the original text.) ; ; in, This represents a rotation matrix formed by rotating about an axis by a certain angle. Represents the translation matrix. This represents the translational offset of the workpiece on the U-shaped dual-axis rotary table; The complete transformation chain acting on the solder joint normal vector is shown in the following formula: ; in, World coordinate system The surface normal vector of the solder joint below. A rotation matrix formed by rotating around the X-axis and Z-axis by a certain angle; Will Substitute the complete transformation chain of the solder joint normal vector, and denote it as... Furthermore, the unified kinematic model equations of the nine-axis linkage robot welding system are obtained: ; ; ; Based on the optimal welding posture conditions, the target tilt joint angle that the U-shaped dual-axis turntable must achieve to satisfy the optimal welding posture conditions is calculated in reverse according to the unified kinematic model equation. and target rotational joint angle .

[0014] Furthermore, the specific method for step 4, which calculates the optimal posture for each weld layer based on the bevel condition of the thick plate, and then determines the U-shaped dual-axis turntable posture angle corresponding to each weld layer, is as follows: Level the weld seam and determine the world coordinate system based on the bevel condition of the thick plate. The surface normal vector of the solder joint below , The normal direction of the weld seam after leveling, which is the highest point in the Z-direction of the current weld layer welding point in the world coordinate system of the current workpiece. and For the normal direction in the world coordinate system x , z The unit normal vector component in the direction is shown in the following formula: ; ; set up The U-shaped dual-axis turntable pose angles corresponding to each layer of weld after weld leveling are shown in the following formula: ; .

[0015] in, , J This represents the number of weld layers.

[0016] The beneficial effects of adopting the above technical solution are as follows: The nine-axis linkage robot welding system and the three-dimensional coordinate calibration method for weld seams provided by this invention only require an ordinary cylinder as a calibration target for hand-eye calibration, without the need for a high-precision calibration plate, and there are no requirements for the placement of the cylinder, making the calibration operation simple; by adopting a nonlinear optimization method based on collinearity constraints, the six-degree-of-freedom transformation matrix between the vision sensing device and the flange coordinate system can be accurately solved, resulting in high calibration accuracy and good repeatability. The coordinate transformation is achieved through a two-step chain calculation of explicitly stripping the nominal tool offset and superimposing the accurate hand-eye calibration matrix, eliminating the influence of installation errors on measurement accuracy, and realizing real-time and accurate mapping of weld seam feature points from the vision sensing device coordinate system to the robot base coordinate system. Attached Figure Description

[0017] Figure 1 This is an overall structural diagram of the nine-axis linkage robot welding system provided in the first embodiment of the present invention; Figure 2 A schematic diagram of the installation of the welding robot, its end-effector, and weld seam tracker provided in the first embodiment of the present invention; Figure 3 This is a flowchart of the automated welding process for robots provided in the first embodiment of the present invention; Figure 4 The second embodiment of the present invention provides a 2D cross-sectional point cloud data map of a cylinder collected by a weld seam tracking instrument for calibration scanning. Figure 5 This is a theoretical layered sequence diagram of a multi-layer, multi-pass weld seam provided in the second embodiment of the present invention; Figure 6 This is a diagram showing the actual layered sequence of a multi-layered, multi-pass weld seam provided in the second embodiment of the present invention.

[0018] In the diagram: 1. U-shaped dual-axis rotary table; 2. Clamping fixture; 3. L-shaped slide table; 4. Welding robot; 5. Automatic torch cleaner; 6. Welding torch; 7. Vision sensor; 8. Wire feeding mechanism. Detailed Implementation

[0019] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0020] First embodiment: In this embodiment, a nine-axis linkage robot welding system is provided to meet the welding space and degree-of-freedom requirements of thick plate and large curved surface components, such as... Figure 1 As shown, it consists of a high-performance welding device, a U-shaped dual-axis turntable 1, a vision sensing device 7, a smoke and dust removal system, and a control computer; In this embodiment, the welding device consists of a welding robot 4, a CLOOS A500FG automated welding host, an automatic torch cleaner 5, and an L-shaped slide table 3.

[0021] like Figure 2 As shown, welding robot 4 is a KUKA KR 8 R2100-2_arc_HW 260kg six-axis industrial robot. Its end flange integrates a vision sensor and is equipped with a professional welding torch 6 and a wire feeding mechanism 8 as end effectors, precisely responsible for scanning and welding the workpiece's weld seam. The CLOOS A500FG automated welding host provides a stable arc and welding parameter control for the welding torch 6, with deep penetration / high-speed pulses. The vision sensor 7 transmits the real-time scanned weld seam image to the control computer. In this embodiment, the vision sensor 7 uses a weld seam tracker to scan the workpiece's weld seam in real time. Welding robot 4 is mounted on an L-shaped slide 3, which serves as the external linear axis of the welding robot, expanding its workspace. In this embodiment, the U-shaped dual-axis rotary table 1 fixes the workpiece to be processed by the clamping fixture 2 set above it. The welding robot, the L-shaped slide table 3 and the U-shaped dual-axis rotary table 1 move together to complete the workpiece scanning and processing motion process. In this embodiment, the clamping fixture 2 adopts a separate three-jaw self-centering chuck to fix the workpiece to be processed.

[0022] The control computer is equipped with a processing monitoring system, which generates weld seam scans and welding process trajectories, and realizes the coordinated control of the welding robot, U-shaped dual-axis turntable 1, vision sensing device 7, and welding torch 6, as well as the coordinate transformation of the measurement points collected by vision sensing device 7 from the sensor coordinate system to the base coordinate system, thus completing the automated welding process of the robot.

[0023] In this embodiment, the fume extraction and dust removal system is located 200mm above the welding point and is used to absorb and remove fumes and dust during the welding process; the automatic torch cleaner 5 is located at the end flange of the welding robot and automatically cleans the welding torch through the control of the welding host.

[0024] Second embodiment: In this embodiment, a weld point posture adjustment method is provided. Applying this method can reduce the impact of installation errors in a nine-axis linkage robot welding system, improve weld feature positioning accuracy, and provide a conversion method for optimizing welding paths through system pre-programming and real-time sensor data fusion. Figure 3 As shown, it includes the following steps: Step 1: Perform hand-eye calibration on the weld seam tracker to obtain the hand-eye calibration matrix; Step 1.1: Data Acquisition; A cylindrical workpiece is fixed on a U-shaped dual-axis turntable. The end effector of the welding robot is controlled to weld the workpiece along a fixed straight line. At N different positions and attitudes, the weld seam tracker scans the cylindrical workpiece, collecting 2D cross-sectional point cloud data, such as... Figure 4 As shown, the set of pose matrices of the end flange in the base coordinate system at each time point is recorded synchronously. , Indicates the position number. .

[0025] Step 1.2: Determine the initial set of center points in the sensor coordinate system based on 2D cross-sectional point cloud data; For the 2D cross-sectional point cloud data at each location, since the contour of the intersection of the line laser and the cylinder is an ellipse, the Y and Z coordinates of the point cloud are extracted (the X direction in the cross-sectional data output by the sensor is zero, i.e., the two-dimensional coordinates within the scanned cross-section). The center coordinates of the cross-sectional ellipse at each location where the line laser intersects the cylinder are calculated and recorded using a direct ellipse fitting algorithm based on least squares (Y and Z components in the sensor coordinate system, with the X component set to zero), thus obtaining the initial set of center points in the sensor coordinate system. .

[0026] Step 1.3: Determine the set of center points of the cylindrical section in the base coordinate system of the robot base based on the initial set of center points in the sensor coordinate system.

[0027] Set up the hand-eye calibration matrix The initial estimated values ​​(obtained through manual measurement) are used to estimate the hand-eye calibration matrix of the initial center points in the sensor coordinate system. The corresponding pose matrix is ​​mapped to the base coordinate system to obtain the set of center points in the base coordinate system. Since all scanned sections are taken from the same cylinder, the set of center points... Theoretically, all the center points of the circle should be strictly collinear.

[0028] In this embodiment, the hand-eye calibration matrix from the sensor to the flange to be determined is denoted as . (Including six parameters: three-dimensional coordinates X, Y, Z and three Euler angles A, B, C for spatial transformation). For the current iteration Calculate the spatial coordinates of each initial center point in the sensor coordinate system in the robot base coordinate system: ; This yields the set of center points of the cylindrical cross-section in the robot's base coordinate system. .

[0029] Step 1.4: Perform three-dimensional spatial straight line fitting and error calculation on the set of center points of the cylindrical section in the base coordinate system of the robot base; Since the calibration process involves scanning the same cylinder along its axial direction, theoretically all the center points of the cylindrical cross-sections... They should be strictly collinear in three-dimensional space. For a set of points... Calculate the centroid (Mean point), and construct the covariance matrix. : ; Perform eigenvalue decomposition on the covariance matrix and take the eigenvector corresponding to the largest eigenvalue as the direction vector of the spatial line. Then calculate the point set. The average Euclidean distance from all the center points of the circle to the fitted line is used as the objective function value (i.e., the error value).

[0030] Step 1.5: Perform nonlinear optimization iterative solution for the objective function and output the final hand-eye calibration matrix.

[0031] The objective function is the average Euclidean distance from the center points of the circle in the base coordinate system to the fitted line. A simplex nonlinear optimization algorithm is used to iteratively solve this problem. The six parameters are used until convergence, and the final hand-eye calibration matrix is ​​output.

[0032] In this embodiment, the initial estimated value of the hand-eye calibration matrix (obtained by manually measuring the optical center of the sensor and the flange) is imported. A simplex nonlinear optimization algorithm is used to continuously iterate and update the algorithm with the goal of minimizing the "average distance error of line fitting" in step 1.4. The six parameters; when the iteration step size meets the convergence threshold or reaches the maximum number of iterations, the final hand-eye calibration matrix parameters are output.

[0033] Step 2: Based on the hand-eye calibration matrix of the weld seam tracker, transform the measurement points collected by the weld seam tracker to the robot base coordinate system in real time; Obtain the final hand-eye calibration matrix Then, during the weld seam scanning stage, the measurement points collected by the weld seam tracker are transformed in real time to the robot base coordinate system according to the following steps: (1) Read the current virtual tool pose matrix from the robot controller Transformation matrix of the preset nominal tool After inverting the equation and multiplying it on the right, the nominal tool offset is removed to obtain the true physical pose of the flange in the base coordinate system. ; The virtual tool pose matrix currently output by the robot system It is determined by the actual position of the flange. Transformation matrix with preset nominal tool Composed of superpositions and combinations, thus satisfying the following relation: To eliminate interference from coarse nominal tool settings, the preset nominal tool transformation matrix is ​​inverted to obtain the inverse transformation matrix. And multiply it by the currently read virtual tool pose matrix. This allows us to extract the pure physical pose matrix of the robot flange in the base coordinate system. The calculation formula is as follows: ; (2) Determine the actual physical pose of the flange in the base coordinate system. With hand-eye calibration matrix Multiplying these values ​​yields the precise pose of the optical origin of the weld seam tracker in the base coordinate system. : ; (3) Precise pose of the optical origin of the weld seam tracker in the base coordinate system The coordinates of the measurement points collected by the weld seam tracker Perform a homogeneous coordinate transformation and output the three-dimensional coordinates of the measured points in the base coordinate system. : ; The above three steps are performed in real time when each frame of scan data arrives, and the output is... This refers to the absolute physical coordinates of the weld after removing installation errors. These absolute physical coordinates of the weld are the welding points on the workpiece, and are used for subsequent welding path planning and adjustment.

[0034] Step 3: Based on the three-dimensional coordinates of the measurement points in the base coordinate system, determine the target joint angles of the U-shaped dual-axis turntable, including the target tilt joint angles and the target rotation joint angles; Establish a unified kinematic model for a nine-axis linkage robot welding system: Establish a model describing the kinematics of the system from the world coordinate system. Welding points on the workpiece A complete coordinate transformation chain for the normal vector, which contains at least the following two transformation matrices in sequence and applies to the solder joint normal vector: Turntable transformation matrix A tilting joint angle E2 of a U-shaped dual-axis turntable and rotational joint angle E3 The coordinate system determined by the turntable base To the world coordinate system The transformation matrix.

[0035] Workpiece installation transformation matrix A coordinate system describing the workpiece Relative to the coordinate system of the turntable base The transformation matrix of the mounting pose, which includes the translational offset of the workpiece on the U-shaped dual-axis turntable. and rotation offset .

[0036] Solder joint normal vector In the workpiece coordinate system The known surface normal vector of the point to be welded is given from the world coordinate system. Welding points on the workpiece The target of the complete coordinate transformation chain of the normal vector.

[0037] In this embodiment, the zero position of the nine-axis linkage robot welding system is defined as follows: the tilt axis E2 is parallel to the world axis X, the rotation axis E3 is parallel to the world axis Z, and the workpiece installation rotation angle is... The two transformation matrices are: (The matrix is ​​not provided in the original text.) ; ; in, This represents a rotation matrix formed by rotating about an axis by a certain angle. This represents the translation matrix.

[0038] The complete transformation chain acting on the solder joint normal vector is shown in the following formula: ; in, World coordinate system The surface normal vector of the solder joint below. A rotation matrix formed by rotating around the X-axis and Z-axis by a certain angle; Will Substitute the complete transformation chain of the solder joint normal vector, and denote it as... Expanding the above equation yields the unified kinematic model equation for a nine-axis linkage robot welding system: ; ; ; Solving the joint angle of the U-shaped dual-axis turntable: Based on the optimal welding posture conditions, the target tilt joint angle that the U-shaped dual-axis turntable must achieve to satisfy the optimal welding posture conditions is calculated in reverse according to the unified kinematic model equations. and target rotational joint angle ; The optimal welding posture condition is a process requirement, namely, the current welding point of the workpiece is the highest point in the Z direction of the world coordinate system, and the cutting plane is horizontal at this time. Therefore, we obtain the following system of equations: ; ; The target tilt joint angle and target rotation joint angle are further obtained as shown in the following formulas: ; ; Step 4: Level the weld seam, calculate the optimal posture for each layer of weld seam according to the bevel condition of the thick plate, and then determine the U-shaped dual-axis turntable posture angle corresponding to each layer of weld seam. Thick plate welding involves the arrangement of multiple layers and multiple passes of welding parameters, such as... Figure 5 As shown. Due to factors such as misalignment and irregular surfaces, actual weld seams require adjustments and calculations for each weld layer based on the bevel condition, such as... Figure 6 As shown, the inverse kinematics of the target tilt joint angle and target rotation joint angle of the U-shaped dual-axis turntable needs to be embedded in a multi-layer, multi-pass arrangement process. The calculation of the optimal posture of each weld needs to be calculated separately as the groove morphology changes, ultimately forming an inter-layer turntable posture angle sequence. , J This represents the number of weld layers.

[0039] Level the weld seam and determine the world coordinate system based on the bevel condition of the thick plate. The surface normal vector of the solder joint below , The normal direction of the weld seam after leveling, which is the highest point in the Z-direction of the current weld layer welding point in the world coordinate system of the current workpiece. and Let X be the unit normal vector components in the x and z directions of the world coordinate system, as shown in the following formula: ; ; The position angles of each turntable after weld leveling are shown in the following formula: ; ; After the weld seam is leveled, there are 4 sets of solutions to the turntable position angle equations for each layer. The current set of turntable position angles is selected according to the joint stroke limit and the rule of being close to the current position angle.

[0040] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the present invention.

Claims

1. A nine-axis linkage robot welding system, characterized in that, It includes welding equipment, a U-shaped dual-axis turntable, a vision sensing device, and a control computer; The welding device includes a welding robot, an automated welding host, and an L-shaped slide table; The welding robot is a six-axis industrial robot with a vision sensor integrated at its end flange and a welding torch as the end effector, responsible for scanning the weld seam and performing welding tasks. The automated welding host provides a stable arc with deep penetration / high-speed pulses and controls welding parameters for the welding torch. The vision sensor uses a weld seam tracker to scan the weld seam of the workpiece in real time and transmits the real-time scanned weld seam image to the control computer. The welding robot is mounted on an L-shaped slide, which serves as the external linear axis of the welding robot, expanding its workspace. The U-shaped dual-axis rotary table fixes the workpiece to be processed by the clamping fixture set above. The welding robot, the L-shaped slide table and the U-shaped dual-axis rotary table move together to complete the workpiece scanning and processing motion process. The control computer is equipped with a processing monitoring system, which generates weld seam scans and welding process trajectories, and realizes the coordinated control of the welding robot, U-shaped dual-axis turntable, vision sensing device, and welding torch, as well as the coordinate transformation of the measurement points collected by the vision sensing device from the sensor coordinate system to the base coordinate system, thus completing the automated welding process of the robot.

2. The nine-axis linkage robot welding system according to claim 1, characterized in that, The system also includes a fume extraction and dust removal system located above the welding point of the workpiece, used to absorb and remove fumes and dust during the welding process.

3. The nine-axis linkage robot welding system according to claim 1, characterized in that, The welding device also includes an automatic torch cleaner located at the end flange of the welding robot. The automatic torch cleaner automatically cleans the welding torch under the control of the welding host.

4. A method for adjusting the posture of a weld point, implemented based on the nine-axis linkage robot welding system described in claim 1, characterized in that, Includes the following steps: Step 1: Perform hand-eye calibration on the weld seam tracker to obtain the hand-eye calibration matrix; Step 2: Based on the hand-eye calibration matrix, transform the measurement points collected by the weld seam tracker to the robot base coordinate system in real time; Step 3: Based on the three-dimensional coordinates of the measurement points in the base coordinate system, determine the target joint angles of the U-shaped dual-axis turntable, including the target tilt joint angles and the target rotation joint angles; Step 4: Level the weld seam, calculate the optimal posture for each layer of weld seam according to the bevel condition of the thick plate, and then determine the U-shaped dual-axis turntable posture angle corresponding to each layer of weld seam.

5. The solder joint posture adjustment method according to claim 4, characterized in that, The specific method for obtaining the hand-eye calibration matrix in step 1, which involves hand-eye calibration of the weld seam tracker, is as follows: Step 1.1: Data Acquisition; A cylindrical workpiece is fixed on a U-shaped dual-axis turntable. The end effector of the welding robot is controlled to weld the workpiece along a fixed straight line. At N different positions and postures, the weld seam tracker scans the cylindrical workpiece, collects 2D cross-sectional point cloud data, and simultaneously records the pose matrix set of the end flange in the base coordinate system at each moment. , Indicates the position number. ; Step 1.2: Determine the initial set of center points in the sensor coordinate system based on 2D cross-sectional point cloud data; For the 2D cross-sectional point cloud data at each location, the Y and Z coordinates of the point cloud are extracted. The coordinates of the center of the cross-sectional ellipse where the laser intersects the cylinder at each location are obtained using a direct ellipse fitting algorithm based on least squares. This yields the initial set of center points in the sensor coordinate system. ; Step 1.3: Determine the set of center points of the cylindrical section in the robot base coordinate system based on the initial set of center points in the sensor coordinate system; Set up the hand-eye calibration matrix The initial estimate is obtained by estimating the hand-eye calibration matrix of the initial center points in the sensor coordinate system. The corresponding pose matrix is ​​mapped to the base coordinate system to obtain the set of center points in the base coordinate system. ; Step 1.4: Perform three-dimensional spatial straight line fitting and error calculation on the set of center points of the cylindrical section in the base coordinate system of the robot base; Pair set Calculate the centroid And construct the covariance matrix : ； Perform eigenvalue decomposition on the covariance matrix and take the eigenvector corresponding to the largest eigenvalue as the direction vector of the spatial line. Then the point set is calculated. The average Euclidean distance from all the center points of the circle to the fitted line is used as the objective function value, i.e., the error value. Step 1.5: Perform nonlinear optimization iterative solution on the objective function and output the final hand-eye calibration matrix; Using the average Euclidean distance from each center point in the set of center points in the base coordinate system to the fitted line as the objective function, the hand-eye calibration matrix is ​​iteratively solved using a simplex nonlinear optimization algorithm. The parameters are calculated until convergence, and the final hand-eye calibration matrix is ​​output.

6. The solder joint posture adjustment method according to claim 5, characterized in that, The specific method for step 2, which transforms the measurement points collected by the weld seam tracker to the robot base coordinate system in real time based on the hand-eye calibration matrix, is as follows: (1) Read the current virtual tool pose matrix from the robot controller Transformation matrix of the preset nominal tool After inverting the equation and multiplying it on the right, the nominal tool offset is removed to obtain the true physical pose of the flange in the base coordinate system. ; Inverting the preset nominal tool transformation matrix yields the inverse transformation matrix. And multiply it by the currently read virtual tool pose matrix. This allows us to extract the pure physical pose matrix of the robot flange in the base coordinate system. ; (2) Determine the actual physical pose of the flange in the base coordinate system. With hand-eye calibration matrix Multiplying these values ​​yields the precise pose of the optical origin of the weld seam tracker in the base coordinate system. : ； (3) Precise pose of the optical origin of the weld seam tracker in the base coordinate system The coordinates of the measurement points collected by the weld seam tracker Perform a homogeneous coordinate transformation and output the three-dimensional coordinates of the measured points in the base coordinate system. : 。 7. The solder joint posture adjustment method according to claim 6, characterized in that, The specific method for determining the target joint angle of the U-shaped dual-axis turntable based on the three-dimensional coordinates of the measurement points in the base coordinate system in step 3 is as follows: Establish a description from the world coordinate system Welding points on the workpiece The complete coordinate transformation chain of the normal vector, which sequentially contains the turntable transformation matrix. and workpiece installation transformation matrix And it acts on the solder joint normal vector. ; The zero-position convention for the nine-axis linkage robot welding system is set as follows: tilt axis E2 is parallel to the world axis X, rotation axis E3 is parallel to the world axis Z, and the workpiece mounting rotation angle is... The two transformation matrices are: (The matrix is ​​not provided in the original text.) ； ； in, This represents a rotation matrix formed by rotating about an axis by a certain angle. Represents the translation matrix. This represents the translational offset of the workpiece on the U-shaped dual-axis rotary table. The complete transformation chain acting on the solder joint normal vector is shown in the following formula: ； in, World coordinate system The surface normal vector of the solder joint below. A rotation matrix formed by rotating around the X-axis and Z-axis by a certain angle; Will Substitute the complete transformation chain of the solder joint normal vector, and denote it as... Furthermore, the unified kinematic model equations of the nine-axis linkage robot welding system are obtained: ； ； ； Based on the optimal welding posture conditions, the target tilt joint angle that the U-shaped dual-axis turntable must achieve to satisfy the optimal welding posture conditions is calculated in reverse according to the unified kinematic model equation. and target rotational joint angle .

8. The solder joint posture adjustment method according to claim 7, characterized in that, The specific method for step 4, which calculates the optimal posture for each weld layer based on the bevel condition of the thick plate, and then determines the U-shaped dual-axis turntable posture angle corresponding to each weld layer, is as follows: Level the weld seam and determine the world coordinate system based on the bevel condition of the thick plate. The surface normal vector of the solder joint below , The normal direction of the weld seam after leveling, which is the highest point in the Z-direction of the current weld layer welding point in the world coordinate system of the current workpiece. and For the normal direction in the world coordinate system x , z The unit normal vector component in the direction is shown in the following formula: ； ； set up The U-shaped dual-axis turntable pose angles corresponding to each layer of weld after weld leveling are shown in the following formula: ； ； in, , J This represents the number of weld layers.

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