Control method of automatic welding robot and electrical structure system

Abstract

The invention discloses a control method of an automatic welding robot and an electrical structure system, and relates to the technical field of electrical control. In order to solve the technical problems that in the prior art, when an existing welding robot deals with a complex welding task, welding path planning, welding current control, temperature adjustment, parameter self-adaptability, welding process monitoring and other aspects are insufficient, the technical scheme is provided, and the invention provides a control method of an automatic welding robot. Comprising the following steps that 1, physical property information of a welding material is collected; 2, data processing is conducted on the feature information, and a preliminary welding path and welding parameters are generated; 3, dynamically adjusting a welding path and welding current and voltage according to real-time data in the welding process; and 4, according to the real-time temperature of the monitored welding area, a cooling control signal is adjusted. The method is suitable for control work of the automatic welding robot.

Description

Technical Field

[0001] The invention relates to the technical field of electrical control, and in particular to a control method for an automatic welding robot. Background Art

[0002] In the industrial manufacturing process, the application of automated welding technology is gradually increasing, and welding robots are widely used in various welding tasks due to their high efficiency and precision. However, with the continuous improvement of the manufacturing industry's requirements for welding quality and precision, existing welding robots have exposed a series of technical difficulties when facing complex workpieces and special welding environments, which urgently need to be improved.

[0003] The welding robots in the prior art have the following deficiencies in welding path planning, welding current regulation, temperature control, welding parameter adjustment and welding process monitoring:

[0004] Welding path planning is not smart enough: Welding robots usually rely on pre-set welding paths for operation, and it is difficult to make real-time adjustments based on the complex shape and dynamic changes of the welding object. Especially when facing complex curves or irregularly shaped welds, the welding path planning lacks accuracy and flexibility, which can easily lead to weld deviation or unstable welding quality.

[0005] Lack of adaptive adjustment of current output: During the welding process, the stability of the welding current directly affects the welding quality. However, welding robots in the prior art usually adopt a fixed or simply adjusted current control method, which cannot adjust the current in real time according to the thickness changes of the welding material and the specific requirements of the weld, which easily leads to uneven welds or insufficient welding strength.

[0006] Inaccurate temperature control: During the welding process, due to high temperature operation, the temperature of the welding point and the surrounding environment changes dramatically. Excessive temperature may cause the material to overheat, deform or be damaged. Existing welding robots generally use timed or manual cooling methods for temperature management, which cannot be accurately controlled according to real-time temperature changes, thus affecting the welding quality and equipment efficiency.

[0007] Weak adaptive adjustment capability of welding parameters: The complexity of welding tasks requires different welding parameters to ensure welding results under different materials and environments. However, existing welding robots lack the ability to dynamically adjust parameters such as welding speed, current, and voltage, and cannot achieve the best welding results under different working conditions, resulting in uneven welding quality and affecting product consistency.

[0008] Insufficient monitoring and feedback mechanism for the welding process: Existing welding robots mostly rely on post-testing of welding quality and lack real-time monitoring and feedback mechanisms. They are unable to make timely adjustments to abnormal situations during the welding process, which can easily lead to weld defects or welding failures, thereby reducing the automation level and overall efficiency of welding.

[0009] To sum up, when dealing with complex welding tasks, welding robots in the existing technology have deficiencies in welding path planning, welding current control, temperature regulation, parameter adaptability and welding process monitoring. There is an urgent need for a new electrical structure and control method that can effectively improve welding accuracy, stability and automation level to meet the requirements of high-precision and complex structure welding. Summary of the invention

[0010] In order to solve the technical problems existing in the prior art, that is, the existing welding robots have deficiencies in welding path planning, welding current control, temperature regulation, parameter adaptability and welding process monitoring when dealing with complex welding tasks, the technical solution provided by the present invention is:

[0011] A control method for an automatic welding robot comprises the following steps:

[0012] Step 1: Collect physical property information of welding materials;

[0013] Step 2: Process the characteristic information to generate preliminary welding path and welding parameters;

[0014] Step 3: Dynamically adjust the welding path, welding current and voltage according to the real-time data of the welding process;

[0015] Step 4: Adjust the cooling control signal according to the real-time temperature of the monitoring welding area.

[0016] Furthermore, a preferred embodiment is provided, wherein the data processing uses an adaptive algorithm to optimize the welding path and welding parameters according to the characteristics and shape of the welding material.

[0017] Based on the same inventive concept, the present invention also provides a control device for an automatic welding robot, comprising the following modules:

[0018] Module 1: Collecting physical property information of welding materials;

[0019] Module 2: Processing the characteristic information to generate preliminary welding path and welding parameters;

[0020] Module 3: Dynamically adjust welding path, welding current and voltage according to real-time data of welding process;

[0021] Module 4: Steps to adjust the cooling control signal based on the real-time temperature of the monitoring welding area.

[0022] Based on the same inventive concept, the present invention also provides an electrical structure system of an automatic welding robot, the system is used to implement the method described, including:

[0023] A control system, used to receive real-time data fed back by sensors and generate welding operation instructions;

[0024] A sensor system for real-time monitoring of the characteristics of welding materials, the temperature of welding points, and parameters such as current and voltage during welding, and transmitting the monitoring data to the control system;

[0025] A welding power supply system, electrically connected to the control system, for dynamically adjusting welding current and voltage according to the welding operation instructions;

[0026] An execution system, comprising a welding head and a driving mechanism, wherein the welding head is connected to a welding power supply system for performing a welding operation, and the driving mechanism performs motion control of a welding path according to instructions of the control system;

[0027] A temperature monitoring and cooling system, wherein the temperature monitoring module is electrically connected to the control system and is used to monitor the real-time temperature of the welding area, and the cooling system is used to adjust the cooling process according to temperature changes;

[0028] The feedback system is electrically connected to the control system and is used to feed back the real-time data monitored during the welding process to the control system.

[0029] Furthermore, a preferred embodiment is provided, wherein the control system includes an adaptive algorithm module for automatically optimizing the welding path, welding current and voltage based on data fed back by the sensor.

[0030] Furthermore, a preferred embodiment is provided, wherein the welding power supply system includes a variable current source and a variable voltage source.

[0031] Furthermore, a preferred embodiment is provided, wherein the feedback system comprises a welding quality monitoring module, and the monitoring module determines the welding quality according to the real-time sensor data and sends a feedback signal to the control system.

[0032] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computer program, and when the computer reads the computer program, the computer executes the described method.

[0033] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium. When the processor reads a computer program stored in the storage medium, the computer executes the method described.

[0034] Based on the same inventive concept, the present invention also provides a computer program product, which is a computer program. When the computer program is executed, the method described above is implemented.

[0035] Compared with the prior art, the technical solution provided by the present invention is beneficial in that:

[0036] The deep learning welding path optimization system achieves accurate planning of the welding path, effectively improving the accuracy and consistency of welding. Compared with the traditional welding path planning method, the deep learning algorithm can automatically optimize the path according to the complex characteristics of the welding material and weld, reduce the errors caused by human intervention, and thus significantly improve the welding quality.

[0037] The adaptive current regulation system ensures stability during the welding process by monitoring the welding current in real time and dynamically adjusting the current output according to the welding environment. Compared with the traditional welding method with fixed current output, the adaptive current regulation method can quickly respond to changes in material thickness and weld width during welding, reducing the impact of current fluctuations on welding quality, and is particularly suitable for complex welding scenarios.

[0038] The intelligent temperature management system monitors the temperature of the welding point and equipment in real time through temperature sensors, and adjusts the temperature through cooling devices to avoid welding defects caused by excessive temperature. Compared with the ordinary periodic cooling method, intelligent temperature management can dynamically adjust the cooling intensity, effectively prevent overheating problems during welding, ensure welding quality and extend equipment life.

[0039] The adaptive welding parameter adjustment system dynamically adjusts the welding speed, voltage and other parameters according to the feedback welding current and temperature data, ensuring the optimal operation under different welding conditions. Compared with traditional fixed parameter welding, the adaptive adjustment system can flexibly respond to changes in welding environment and materials, significantly improve welding efficiency, and reduce the risk of welding defects caused by environmental changes.

[0040] The real-time monitoring and feedback adjustment system uses a variety of sensors to monitor the welding process in all directions, and can promptly detect and correct abnormalities in the welding process. Compared with the method that relies on manual monitoring, the real-time feedback system can respond quickly and automatically adjust parameters to avoid the decline of welding quality, while improving the automation level and work efficiency of the welding process.

[0041] It is suitable for use in the control of automatic welding robots. DETAILED DESCRIPTION

[0042] In order to make the advantages and benefits of the technical solution provided by the present invention more clearly reflected, the technical solution provided by the present invention is now further described in detail, specifically:

[0043] A brief description of the control method:

[0044] The control method is divided into six steps: first, input and process the welding task data, followed by path planning, then adjust the welding current, temperature and welding parameters, and finally perform real-time monitoring and feedback adjustment through sensors to ensure the smooth completion of the welding task.

[0045] Detailed step description:

[0046] 1. Welding task data input and initialization

[0047] Brief description: The user or system inputs the basic information of the welding task into the system to complete the initialization process, including welding materials, weld requirements, etc.

[0048] Detailed description:

[0049] The system collects basic data of the welding task from user input or through sensors. These data include: type of welding material, thickness, weld length and shape, working environment temperature, etc.

[0050] The system initializes welding parameters, such as standard current, voltage range and preset welding speed. After the data input is completed, the system generates a preliminary welding task configuration.

[0051] Output: The initialized mission configuration file will serve as input for subsequent path planning and parameter adjustment.

[0052] 2. Welding path planning

[0053] Brief description: Based on the input task data, the system uses deep learning algorithms to plan the welding path.

[0054] Detailed description:

[0055] The system scans the surface of the welding material through a camera or laser sensor, combines the input task data, and uses a deep learning algorithm to analyze the material shape and weld characteristics.

[0056] Based on the thickness, shape and weld requirements of the welding material, the system calculates the optimal welding path, including the welding point, the starting and ending positions, and the moving speed along the path.

[0057] The system also marks areas on the welding path that require special control, such as areas where temperature fluctuations may occur or where the weld is too narrow.

[0058] Output: The optimal welding path serves as input for subsequent welding parameter adjustment.

[0059] 3. Adaptive current regulation

[0060] Brief description: According to the path planning results, the system dynamically adjusts the welding current to ensure the stability of the welding process.

[0061] Detailed description:

[0062] The system analyzes the welding requirements of different path segments based on the output data of welding path planning, especially the thickness of the material and the complexity of the weld.

[0063] The system monitors the current welding current in real time through the current sensor and adjusts the current output based on the local characteristics of the welding path (such as thickness change, weld width, etc.).

[0064] When the material resistance changes during welding, the system instantly compensates or reduces the current to maintain the quality and consistency of the weld joint.

[0065] Output: The adjusted real-time welding current data will be used as input for the next step of temperature control.

[0066] 4. Intelligent temperature management

[0067] Brief description: Real-time monitoring of the temperature of the welding area and robot equipment, and adjustment of the temperature to ensure that there is no overheating during the welding process.

[0068] Detailed description:

[0069] Temperature sensors monitor the soldering point and the surrounding environment in real time, including the temperature of the soldering point and the operating temperature of key components such as the robot motor.

[0070] Based on the welding current data output in step 3, the system predicts the impact of current changes on temperature and dynamically adjusts the power of the cooling fan or liquid cooling system to avoid overheating of the welding point.

[0071] When the temperature exceeds the safe range, the system will trigger an alarm and reduce the welding speed to ensure that the welding quality is not affected by high temperature.

[0072] Output: The temperature data after temperature adjustment will be used for real-time monitoring and feedback adjustment stage.

[0073] 5. Adaptive welding parameter adjustment

[0074] Brief description: According to the real-time monitoring of welding current and temperature data, the welding speed, voltage and other parameters are dynamically adjusted to ensure the best welding effect.

[0075] Detailed description:

[0076] The system combines the current regulation result in step 3 and the temperature data in step 4 to comprehensively analyze the actual situation during the welding process.

[0077] Automatically adjust parameters such as welding speed and welding voltage. For example, when the temperature rises close to the upper limit, the system will reduce the welding speed to prevent damage to the welding material; when the welding path section requires high current, the system will adjust the voltage accordingly.

[0078] The system also automatically corrects parameters based on material properties and environmental conditions to ensure consistent welding quality under different working conditions.

[0079] Output: The optimized welding parameters will be transmitted to the real-time monitoring and feedback adjustment system.

[0080] 6. Real-time monitoring and feedback adjustment

[0081] Brief description: Through monitoring equipment such as cameras, temperature sensors and current sensors, data during the welding process can be obtained in real time and feedback adjustments can be made.

[0082] Detailed description:

[0083] The system uses a variety of sensors to monitor the current, temperature, weld quality, etc. during the welding process in real time and generate feedback data.

[0084] If the sensor detects welding anomalies, such as uneven weld width, excessive welding point temperature or unstable current, the system will immediately make feedback adjustments to modify the welding parameters and prevent welding defects.

[0085] The feedback data is not only used for the current welding task, but is also stored in the system for reference in future welding tasks, thus improving the system’s self-learning capabilities.

[0086] Output: The feedback data during the welding process is used as a summary of the completed welding task and provides a reference for subsequent welding tasks. The electrical structure of the system is:

[0087] Modular power management system, adaptive current regulation system, intelligent temperature management system, deep learning welding path optimization system, adaptive welding parameter adjustment system and multi-mode welding control system.

[0088] 2. Connection relationship between systems:

[0089] Modular power management system

[0090] The system provides power supply for different subsystems (such as motor drive system, welding power supply, sensor module, etc.) through independent power modules. Each power module is directly connected to the corresponding system and has a built-in intelligent control chip to monitor and adjust the voltage and current of each system in real time.

[0091] The modular power management system is connected to the adaptive current regulation system, which obtains welding current data through current sensors and provides energy guarantee for automatic regulation of welding current.

[0092] Adaptive current regulation system

[0093] The system works closely with the modular power management system to monitor welding current changes in real time through current sensors and controllers, and automatically adjusts the welding current output according to the different characteristics of the welding task and material to ensure current stability during the welding process.

[0094] The system is also connected to the deep learning welding path optimization system, which adjusts the current output in real time according to the path planning results to ensure that the current meets the optimal path requirements during the welding process.

[0095] Intelligent temperature management system

[0096] The intelligent temperature management system is connected to the welding area, robot body and motor drive system through temperature sensors, monitors the welding point and robot temperature in real time, and adjusts the temperature through cooling devices (such as fans or liquid cooling systems).

[0097] This system works together with the adaptive current regulation system to ensure that temperature changes during the welding process will not affect the stability of the current, thereby avoiding welding quality problems caused by excessive temperature.

[0098] Deep learning welding path optimization system

[0099] The system integrates detection equipment such as cameras or laser sensors to obtain real-time data on welding environment, materials and weld characteristics. It is connected to the control system and autonomously plans the welding path through a deep learning algorithm.

[0100] The system works together with the adaptive current regulation system and the adaptive welding parameter adjustment system. The results of welding path optimization will directly affect the adjustment of key parameters such as welding current and welding speed, thereby ensuring accurate execution of the welding process.

[0101] Adaptive welding parameter adjustment system

[0102] The system automatically adjusts key parameters of the welding process, such as welding voltage, current and welding speed, through data feedback of welding current, temperature and welding path.

[0103] Closely connected with the deep learning welding path optimization system and the adaptive current regulation system, the welding parameters are dynamically adjusted according to the path planning results and the actual characteristics of the welding materials to ensure efficient and high-quality welding operations.

[0104] Multi-mode welding control system

[0105] The system is connected to all core systems, allowing users to select different welding modes (such as spot welding, continuous welding, pulse welding, etc.) according to welding requirements. The system will automatically optimize the parameters of each system according to the selected welding mode to ensure welding stability in different modes.

[0106] The system works in conjunction with the adaptive welding parameter adjustment system to ensure precise control of welding parameters in different welding modes by adjusting current and voltage output.

[0107] 3. Cooperation relationship between systems:

[0108] The modular power management system is the basis of all systems. Through intelligent management, it provides a stable power supply to other systems, especially providing energy support for the regulation and control of welding current.

[0109] The adaptive current regulation system works with the temperature management and path optimization systems during the welding process to ensure stable current output during the welding process and avoid current fluctuations caused by temperature and path changes.

[0110] The intelligent temperature management system uses temperature sensors and cooling systems to adjust the temperature of the welding area and equipment in real time to ensure that equipment safety and welding quality are not affected by high temperatures. At the same time, it cooperates with the current regulation system to prevent temperature fluctuations caused by current changes.

[0111] The deep learning welding path optimization system dynamically adjusts the welding path during the entire welding process, and controls the adjustment of current and welding parameters through feedback data, making the welding process more intelligent and precise.

[0112] The adaptive welding parameter adjustment system adjusts the welding current, welding speed and other parameters in real time according to the feedback data, and cooperates with the welding path optimization system and multi-mode welding control system to achieve efficient welding.

[0113] The multi-mode welding control system coordinates various systems according to the requirements of different welding tasks, completes welding tasks with optimal parameters, and adapts to operational requirements in different modes.

[0114] in conclusion:

[0115] The electrical structure system achieves high precision and stability in the welding process through modular management, real-time feedback and intelligent control. The connection and coordination between systems ensures efficient execution of various tasks and can provide intelligent and flexible welding control in complex welding environments.

[0116] In specific practical work:

[0117] Example 1: Small steel plate welding task

[0118] Task description: Automatically weld small steel plates with a thickness of 5 mm. The weld is straight and 1 meter long.

[0119] step:

[0120] The user inputs the material, thickness and weld length of the steel plate, and the system automatically initializes the welding parameters, including current, voltage range and welding speed.

[0121] The control system uses a camera to identify the surface of the steel plate, perform path planning, and generate the optimal welding path for straight welds.

[0122] The execution system starts the welding head and moves it along the welding path. During the welding process, the current sensor monitors the welding current in real time and adjusts the output.

[0123] Temperature sensors monitor the temperature of welds and equipment in real time, and the cooling system adjusts the cooling intensity based on feedback data to avoid overheating.

[0124] After welding is completed, the system stores all data from the welding process, generates a welding report, and can be used as a reference for subsequent tasks.

[0125] Example 2: Large Pipeline Welding Task

[0126] Task description: Automatically weld large pipes with a thickness of 10 mm. The weld is circular and 2 meters long.

[0127] step:

[0128] The user inputs the pipe material, thickness and weld length, and the system automatically initializes the welding parameters, including high current output and medium welding speed.

[0129] The control system uses a camera to scan the pipe surface, combines the material thickness, generates the welding path of the circular weld, and marks the area of ​​thickness change.

[0130] The execution system starts the welding head according to the path planning results and welds along the pipe surface. The current sensor monitors the current in real time and adjusts the output according to the thickness.

[0131] The system starts the air cooling device to ensure that the welding point and equipment temperature are within a safe range during the welding process to avoid local overheating of the pipeline.

[0132] Through the real-time monitoring system, the weld quality during the welding process is detected and feedback is adjusted, and a data report is generated after welding is completed.

[0133] Example 3: Precision equipment welding task

[0134] Task description: Automated welding of the casing of precision electronic equipment requires high-precision welding, with a curved weld and a length of 0.5 meters.

[0135] step:

[0136] The user inputs the material of the equipment shell and the weld curve, and the system automatically initializes the low current and low speed welding parameters.

[0137] The control system scans the equipment casing through a camera, generates the path of the complex curved weld, and marks the areas that require delicate operations.

[0138] The execution system starts the welding head and performs precise welding along the curved path. During the welding process, the current sensor and voltage sensor work together to ensure welding accuracy.

[0139] The temperature sensor monitors the shell temperature in real time and starts the liquid cooling system to adjust the temperature to prevent the shell from deforming due to high temperature of welding.

[0140] The system uses sensors to monitor the quality of the weld throughout the process, generates a detailed quality report after welding is completed, and records the welding parameters for subsequent task optimization.

[0141] The technical solution provided by the present invention is further described in detail above through several specific implementation modes in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the several specific implementation modes described above are not intended to be used as limitations on the present invention. Any reasonable modification and improvement of the present invention, combination of implementation modes and equivalent substitution within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A control method for an automatic welding robot, characterized in that: The following steps are involved: Step 1: Collect physical property information of welding materials; Step 2: Process the characteristic information to generate preliminary welding path and welding parameters; Step 3: Dynamically adjust the welding path, welding current and voltage according to the real-time data of the welding process; Step 4: Adjust the cooling control signal according to the real-time temperature of the monitoring welding area.

2. The control method according to claim 1, characterized in that: The data processing uses an adaptive algorithm to optimize the welding path and welding parameters according to the characteristics and shape of the welding material.

3. A control device for an automatic welding robot, characterized in that: Includes the following modules: Module 1: Collecting physical property information of welding materials; Module 2: Processing the characteristic information to generate preliminary welding path and welding parameters; Module 3: Dynamically adjust welding path, welding current and voltage according to real-time data of welding process; Module 4: Steps to adjust the cooling control signal based on the real-time temperature of the monitoring welding area.

4. An electrical structure system of an automatic welding robot, characterized in that: The system is used to implement the method according to claim 1, comprising: A control system, used to receive real-time data fed back by sensors and generate welding operation instructions; A sensor system for real-time monitoring of the characteristics of welding materials, the temperature of welding points, and parameters such as current and voltage during welding, and transmitting the monitoring data to the control system; A welding power supply system, electrically connected to the control system, for dynamically adjusting welding current and voltage according to the welding operation instructions; An execution system, comprising a welding head and a driving mechanism, wherein the welding head is connected to a welding power supply system for performing a welding operation, and the driving mechanism performs motion control of a welding path according to instructions of the control system; A temperature monitoring and cooling system, wherein the temperature monitoring module is electrically connected to the control system and is used to monitor the real-time temperature of the welding area, and the cooling system is used to adjust the cooling process according to temperature changes; The feedback system is electrically connected to the control system and is used to feed back the real-time data monitored during the welding process to the control system.

5. The electrical structure system according to claim 4, characterized in that: The control system includes an adaptive algorithm module that automatically optimizes the welding path, welding current and voltage based on data fed back by the sensor.

6. The electrical structure system according to claim 4, characterized in that: The welding power supply system includes a variable current source and a variable voltage source.

7. The electrical structure system according to claim 4, characterized in that: The feedback system includes a welding quality monitoring module, which determines the welding quality according to the real-time sensor data and sends a feedback signal to the control system.

8. A computer storage medium for storing a computing program, characterized in that: When the computer reads the computer program, the computer executes the method of claim 1.

9. A computer, comprising a processor and a storage medium, characterized in that: When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 1 .

10. A computer program product, being a computer program, characterized in that When the computer program is executed, the method of claim 1 is implemented.