A welding processing system and method based on a digital twin monitoring model

Abstract

The application discloses a kind of welding processing system and method based on digital twin monitoring model, it is characterized in that, comprising: positioning feeding system;Welding processing system;Digital twin monitoring control system, for through equipment and sensor data acquisition, real-time acquisition and calculation welding position state, welding thermal field state, shielding gas flow field state when welding processing, and based on the result compared with digital twin monitoring model state threshold, drive control system controls welding processing system makes corresponding dynamic stable adjustment, so that keep in stable value in processing process;Monitoring sensor;Positioning discharging system.It is based on the precise repetition, intelligent function provided by automatic welding equipment, for the welding processing of batch workpiece, according to the welding workpiece characteristics and process technical requirements, corresponding digital twin welding monitoring model and control correlation application system are constructed, and production quality and efficiency are effectively balanced by real-time monitoring welding process elements.

Description

Technical Field

[0001] This invention relates to the fields of mechanical processing and manufacturing, and industrial digital twin application technology, specifically to a welding processing system and method based on a digital twin monitoring and measurement model. Background Technology

[0002] Welding is a crucial fundamental manufacturing technology, involving complex physicochemical changes in its process and results, and encompassing a diverse and intricate range of industry sub-sectors. The efficiency and quality of welding processes remain key constraints in manufacturing. While batch welding now widely employs varying degrees of automation, with batch sampling inspection as a production method, the irreversible nature of the welding process introduces risks and losses related to product batch quality. Currently, the monitoring of automated welding systems primarily focuses on setting and monitoring key equipment parameters, failing to monitor and assess the combined effects of equipment and workpiece in the welding process and its outcome. Consequently, quality risks associated with batch processing persist.

[0003] Digital twin models, with their data-driven and virtual-real mapping interaction features, can be used to describe and calculate the interaction of production factors and processes during manufacturing. Currently, however, digital twin applications in the manufacturing sector suffer from inadequate system composition. Due to a lack of system and methodological constraints, the related model construction and application methods are redundant and complex, making them difficult to implement in engineering practice and technology. They cannot effectively solve the problems and needs of enterprises in specific products and production scenarios. Summary of the Invention

[0004] The purpose of this invention is to address the current limitations of digital twin systems in the manufacturing field, which suffer from redundant and complex dimensions, difficulty in engineering practice and technological implementation, and inability to effectively solve the needs and problems of enterprise production. This invention provides a welding processing system and method based on a digital twin monitoring model. Building upon the precise, repeatable, and intelligent functions provided by commonly available automated welding equipment, this invention focuses on key factors affecting product quality and performance indicators during the welding process, based on the workpiece's technical characteristics, process requirements, and production scenario. It constructs a corresponding digital twin welding monitoring model and a control-related application system to monitor welding process elements in real time, achieving an effective balance between production quality and efficiency.

[0005] The technical solution of the present invention is as follows:

[0006] A welding process system based on a digital twin monitoring model includes:

[0007] A positioning and feeding system is used to transport or control workpieces to be welded and maintain them in the same position and orientation.

[0008] The solder processing system is connected to the positioning and feeding system and is controlled by the control system to maintain or adjust the processing technology, functional actions, and condition parameters for welding workpieces.

[0009] The digital twin monitoring and control system includes a digital twin monitoring model system and a control system. It is used to acquire and calculate the welding position state, welding thermal field state, and shielding gas flow field state in real time through equipment and sensor data acquisition. Based on the comparison with the state threshold of the digital twin monitoring model, it drives the control system to make corresponding dynamic and stable adjustments to the welding process system so that it remains within a stable value during the process.

[0010] Monitoring sensors are used to monitor and collect data on the welding process status, providing data for the calculation of the digital twin monitoring model system in the digital twin monitoring and control system;

[0011] The positioning and feeding system is connected to the welding processing system and is used to transport or control post-welding work in the same position and posture.

[0012] Furthermore, the digital twin monitoring model system is a functional system that collects and calculates welding position status, welding thermal field status, and shielding gas flow field data of equipment, workpiece, and sensors; the control system can maintain and change the parameters and functions of welding processing system equipment, devices, and instruments according to changes in state values, and can be driven by the state data output by the digital twin monitoring model.

[0013] Furthermore, the welding processing system includes automatic clamping equipment and automatic welding equipment, and the processing from loading to unloading adopts one or more automated operation systems.

[0014] Furthermore, the positioning and feeding system is one or more systems that ensure the workpiece maintains a consistent position and orientation before entering the welding processing system, including manual and automated devices and equipment.

[0015] Furthermore, the positioning and feeding system is one or more systems that enable the welding processing system to transport and control the welded workpiece with the same equipment operation and workpiece position and posture, including manual and automated equipment.

[0016] Furthermore, the data on the welding process status includes the welding position status of the equipment and workpiece, the welding thermal field status, and the shielding gas flow field status.

[0017] This invention also includes a welding process method based on a digital twin monitoring model, characterized in that a method for controlling a welding process system based on a digital twin monitoring model includes:

[0018] Construct a digital twin monitoring model to describe the elements of the automated welding process;

[0019] Construct a digital twin monitoring and control system that includes a digital twin monitoring model system and an equipment control system;

[0020] The positioning and feeding system ensures that the workpieces to be welded enter the welding process system in the same position and orientation.

[0021] The welding processing system performs welding processing using the same process flow and equipment actions;

[0022] After processing is completed, the welding system transfers the welded workpiece to the positioning and unloading system using the same equipment actions and workpiece position and posture.

[0023] During the processing, the digital twin monitoring and control system is used to acquire and calculate the welding position status, welding thermal field status, and shielding gas flow field status of the equipment and workpiece in real time through data acquisition from equipment and sensors. Based on the comparison with the state threshold of the monitoring model, the system drives the control system to make corresponding dynamic and stable adjustments to the welding processing system, so that it remains within a stable value during the processing.

[0024] Furthermore, the processing method is a method of performing welding operations using automated control, including the procedures, processes, and actions of workpiece picking and placing, assembly, clamping, and welding, and the processing equipment includes automatic clamping and assembly equipment and welding robots.

[0025] Furthermore, the digital twin monitoring and control system includes a digital twin monitoring model system and a control system; the digital twin monitoring model system is a digital twin model functional system that performs real-time calculations on the position and status of equipment and workpiece, the welding thermal field status, and the shielding gas flow field status during the welding process; the control system is a welding processing control system that can maintain and change the parameters and functional actions of welding processing system equipment, devices, instruments, etc. according to value changes; the digital twin monitoring model and the control system have a state value change-driven relationship.

[0026] Furthermore, the digital twin monitoring and control system includes a digital twin monitoring model system whose model state thresholds are calculated based on model theory, historical production data, and quality inspection data, and are dynamically corrected by machine learning and intelligent algorithms.

[0027] Compared with existing technologies, the advantages of this invention are:

[0028] 1. A welding processing system and method based on a digital twin monitoring model, which improves the monitoring of traditional equipment parameters to the monitoring of comprehensive elements of the welding process itself for batch welding production, thereby ensuring production quality and efficiency.

[0029] 2. A welding processing system and method based on a digital twin monitoring model, which enables a model-based comprehensive description and evaluation of temperature, position, and gas protection for equipment and workpieces during welding processing, ensuring stable and continuous management of welding quality elements during processing, thereby reducing the risks of mass production;

[0030] 3. A welding processing system and method based on a digital twin monitoring model, which, for specific production, can significantly simplify and reduce the complexity, technical difficulty and computing power requirements of digital twin models and applications by accurately repeating the entire welding process and focusing on key factors through system design. This effectively improves enterprise needs and accelerates the application of the technology. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the system framework of a welding process system and method based on a digital twin monitoring model.

[0032] Figure 2 This is a flowchart of the drive control system for a welding process system and method based on a digital twin monitoring model.

[0033] Figure 3 This is a schematic diagram of a welding process method for a welding process system and method based on a digital twin monitoring model.

[0034] Figure 4 This is a schematic diagram of a welding process system and method based on a digital twin monitoring model. Detailed Implementation

[0035] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0036] The welding position state, welding thermal field state, and protective gas flow field state of the digital twin monitoring model equipment and workpiece described in this invention are all range values. The relevant calculations and range calibration have been completed by existing simulation algorithms. The data acquisition and analysis of the equipment and sensors including spatial position, temperature, and gas detection have been completed by relevant technology products. The control of the equipment's operating parameters and functional actions is completed through existing equipment functions and interfaces, industrial PID control algorithms, etc. The specific calculation and control process is not the subject of this invention, so it will not be described in detail here.

[0037] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0038] Please see Figure 1-4 A welding processing system based on a digital twin monitoring model, such as Figure 1 , Figure 4 As shown, it includes:

[0039] The positioning and feeding system is used to transport or control the workpieces to be welded and maintain the same position and posture. Positioning and workpiece posture can be achieved by means of equipment clamping device or structure and photoelectric tube detection. Transport can be achieved by means of non-powered gravity chute or conveying mechanism or by means of powered transport such as conveyor belt and drive motor control.

[0040] The welding processing system includes an automatic clamping system and automatic welding equipment. The processing from loading to unloading adopts one or more of the following automated operation systems: the gripping, clamping, assembly, welding, and post-weld unloading of the workpiece after it enters the welding processing system from the positioning loading point are achieved by automatic clamping and assembly equipment such as clamping machines and welding robots; the automatic welding equipment is equipment that automates the welding process, such as welding robots or similar equipment.

[0041] like Figure 3 and Figure 4As shown, the digital twin monitoring and control system includes a monitoring model system and a control system. The welding process monitoring model within the monitoring model system is constructed based on the production scenario, primarily including equipment conditions, workpiece technical characteristics, process technology requirements, and processing elements. This includes a calculation and analysis system for welding position status, welding thermal field status, and shielding gas flow field status. This model system uses real-time acquired equipment data, such as welding robot joint operating parameters, welding torch current, voltage, and shielding gas pressure and flow rate, and sensor data, such as equipment and workpiece dimensions, spatial distance, welding area temperature, workpiece thermal field distribution, and shielding gas coverage concentration, to assess the welding position status during the welding process. The system performs real-time calculations and monitoring of various parameters, including welding torch position and orientation, workpiece assembly position relationship, welding surface gap, and coaxiality; welding thermal field status, such as total welding heat, weld point temperature, and workpiece thermal field distribution; and shielding gas flow field status, such as concentration, diffusion pattern, and coverage area. These parameters are compared with the state threshold information of the monitoring model. This threshold information is dynamically corrected based on theoretical calculations from the model, historical production data, and quality inspection data. The monitoring model system, based on the comparison results, drives the control system to maintain or adjust the operating parameters of the automatic welding equipment in real time, ensuring that the welding process is always within the allowable range evaluated by the monitoring model, thereby ensuring process control and welding quality.

[0042] In another embodiment of the welding process system that employs a digital twin monitoring model, the welding process of conveyor line equipment roller components is taken as an example:

[0043] like Figure 4 As shown, the roller components are batch welded parts with general process requirements, including one cylinder and two shaft ends. The welding relationship and process of the components are clear and simple, but the batch quantity is huge.

[0044] The welding process of this workpiece involves welding the shaft head along the assembly gap after it is inserted into the cylinder. The main factors affecting the processing quality are the assembly position and gap of the cylinder shaft head, the position and distance of the welding point between the welding torch and the workpiece, the temperature of the welding point and the temperature of the workpiece, and the coverage and concentration of the protective gas.

[0045] Based on the precise repeatability of the welding process and the control of the system equipment established by the fixed-point feeding, fixed-point discharging and automatic welding processing system, and based on the technical characteristics, technical requirements, processing process and main factors affecting the processing quality of the roller workpiece, a digital twin production process monitoring model is constructed to describe and calculate the roller welding process, including the welding position distance state, welding thermal field state and shielding gas flow state.

[0046] Based on the digital twin model of the roller welding process, a digital twin monitoring and control system is constructed, which includes a digital twin monitoring model system and an equipment control system that are driven together.

[0047] like Figure 4As shown, after the cylinder and shaft head workpiece are fixed in position and posture by the positioning and feeding system, the automatic clamping equipment of the automatic welding processing system and the welding robot gripper work together to clamp and assemble the cylinder and shaft head into place. The welding robot then begins to perform the welding operation. After the welding is completed, the welding robot transfers the roller workpiece from the automatic clamping equipment to the corresponding position on the positioning and unloading system.

[0048] The digital twin monitoring and control system monitors and controls the entire process described above: The monitoring model system collects input equipment operating parameters, sensor data on the spatial distance between the equipment and the workpiece, welding area temperature, and shielding gas coverage and diffusion, and performs real-time monitoring and calculation of the welding position status, welding thermal field status, and shielding gas flow field status during the welding process. It monitors and calculates the gripping, clamping, assembly, and weld point position movement of the equipment and workpiece, and compares this data with the welding position status thresholds of the monitoring model system to determine whether it falls within the threshold range. This mainly includes assembly relationships, assembly positions, assembly gaps, coaxiality, and welding positions. Based on the threshold comparison results, the monitoring model system drives the control system to synchronously maintain or adjust the corresponding operating parameters and status actions of the equipment, such as the position and angle of the gripper's actions and the position and posture of the welding torch.

[0049] The system monitors and calculates the temperature distribution and changes in the welding area during welding by the welding robot's welding torch, and compares these with the welding thermal field threshold values ​​of the monitoring model system to determine whether the temperature is within the threshold range. This mainly includes the total welding heat, weld point temperature, and workpiece temperature. Based on the threshold comparison results, the monitoring model system drives the control system to synchronously maintain or adjust the corresponding operating parameters of the equipment, such as the welding torch current, voltage, and wire feed speed.

[0050] The monitoring and calculation system calculates the coverage state of the shielding gas when the welding robot's welding torch performs welding, and compares it with the shielding gas flow field state threshold of the monitoring model system to determine whether it is within the threshold range. This mainly includes the shielding gas blowing and diffusion, coverage range, pressure, flow rate, and concentration. Based on the threshold comparison judgment results, the monitoring model system drives the control system to synchronously maintain or adjust the corresponding operating parameters of the equipment, such as the valve opening and blowing angle of the gas delivery mechanism.

[0051] In the above process, the model state threshold is calculated based on model theory, production history data, and quality inspection data, and is dynamically corrected by machine learning and intelligent algorithms.

[0052] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A welding process system based on a digital twin monitoring model, characterized in that, include: A positioning and feeding system is used to transport or control workpieces to be welded and maintain them in the same position and orientation. The welding processing system is connected to the positioning and feeding system and is controlled by the control system to maintain or adjust the processing technology, functional actions, and condition parameters for welding workpieces. The digital twin monitoring and control system includes a digital twin monitoring model system and a control system. It is used to acquire and calculate the welding position state, welding thermal field state, and shielding gas flow field state in real time through equipment and sensor data acquisition. Based on the comparison with the state threshold of the digital twin monitoring model, it drives the control system to make corresponding dynamic and stable adjustments to the welding process system so that it remains within a stable value during the process. Monitoring sensors are used to monitor and collect data on the welding process status, providing data for the calculation of the digital twin monitoring model system in the digital twin monitoring and control system; The positioning and feeding system is connected to the welding processing system to maintain the same position and posture when conveying or controlling the welded workpiece. The usage methods of this digital twin monitoring model for welding processing systems include: Construct a digital twin monitoring model to describe the elements of the automated welding process; Construct a digital twin monitoring and control system that includes a digital twin monitoring model system and an equipment control system; The positioning and feeding system ensures that the workpieces to be welded enter the welding process system in the same position and orientation. The welding processing system performs welding processing using the same process flow and equipment actions; After processing is completed, the welding system transfers the welded workpiece to the positioning and unloading system using the same equipment actions and workpiece position and posture. During the processing, the digital twin monitoring and control system is used to acquire and calculate the welding position status, welding thermal field status, and shielding gas flow field status of the equipment and workpiece in real time through data acquisition from equipment, workpiece, and sensors. Based on the comparison with the state threshold of the monitoring model, the system drives the control system to make corresponding dynamic and stable adjustments to the welding processing system, so that it remains within a stable value during the processing. The processing method is to use automated control to execute the welding operation process, including the procedures, processes and actions of workpiece picking and placing, assembly, clamping and welding, and the processing equipment includes automatic clamping and assembly equipment and welding robots; The digital twin monitoring and control system comprises a digital twin monitoring model system and a control system. The digital twin monitoring model system is a functional system that performs real-time calculations of the welding position status, welding thermal field status, and shielding gas flow field status of the equipment and workpiece during the welding process. The control system is a welding processing control system that can maintain and change the parameters and functional actions of the welding processing system equipment, devices, and instruments according to value changes. The digital twin monitoring model system and the control system have a state value change-driven relationship. The digital twin monitoring and control system includes a digital twin monitoring model system. The model state thresholds are calculated based on model theory, historical production data, and quality inspection data, and are dynamically corrected by machine learning and intelligent algorithms.

2. The welding processing system based on a digital twin monitoring model according to claim 1, characterized in that, The digital twin monitoring model system is a functional system that collects and calculates welding position status, welding thermal field status, and shielding gas flow field status data of equipment, workpiece, and sensors. The control system can maintain and change the parameters and functions of the welding processing system equipment, devices, and instruments according to changes in state values, and can be driven by the state data output by the digital twin monitoring model system.

3. The welding processing system based on a digital twin monitoring model according to claim 1, characterized in that, The welding processing system includes automatic clamping equipment and automatic welding equipment, and the processing from loading to unloading adopts one or more automated operation systems.

4. The welding processing system based on a digital twin monitoring model according to claim 1, characterized in that, The positioning and feeding system is one or more systems that ensure the workpiece maintains a consistent position and posture before entering the welding processing system, including manual and automated devices and equipment.

5. A welding processing system based on a digital twin monitoring model according to claim 1, characterized in that, The positioning and feeding system is one or more systems that enable the welding processing system to transport and control the welded workpiece with the same equipment operation and workpiece position and posture, including manual and automated devices and equipment.

6. A welding processing system based on a digital twin monitoring model according to claim 1, characterized in that, The welding processing status data includes the welding position status of the equipment and workpiece, the welding thermal field status, and the shielding gas flow field status.

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