Robot partition machining method and system for large-size feature machining of spherical shell component

Abstract

The invention discloses a robot partition machining method and system for large-size feature machining of a spherical shell component, solves the problem that an ultra-large square hole with the size exceeding the working space of a robot cannot be machined, and belongs to the field of robot application. The method is achieved based on in-situ robot machining equipment, and a large-size square hole to be machined is divided into a plurality of machining subareas; the multiple machining partitions at the same height are divided into the same layer, and shared robot installation position parameters are set for the multiple machining partitions on the same layer and comprise the installation polar diameter and the installation polar angle of the robot on the side wall of the arch mechanism; establishing a multi-station optimization model by taking a robot rigidity performance index and a base counter-force index as objective functions and taking a robot mounting position parameter and an arch mechanism rotation angle as decision variables; the multi-station optimization model is solved, and optimal robot station parameters of each layer are obtained; and the robot is installed according to the optimal robot station parameters, and square hole machining is completed according to the partition machining program of each layer.

Description

Technical Field

[0001] This invention relates to a robotic partitioning machining method and system for machining large-size features of spherical shell components, belonging to the field of robotic applications. Background Technology

[0002] The ability to process ultra-large parts is a key issue in the manufacturing industry. Traditional methods for processing ultra-large workpieces mainly involve using large-scale, customized machine tools or adjusting the workpiece clamping position, which suffers from high processing costs, complex processes, and low yield rates. Industrial robots, due to their large workspace and high flexibility, are very suitable for processing these structural parts. Furthermore, by rationally designing the hole-opening process, both efficiency and processing quality can be guaranteed.

[0003] Many innovative methods have been proposed for machining holes in ultra-large spherical components, and several technological innovations have been achieved. For example, CN120619438A proposes a method for on-site measurement, positioning, and machining of large spherical shell components. This method employs a rotary arch-shaped on-site machining system and establishes a three-dimensional spatial coordinate system for the spherical shell. A laser tracker is used to measure and establish the connection between the three-dimensional coordinate systems to guide the robot machining. Another example is CN120619438A, which proposes a precision in-situ machining equipment and method for ultra-large components. An arch-shaped rotary machining equipment is designed for ultra-large spherical tank components, ensuring the component remains in its installation position and reducing transportation costs. While these solutions all address hole machining in large spherical shells, the hole size does not exceed the robot's machining space, and the impact of the robot's position on machining quality is not considered. Summary of the Invention

[0004] To address the problem that ultra-large square holes cannot be processed due to their size exceeding the robot's workspace, this invention provides a robot-based partitioned machining method and system for machining large-size features of spherical shell components.

[0005] This invention discloses a robotic partitioning processing method for large-size feature processing of spherical shell components. The method is based on an in-situ robotic processing device, which includes an arch mechanism (4), an industrial robot (5), and a mounting bracket (6). The arch mechanism (4) is mounted on a foundation (2), and the rotation center axis of the arch mechanism (4) coincides with the foundation axis and can rotate around the axis. The industrial robot (5) is fixed to the side wall of the arch mechanism (4) via the mounting bracket (6), and its mounting position on the arch mechanism (4) is adjustable. The processing method includes:

[0006] S1. Divide the large square hole to be processed into multiple processing zones and set the splicing area between the zones;

[0007] S2. Divide multiple processing zones at the same height into the same layer, and set shared robot installation position parameters for multiple processing zones in the same layer. The installation position parameters include the robot's installation polar diameter and installation polar angle on the side wall of the arch mechanism.

[0008] S3. Using the robot stiffness performance index and the base reaction force index as objective functions, and the robot installation position parameters and the rotation angle of the arch mechanism as decision variables, a multi-station optimization model is established.

[0009] S4. Solve the multi-station optimization model to obtain the optimal robot station parameters for each layer;

[0010] S5. Install the robot according to the optimal robot positioning parameters, and complete the square hole machining according to the machining program of each layer.

[0011] As a preferred option, in S4, a multi-objective mantis search algorithm is used to solve the multi-station optimization model, and the Powerball gradient method is introduced into the multi-objective mantis search algorithm to accelerate convergence. The Powerball gradient method is applied to the exploration and development phases of the multi-objective mantis search algorithm. In the exploration phase, when an ambush or pursuit strategy is adopted, the position update in the ambush strategy is as follows:

[0012]

[0013] in, , The first The mantis in the first generation and first The position in the middle, For interval Random values ​​within, For the largest algebra, As the best solution at present, A solution randomly selected from the current population. For the Poweraball gradient method; Represents the Hadamard product of two vectors;

[0014] The position in the pursuit strategy is updated as follows:

[0015]

[0016] in, Generated by levy flight, For values ​​that follow a standard normal distribution, It is a binary vector. as well as This represents a randomly generated value, ranging from 0 to 1, and is immediately adjacent to the given value. For interval Random values ​​within, and A solution randomly selected from the current population;

[0017] During the development phase, the location is updated as follows:

[0018]

[0019] in, This is the best overall solution for the current stage. This refers to the mantis's attack speed.

[0020] As a preferred option, the multi-station optimization model search space satisfies the robot installation position constraints and the rotation constraints of the arch mechanism;

[0021] Establish a mounting surface reference coordinate system with the mounting surface design center as the origin. The robot mounting position constraint is that the robot mounting position parameters within the mounting surface reference coordinate system satisfy the following:

[0022]

[0023] in, It is the installation polar diameter corresponding to the robot's installation position in polar coordinates. It is the installation polar angle corresponding to the robot's installation position in polar coordinates. The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates and These are the inner and outer radii of the mounting surface, respectively. and These represent the minimum and maximum angular constraints for the site design, respectively.

[0024] The rotation constraint of the arched mechanism is that the rotation angle of the arched mechanism in the robot's base coordinate system satisfies the following:

[0025]

[0026] in, The rotation angle of the arched mechanism. An auxiliary angle used to describe changes in stance posture. For the chord length, To stand in the robot's base coordinate system The change in direction To stand in the robot's base coordinate system Change in direction For the rotation of the station position around the direction in the robot's base coordinate system, The radius of the center of rotation of the arched mechanism is... The offset between the rotation center and the mounting surface design center is specified. Robot base coordinate system The angle between the direction and the line connecting the center of rotation of the arched mechanism. , It is the arctangent function.

[0027] As a preferred option, the search space of the multi-station optimization model satisfies both kinematic and collision constraints;

[0028] The kinematic constraints are expressed as follows:

[0029]

[0030] in, For robot kinematic constraints, , , Indicates the number of degrees of freedom of the robot. The trace of the matrix, It is a Jacobian matrix; For the robot's first Each joint angle , , They are respectively The minimum and maximum values;

[0031] The collision constraints are:

[0032] .

[0033] As a preferred option, the robot installation position parameters and the rotation angle of the arch mechanism are obtained. Homogeneous transformation matrix from robot base coordinate system to robot flange coordinate system :

[0034]

[0035] in, Let be the homogeneous transformation matrix from the robot's base coordinate system to the workpiece coordinate system. The homogeneous transformation matrix from the workpiece coordinate system to the machining task coordinate system is programmed. Let be the homogeneous transformation matrix from the robot flange coordinate system to the tool coordinate system. This is the homogeneous transformation matrix from the tool coordinate system to the workpiece coordinate system; To stand in the robot's base coordinate system The change in direction To stand in the robot's base coordinate system Change in direction The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The angle of rotation for the arched mechanism.

[0036] Alignment transformation matrix Inverse kinematics is performed to obtain the robot joint angles corresponding to each station. Based on these robot joint angles, the robot stiffness performance index and the base reaction force index are calculated.

[0037] As a preferred option, the robot's stiffness performance indicators are:

[0038]

[0039] in, , This represents the stiffness of the robot in a single posture during the execution of the machining path. , Represents the force-displacement matrix. This represents the weighted relationship between the mathematical expectation and the standard deviation of robot stiffness.

[0040] As a preferred option, the base reaction force index is:

[0041]

[0042] in, The base reaction force represents the robot's reaction force in a single posture. , and All are weighting coefficients. The L2 norm of a vector. This represents the constraint reaction force provided by the base to the robot's first link. This is represented as the constraint reaction torque provided by the base to the robot's first link.

[0043] As a preferred option, during machining, for the first machining section, a reverse feed method opposite to the milling path direction is adopted;

[0044] For other machining zones, the forward feed method is adopted, taking advantage of the spatial conditions created by the previous machining.

[0045] As a preferred method, a combination of long and short blades is used in the machining process:

[0046] Roughing tasks use a combination of short and long overhanging tools for milling grooves; finishing tasks use long overhanging tools for milling edges.

[0047] The beneficial effects of this invention are as follows: by rationally dividing the processing zones and setting splicing areas, it solves the problems of the square hole size to be processed exceeding the robot's working space and preventing insufficient or over-cutting, while ensuring that there is still room for tool entry in the next zone; by establishing a robot multi-station optimization model with an embedded hierarchical station parameter sharing mechanism, aiming at the collaborative optimization of the mutually constraining robot stiffness and base reaction force, it can determine the installation position for each station that optimizes the overall performance of the system, thereby improving the processing accuracy; by accelerating the convergence of the algorithm through the Pb-MOMSA algorithm; and by combining long and short tools, differentiated tool entry strategies, and a roughing-to-finishing processing scheme, it improves the surface quality of the processed material. Attached Figure Description

[0048] Figure 1 Schematic diagram of an in-situ robotic machining system for spherical shells;

[0049] Figure 2 Flowchart for solving the multi-station robot design model embedded in the hierarchical station parameter sharing mechanism;

[0050] Figure 3 A schematic diagram showing the division and splicing areas for processing extra-large square holes;

[0051] Figure 4 Schematic diagram of the inner support baffle of an extra-large square hole;

[0052] Figure 5 This is a schematic diagram of the coordinate system of the robot machining system;

[0053] Figure 6 This is a schematic diagram of a hierarchical station parameter sharing mechanism;

[0054] Figure 7 Schematic diagram of tool infeed methods for machining trajectories in different zones;

[0055] Figure 8 This is a schematic diagram of the machining areas using roughing, finishing, and long / short cutting tools. Detailed Implementation

[0056] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0058] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the scope of the invention.

[0059] This embodiment describes a robotic partitioning machining method for machining large-size features of spherical shell components. This method is implemented using an in-situ robotic machining device, such as... Figure 1 As shown, it includes an arched mechanism 4, an industrial robot 5, a mounting bracket 6, a calibration column 7, a laser tracker measurement system 8, and a support baffle 9;

[0060] The center of the spherical shell 1 is located on the reference axis of the foundation 2. The geometric center of the square hole 3 passes through the center of the spherical shell 1, and the length and width of the square hole 3 are parallel and perpendicular to the reference axis of the foundation 2, respectively. The arched mechanism 4 is installed on the foundation, and its rotation center axis coincides with the axis of the foundation 2, and it can rotate around this coincident axis. The industrial robot 5 is fixed to the arched mechanism 4 by the mounting bracket 6. The calibration column 7 and the laser tracker measurement system 8 are both set on the foundation to accurately locate the installation position and calibrate the robot's basic coordinate system and the workpiece coordinate system used for processing. The middle part of the support baffle along the processing contour of the square hole is fixed to the inner wall of the spherical shell by welding. The middle part of its length is welded along the processing contour of the square hole, thereby providing an upward auxiliary support force for the intermediate material during the cutting process and preventing the material from sagging or falling off due to its own weight.

[0061] The robot partitioning processing method of this embodiment includes:

[0062] Step 1: Divide the large square hole to be processed into multiple processing zones and set the splicing area between the zones;

[0063] For machining ultra-large square holes, an orthogonal grid is used to divide the machining area and a splicing process is implemented. Support baffles are welded inside the square holes to address the limitations of the robot's workspace and prevent tool jamming caused by scrap material. Specifically, for machining ultra-large square holes, an in-situ robotic machining system for spherical shells is established. Relevant system and machining parameters are determined. The square hole length L is 3200mm, and the square hole width D is 2200mm. The square hole is evenly divided into four areas—machining zone 1, machining zone 2, machining zone 3, and machining zone 4—in a clockwise direction, and barriers are set between each zone. A 50mm overlapping area for the processing path is provided, and a support baffle is welded inside the square hole. A 50mm wide overlapping area for the processing path is set between each adjacent section to eliminate the undercut phenomenon that may occur during the splicing of the sections.

[0064] like Figure 4 As shown, a support baffle is welded inside the square hole. The support baffle 9 is a long strip of steel plate.

[0065] Step 2: Divide multiple processing zones at the same height into the same layer, and set shared robot installation position parameters for multiple processing zones on the same layer. The installation position parameters include the robot's installation polar diameter and installation polar angle on the side wall of the arch mechanism.

[0066] The layered station position parameter sharing mechanism in this step divides the processing area at the same height into layers, and each layer's stations share the same robot installation position, i.e. and The values ​​are the same to reduce the number of times the robot needs to be installed;

[0067] Step 3: Using the robot stiffness performance index and the base reaction force index as objective functions, and the robot installation position parameters and the rotation angle of the arch mechanism as decision variables, establish a multi-station optimization model;

[0068] The constraints are the robot mounting position constraint on the side wall of the arched mechanism, and the rotation constraint, kinematic constraint, and collision constraint of the arched mechanism.

[0069] Specifically, the robot mounting position constraint on the side wall of the arched mechanism and the rotation constraint of the arched mechanism are determined by establishing robot coordinate systems in two orthogonal reference planes, which together determine the robot's position on the arched structure; the robot mounting position constraint is determined by polar coordinate parameters. Defined as follows: with the center of the mounting surface design as the origin, the XOZ plane of the mounting surface design center reference coordinate system represents the robot's station search space, expressed as:

[0070]

[0071] in, It is the polar radius corresponding to the robot's installation position in polar coordinates. It is the polar angle corresponding to the robot's installation position in polar coordinates. The robot installation position is based on the design center of the installation surface. Directional coordinates The robot installation position is based on the design center of the installation surface. Directional coordinates and These are the inner and outer radii of the mounting surface, respectively. and These represent the minimum and maximum angular constraints of the station design, respectively.

[0072] The rotational constraint of the arched mechanism is determined by polar coordinate parameters. Defined as follows: with the rotation center as the reference datum for the robot's stationary search space, the robot's stationary search space is represented in the XOY plane of the robot's base coordinate system as:

[0073]

[0074] in, The rotation angle of the arched mechanism. An auxiliary angle used to describe changes in stance posture. For the chord length, To stand in The change in direction To stand in Change in direction To position around Rotation of direction The radius of the center of rotation of the arched mechanism is... The offset between the rotation center and the mounting surface design center is specified. Robot base coordinate system The angle between the direction and the line connecting the rotation center of the arched mechanism is used to describe the change in robot's standing posture, and is defined by the following formula:

[0075] ,

[0076] in, It is the arctangent function.

[0077] The kinematic constraints are expressed as follows:

[0078] ,

[0079] ,

[0080] in, To constrain the robot's kinematics and avoid singularities, the calculation method is as follows:

[0081] ,

[0082] ,

[0083] Where n represents the number of robot degrees of freedom, tr() is the trace of the matrix, and J N It is a Jacobian matrix;

[0084] Collision constraints can be expressed as:

[0085] Based on the robot's installation position constraints on the sidewall of the arched mechanism and the rotation constraints of the arched mechanism, a mathematical model of the robot's station search space is established and integrated into the system coordinate transformation chain. Finally, the robot's joint angles are solved in a unified Cartesian coordinate system; specifically, as shown... Figure 5The diagram shows the system coordinate transformation relationships. {BASE} represents the robot base coordinate system, located at the bottom of robot joint 1; {R6} represents the robot flange coordinate system; {TCP} represents the tool coordinate system, which is related to the end effector structure and tool length; {WP} represents the workpiece coordinate system; and {CL} is the programming coordinate system of the machining program, with the center of the sphere as its origin.

[0086] By transforming coordinates, the robot's installation position parameters and the rotation angle of the arch mechanism are obtained. Homogeneous transformation matrix from robot base coordinate system to robot flange coordinate system :

[0087]

[0088] in, Let be the homogeneous transformation matrix from the robot's base coordinate system to the workpiece coordinate system. The homogeneous transformation matrix from the workpiece coordinate system to the machining task coordinate system is programmed. Let be the homogeneous transformation matrix from the robot flange coordinate system to the tool coordinate system. This is the homogeneous transformation matrix from the tool coordinate system to the workpiece coordinate system; the robot base coordinate system is located at the bottom of robot joint 1; and the angles of each joint are solved using robot inverse kinematics. :

[0089] ;

[0090] Alignment transformation matrix Inverse kinematics is performed to obtain the robot joint angles corresponding to each station. Based on these robot joint angles, the robot stiffness performance index and the base reaction force index are calculated.

[0091] Robot stiffness reflects the weak rigidity of its structure. Increasing the robot's stiffness helps improve its resistance to deformation and vibration, thereby improving processing quality. The specific calculation formula is as follows:

[0092]

[0093] in, , representing the stiffness corresponding to the discrete postures of the robot during the execution of the machining path, where , representing the rigidity of the robot in a single posture, in the formula Represents the force-displacement matrix. This represents the weighted relationship between the mathematical expectation and the standard deviation of robot stiffness.

[0094] The base reaction force is the main cause of deformation in flexible mounting bases. Suppressing the base reaction force helps improve the accuracy of the robot's end effector, thereby improving machining accuracy. The specific calculation formula is as follows:

[0095] ,

[0096] in, The base reaction force representing the robot in a single posture is calculated as follows:

[0097] ,

[0098] in, and These are all weighting coefficients to ensure uniformity of magnitude. The L2 norm of a vector. This represents the constraint reaction force provided by the base to the robot's first link. This is represented as the constraint reaction torque provided by the base to the robot's first link.

[0099] Step 4: Solve the multi-station optimization model to obtain the optimal robot station parameters for each layer;

[0100] A multi-station robot optimization model with an embedded hierarchical station parameter sharing mechanism, based on the maximum robot stiffness performance of all robot stations in each layer ( ) and minimum base reaction force ( Using the objective function , and the constraints of robot installation position, arch mechanism rotation angle, robot kinematics, and collision angle, the decision variables for each layer are output. , and Value, assuming there are k stations in the nth layer, the objective function of the optimization model for this layer is expressed as:

[0101] ;

[0102] Step 5: Install the robot according to the optimal robot positioning parameters, and complete the square hole machining according to the machining program of each layer.

[0103] This implementation uses the multi-objective mantis search algorithm to solve the multi-station optimization model, and introduces the Powerball gradient method into the multi-objective mantis search algorithm to accelerate convergence;

[0104] The Powerball gradient method is applied in the exploration and development phases of MOMSA. The exploration phase employs an ambush or pursuit strategy. The ambush strategy simulates a stealthy predator attack, represented as:

[0105] ,

[0106] in, For the i-th generation mantis in the first... The position in the middle, For interval Random values ​​within, For the largest algebra, As the best solution at present, A solution randomly selected from the current population. The function of the Poweraball gradient method is expressed as: ,in, For the original gradient, For symbolic functions, Powerball is the exponent. Represents the Hadamard product of two vectors;

[0107] The pursuit strategy simulates the active pursuit of a hunting predator, and is represented as:

[0108] ,

[0109] in, Generated by levy flight, For values ​​that follow a standard normal distribution, It is a binary vector. as well as This represents a randomly generated value, ranging from 0 to 1, and is immediately adjacent to the given value. For interval Random values ​​within, and A solution randomly selected from the current population;

[0110] During the development phase, the behavior of a praying mantis capturing its prey is simulated as follows:

[0111] ,

[0112] in, This is the best overall solution for the current stage. This refers to the mantis's attack speed.

[0113] Solve the multi-objective station design optimization model embedded in the hierarchical station parameter sharing mechanism, obtain multiple Pareto solutions, and use TOPSIS for decision-making to determine the robot station parameters corresponding to each layer one by one;

[0114] The machining process employs a combination of long and short cutters, a differentiated feed strategy, and a roughing-to-finish approach. Computer-aided manufacturing software is used to develop the cutting process plan and generate machining programs for all stations. Specifically, an indexable three-tooth end mill can be selected, with a tool diameter of... The diameter of the tool holder is 40mm. The diameter is 32mm, with a 4mm clearance on one side to facilitate chip removal and prevent collisions during deep processing.

[0115] The differentiated tool infeed strategy in this embodiment is as follows: Since the first machining zone lacks tool infeed space, a reverse tool infeed method, opposite to the milling path direction, is used in the first machining zone. Other zones utilize the space created by previous machining operations and employ a forward tool infeed method. For example... Figure 7 As shown, the tool infeed methods for different machining zones are differentiated. Due to the lack of tool infeed space in machining zone 1, a reverse tool infeed method opposite to the milling path direction is adopted in machining zone 1. Other zones utilize the space conditions formed by previous machining and adopt a forward tool infeed method. At the same time, in order to reduce the dynamic impact load generated during the tool infeed process, a cutting feed rate of 50% is adopted in the tool infeed stage.

[0116] The combination of long and short tools in this embodiment is specifically as follows: for roughing tasks, short and long overhanging tools are used in combination for milling grooves; for finishing tasks, long overhanging tools are used for milling edges. For example... Figure 8 As shown, the roughing task uses short and long overhanging tools for slot milling. The depth of cut and width of cut of the long and short tools are 0.5 mm and 40 mm, and 1 mm and 40 mm, respectively, and the feed rate is 30 mm / s. The finishing task uses a long overhanging tool for edge milling. The depth of cut and width of cut of the long tool are 3 mm and 3 mm, respectively, and the feed rate is 15 mm / s.

[0117] Finally, a laser tracker was used to accurately locate the installation position of the station and calibrate the basic coordinate system of the robot and the workpiece coordinate system used for processing. All station processing was completed and the baffle was removed.

[0118] This embodiment also provides a robotic partitioning machining system for machining large-size features of spherical shell components, including an in-situ robotic machining device, at least one storage device, at least one processor, and a computer program stored in the storage device and executable on the processor. When the processor executes the computer program, it implements the steps of the robotic partitioning machining method of this embodiment. The robotic partitioning machining system of this embodiment, through the coordinated work of the hardware system and the software program, successfully solves the problems of insufficient robot workspace and inconsistent machining quality across multiple stations in the machining of ultra-large square holes, achieving efficient, high-precision, and high-quality automated machining of spherical shell components.

[0119] To verify the acceleration convergence capability of the Powerball gradient method, Table 1 presents a comparison of the acceleration capabilities of the Powerball gradient method and the default method, based on the specific implementation methods described above. Key evaluation metrics include convergence algebra and computation time. It is evident that the Powerball gradient method can achieve effective acceleration in the optimization algorithm, and the acceleration effect is even better in the second layer of optimization compared to the first layer.

[0120] Table 1 Comparison of acceleration capabilities using the Powerball gradient method

[0121]

[0122] To verify whether the method of using an industrial robot for multi-station, zoned machining of ultra-large square holes in spherical shells meets the manufacturing accuracy and surface quality requirements for such ultra-large local features, the manufacturing accuracy was analyzed based on hole size and position deviations. The following analysis method was developed: The inner surface coordinates of the square hole were measured using a laser tracker 8. Four planes (upper, lower, left, and right) were fitted, generating the center planes of the upper and lower planes and the left and right planes respectively. The intersection axis of two planes was found, and this axis intersects with the theoretical surface of the spherical shell to determine a positioning reference point. The coordinates of this point in the X and Y directions in the workpiece coordinate system {WP} were measured. The size deviation was then analyzed. The positional deviation is (-0.1800, 0.1765). The values ​​are (0.2114, -0.1007), which is better than the standard of dimensional accuracy less than 0.20 mm and positional accuracy better than 0.22 mm. The surface quality of the machined surface was analyzed from the contour error, surface angle error and adjacent angle error of each surface. The specific values ​​are shown in Table 2, and a relatively consistent overall surface quality of the machined surface was obtained.

[0123] Table 2 Statistical results of machining errors on each plane of the square hole

[0124]

[0125] Based on the above principles, a set of optimal station parameters for improving robot processing quality can be obtained through a series of calculations. This determines the robot's installation position on the arched mechanism, reduces the impact of vibration and base reaction force caused by insufficient robot processing rigidity on robot processing, and improves the surface quality of the processed material through a combination of long and short tools, differentiated tool feed strategies, and a roughing-then-finishing processing scheme.

[0126] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A robotic partitioning machining method for machining large-size features of spherical shell components, characterized in that, The method is based on an in-situ robotic processing device, which includes an arch mechanism (4), an industrial robot (5), and a mounting bracket (6). The arch mechanism (4) is installed on a foundation (2), and the rotation center axis of the arch mechanism (4) coincides with the foundation axis and can rotate around the axis. The industrial robot (5) is fixed to the side wall of the arch mechanism (4) through the mounting bracket (6), and its installation position on the arch mechanism (4) is adjustable. The processing method includes: S1. Divide the large square hole to be processed into multiple processing zones and set the splicing area between the zones; S2. Divide multiple processing zones at the same height into the same layer, and set shared robot installation position parameters for multiple processing zones in the same layer. The installation position parameters include the robot's installation polar diameter and installation polar angle on the side wall of the arched mechanism. S3. Using the robot stiffness performance index and the base reaction force index as objective functions, and the robot installation position parameters and the rotation angle of the arch mechanism as decision variables, a multi-station optimization model is established. S4. Solve the multi-station optimization model to obtain the optimal robot station parameters for each layer; S5. Install the robot according to the optimal robot positioning parameters and complete the square hole machining according to the machining program of each layer.

2. The robot partitioning processing method according to claim 1, characterized in that, In S4, a multi-objective mantis search algorithm is used to solve the multi-station optimization model, and the Powerball gradient method is introduced into the multi-objective mantis search algorithm to accelerate convergence. The Powerball gradient method is applied to the exploration and development phases of the multi-objective mantis search algorithm. In the exploration phase, when an ambush or pursuit strategy is adopted, the position update in the ambush strategy is as follows: in, , The first The mantis in the first generation and first The position in the middle, For interval Random values ​​within, For the largest algebra, As the best solution at present, A solution randomly selected from the current population. For the Poweraball gradient method; Represents the Hadamard product of two vectors; The position in the pursuit strategy is updated as follows: in, Generated by levy flight, For values ​​that follow a standard normal distribution, It is a binary vector. as well as This represents a randomly generated value, ranging from 0 to 1, and is immediately adjacent to the given value. For interval Random values ​​within, and A solution randomly selected from the current population; During the development phase, the location is updated as follows: in, This is the best overall solution for the current stage. This refers to the mantis's attack speed.

3. The robot partitioning processing method according to claim 1, characterized in that, The search space of the multi-station optimization model satisfies the robot installation position constraints and the rotation constraints of the arch mechanism. Establish a mounting surface reference coordinate system with the mounting surface design center as the origin. The robot mounting position constraint is that the robot mounting position parameters within the mounting surface reference coordinate system satisfy the following: in, It is the installation polar diameter corresponding to the robot's installation position in polar coordinates. It is the installation polar angle corresponding to the robot's installation position in polar coordinates. The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates and These are the inner and outer radii of the mounting surface, respectively. and These represent the minimum and maximum angular constraints for the site design, respectively. The rotation constraint of the arched mechanism is that the rotation angle of the arched mechanism in the robot's base coordinate system satisfies the following: in, The rotation angle of the arched mechanism. An auxiliary angle used to describe changes in stance posture. For the chord length, To stand in the robot's base coordinate system The change in direction To stand in the robot's base coordinate system Change in direction For the rotation of the station position around the direction in the robot's base coordinate system, The radius of the center of rotation of the arched mechanism is... The offset between the rotation center and the mounting surface design center is specified. Robot base coordinate system The angle between the direction and the line connecting the center of rotation of the arched mechanism. , It is the arctangent function.

4. The robot partitioning processing method according to claim 1, characterized in that, The search space of the multi-station optimization model satisfies kinematic constraints and collision constraints; The kinematic constraints are expressed as follows: in, For robot kinematic constraints, , , Indicates the number of degrees of freedom of the robot. The trace of the matrix, It is a Jacobian matrix; For the robot's first Each joint angle , , They are respectively The minimum and maximum values; The collision constraint is: 。 5. The robot partitioning processing method according to claim 1, characterized in that, In S3, the robot's installation position parameters and the rotation angle of the arch mechanism are obtained through coordinate transformation. Homogeneous transformation matrix from robot base coordinate system to robot flange coordinate system : in, Let be the homogeneous transformation matrix from the robot's base coordinate system to the workpiece coordinate system. The homogeneous transformation matrix from the workpiece coordinate system to the machining task coordinate system is programmed. Let be the homogeneous transformation matrix from the robot flange coordinate system to the tool coordinate system. This is the homogeneous transformation matrix from the tool coordinate system to the workpiece coordinate system; To stand in the robot's base coordinate system The change in direction To stand in the robot's base coordinate system Change in direction The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The robot's installation position in the mounting surface reference coordinate system is... Directional coordinates The rotation angle of the arched mechanism; Alignment transformation matrix Inverse kinematics is performed to obtain the robot joint angles corresponding to each station. Based on these robot joint angles, the robot stiffness performance index and base reaction force index are calculated.

6. The robot partitioning processing method according to claim 1, characterized in that, The robot's stiffness performance indicators are: in, , This represents the stiffness of the robot in a single posture during the execution of the machining path. , Represents the force-displacement matrix. This represents the weighted relationship between the mathematical expectation and the standard deviation of robot stiffness.

7. The robot partitioning processing method according to claim 1, characterized in that, The base reaction force index is: in, The base reaction force represents the robot's reaction force in a single posture. , and All are weighting coefficients. The L2 norm of a vector. This represents the constraint reaction force provided by the base to the robot's first link. This represents the constraint reaction torque provided by the base to the robot's first link.

8. The robot partitioning processing method according to claim 1, characterized in that, During machining, for the first machining section, a reverse feed method is used that is opposite to the direction of the milling path; For other machining zones, the forward feed method is adopted by utilizing the spatial conditions formed by the previous machining.

9. The robot partitioning processing method according to claim 8, characterized in that, A machining method combining long and short blades is employed. Roughing tasks use a combination of short and long overhanging tools for milling grooves; finishing tasks use long overhanging tools for milling edges.

10. A robotic partitioning machining system for machining large-size features of spherical shell components, comprising the in-situ robotic machining equipment, a storage device, a processor, and a computer program stored in the storage device and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the robot partitioning processing method as described in any one of claims 1 to 9.

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