Robot medium and thick plate welding control method based on expert database and integrated welding system

Abstract

The invention discloses a robot medium and thick plate welding control method based on an expert database and an integrated welding system.The expert database is established, the expert database comprises multiple sets of weld joint data, and each set of weld joint data comprises workpiece condition parameters, the number of welding passes and welding parameters of each pass which correspond to one another; workpiece condition parameters are selected according to welding requirements, and weld joint data meeting the welding requirements are obtained from the expert database; modifying or storing the welding pass number and each pass welding parameter corresponding to the set of welding seam data, and generating a multi-layer multi-pass parameter group; writing a starting point and an ending point of a welding seam, inserting a multi-layer and multi-pass parameter group, calling matched welding pass number and welding parameters of each pass in the multi-layer and multi-pass parameter group, and controlling a robot to perform welding according to the multi-layer and multi-pass parameter group, so that the welding parameters of each pass are better matched with parameters of welding requirements, the welding seam fusion degree is better, and the fusion depth better meets the requirements; the probability of weld seam undercut and cracks is reduced, and the quality of thick plate welding in the robot is improved.

Description

Technical Field

[0001] This invention relates to the field of robotic welding technology, and in particular to a robotic control method and integrated welding system for medium and thick plates based on an expert database. Background Technology

[0002] Because welding medium and heavy plates requires deep and wide welds, it typically involves multi-layer, multi-pass welding processes, necessitating precise control of parameters such as welding current, voltage, and welding speed. Current robotic welding technology usually employs manual programming of the robot. First, the parameters for one weld seam are programmed and welded. Then, based on the welding results of the previous weld seam, the parameters for the second weld seam are programmed and welded, and so on. This process requires programming N weld seams and setting N parameters to complete the welding of medium and heavy plate workpieces. This type of welding control relies entirely on manual programming, and the parameters are based on experience or debugging. Each time a weld seam or workpiece is switched, reprogramming, parameter setting, and debugging are required. For example, for a 50-pass weld seam, manual programming and debugging to obtain a qualified weld seam can take more than two days, resulting in long programming time, long debugging time, and a large number of workpieces used for machine setup.

[0003] Currently, although there are pre-programmed welding programs for multiple weld seams used for repeated welding of the same workpiece, the following problems exist:

[0004] Firstly, variations in the incoming workpiece materials, such as changes in wire extension, increased resistance in the wire feed tube or welding torch, and differences in gas flow rate; or changes in external conditions of the welding torch or welding machine, such as changes in weld cleanliness or internal conditions of the welding machine, can all lead to changes in the welding current, causing a deviation from the set current. If the pre-programmed parameter values ​​are too small, some weld beads or the overall weld may be too small, resulting in incomplete fusion or insufficient penetration. If the pre-programmed parameter values ​​are too large, it can lead to undercut and cracks in the weld.

[0005] Secondly, the lack of calibration for the deviation between pre-programmed current and actual welding current leads to a mismatch between actual and required parameters. Furthermore, the inability to diagnose and compensate for the current during the welding process results in a large deviation between the welded product and the welding requirements, leading to a low pass rate. Summary of the Invention

[0006] The purpose of this invention is to address the problems of incomplete weld fusion, insufficient penetration, or weld undercut and cracks that arise when there are differences in the incoming materials of the workpiece or changes in the external conditions of the welding torch or welding machine. This invention provides a robotic welding control method and integrated welding system based on an expert database for medium-thick plates.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A robot-based control method for welding medium-thick plates, based on an expert database, includes the following steps:

[0009] S1. Establish an expert database, which includes multiple sets of weld data; each set of weld data includes corresponding workpiece condition parameters, number of welding passes, and welding parameters for each pass.

[0010] S2. Based on the welding requirements of the workpiece, select the workpiece condition parameters, and then obtain at least one set of weld data that meets the welding requirements from the expert database; modify or save the number of welding passes and the welding parameters of each pass corresponding to the set of weld data, and then generate a multi-layer multi-pass parameter group.

[0011] S3. Write the start and end points of the weld, insert the multi-layer multi-pass parameter group, call the matching number of welding passes and welding parameters of each pass in the multi-layer multi-pass parameter group, and then control the robot to weld according to the parameters of the multi-layer multi-pass parameter group.

[0012] The robot-based medium-thick plate welding control method described in this invention establishes an expert database. Based on the welding requirements of the workpiece, it can quickly obtain at least one set of weld data that meets the welding load requirements by selecting workpiece condition parameters. This eliminates the need for manual programming of the number of welding passes and welding parameters for each weld. When there are differences in the incoming workpiece material or changes in the external conditions of the welding torch or welding machine, it can quickly switch to at least one more suitable set of weld data by selecting workpiece condition parameters that meet the welding requirements. Through simple modifications or direct saving, it can generate multi-layer, multi-pass parameter sets that better meet the welding requirements, making each welding parameter more compatible with the welding requirements. This results in better weld fusion and penetration depth during welding, reducing the probability of weld undercut and cracks caused by large deviations in each welding parameter, and improving the quality of robot-based medium-thick plate welding.

[0013] Preferably, the robot-based medium-thick plate welding control method based on an expert database according to the present invention includes the following steps in establishing the expert database:

[0014] Based on the welding requirements of the experimental workpiece, the workpiece condition parameters are set; the workpiece condition parameters include: groove type, groove angle, blunt edge, weld thickness, welding wire type, gas type, and welding wire extension length;

[0015] Set multiple workpiece condition parameters, perform multiple experimental welding experiments on multiple experimental workpieces, and record the number of welding passes and the welding parameters for each experimental welding experiment.

[0016] The experimental welded products are evaluated, and the number of weld passes and the welding parameters of each pass corresponding to the qualified welds are selected as weld data. The corresponding workpiece condition parameters, number of weld passes and welding parameters of each pass are entered into the expert database to establish each set of weld data.

[0017] As a preferred embodiment of the present invention, the expert database is established through the above steps, so that the detailed parameters of the database are derived from the data selected and filled by engineers based on welding experiments under actual conditions. This further optimizes the matching degree between the number of welding passes and the welding parameters of each pass in the expert database and the workpiece condition parameters, thereby improving the reliability of each set of weld data in the expert database.

[0018] Preferably, the robot-based medium-thick plate welding control method based on an expert database according to the present invention further includes the following steps in establishing the expert database:

[0019] Workpiece condition parameters, number of welding passes, and welding parameters for each pass are recorded in a database to create multiple sets of weld data database files; each set of weld data is numbered to form a corresponding process document number.

[0020] A database interface is created, which includes a selection module and a modification module for workpiece condition parameters. By selecting or modifying the workpiece condition parameters, the number of welding passes and the parameters for each pass can be displayed on the database interface.

[0021] As a preferred embodiment of the present invention, the establishment of an expert database through the above steps can provide users with a more convenient operating interface. By selecting or modifying the workpiece condition parameters, the corresponding set of weld data can be quickly called through the process file number, thereby displaying the number of welding passes and the welding parameters of each pass. This allows for the rapid acquisition of a pass distribution and specific parameters that better match the workpiece to be welded, further improving the efficiency of welding parameter setting.

[0022] Preferably, the robot-based medium-thick plate welding control method based on an expert database of the present invention performs current calibration before step S1, specifically including the following steps:

[0023] Select a calibration workpiece with a specified length, width, and thickness; program at least two robot programs using a teach pendant, each with a different extension length; set the welding length, and corresponding to the welding length, set the welding process current to gradually change from the minimum current value to the maximum current value;

[0024] Welding of the calibrated workpiece begins, and the first actual welding current during the welding process is collected; the first actual welding current is compared with the set current to generate a current-correspondence curve table.

[0025] Based on the set current of each welding parameter in the expert database, the corresponding output current is output, and the welding machine is controlled by the output current to perform welding.

[0026] As a preferred embodiment of the present invention, by means of current calibration, when there are differences in the incoming materials of the workpiece, such as welding wires with different extension lengths, a corresponding output current can be output. The output current is used to control the welding machine to perform welding, thereby eliminating the deviation between the actual welding current and the set current caused by the change in the extension length of the welding wire. This further improves the fusion of the weld, increases the rate of compliance of the welding penetration, reduces the probability of weld undercut or cracks, and further improves the welding quality.

[0027] Preferably, in the robot-based medium-thick plate welding control method based on an expert database described in this invention, step S3 further includes current self-diagnosis and current adjustment, specifically comprising the following steps:

[0028] The second actual welding current is collected and returned to the welding control system; the trend of the second actual welding current is judged; if the second actual welding current continuously exceeds the threshold range within a set time, the set current is adjusted so that the second actual welding current meets the welding requirements.

[0029] As a preferred embodiment of the present invention, current is the most critical parameter in multi-layer and multi-pass welding, and it needs to be precisely controlled during the welding process. Through current self-diagnosis and current adjustment, if the value of the second actual welding current is too small, the output current is increased; if the value of the second actual welding current is too large, the output is reduced. Even if the current fluctuates greatly, the system automatically reduces or increases the current, making it less likely for the weld to have incomplete fusion or insufficient penetration, or obvious defects such as undercut and cracks, thereby improving the weld qualification rate.

[0030] Preferably, in the robot-based medium-thick plate welding control method based on an expert database of the present invention, the current calibration further includes verifying the current-corresponding curve table, specifically including the following steps:

[0031] Select the verification current, output the first actual welding current corresponding to the verification current according to the current curve table, and perform verification welding; collect the third actual welding current during the verification welding process, and compare the deviation between the third actual welding current and the verification current; if the deviation between the third actual welding current and the verification current is less than the deviation threshold, the current calibration is deemed qualified.

[0032] As a preferred embodiment of the present invention, by selecting a verification current and performing verification welding on the current-corresponding curve table, the qualification of the current-corresponding curve table is verified, which further improves the reliability of current calibration, reduces the possibility of deviation between the actual welding current and the set current, and improves welding quality.

[0033] Preferably, in the robot-based medium-thick plate welding control method based on an expert database of the present invention, the current calibration further includes optimizing the current-corresponding curve table, specifically including the following steps:

[0034] If the deviation between the third actual welding current and the verification current is greater than the deviation threshold, the current calibration and verification of the current corresponding curve table shall be performed again until the current calibration is qualified and then the current corresponding curve table shall be saved.

[0035] As a preferred embodiment of the present invention, by optimizing the current correspondence curve table, the accuracy of the current correspondence curve table is further improved, the possibility of deviation between the actual welding current and the set current is reduced, and the welding quality is improved.

[0036] Preferably, the robot-based medium-thick plate welding control method based on an expert database of the present invention, wherein inserting the multi-layer, multi-pass parameter group specifically includes the following steps:

[0037] Load the expert database; select workpiece condition parameters according to the requirements of the workpiece to be welded, and select the corresponding number of welding passes and welding parameters for each pass, and output multi-layer multi-pass parameter groups.

[0038] As a preferred embodiment of the present invention, the above-described steps of inserting multi-layer multi-pass parameter groups enable the rapid and accurate insertion of multi-layer multi-pass parameter groups, thereby rapidly and accurately generating multi-layer multi-pass parameter groups and further improving the efficiency of welding programming and setting.

[0039] To achieve the objectives of this invention, another technical solution is provided:

[0040] An integrated welding system includes: a robot control module, a power supply module, and an expert database module; the robot control module is used to work with the power supply module and the expert database module to control a robotic welding machine to perform welding operations; the power supply module is connected to the robot control module via an internal control bus, and can cooperate with the robot control module to control the welding current and welding voltage of the robotic welding machine; the expert database is used to collect and store workpiece condition parameters, the number of welding passes, and welding parameters for each pass, thereby generating multi-layer, multi-pass parameter groups.

[0041] The integrated welding system described in this invention, through the cooperation of a robot control module, a power supply module, and an expert data module, can generate multi-layer, multi-pass parameter sets that better meet welding requirements through simple modifications or direct saving during use. Controlling the robot welding machine to perform medium-thick plate welding based on these multi-layer, multi-pass parameter sets not only reduces the probability of weld undercut and cracks caused by large deviations in welding parameters per pass, but also improves the quality of robot welding of medium-thick plates. Furthermore, depending on the actual weld type, such as fillet welds and vertical welds, the system controls the generation and adjustment of multi-layer, multi-pass parameter sets that closely match the actual workpiece, thus achieving a high-quality weld. The integrated welding system, through the combined power supply module and expert data module, can control the input and retrieval of process documents within the welding machine, resulting in a high degree of integration and stability for the entire system.

[0042] Preferably, the integrated welding system of the present invention further includes a current calibration module and a current self-diagnosis and adjustment module; the current calibration module is used to collect the actual welding current and, in conjunction with the robot control module, generate a current-corresponding curve table; the current self-diagnosis and adjustment module is used to monitor the real-time actual welding current and, in conjunction with the robot control module, adjust the set current.

[0043] In multi-layer, multi-pass welding, current is a critical parameter, and voltage changes with current. As a preferred embodiment of the present invention, by setting a current calibration module and a current self-diagnosis and adjustment module, the given value during welding is made close to the actual value, so that the current is controlled within the deviation threshold range under the same current extension. Through the self-diagnosis and adjustment module, the oscillation caused by real-time current adjustment can be avoided, which would cause the weld to fluctuate in size. The set current is very close to the actual welding current, and even closer to the current in the expert database. Even if the current fluctuates greatly, the system automatically reduces or increases the current, making the weld less prone to obvious defects, thereby further improving the welding quality.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] 1. The robot-controlled welding of medium and thick plates does not require manual programming of the number of welding passes and welding parameters for each weld. When there are differences in the incoming materials of the workpiece or changes in the external conditions of the welding torch or welding machine, the robot can quickly switch to at least one more matching set of weld data by selecting workpiece condition parameters that meet the welding requirements. Through simple modification or direct saving, the robot can generate multi-layer and multi-pass parameter groups that better meet the welding requirements, making each welding parameter and the welding requirements more matched. This results in better weld fusion and penetration depth during welding, reducing the probability of weld undercut and cracks caused by large deviations in each welding parameter, and improving the quality of robot welding of medium and thick plates.

[0046] 2. The integrated welding system, during welding programming or setup, can automatically generate multi-layer, multi-pass parameter sets that better meet welding requirements by selecting workpiece condition parameters that meet the welding requirements. These multi-layer, multi-pass parameter sets are then used to control the robotic welding machine for welding medium-thick plates. This not only reduces the probability of weld undercut and cracks caused by large deviations in welding parameters per pass, thus improving the quality of robotic welding of medium-thick plates, but also allows for the generation and adjustment of multi-layer, multi-pass parameter sets that closely match the actual workpiece, based on the different weld types, such as fillet welds and vertical welds. This enables the completion of a high-quality weld. Furthermore, the system can control the input and retrieval of process documents within the welding machine, resulting in a high degree of integration and stability. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating the robot-based medium-thick plate welding control method based on an expert database according to the present invention.

[0048] Figure 2 This is a schematic diagram of the current calibration process of the present invention;

[0049] Figure 3 This is a schematic diagram of the current calibration state of the present invention;

[0050] Figure 4 This is a schematic diagram of the current self-diagnosis and current adjustment process of the present invention;

[0051] Figure 5 This is a schematic diagram of the modular structure of the integrated welding system of the present invention;

[0052] Reference numerals: 1. Welding machine; 2. Calibrated workpiece; 3. Robot welding module. Detailed Implementation

[0053] The present invention will now be described in detail with reference to the accompanying drawings.

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0055] Example 1:

[0056] refer to Figure 1 As shown, this embodiment discloses a robot-based control method for welding medium-thick plates using an expert database, comprising the following steps:

[0057] S1. Establish an expert database, which includes multiple sets of weld data; each set of weld data includes corresponding workpiece condition parameters, number of welding passes, and welding parameters for each pass.

[0058] S2. Based on the welding requirements of the workpiece, select the workpiece condition parameters, and then obtain at least one set of weld data that meets the welding requirements from the expert database; modify or save the number of welding passes and the welding parameters of each pass corresponding to the set of weld data, and then generate a multi-layer multi-pass parameter group.

[0059] S3. Write the start and end points of the weld, insert multi-layer multi-pass parameter groups, call the matching number of welding passes and welding parameters of each pass in the multi-layer multi-pass parameter groups, and then control the robot to weld according to the parameters of the multi-layer multi-pass parameter groups.

[0060] The expert database described in this invention can be established by collecting data on the actual number of welding passes and the welding parameters for each pass, or by conducting welding experiments on standard workpieces and collecting the number of welding passes and the welding parameters for each pass during the welding experiments. In this embodiment, establishing the expert database may specifically include the following steps:

[0061] Based on the welding requirements of the experimental workpiece, the workpiece condition parameters are set; the workpiece condition parameters include: groove type, groove angle, blunt edge, weld thickness, welding wire type, gas type, and welding wire extension length;

[0062] Set multiple workpiece condition parameters, perform multiple experimental welding experiments on multiple experimental workpieces, and record the number of welding passes and the welding parameters for each experimental welding experiment.

[0063] The experimental welded products are evaluated, and the number of weld passes and the welding parameters of each pass corresponding to the qualified welds are selected as weld data. The corresponding workpiece condition parameters, number of weld passes and welding parameters of each pass are entered into the expert database to establish each set of weld data.

[0064] It should be noted that the mutual correspondence and matching mentioned in this invention are understood to mean that the workpiece condition parameters, the number of welding passes, and the welding parameters for each pass in each set of weld data can be corresponding or matched through the process document number, which can be achieved through normal data storage or data retrieval. For example, the workpiece condition parameters, the number of welding passes, and the welding parameters for each pass correspond one-to-one.

[0065] The workpiece condition parameters of this invention are entered according to the actual workpiece being welded. Typical workpiece condition parameters include the following: bevel type is V / single V / right angle / vertical angle, bevel angle is 30°, 45°, 60°, blunt edge is 0~6mm, weld depth is 12~100mm, welding wire type is 1.2mm / 1.4mm / 1.6mm, gas type is carbon dioxide or mixed gas, and welding wire extension length is 15mm or 25mm.

[0066] More specifically, establishing an expert database may further include the following steps: recording workpiece condition parameters, the number of welding passes, and the parameters for each pass into the database to create multiple sets of weld data database files; numbering each set of weld data to form a corresponding process document number; creating a database interface, which includes a selection module and a modification module for workpiece condition parameters; and displaying the number of welding passes and the parameters for each pass on the database interface by selecting or modifying the workpiece condition parameters. For example, in an integrated welding system, a process document number can be specified, and the document number can include parameters such as arc stiffness, cladding coefficient, arc initiation parameters, waveform parameters, and crater filling parameters.

[0067] The welding parameters described in this invention are understood as the operating parameters for controlling the robotic welding machine 1 to complete each welding pass; specifically, they may include: welding current of 50-400A, welding voltage of -10~+10, welding speed of 1~100, process document number of 0~100, oscillation frequency of 0.1~4, oscillation amplitude of 0.1~50, left oscillation stop time of 0.1~10, right oscillation stop time of 0.1~10, front and rear tilt angle of 0~90°, left and right tilt angle of 0~90°, arc start offset value XYZ of 0~150, arc end offset value XYZ of 0~150 respectively, and welding direction of forward or reverse.

[0068] Because medium and thick plate workpieces are prone to deformation during prolonged welding, factors such as changes in wire extension, wire feeding resistance of the wire feed tube / welding torch, welding gas composition, and weld cleanliness can all lead to variations in the actual welding current. Further improvements to this invention refer to... Figure 2 and Figure 3 As shown, current calibration is performed before step S1, specifically including the following steps: selecting a calibration workpiece 2 with a specified length, width, and thickness; programming at least two robot programs via a teach pendant, each with a different extension length; setting the welding length, and corresponding to the welding length, setting the current during the welding process to gradually change from the minimum current value to the maximum current value; starting welding the calibration workpiece 2 and collecting the first actual welding current during the welding process; comparing the first actual welding current with the set current to generate a current-correspondence curve table; outputting the corresponding output current based on the set current of each welding parameter in the expert database, and controlling the welding machine 1 to perform welding with the output current.

[0069] For example, in multi-layer, multi-pass welding, current is the most critical parameter. Voltage changes with current, so current calibration is performed, referencing... Figure 3As shown, prepare a carbon steel plate with a length of 1.0m, a width of 0.1m, and a thickness of 10mm. Manually program two robot programs using a teach pendant. Each robot program uses welding wire with extension lengths of 15mm and 25mm, respectively. From left to right, the current is set to gradually increase from 50A to 400A, with a length of 0.8-1.0 meters. Open the calibration interface, specify the calibration program number, and start welding. During welding, the system automatically collects the feedback current, compares the actual welding current with the set current, and generates a current-to-current curve table. After saving, the welding current will be generated according to the curve in the current-to-current curve table, so that the given current value during welding is close to the actual current value.

[0070] It should be noted that the current-corresponding curve table described in this invention is understood as a current-corresponding curve table related to the set current and the actual welding current. For example, when generating the current-corresponding curve table, a rectangular coordinate curve with a set current interval of 5A for welding wires with extension lengths of 15mm and 25mm can be established. The horizontal axis value can be given as 50A / 55A / 60A~400A. Each horizontal axis value is output for 1 second, and the actual current value signal is collected. After averaging the actual current value signal, the corresponding actual current value is recorded as the vertical axis, and the difference within 5A is equally divided. After saving, the actual output current value can be obtained under the condition of welding wires with extension lengths of 15mm and 25mm. If the expert database requires a welding current of 132A, the system will output the value to welding machine 1 according to the actual needs.

[0071] Specifically, current, as the most critical parameter in multi-layer, multi-pass welding, requires precise control during the welding process. (Refer to...) Figure 4 As shown, S3 of the present invention further includes current self-diagnosis and current adjustment, specifically including the following steps: acquiring the second actual welding current and returning it to the welding control system; judging the trend of the second actual welding current; if the second actual welding current continuously exceeds the threshold range within a set time, adjusting the set current so that the second actual welding current is adjusted to meet the welding requirements.

[0072] For example, to avoid oscillations caused by real-time current adjustment leading to inconsistent weld size, this invention samples the current of welding machine 1 during the welding process and performs filtering and averaging. Welding machine 1 feeds back the real-time current to the system via a bus, with the data transmission time set to 100ns. Data statistics are performed to determine the current trend. If the current exceeds 20A continuously within 3 seconds, the set current is automatically increased or decreased through PID adjustment. The deviation is compensated by the corresponding current value to welding machine 1. If the current is too low, the output is increased; if it is too high, the output is decreased. If the current is 10A too low, it is increased by 10A to ensure that the welding current is consistent with the set value required for multiple layers and multiple passes.

[0073] Specifically, the current calibration also includes verifying the current correspondence curve table, which specifically includes the following steps: selecting a verification current, outputting the first actual welding current corresponding to the verification current according to the current correspondence curve table, and performing verification welding; collecting the third actual welding current during the verification welding process, and comparing the deviation between the third actual welding current and the verification current; if the deviation between the third actual welding current and the verification current is less than the deviation threshold, the current calibration is deemed qualified.

[0074] Specifically, the current calibration also includes optimizing the current-corresponding curve table, which specifically includes the following steps:

[0075] If the deviation between the third actual welding current and the verification current is greater than the deviation threshold, the current calibration and verification of the current corresponding curve table should be performed again until the current calibration is qualified, and then the current corresponding curve table should be saved.

[0076] The insertion of multi-layer, multi-channel parameter groups as described in this invention specifically includes the following steps:

[0077] Load the expert database; select workpiece condition parameters according to the requirements of the workpiece to be welded, and select the corresponding number of welding passes and welding parameters for each pass, and output multi-layer multi-pass parameter groups.

[0078] Example 2:

[0079] refer to Figure 5 As shown, based on Embodiment 1, this embodiment discloses an integrated welding system that implements the robot-based medium-thick plate welding control method of Embodiment 1, which is based on an expert database. The system includes: a robot control module, a power supply module, and an expert database module. The robot control module is used to coordinate with the power supply module and the expert database module to control the robot welding machine 1 to perform welding operations. The power supply module is connected to the robot control module via an internal control bus, enabling it to control the welding current and welding voltage of the robot welding machine 1 in conjunction with the robot control module. The expert database is used to collect and store workpiece condition parameters, the number of welding passes, and the welding parameters for each pass, thereby generating multi-layer, multi-pass parameter sets. (Reference) Figure 4 and Figure 5 As shown, the robot welding machine 1 of the present invention is understood as the robot welding machine 1 in the robot welding module 3. The robot welding module 3 realizes the execution of robot welding by receiving integrated control from the robot module and the power module.

[0080] Specifically, the integrated welding system described in this embodiment further includes: a current calibration module and a current self-diagnosis and adjustment module; the current calibration module is used to collect the actual welding current and, in conjunction with the robot control module, generate a current-corresponding curve table; the current self-diagnosis and adjustment module is used to monitor the real-time actual welding current and, in conjunction with the robot control module, adjust the set current.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A robotic control method for welding medium-thick plates based on an expert database, characterized in that, Includes the following steps: S1. Establish an expert database, which includes multiple sets of weld data; each set of weld data includes corresponding workpiece condition parameters, number of welding passes, and welding parameters for each pass. S2. Based on the welding requirements of the workpiece, select the workpiece condition parameters, and then obtain at least one set of weld data that meets the welding requirements from the expert database; modify or save the number of welding passes and the welding parameters of each pass corresponding to the set of weld data, and then generate a multi-layer multi-pass parameter group. S3. Write the start and end points of the weld, insert the multi-layer multi-pass parameter group, call the matching number of welding passes and welding parameters of each pass in the multi-layer multi-pass parameter group, and then control the robot to weld according to the parameters of the multi-layer multi-pass parameter group.

2. The robot-based control method for welding medium-thick plates based on an expert database according to claim 1, characterized in that, The establishment of the expert database specifically includes the following steps: Based on the welding requirements of the experimental workpiece, the workpiece condition parameters are set; the workpiece condition parameters include: groove type, groove angle, blunt edge, weld thickness, welding wire type, gas type, and welding wire extension length; Set multiple workpiece condition parameters, perform multiple experimental welding experiments on multiple experimental workpieces, and record the number of welding passes and the welding parameters for each experimental welding experiment. The experimental welded products are evaluated, and the number of weld passes and the welding parameters of each pass corresponding to the qualified welds are selected as weld data. The corresponding workpiece condition parameters, number of weld passes and welding parameters of each pass are entered into the expert database to establish each set of weld data.

3. The robot-based control method for welding medium-thick plates based on an expert database according to claim 1, characterized in that, The establishment of the expert database also includes the following steps: Workpiece condition parameters, number of welding passes, and welding parameters for each pass are recorded in a database to create multiple sets of weld data database files; each set of weld data is numbered to form a corresponding process document number. A database interface is created, which includes a selection module and a modification module for workpiece condition parameters. By selecting or modifying the workpiece condition parameters, the number of welding passes and the parameters for each pass can be displayed on the database interface.

4. The robot-based control method for welding medium-thick plates based on an expert database according to claim 1, characterized in that, The current calibration is performed before step S1, specifically including the following steps: Select a calibration workpiece with a specified length, width and thickness (2); program at least two robot programs through a teach pendant, each robot program having a different extension length; set the welding length, and corresponding to the welding length, set the current during the welding process to gradually change from the minimum current value to the maximum current value; Welding of the calibrated workpiece (2) begins, and the first actual welding current during the welding process is collected; the first actual welding current and the set current are compared to generate a current-corresponding curve table; Based on the set current of each welding parameter in the expert database, the corresponding output current is output, and the welding machine (1) is controlled by the output current to perform welding.

5. The robot-based control method for welding medium-thick plates based on an expert database according to claim 4, characterized in that, S3 further includes current self-diagnosis and current adjustment, specifically including the following steps: The second actual welding current is collected and returned to the welding control system; the trend of the second actual welding current is judged; if the second actual welding current continuously exceeds the threshold range within a set time, the set current is adjusted so that the second actual welding current meets the welding requirements.

6. The robot-based medium-thick plate welding control method according to claim 4, characterized in that, The current calibration also includes verifying the current-corresponding curve table, specifically including the following steps: Select the verification current, output the first actual welding current corresponding to the verification current according to the current curve table, and perform verification welding; collect the third actual welding current during the verification welding process, and compare the deviation between the third actual welding current and the verification current; if the deviation between the third actual welding current and the verification current is less than the deviation threshold, the current calibration is deemed qualified.

7. The robot-based control method for welding medium-thick plates based on an expert database according to claim 6, characterized in that, The current calibration also includes optimizing the current-corresponding curve table, specifically including the following steps: If the deviation between the third actual welding current and the verification current is greater than the deviation threshold, the current calibration and verification of the current corresponding curve table shall be performed again until the current calibration is qualified and then the current corresponding curve table shall be saved.

8. The robot-based control method for welding medium-thick plates according to any one of claims 1-7, characterized in that, The insertion of the multi-layer, multi-channel parameter group specifically includes the following steps: Load the expert database; select workpiece condition parameters according to the requirements of the workpiece to be welded, and select the corresponding number of welding passes and welding parameters for each pass, and output multi-layer multi-pass parameter groups.

9. An integrated welding system, characterized in that, The robot-based medium-thick plate welding control method based on an expert database as described in any one of claims 1-8 includes: a robot control module, a power supply module, and an expert database module; the robot control module is used to combine the power supply module and the expert database module to control the robot welding machine (1) to perform welding operations; the power supply module is connected to the robot control module through an internal control bus, and can cooperate with the robot control module to control the welding current and welding voltage of the robot welding machine (1); the expert database is used to collect and store workpiece condition parameters, number of welding passes, and welding parameters for each pass, and to generate multi-layer multi-pass parameter groups.

10. The integrated welding system according to claim 9, characterized in that, Also includes: The system includes a current calibration module and a current self-diagnosis and adjustment module. The current calibration module is used to collect the actual welding current and, in conjunction with the robot control module, generate a current-corresponding curve table. The current self-diagnosis and adjustment module is used to monitor the real-time actual welding current and, in conjunction with the robot control module, adjust the set current.

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