Robot welding auxiliary control system and method

Abstract

The invention discloses a robot welding auxiliary control system and method in the technical field of arc welding robots, the system comprises a robot controller and a cloud function module cluster which are in two-way communication connection, and the cluster comprises a process reasoning module, a program generation module, a program simulation module and an expert analysis module. The process reasoning module generates initial welding process parameters; the program generation module generates a welding program according to the welding structure model, the workstation model and the initial welding process parameters; the program simulation module simulates a welding program and downloads the program and a result to the robot controller for an operator to adjust; and the expert analysis module is used for analyzing all programs and equipment data and transmitting a finally confirmed welding program to the robot controller and the process reasoning module. According to the method, the problem of insufficient precision caused by geometric deviation between a workpiece object and a model can be effectively solved, and intelligent generation and self-adaptive adjustment of a welding program are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of arc welding robots, in particular to a robot welding auxiliary control system and method. BACKGROUND

[0002] Robots play an increasingly important role in manufacturing sub-sectors, and robot automated welding equipment is an indispensable automated production equipment in industrial production processes, which not only meets the modern production needs of enterprises, but also needs to reduce production costs and adapt to complex production environments. Robot automated welding technology is a technology that intelligently acquires target workpiece information, combines a robot control system, and automatically controls the welding steps.

[0003] Currently, the programming of welding robots mainly relies on manual teaching by operators based on workpiece physical objects and corresponding three-dimensional drawings, as well as extracting weld information from model files and completing preliminary trajectory planning accordingly. However, in actual operation, due to positioning deviations, assembly errors, and local geometric differences between workpiece physical objects and theoretical models, combined with the need for different welding parameters for different welds, the pre-generated program is difficult to directly apply. Especially for complex workpieces or workstations equipped with external axis positioners, the programming complexity increases significantly, which not only prolongs the operation time, but also increases the equipment downtime, seriously affecting the equipment utilization and overall production efficiency.

[0004] The existing technical solution is that after downloading the program to the robot controller, the operator performs manual action confirmation on site and manually fine-tunes the welding trajectory and welding specification parameters. However, this approach has obvious limitations: on the one hand, the technical level of the on-site operator varies, which may result in the fine-tuned program being difficult to achieve the best state in terms of running efficiency and weld quality; on the other hand, there is a lack of effective audit mechanism, which cannot timely identify and correct problems that may occur during fine-tuning, thereby affecting the quality and efficiency of the overall welding production. SUMMARY

[0005] The purpose of the present application is to provide a robot welding auxiliary control system and method, which realizes adaptive adjustment of the welding program, avoids the influence of the operator's technical level on the program running efficiency, and guarantees the overall quality of the welded parts.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a robot welding auxiliary control system, comprising a robot controller and a cloud function module cluster connected by bidirectional communication;

[0008] The cloud function module cluster comprises:

[0009] a process reasoning module configured to generate initial welding process parameters according to an existing standard process library, a process database, and data information provided by the robot controller;

[0010] a program generation module configured to generate an initial welding program according to the acquired welding structure model, the work station model, and the initial welding process parameters, the initial welding program including a homing trajectory action program and a welding trajectory action program;

[0011] a program simulation module configured to simulate the homing trajectory action program and / or the welding trajectory action program in the initial welding program, and to download the initial welding program and corresponding simulation results to the robot controller, so that an operator adjusts the initial welding process parameters through the robot controller to acquire an adjusted welding program;

[0012] an expert analysis module configured to analyze and review the initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller, and equipment operation data, and to transmit a finally confirmed welding program to the robot controller and the process reasoning module, so that the robot controller controls the robot to perform welding actions, and the process reasoning module updates and optimizes the existing standard process library and the process database according to the finally confirmed welding program.

[0013] Further, the cloud function module cluster further includes an equipment management module configured to register and manage a plurality of welding equipment in a factory, collect real-time operation data of each welding equipment, and upload the data to the expert analysis module after adding equipment identification information to the data.

[0014] Further, the program generation module includes:

[0015] a model management sub-module configured to manage three-dimensional models of the welding structure model and the work station model;

[0016] a scene building sub-module configured to build a virtual work station scene according to the work station model;

[0017] a system calibration sub-module configured to perform system calibration on the virtual work station scene through a calibration algorithm, so as to eliminate position errors caused by equipment and workpiece placement;

[0018] a weld seam extraction sub-module configured to process the welding structure model to extract and screen out weld seam coordinate information;

[0019] a trajectory planning sub-module configured to plan and generate trajectory points according to the weld seam coordinate information;

[0020] a process matching sub-module, configured to match a welding process parameter to a welding seam feature represented by the welding seam coordinate information, and generate an initial welding program according to the welding seam coordinate information and the welding process parameter.

[0021] Further, the program generation module further comprises a collision detection sub-module, configured to perform motion simulation and collision interference checking on the initial welding program.

[0022] Further, the welding process parameter comprises a welding power parameter, a motion control parameter and a welding action parameter.

[0023] Further, the process inference module comprises:

[0024] an artificial intelligence algorithm sub-module, configured to perform process inference and generate the initial welding process parameter according to welding task parameters extracted from the existing standard process library, the process database and data information provided by the robot controller;

[0025] an expert knowledge base sub-module, configured to store expert knowledge of welding process, and the artificial intelligence algorithm sub-module calls the expert knowledge base to optimize the process inference process.

[0026] Further, the process inference module further comprises an adaptive learning sub-module, configured to optimize the artificial intelligence algorithm sub-module or the expert knowledge base sub-module according to real-time feedback data of the welding process, so as to dynamically adjust the welding process parameters generated subsequently.

[0027] In a second aspect, the present application further provides a robot welding auxiliary control method based on the robot welding auxiliary control method in the first aspect, comprising the following steps:

[0028] inference and generation of initial welding process parameters according to welding task parameters provided by the existing standard process library, the process database and the robot controller;

[0029] generation of an initial welding program based on the initial welding process parameters, a welding structure model and a workstation model; the initial welding program comprises a homing trajectory action program and a welding trajectory action program;

[0030] simulation of the homing trajectory action program and / or the welding trajectory action program in the initial welding program, and transmission of the initial welding program and the corresponding simulation result to the robot controller, so that an operator adjusts the initial welding process parameters through the robot controller to obtain an adjusted welding program;

[0031] The initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller and the equipment operation data are analyzed and audited, and the finally confirmed welding program is transmitted to the robot controller and the process reasoning module respectively, so that the robot controller controls the robot to perform the welding action, and the process reasoning module updates and optimizes the existing standard process library and process database according to the finally confirmed welding program.

[0032] Further, based on the initial welding process parameters, the welding structure model and the workstation model, an initial welding program is generated, including the following steps:

[0033] The three-dimensional model of the welding structure model and the workstation model is managed;

[0034] A virtual workstation scene is built according to the workstation model;

[0035] The virtual workstation scene is calibrated by a calibration algorithm to eliminate the position error caused by the equipment and the workpiece placement;

[0036] The welding structure model is processed to extract and filter out the weld coordinate information;

[0037] The trajectory points are planned and generated according to the weld coordinate information;

[0038] According to the weld characteristics represented by the weld coordinate information, appropriate welding process parameters are matched for the trajectory, and the initial welding program is generated according to the trajectory points and the process parameters.

[0039] Compared with the prior art, the present application has the following advantages:

[0040] 1、The robot welding auxiliary control system disclosed by the present application automatically generates a welding program through a three-dimensional model, and combines on-site fine tuning and remote expert review, effectively improving the accuracy of the welding program and the weld quality, and avoiding errors caused by uneven technical levels of operators through an expert analysis module. The system realizes automatic uploading and management of program data, facilitates remote collaboration and program management, and promotes the digitalization and intelligentization process of welding production;

[0041] 2、The robot welding auxiliary control method disclosed by the present application combines three-dimensional model technology and virtual scene calibration to provide a data basis for welding trajectory planning and reduce program correction caused by model and actual workpiece deviation. The method supports dynamic adjustment of welding process parameters, optimizes welding parameters according to real-time equipment operation data, and improves the stability of the welding process. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 It is a schematic diagram of the principle of the robot welding auxiliary control system of the embodiment of the present application.

[0043] Figure 2 A schematic diagram of a cloud structure of a robot welding auxiliary control system according to an embodiment of the present application;

[0044] Figure 3 A schematic diagram of steps of a robot welding auxiliary control method according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The description of the at least one exemplary embodiment is actually only illustrative, but not as any limitation on the present application and its application or use. Embodiment 1

[0046] As shown in Figure 1 and Figure 2 The present application provides a robot welding auxiliary control system, which comprises a robot controller and a cloud function module cluster connected in bidirectional communication.

[0047] In this embodiment, the robot controller has an Internet of Things function, and realizes the communication function between the robot controller and the cloud function module cluster by accessing a network, and supports the OPC UA protocol, thereby realizing the downloading and uploading of the welding program file.

[0048] In this embodiment, the cloud function module cluster comprises a process reasoning module, a program generation module, a program simulation module and an expert analysis module.

[0049] The process reasoning module is configured to generate initial welding process parameters according to the existing standard process library, the process database and the data information provided by the robot controller.

[0050] The robot welding auxiliary control system provided by the embodiment is designed for a workpiece welding task, and process reasoning needs to be performed according to an actual welding scene and workpiece weld data to determine initial process parameters that can ensure efficient operation of the robot welding auxiliary control system and achieve high-quality welds. Specifically, the process reasoning module includes an artificial intelligence algorithm submodule, an expert knowledge base submodule, and a self-adaptive learning submodule. The artificial intelligence algorithm submodule performs process reasoning and generates the initial welding process parameters according to welding task parameters extracted from data information provided by the existing standard process library, the process database, and the robot controller. In order to make the process reasoning more professional, the expert knowledge base submodule stores expert knowledge of welding processes, and the artificial intelligence algorithm submodule optimizes the process reasoning process by calling the expert knowledge base. The self-adaptive learning submodule optimizes the artificial intelligence algorithm submodule or the expert knowledge base submodule according to real-time feedback data of the welding process to dynamically adjust subsequent generated welding process parameters, thereby improving the quality of the welded workpiece.

[0051] A program generation module is configured to generate an initial welding program according to the acquired welding structure model, the workstation model, and the initial welding process parameters. The initial welding program includes a homing trajectory action program and a welding trajectory action program. In the embodiment, the initial welding program is generated by function modules in the program generation module. Specifically, the program generation module includes:

[0052] A model management submodule is configured to manage three-dimensional models of the welding structure model and the workstation model. The workstation model includes three-dimensional models of a welding robot, an external axis, a positioner, and a base. In the actual market, robot manufacturers and other device manufacturers provide three-dimensional drawings in step format and other formats. The model management submodule can convert the three-dimensional drawings in step format into a file type that can be recognized by a three-dimensional engine and save and manage the converted files, so that the files can be directly used in subsequent new projects.

[0053] A scene building submodule is configured to build a virtual workstation scene according to the workstation model, and can build the virtual workstation scene according to an actual workstation scene built by a user or according to design drawings of a workstation provided by the user.

[0054] The system calibration sub-module is configured to calibrate the virtual workstation scene by using a calibration algorithm, so as to eliminate the position error caused by the equipment and the workpiece placement. In the actual scene, when the workpiece to be welded is placed by a person or positioned by a clamp, the workpiece to be welded in the actual scene has an error with the virtual workstation scene built by the scene building sub-module due to the human error or the positioning error. The calibration algorithm is used to make the workpiece in the actual workstation scene have the same position as the workpiece in the virtual workstation scene, so as to eliminate the position error.

[0055] The weld extraction sub-module is configured to analyze and process the workpiece in the virtual workstation scene, extract the weld position of the workpiece, extract a plurality of lines according to the characteristics of the workpiece, define the lines as the weld according to the weld definition rule, and extract the actual weld, and then obtain the weld coordinate information by calculation.

[0056] The trajectory planning sub-module is configured to plan and generate the trajectory point according to the given weld coordinate information. The trajectory point is generated by connecting each weld according to the given rule according to the weld coordinate information, the robot motion algorithm and the external axis motion algorithm of the positioner.

[0057] The process matching sub-module is configured to match the appropriate welding process parameters for the trajectory according to the weld characteristics represented by the weld coordinate information, and generate the initial welding program according to the trajectory point and the process parameters.

[0058] The collision detection sub-module is configured to simulate the motion of the welding program and check the collision interference, so as to reduce the damage to the equipment in the actual scene.

[0059] In the embodiment, the program simulation module is configured to simulate the location trajectory action program and / or the welding trajectory action program in the welding program in the virtual workstation scene built by the scene building sub-module, so as to obtain the simulation result, and then the program download module is configured to download the welding program and the corresponding simulation result to the robot controller. The operator in the workstation scene adjusts the initial welding process parameters through the robot controller, and obtains the adjusted welding program.

[0060] In the embodiment, the expert analysis module is configured to analyze and audit the initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller and the equipment running data, and transmit the finally confirmed welding program to the robot controller and the process reasoning module, so that the robot controller controls the robot to perform the welding action, and the process reasoning module updates and optimizes the existing standard process library and process database according to the finally confirmed welding program.

[0061] In the present embodiment, the cloud function module cluster further comprises a device management module. Since a robot factory contains many devices, including robots and electric welding machines, real-time running data of each device needs to be acquired to facilitate analysis of the running conditions of the devices. To this end, the device management module is configured to register and manage multiple welding devices in the factory, collect real-time running data of the welding devices, and upload the data with device identification information to the expert analysis module. Embodiment 2

[0062] The present embodiment provides a robot welding auxiliary control method. The method is implemented based on the robot welding auxiliary control system of embodiment 1. As shown in Figure 3 The method comprises the following steps:

[0063] Step 1: generating initial welding process parameters according to existing standard process library, process database, and welding task parameters provided by a robot controller;

[0064] In the present embodiment, the process reasoning module generates the initial welding process parameters according to existing standard process library, process database, and welding task parameters provided by a robot controller. The process reasoning module comprises an artificial intelligence algorithm submodule, an expert knowledge base submodule, and an adaptive learning submodule. The artificial intelligence algorithm submodule calls the expert knowledge base of the expert knowledge base submodule to optimize the process reasoning process. The adaptive submodule optimizes the artificial intelligence algorithm submodule or the expert knowledge base submodule according to real-time feedback data of the welding process.

[0065] Step 2: generating an initial welding program based on the initial welding process parameters, a welding structure model, and a workstation model. The initial welding program comprises a homing trajectory action program and a welding trajectory action program.

[0066] Step 3: simulating the homing trajectory action program and / or the welding trajectory action program in the initial welding program, and downloading the initial welding program and the corresponding simulation results to the robot controller to enable an operator to adjust the initial welding process parameters through the robot controller and obtain an adjusted welding program.

[0067] In the present embodiment, the program simulation module simulates the welding program in the virtual workstation scene built by the scene building submodule, thereby ensuring correct welding trajectory, no collision interference, correct process matching, and correct program structure, and obtaining the simulated welding program and the corresponding simulation results.

[0068] The welding program after simulation and the corresponding simulation results are transmitted to the robot controller through a program transmission module, and an operator on site of the workstation adjusts and optimizes the initial welding process parameters through the robot controller to obtain an adjusted welding program.

[0069] Step four: analyzing and auditing the initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller and the equipment operation data, and transmitting the finally confirmed welding program to the robot controller and the process reasoning module respectively, so that the robot controller controls the robot to perform welding actions and the process reasoning module updates and optimizes the existing standard process library and process database according to the finally confirmed welding program.

[0070] In the embodiment, the expert analysis module comprehensively analyzes and audits the initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller and the related equipment operation data, generates a finally confirmed welding program, and sends the program to the robot controller. The robot controller drives the robot to perform welding work according to the final welding program. The process reasoning module receives the finally confirmed welding program from the expert analysis module, and updates and optimizes the existing standard process library and process database according to the finally confirmed welding program.

[0071] In the embodiment, the initial welding program is generated based on the initial welding process parameters, the welding structure model and the workstation model, and mainly includes the following steps:

[0072] The three-dimensional models of the welding structure model and the workstation model are managed;

[0073] A virtual workstation scene is built according to the workstation model;

[0074] The virtual workstation scene is calibrated by a calibration algorithm to eliminate position errors caused by equipment and workpiece placement;

[0075] The welding structure model is processed to extract and select weld coordinate information;

[0076] Trajectory points are planned and generated according to the weld coordinate information;

[0077] According to the weld characteristics represented by the weld coordinate information, appropriate welding process parameters are matched for the trajectory, and an initial welding program is generated according to the trajectory points and the process parameters.

[0078] The above merely describes the preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, some improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. A robot welding auxiliary control system, characterized in that, This includes a robot controller with bidirectional communication connectivity and a cluster of cloud-based functional modules; The cloud-based functional module cluster includes: Process reasoning module: used to generate initial welding process parameters based on existing standard process library, process database and data information provided by the robot controller; Program generation module: used to generate an initial welding program based on the acquired welding structure model, workstation model and the initial welding process parameters. The initial welding program includes a positioning trajectory action program and a welding trajectory action program. The program simulation module is used to simulate the positioning trajectory action program and / or welding trajectory action program in the initial welding program, and to download the initial welding program and the corresponding simulation results to the robot controller, so that the operator can adjust the initial welding process parameters through the robot controller and obtain the adjusted welding program. The expert analysis module is used to analyze and review the initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller, and the equipment operation data. The final confirmed welding program is then transmitted to the robot controller and the process reasoning module, so that the robot controller controls the robot to perform welding actions and the process reasoning module updates and optimizes the existing standard process library and process database based on the final confirmed welding program.

2. The robot welding auxiliary control system according to claim 1, characterized in that, The cloud-based functional module cluster also includes an equipment management module, which is used to register and manage multiple welding devices in the factory, collect real-time operating data of each welding device, and upload the data to the expert analysis module after adding device identification information.

3. The robot welding auxiliary control system according to claim 1, characterized in that, The program generation module includes: The model management submodule is used to manage the three-dimensional models of the welding structure model and the workstation model; The scene building submodule is used to build a virtual workstation scene based on the workstation model. The system calibration submodule is used to perform system calibration on the virtual workstation scene through a calibration algorithm to eliminate positional errors caused by the placement of equipment and workpieces. The weld extraction submodule is used to process the welded structure model to extract and filter the weld coordinate information; The trajectory planning submodule is used to plan and generate trajectory points based on the weld coordinate information. The process matching submodule is used to match suitable welding process parameters for the trajectory based on the weld features represented by the weld coordinate information, and to generate the initial welding program based on the trajectory points and process parameters.

4. The robot welding auxiliary control system according to claim 3, characterized in that, The program generation module also includes a collision detection submodule, which is used to perform motion simulation and collision interference checks on the initial welding program.

5. The robot welding auxiliary control system according to claim 1, characterized in that, The welding process parameters include welding power supply parameters, motion control parameters, and welding action parameters.

6. The robot welding auxiliary control system according to claim 1, characterized in that, The process reasoning module includes: The artificial intelligence algorithm submodule is used to perform process reasoning and generate the initial welding process parameters based on the welding task parameters extracted from the existing standard process library, process database and data information provided by the robot controller; The expert knowledge base submodule is used to store expert knowledge about welding processes. The artificial intelligence algorithm submodule calls the expert knowledge base to optimize the process reasoning process.

7. The robot welding auxiliary control system according to claim 6, characterized in that, The process reasoning module also includes an adaptive learning submodule, which is used to optimize the artificial intelligence algorithm submodule or the expert knowledge base submodule based on real-time feedback data of the welding process, so as to dynamically adjust the welding process parameters generated subsequently.

8. A robot welding auxiliary control method based on the system of claim 1, characterized in that, Includes the following steps: Based on the existing standard process library, process database, and welding task parameters provided by the robot controller, the initial welding process parameters are inferred and generated. Based on the initial welding process parameters, welding structure model, and workstation model, an initial welding program is generated; the initial welding program includes a positioning trajectory action program and a welding trajectory action program. The positioning trajectory action program and / or welding trajectory action program in the initial welding program are simulated, and the initial welding program and the corresponding simulation results are downloaded to the robot controller so that the operator can adjust the initial welding process parameters through the robot controller and obtain the adjusted welding program. The initial welding program generated by the program generation module, the adjusted welding program uploaded by the robot controller, and the equipment operation data are analyzed and reviewed. The final confirmed welding program is then transmitted to the robot controller and the process reasoning module, respectively, so that the robot controller controls the robot to perform welding actions and the process reasoning module updates and optimizes the existing standard process library and process database based on the final confirmed welding program.

9. The robot welding auxiliary control method according to claim 8, characterized in that, Based on the initial welding process parameters, welding structure model, and workstation model, an initial welding program is generated, including the following steps: Manage the 3D models of the welding structure model and the workstation model; Build a virtual workstation scene based on the workstation model; The virtual workstation scene is calibrated using a calibration algorithm to eliminate positional errors caused by the placement of equipment and workpieces. The weld structure model is processed to extract and filter the weld coordinate information; The trajectory points are planned and generated based on the weld coordinate information; Based on the weld features represented by the weld coordinate information, appropriate welding process parameters are matched to the trajectory, and an initial welding program is generated based on the trajectory points and process parameters.

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