Intelligent bending digital twin system

Abstract

The application is suitable for the technical field of intelligent control of bending processing, and provides an intelligent bending digital twin system, which comprises a physical entity unit, a digital twin virtual unit, a data interaction unit, a process simulation optimization unit and an intelligent decision control unit; in the application, the bending machine, the industrial robot, the multifunctional gripper, the feeding rack, the centering table and the discharging rack can be cooperatively operated under the unified data link through the cooperation of the physical entity unit, the digital twin virtual unit and the data interaction unit, the digital twin virtual unit can synchronously display the equipment position, the plate material transfer state and the processing progress, compared with the traditional single machine operation mode, the problems of invisible equipment state, non-intuitive action cooperation and difficult fault positioning are reduced, and the stability and maintenance convenience of the bending production process are improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for bending processes, and particularly relates to an intelligent bending digital twin system. Background Technology

[0002] Bending is an important process in sheet metal forming. It usually relies on bending machines to bend the sheet metal and manual or robotic loading and unloading. In automated production scenarios, bending machines, industrial robots, grippers, feeding equipment, centering equipment and unloading equipment mostly operate independently. The coordination between each piece of equipment mainly relies on on-site debugging, manual teaching and single-machine program control. Before processing, it is necessary to repeatedly set the bending sequence, robot trajectory and gripper clamping position according to different workpieces.

[0003] Existing bending processes suffer from problems such as long debugging cycles, difficulties in equipment communication adaptation, the need for repeated on-site teaching of robot trajectories, and untimely feedback on bending quality in multi-variety, small-batch production. It is also difficult to form a unified data loop between the bending machine and auxiliary equipment, resulting in limited processing efficiency, stability, and quality control capabilities. Summary of the Invention

[0004] This invention provides an intelligent bending digital twin system, which aims to solve the problems mentioned in the background art.

[0005] The present invention is implemented as follows: an intelligent bending digital twin system includes a physical entity unit, a digital twin virtual unit, a data interaction unit, a process simulation and optimization unit, and an intelligent decision control unit;

[0006] The physical entity unit includes a bending machine, an industrial robot, a multi-functional gripper, a feeding rack, a centering platform, a discharge rack, and a vision inspection module. The industrial robot is connected to the multi-functional gripper and is used to transfer sheet metal between the feeding rack, the centering platform, the bending machine, and the discharge rack. The vision inspection module is used to collect processing quality data of the workpiece after bending.

[0007] The digital twin virtual unit is used to establish a three-dimensional virtual model corresponding to the physical entity unit, and to form a virtual processing scene based on the operating status of the physical entity unit.

[0008] The data interaction unit is connected to the physical entity unit, the digital twin virtual unit, the process simulation optimization unit, and the intelligent decision control unit, respectively. It is used to collect equipment operation data, sheet material parameter data, and processing status data, and to perform protocol adaptation, format conversion, and fusion processing.

[0009] The process simulation and optimization unit is used to import workpiece drawings, generate bending process programs, multi-functional gripper positioning parameters and industrial robot motion trajectories, and perform virtual simulation verification.

[0010] The intelligent decision control unit is used to receive data verified by virtual simulation and generate control commands to drive the physical entity unit to complete automatic bending processing.

[0011] Preferably, the digital twin virtual unit includes a model building module, a state mapping module, and a virtual display module;

[0012] The model building module is used to create a three-dimensional virtual model based on the equipment dimensions, installation position and motion parameters of the bending machine, industrial robot, multi-functional gripper, feeding rack, centering platform and discharge rack.

[0013] The state mapping module is connected to the data interaction unit and is used to receive the stroke data of the bending machine, the posture data of the industrial robot, the clamping state data of the multi-functional gripper, and the processing position data of the sheet metal.

[0014] The virtual display module is used to synchronously display the processing actions and operating status of the physical entity unit based on the data received by the status mapping module.

[0015] Preferably, the state mapping module matches the data of the bending machine slider position, industrial robot joint angle, multi-functional gripper clamping opening and closing state, sheet material transfer position, and processing progress with the corresponding three-dimensional virtual model according to the timestamp, so that the three-dimensional virtual model displays synchronous actions according to the actual running sequence of the physical entity units.

[0016] Preferably, the data interaction unit includes a data acquisition module, a protocol adaptation module, a data fusion module, and a data distribution module;

[0017] The data acquisition module collects pressure, stroke, alarm and processing status data of the bending machine, position, posture and trajectory execution data of the industrial robot, and workpiece inspection data fed back by the vision inspection module.

[0018] The protocol adaptation module is used to convert the communication data between the bending machine, industrial robot, vision inspection module and digital twin virtual unit.

[0019] The data fusion module is used to uniformly process equipment operation data, sheet material parameter data, and processing status data;

[0020] The data distribution module is used to send the processed data to the digital twin virtual unit, the process simulation optimization unit, and the intelligent decision control unit, respectively.

[0021] Preferably, the process simulation optimization unit includes a drawing import and parsing module, a bending programming module, a gripper positioning and planning module, a robot trajectory planning module, and a simulation verification module;

[0022] The drawing import and parsing module is used to import workpiece drawings and parse the sheet material, sheet thickness, dimensions, bending angle, and bending position.

[0023] The bending programming module is used to generate bending sequence, bending pressure and bending stroke based on the analysis results;

[0024] The gripper positioning and planning module is used to generate the clamping position and clamping posture of the multi-functional gripper based on the workpiece's external dimensions and bending position.

[0025] The robot trajectory planning module is used to generate the motion trajectory of the industrial robot during the processes of picking up materials from the feeding rack, positioning the centering platform, loading and unloading materials from the bending machine, and unloading materials from the discharge rack.

[0026] The simulation verification module is used to perform virtual simulation verification of bending sequence, gripper holding posture and industrial robot motion trajectory.

[0027] Preferably, the bending programming module is the CADMAN-B bending programming module, and the gripper positioning and planning module, robot trajectory planning module, and simulation verification module are the CADMAN-SIM simulation modules;

[0028] The CADMAN-B bending programming module generates bending machine processing programs based on workpiece drawings, while the CADMAN-SIM simulation module generates multi-functional gripper positioning parameters and collision-free motion trajectories for industrial robots based on workpiece shape, workpiece size, and bending sequence.

[0029] Preferably, the simulation verification module sequentially simulates the process of industrial robot picking up materials, multi-functional gripper holding, centering platform positioning, bending machine bending, detection position stopping and material unloading from the discharge rack in the virtual processing scenario, and identifies robot trajectory interference, workpiece posture deviation, gripper holding position deviation and bending parameter deviation that occur during the simulation.

[0030] The process simulation optimization unit corrects the bending process, multi-functional gripper positioning parameters, and industrial robot motion trajectory based on the identification results, and sends the corrected data to the intelligent decision control unit.

[0031] Preferably, the visual detection module includes an image acquisition component and a detection feedback component;

[0032] The image acquisition component is used to acquire the contour image, edge image, or bending area image of the workpiece after bending.

[0033] The detection feedback component is used to obtain workpiece size accuracy data and bending angle data based on the contour image, edge image, or bending area image, and then send the workpiece size accuracy data and bending angle data to the intelligent decision control unit via the data interaction unit.

[0034] Preferably, the intelligent decision control unit includes an instruction conversion module, an offline execution module, an exception handling module, and a human-machine collaboration module;

[0035] The instruction conversion module is used to convert the bending process program, multi-functional gripper positioning parameters and industrial robot motion trajectory output by the process simulation optimization unit into bending machine control instructions, industrial robot control instructions and multi-functional gripper control instructions.

[0036] The offline execution module is used to invoke the control commands to drive the physical entity unit to run automatically without on-site teaching;

[0037] The anomaly handling module is used to generate process parameter adjustment instructions or shutdown warning instructions based on equipment alarm data, workpiece size accuracy data and bending angle data.

[0038] The human-machine collaboration module is used to receive manual intervention instructions and correct the current processing flow or processing parameters according to the manual intervention instructions.

[0039] Preferably, the anomaly handling module includes a bending deviation evaluation model, which calculates a comprehensive deviation value based on the dimensional accuracy data, bending angle data, and actual execution data of the bending machine fed back by the visual inspection module. The comprehensive deviation value The following relationship must be satisfied:

[0040]

[0041] in, The actual bending angle detected by the vision inspection module. The target bending angle generated by the process simulation optimization unit. The actual side length dimension detected by the vision inspection module. The target side length dimension generated for the process simulation optimization unit. The actual operating pressure of the bending machine. The target bending pressure generated for the bending programming module. , , These are the weighting coefficients for angular deviation, dimensional deviation, and pressure deviation, respectively.

[0042] When the comprehensive deviation value When the deviation exceeds a preset threshold, the anomaly handling module sends a process parameter correction instruction to the instruction conversion module. The instruction conversion module then corrects the bending pressure, bending stroke, industrial robot material handling point, centering and feeding point, or bending feeding point of the subsequent workpiece according to the process parameter correction instruction.

[0043] Compared with related technologies, the intelligent bending digital twin system provided by this invention has the following beneficial effects:

[0044] 1. In this invention, through the cooperation of physical entity units, digital twin virtual units and data interaction units, bending machines, industrial robots, multi-functional grippers, feeding racks, centering platforms and unloading racks can operate collaboratively under a unified data link. The digital twin virtual units can synchronously display equipment positions, sheet material transfer status and processing progress. Compared with the traditional single-machine operation mode, it reduces the problems of invisible equipment status, unintuitive action coordination and difficulty in fault location, and improves the stability and maintenance convenience of the bending production process.

[0045] 2. In this invention, the workpiece drawing is imported through the process simulation optimization unit, and bending process program, multi-functional gripper positioning parameters and industrial robot motion trajectory are generated. This allows the bending sequence, gripper posture and robot trajectory to be verified in a virtual processing scenario before processing, reducing on-site manual teaching and repeated trial bending and debugging processes. It is especially suitable for bending processing of multiple varieties and small batches of sheet metal, which can shorten changeover time and improve production efficiency and processing adaptability.

[0046] 3. In this invention, a processing quality feedback link is formed by a vision inspection module, a data interaction unit, and an intelligent decision control unit. The vision inspection module can collect the dimensional accuracy data and bending angle data of the workpiece after bending. The anomaly handling module combines the bending deviation evaluation model to judge the processing deviation and corrects the bending pressure, bending stroke, and robot position of the subsequent workpiece. Compared with the method of relying solely on manual sampling inspection, the bending quality control accuracy and automated closed-loop adjustment capability are improved. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the overall system architecture and data flow of the present invention;

[0048] Figure 2 This is a schematic diagram illustrating the mapping relationship between the physical entity units and the digital twin virtual units of this invention;

[0049] Figure 3 This is a schematic diagram of the automatic bending process of the present invention;

[0050] Figure 4 This is a schematic diagram of the data interaction unit and control command transmission of the present invention;

[0051] Figure 5 This is a schematic diagram of the bending deviation evaluation and closed-loop correction process of the present invention. Detailed Implementation

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0053] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0054] Example 1

[0055] A preferred embodiment of the intelligent bending digital twin system provided by the present invention is as follows: Figures 1 to 5 As shown: An intelligent bending digital twin system includes a physical entity unit, a digital twin virtual unit, a data interaction unit, a process simulation and optimization unit, and an intelligent decision control unit. The physical entity unit includes a bending machine, an industrial robot, a multi-functional gripper, a feeding rack, a centering platform, a discharge rack, and a vision inspection module. The industrial robot is connected to the multi-functional gripper and is used to transfer sheet metal between the feeding rack, the centering platform, the bending machine, and the discharge rack. The vision inspection module is used to collect processing quality data of the workpiece after bending.

[0056] In this embodiment, the feeding rack is used to carry the sheet material to be processed. The industrial robot drives the multi-functional gripper to grab the sheet material from the feeding rack and transport the sheet material to the centering platform for positioning and calibration. After centering, the sheet material is sent to the processing position of the bending machine. The bending machine completes the bending action according to the bending pressure, bending stroke and bending sequence issued by the intelligent decision control unit. The bent workpiece is then transferred by the industrial robot to the unloading rack or the inspection position.

[0057] In a further preferred embodiment of the present invention, the digital twin virtual unit is used to establish a three-dimensional virtual model corresponding to the bending machine, industrial robot, multi-functional gripper, feeding rack, centering platform and unloading rack, and to form a virtual processing scene according to the operating status of the physical entity unit.

[0058] In this embodiment, the digital twin virtual unit establishes a virtual model based on the size, installation position, motion stroke and motion parameters of each device. The data interaction unit transmits the position of the bending machine slider, the joint angle of the industrial robot, the opening and closing state of the multi-functional gripper and the transfer position of the sheet metal to the digital twin virtual unit, so that the virtual model can be displayed synchronously according to the actual operation process of the physical entity unit.

[0059] In a further preferred embodiment of the present invention, the data interaction unit is connected to the physical entity unit, the digital twin virtual unit, the process simulation optimization unit, and the intelligent decision control unit, respectively, and is used to collect equipment operation data, sheet material parameter data, and processing status data, and to perform protocol adaptation, format conversion, and fusion processing.

[0060] In this embodiment, the data interaction unit collects pressure, stroke, alarm and processing status data of the bending machine, position, posture and trajectory execution data of the industrial robot, and detection data fed back by the vision inspection module. Data generated by different devices are adapted to form a unified data format after protocol adaptation, and then sent to the digital twin virtual unit, process simulation optimization unit and intelligent decision control unit according to their purpose.

[0061] In a further preferred embodiment of the present invention, the process simulation optimization unit is used to import workpiece drawings, generate bending process programs, multi-functional gripper positioning parameters and industrial robot motion trajectories, and perform virtual simulation verification.

[0062] In this embodiment, after importing the workpiece drawing, the process simulation optimization unit analyzes the material, thickness, size, bending angle and bending position of the sheet metal to generate the bending sequence, bending pressure and bending stroke. At the same time, it determines the clamping position and clamping posture of the multi-functional gripper based on the shape of the workpiece and the bending position, and plans the motion trajectory of the industrial robot in the process of picking up, centering, feeding and unloading materials.

[0063] In a further preferred embodiment of the present invention, the intelligent decision control unit is used to receive the bending process program verified by virtual simulation, the positioning parameters of the multi-functional gripper and the motion trajectory of the industrial robot, and generate control commands to drive the physical entity unit to complete the automatic bending process.

[0064] In this embodiment, the intelligent decision control unit converts the data output by the process simulation optimization unit into control commands for the bending machine, industrial robot, and multi-functional gripper, enabling the bending machine, industrial robot, and multi-functional gripper to operate according to the simulated and verified paths and parameters, thereby reducing on-site teaching and repeated debugging processes.

[0065] Example 2

[0066] Based on Embodiment 1, a preferred embodiment of the intelligent bending digital twin system provided by the present invention is as follows: Figures 1 to 3 As shown: The process simulation optimization unit includes a drawing import and parsing module, a bending programming module, a gripper positioning and planning module, a robot trajectory planning module, and a simulation verification module. The intelligent decision control unit includes an instruction conversion module, an offline execution module, an exception handling module, and a human-machine collaboration module.

[0067] In this embodiment, the drawing import and parsing module identifies the sheet material, sheet thickness, dimensions, bending angle, and bending position in the workpiece drawing. The bending programming module generates a bending machine processing program based on the parsing results. The gripper positioning and planning module determines the clamping point based on the workpiece size and bending position. The robot trajectory planning module generates the continuous motion trajectory of the industrial robot from the feeding rack to the unloading rack.

[0068] In a further preferred embodiment of the present invention, the bending programming module is the CADMAN-B bending programming module, and the gripper positioning and planning module, the robot trajectory planning module, and the simulation verification module are the CADMAN-SIM simulation module.

[0069] In this embodiment, the CADMAN-B bending programming module is used to generate the bending sequence, bending pressure, and bending stroke, while the CADMAN-SIM simulation module is used to generate the multi-functional gripper positioning parameters and the collision-free motion trajectory of the industrial robot. The simulation verifies the material picking, clamping, centering, bending, detection position dwell, and material unloading processes in a virtual processing scenario.

[0070] In a further preferred embodiment of the present invention, the visual inspection module includes an image acquisition component and a detection feedback component. The image acquisition component is used to acquire the contour image, edge image, or bending area image of the workpiece after bending. The detection feedback component is used to acquire workpiece dimensional accuracy data and bending angle data.

[0071] In this embodiment, the vision inspection module sends the inspection results to the intelligent decision control unit via the data interaction unit. The anomaly handling module judges the processing status based on the equipment alarm data, workpiece size accuracy data, and bending angle data. When the inspection results exceed the preset allowable range, it generates a process parameter adjustment command or a shutdown warning command.

[0072] In a further preferred embodiment of the present invention, the anomaly handling module is equipped with a bending deviation evaluation model, which calculates a comprehensive deviation value based on the dimensional accuracy data, bending angle data, and actual execution data of the bending machine fed back by the visual inspection module. .

[0073] In this embodiment, the comprehensive deviation value satisfy ,in The actual bending angle detected by the vision inspection module. The target bending angle generated by the process simulation optimization unit. The actual side length dimension detected by the vision inspection module. The target side length dimension generated for the process simulation optimization unit. The actual operating pressure of the bending machine. The target bending pressure generated for the bending programming module. , , These are the weighting coefficients for angular deviation, dimensional deviation, and pressure deviation, respectively. When the comprehensive deviation value E is greater than the preset deviation threshold, the anomaly handling module sends a correction instruction to the instruction conversion module, so that the bending pressure, bending stroke, industrial robot picking point, centering and feeding point, or bending feeding point of the subsequent workpiece are corrected.

[0074] In summary, during system operation, the feeding rack in the physical unit is used to place the sheet metal to be processed. The industrial robot is connected to the multi-functional gripper, which, driven by the industrial robot, picks up the sheet metal from the feeding rack and transports it to the centering platform for positioning and calibration. After centering, the industrial robot continues to feed the sheet metal into the processing position of the bending machine. The bending machine executes the bending action according to the bending pressure, bending stroke, and bending sequence issued by the intelligent decision control unit. After bending, the workpiece is transferred by the industrial robot to the inspection position or the unloading rack. The vision inspection module acquires images of the workpiece contour, edge lines, or bending area, and obtains dimensional accuracy data and bending data. The data interaction unit collects pressure, stroke, alarm, and processing status data of the bending machine, position, posture, and trajectory execution data of the industrial robot, and detection data fed back by the vision inspection module throughout the entire processing. Then, through protocol adaptation, format conversion, and data fusion, the processed data is transmitted to the digital twin virtual unit, process simulation optimization unit, and intelligent decision control unit, respectively. The digital twin virtual unit establishes a 3D virtual model based on the dimensions, positions, and motion parameters of the bending machine, industrial robot, multi-functional gripper, feeding rack, centering platform, and unloading rack, and records the bending machine slider position and robot joint angles according to timestamps. The gripper's opening and closing states and the sheet metal transfer position are mapped to the corresponding models, enabling synchronized display of the virtual machining scene and physical entity units. After importing the workpiece drawings, the process simulation optimization unit analyzes the sheet metal material, thickness, dimensions, bending angle, and bending position. The bending programming module generates the bending sequence, bending pressure, and bending stroke. The gripper positioning planning module generates the clamping position and posture, and the robot trajectory planning module generates the material picking, centering, loading / unloading, and unloading trajectories. The simulation verification module then simulates the entire bending process in the virtual machining scene. When trajectory interference, workpiece posture deviation, gripper clamping deviation, or bending parameter deviation is detected, the process data is adjusted accordingly. The intelligent decision control unit receives the data after simulation verification and converts it into control commands for the bending machine, industrial robot, and multi-functional gripper. This allows the physical entity unit to run automatically without on-site teaching. When the bending angle, side length, or actual pressure of the bending machine fed back by the vision inspection module deviates from the target parameters, the anomaly handling module calculates the comprehensive deviation value through the bending deviation evaluation model. When the deviation exceeds the preset threshold, it corrects the bending pressure, bending stroke, and robot position of the subsequent workpiece. This forms a closed-loop bending control process from drawing import, virtual simulation, physical processing, vision inspection, and parameter correction.

[0075] It is worth noting that the circuits, electronic components, and modules involved in this invention are all existing technologies, which can be fully implemented by those skilled in the art, and need not be elaborated upon. The content protected by this invention does not involve improvements to the software and methods.

[0076] It should be understood that the disclosed apparatus can be implemented in other ways, given the several embodiments provided in this application. For example, the apparatus embodiments described above are merely illustrative; the division of units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or communication connections shown or discussed may be through some interfaces; the indirect coupling or communication connections between devices or units may be telecommunications or other forms.

[0077] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still combine, add, delete, or otherwise adjust the features of the various embodiments of the present invention according to the circumstances without conflict or creative effort, thereby obtaining different technical solutions that do not fundamentally depart from the concept of the present invention. These technical solutions also fall within the scope of protection of the present invention.

Claims

1. An intelligent bending digital twin system, characterized in that, It includes physical entity units, digital twin virtual units, data interaction units, process simulation and optimization units, and intelligent decision control units; The physical entity unit includes a bending machine, an industrial robot, a multi-functional gripper, a feeding rack, a centering platform, a discharge rack, and a vision inspection module. The industrial robot is connected to the multi-functional gripper and is used to transfer sheet metal between the feeding rack, the centering platform, the bending machine, and the discharge rack. The vision inspection module is used to collect processing quality data of the workpiece after bending. The digital twin virtual unit is used to establish a three-dimensional virtual model corresponding to the physical entity unit, and to form a virtual processing scene based on the operating status of the physical entity unit. The data interaction unit is connected to the physical entity unit, the digital twin virtual unit, the process simulation optimization unit, and the intelligent decision control unit, respectively. It is used to collect equipment operation data, sheet material parameter data, and processing status data, and to perform protocol adaptation, format conversion, and fusion processing. The process simulation and optimization unit is used to import workpiece drawings, generate bending process programs, multi-functional gripper positioning parameters and industrial robot motion trajectories, and perform virtual simulation verification. The intelligent decision control unit is used to receive data verified by virtual simulation and generate control commands to drive the physical entity unit to complete automatic bending processing.

2. The intelligent bending digital twin system according to claim 1, characterized in that, The digital twin virtual unit includes a model building module, a state mapping module, and a virtual display module; The model building module is used to create a three-dimensional virtual model based on the equipment dimensions, installation position and motion parameters of the bending machine, industrial robot, multi-functional gripper, feeding rack, centering platform and discharge rack. The state mapping module is connected to the data interaction unit and is used to receive the stroke data of the bending machine, the posture data of the industrial robot, the clamping state data of the multi-functional gripper, and the processing position data of the sheet metal. The virtual display module is used to synchronously display the processing actions and operating status of the physical entity unit based on the data received by the status mapping module.

3. The intelligent bending digital twin system according to claim 2, characterized in that, The state mapping module matches the data of the bending machine slider position, industrial robot joint angle, multi-functional gripper clamping opening and closing status, sheet material transfer position, and processing progress with the corresponding three-dimensional virtual model according to the timestamp, so that the three-dimensional virtual model displays synchronous actions according to the actual running sequence of the physical entity units.

4. The intelligent bending digital twin system according to claim 1, characterized in that, The data interaction unit includes a data acquisition module, a protocol adaptation module, a data fusion module, and a data distribution module; The data acquisition module collects pressure, stroke, alarm and processing status data of the bending machine, position, posture and trajectory execution data of the industrial robot, and workpiece inspection data fed back by the vision inspection module. The protocol adaptation module is used to convert the communication data between the bending machine, industrial robot, vision inspection module and digital twin virtual unit. The data fusion module is used to uniformly process equipment operation data, sheet material parameter data, and processing status data; The data distribution module is used to send the processed data to the digital twin virtual unit, the process simulation optimization unit, and the intelligent decision control unit, respectively.

5. The intelligent bending digital twin system according to claim 1, characterized in that, The process simulation optimization unit includes a drawing import and parsing module, a bending programming module, a gripper positioning and planning module, a robot trajectory planning module, and a simulation verification module. The drawing import and parsing module is used to import workpiece drawings and parse the sheet material, sheet thickness, dimensions, bending angle, and bending position. The bending programming module is used to generate bending sequence, bending pressure and bending stroke based on the analysis results; The gripper positioning and planning module is used to generate the clamping position and clamping posture of the multi-functional gripper based on the workpiece's external dimensions and bending position. The robot trajectory planning module is used to generate the motion trajectory of the industrial robot during the processes of picking up materials from the feeding rack, positioning the centering platform, loading and unloading materials from the bending machine, and unloading materials from the discharge rack. The simulation verification module is used to perform virtual simulation verification of bending sequence, gripper holding posture and industrial robot motion trajectory.

6. The intelligent bending digital twin system according to claim 5, characterized in that, The bending programming module is the CADMAN-B bending programming module, and the gripper positioning and planning module, robot trajectory planning module, and simulation verification module are the CADMAN-SIM simulation modules. The CADMAN-B bending programming module generates bending machine processing programs based on workpiece drawings, while the CADMAN-SIM simulation module generates multi-functional gripper positioning parameters and collision-free motion trajectories for industrial robots based on workpiece shape, workpiece size, and bending sequence.

7. The intelligent bending digital twin system according to claim 5, characterized in that, The simulation verification module sequentially simulates the process of industrial robot picking up materials, multi-functional gripper holding, centering platform positioning, bending machine bending, detection position stopping and material unloading from the discharge rack in a virtual processing scenario, and identifies robot trajectory interference, workpiece posture deviation, gripper holding position deviation and bending parameter deviation that occur during the simulation. The process simulation optimization unit corrects the bending process, multi-functional gripper positioning parameters, and industrial robot motion trajectory based on the identification results, and sends the corrected data to the intelligent decision control unit.

8. The intelligent bending digital twin system according to claim 1, characterized in that, The visual detection module includes an image acquisition component and a detection feedback component; The image acquisition component is used to acquire the contour image, edge image, or bending area image of the workpiece after bending. The detection feedback component is used to obtain workpiece size accuracy data and bending angle data based on the contour image, edge image, or bending area image, and then send the workpiece size accuracy data and bending angle data to the intelligent decision control unit via the data interaction unit.

9. The intelligent bending digital twin system according to claim 8, characterized in that, The intelligent decision control unit includes an instruction conversion module, an offline execution module, an exception handling module, and a human-machine collaboration module; The instruction conversion module is used to convert the bending process program, multi-functional gripper positioning parameters and industrial robot motion trajectory output by the process simulation optimization unit into bending machine control instructions, industrial robot control instructions and multi-functional gripper control instructions. The offline execution module is used to invoke the control commands to drive the physical entity unit to run automatically without on-site teaching; The anomaly handling module is used to generate process parameter adjustment instructions or shutdown warning instructions based on equipment alarm data, workpiece size accuracy data and bending angle data. The human-machine collaboration module is used to receive manual intervention instructions and correct the current processing flow or processing parameters according to the manual intervention instructions.

10. The intelligent bending digital twin system according to claim 9, characterized in that, The anomaly handling module includes a bending deviation evaluation model, which calculates a comprehensive deviation value based on dimensional accuracy data, bending angle data, and actual execution data from the bending machine fed back by the visual inspection module. The comprehensive deviation value The following relationship must be satisfied: in, The actual bending angle detected by the vision inspection module. The target bending angle generated by the process simulation optimization unit. The actual side length dimension detected by the vision inspection module. The target side length dimension generated for the process simulation optimization unit. The actual operating pressure of the bending machine. The target bending pressure generated for the bending programming module. , , These are the weighting coefficients for angular deviation, dimensional deviation, and pressure deviation, respectively. When the comprehensive deviation value When the deviation exceeds a preset threshold, the anomaly handling module sends a process parameter correction instruction to the instruction conversion module. The instruction conversion module then corrects the bending pressure, bending stroke, industrial robot material handling point, centering and feeding point, or bending feeding point of the subsequent workpiece according to the process parameter correction instruction.

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