Robot collaborative welding control method and system for water purifier barrel and end cover

Abstract

The invention discloses a robot collaborative welding control method and system for a water purifier barrel and an end cover, and relates to the technical field of welding, and the robot collaborative welding control method comprises the steps that N welding robots are obtained, welding areas are distributed, and to-be-welded operation areas of the N robots are obtained; a historical welding control database of the water purifier is constructed, traversal optimization is conducted in the historical welding control database of the water purifier according to the attribute parameter set of the to-be-welded operation areas of the N robots, and N initial robot welding control parameters are generated; identifying posture position information of a target water purifier cylinder and an end cover, carrying out collaborative optimization on the N initial robot welding control parameters, and determining robot welding collaborative control parameters; and cooperative welding operation and feedback compensation control are conducted on the target water purifier barrel and the end cover based on the robot welding cooperative control parameters. The technical problem that multi-robot efficient collaborative operation is difficult to achieve in welding operation in the prior art is solved, and the technical effect of multi-robot efficient collaborative welding is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of welding, in particular to a robot collaborative welding control method and system for a water purifier cylinder and end cover. BACKGROUND

[0002] In the production process of the water purifier cylinder and end cover, the welding quality is directly related to the sealing performance and service life of the product. The traditional single robot or manual welding method is difficult to meet the production demand of high efficiency and high precision. Due to the lack of effective regional distribution and coordinated control, multi-robot collaborative welding is prone to operation conflict and insufficient precision, low collaborative efficiency, poor welding consistency, and difficult to support large-scale and continuous automatic production. SUMMARY

[0003] The present application provides a robot collaborative welding control method and system for a water purifier cylinder and end cover, which is used to solve the technical problem that the existing welding operation is difficult to realize multi-robot high-efficiency collaborative operation.

[0004] In view of the above problems, the present application provides a robot collaborative welding control method and system for a water purifier cylinder and end cover.

[0005] In a first aspect of the present application, a robot collaborative welding control method for a water purifier cylinder and end cover is provided, the method comprising: Obtaining N welding robots, distributing welding regions for a target water purifier cylinder and end cover based on the N welding robots, obtaining N robot to-be-welded operation regions; constructing a water purifier historical welding control database, traversing and optimizing in the water purifier historical welding control database according to the attribute parameter set of the N robot to-be-welded operation regions, generating N initial robot welding control parameters; identifying the posture position information of the target water purifier cylinder and end cover by using a visual sensor, collaboratively optimizing the N initial robot welding control parameters based on the posture position information, determining robot welding collaborative control parameters; starting the N welding robots to perform collaborative welding operation and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters.

[0006] In a second aspect of the present application, a robot collaborative welding control system for a water purifier cylinder and end cover is provided, the system comprising: The welding area distribution module is used for obtaining N welding robots, performing welding area distribution on the target water purifier cylinder and end cover based on the N welding robots, and obtaining N robot welding work areas; the traversal optimization module is used for constructing a water purifier historical welding control database, performing traversal optimization in the water purifier historical welding control database according to attribute parameter sets of the N robot welding work areas, and generating N initial robot welding control parameters; the collaborative optimization module is used for identifying posture position information of the target water purifier cylinder and end cover by using a visual sensor, performing collaborative optimization on the N initial robot welding control parameters based on the posture position information, and determining robot welding collaborative control parameters; and the welding control module is used for starting the N welding robots to perform collaborative welding work and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters.

[0007] The one or more technical solutions provided in the present application have at least the following technical effects or advantages: The present application obtains N welding robots, performs welding area distribution on the target water purifier cylinder and end cover based on the N welding robots, and obtains N robot welding work areas; a water purifier historical welding control database is constructed, traversal optimization is performed in the water purifier historical welding control database according to attribute parameter sets of the N robot welding work areas, and N initial robot welding control parameters are generated; posture position information of the target water purifier cylinder and end cover is identified by using a visual sensor, collaborative optimization is performed on the N initial robot welding control parameters based on the posture position information, and robot welding collaborative control parameters are determined; and the N welding robots are started to perform collaborative welding work and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters. The present application solves the technical problem that the existing welding work is difficult to realize efficient collaborative work of multiple robots, and achieves the technical effect of efficient collaborative welding of multiple robots by reasonably distributing welding areas, generating initial control parameters based on a historical welding database, identifying postures by using a visual sensor and performing collaborative optimization on control parameters, and introducing feedback compensation control in the welding process. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0009] Figure 1 A robot collaborative welding control method flowchart of a water purifier cylinder and end cover is provided for the embodiments of the present application. Figure 2This is a schematic diagram of the robot collaborative welding control system for the water purifier cylinder and end cap provided in an embodiment of this application.

[0010] Figure labeling: Welding area allocation module 11, Traversal optimization module 12, Collaborative optimization module 13, Welding control module 14. Detailed Implementation

[0011] This application provides a robotic collaborative welding control method and system for water purifier cylinders and end caps. It addresses the technical problem that existing welding operations struggle to achieve efficient collaborative welding by multiple robots. By rationally allocating the welding area, generating initial control parameters based on a historical welding database, using visual sensors to achieve posture recognition and collaborative optimization of control parameters, and introducing feedback compensation control during the welding process, the technical effect of achieving efficient collaborative welding by multiple robots is achieved.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, this application provides a robotic collaborative welding control method for the water purifier cylinder and end cap, the method including: Step S100: Obtain N welding robots, and allocate welding areas to the target water purifier cylinder and end cap based on the N welding robots to obtain N robot welding operation areas.

[0015] In the embodiment of the present application, first, N welding robots for welding are acquired. Then, the welding area of the target water purifier cylinder and end cover is allocated based on the N welding robots. In this process, first, the target water purifier cylinder and end cover are three-dimensionally modeled to generate a three-dimensional model of the water purifier cylinder and end cover. Then, welding area identification is performed on the three-dimensional model of the water purifier cylinder and end cover to determine the water purifier welding area. Next, the capability of the N welding robots is evaluated to acquire N welding capability constraint parameters. Finally, the water purifier welding area is allocated based on the welding capability constraint parameters to obtain the N robot welding work area.

[0016] Further, the method provided by the embodiment of the present application further comprises: Based on the structure design data and material attribute data of the target water purifier cylinder and end cover, a three-dimensional model of the water purifier cylinder and end cover is generated. The welding area of the water purifier is identified on the three-dimensional model of the water purifier cylinder and end cover to obtain the water purifier welding area. The N welding capability constraint parameters of the N welding robots are evaluated. Based on the N welding capability constraint parameters, the water purifier welding area is allocated to obtain the N robot welding work area.

[0017] In the embodiment of the present application, first, based on the pre-stored structure design data and material attribute data of the target water purifier cylinder and end cover, a three-dimensional model is generated. The structure design data includes geometric dimensions, assembly reference, and weld design symbols. The material attribute data includes thermal expansion coefficient, thermal conductivity, and yield strength. In the three-dimensional modeling process, the parametric modeling method is adopted. The geometric dimensions, assembly reference, and weld design symbols in the structure design data are input. Combined with the thermal expansion coefficient, thermal conductivity, and yield strength in the material attribute data, the steps of establishing part coordinate system, generating geometric contour, defining assembly relationship, and adding weld feature are sequentially completed to obtain the three-dimensional model of the water purifier cylinder and end cover containing geometric shape, welding interface, and spatial pose information.

[0018] Next, the welding area of the water purifier is identified on the three-dimensional model of the water purifier cylinder and end cover according to the welding work target. The welding work target is the specific area that needs to be welded. The geometric feature recognition method is adopted to extract the weld feature line and bevel boundary in the three-dimensional model of the water purifier cylinder and end cover, identify the welding interface, and use the path tracking method to calibrate the arc starting point, arc ending point, welding direction, and weld length. According to the weld type and bevel form, the area is classified, the structure connection position is converted into a spatial work object that can be executed by a robot, and the water purifier welding area is obtained.

[0019] Subsequently, the N welding robots participating in the welding are evaluated for welding capability. In this process, a kinematics modeling method is adopted, the reachable workspace and pose feasible region of the end effector are calculated using forward and inverse kinematics, the process parameter range is determined in combination with the power source and wire feeder, and the reachability and trajectory interference within the water purifier to-be-welded region are verified through offline simulation to obtain N welding capability constraint parameters including spatial constraint parameters, process constraint parameters and pose constraint parameters.

[0020] Finally, the to-be-welded region of the water purifier is allocated for the work region based on the N welding capability constraint parameters. In this process, first, the weld, material and position characteristics of the to-be-welded region of the water purifier are extracted to form a multi-dimensional feature set of the water purifier welding region. Then, the multi-dimensional feature set of the water purifier welding region is subjected to clustering analysis and region division to obtain a set of clustered welding regions of the water purifier. Next, the set of clustered welding regions of the water purifier is preliminarily matched according to the N welding capability constraint parameters to determine N preliminary robot welding regions. Finally, the N preliminary robot welding regions are subjected to conflict detection and load balancing optimization to obtain N robot to-be-welded work regions.

[0021] Further, the method provided by the application embodiment further comprises the following steps: The weld, material and position characteristics of the to-be-welded region of the water purifier are extracted to obtain a multi-dimensional feature set of the water purifier welding region. The multi-dimensional feature set of the water purifier welding region is subjected to clustering analysis and region division to obtain a set of clustered welding regions of the water purifier. The set of clustered welding regions of the water purifier is preliminarily matched according to the N welding capability constraint parameters to determine N preliminary robot welding regions. The N preliminary robot welding regions are subjected to conflict detection and load balancing optimization to obtain N robot to-be-welded work regions.

[0022] In the application embodiment, first, the weld, material and position characteristics of the to-be-welded region of the water purifier are extracted. The weld characteristics include weld type, weld length, weld direction and spatial pose, the material characteristics include the type and thermal physical properties of the base material for welding, and the position characteristics include the spatial coordinates and pose information of the weld in the three-dimensional model of the cylinder and end cover. Through feature extraction, a multi-dimensional feature set of the water purifier welding region is formed.

[0023] Next, the multi-dimensional feature set of the water purifier welding region is subjected to clustering analysis and region division. In this process, the K-means clustering method is adopted, the multi-dimensional feature set of the water purifier welding region is subjected to standardization processing, the similarity between features is calculated using the Euclidean distance, the welding regions are divided into several categories according to the similarity, and the automatic grouping and spatial partitioning of the weld regions are completed by setting the similarity threshold and the minimum cluster size to obtain a set of clustered welding regions of the water purifier.

[0024] Subsequently, the set of clustered welding areas of the water purifier is preliminarily matched according to N welding capability constraint parameters. A method based on reachability matching is adopted. The forward and inverse kinematics models of the N welding robots are used to calculate the reachable workspaces and pose feasible regions of each robot in the workpiece coordinate system. The spatial position features of the clustered welding areas are compared with the reachable regions of the robots, and the matching results are recorded through a reachability matrix. The linear distribution method is used to complete task distribution under the premise of meeting the spatial constraints, and N preliminary robot welding areas are obtained.

[0025] Finally, conflict detection and load balancing optimization are performed on the N preliminary robot welding areas. A trajectory conflict detection method based on time and space constraints is adopted. The robot trajectory planning algorithm is used to simulate the motion trajectories of each robot in the corresponding welding area, and path intersection, trajectory interference, and station conflict are detected. For the conflict part, the operation sequence is adjusted, the start time is modified, and the local trajectory is re-planned for elimination. Subsequently, a load balancing optimization method is adopted. The task is adjusted and redistributed according to the corresponding number of welds, total weld length, and operation time of each robot, so that the task distribution of each robot tends to be balanced. Through the above steps, N robot welding areas are obtained.

[0026] Step S200: Construct a water purifier historical welding control database. According to the attribute parameter set of the N robot welding areas, the water purifier historical welding control database is traversed and optimized to generate N initial robot welding control parameters.

[0027] In the embodiments of the present application, first, a data collection and classification modeling method is adopted. The historical welding control data formed in the past water purifier welding process is classified and arranged according to the dimensions of weld type, groove form, material attribute, welding position, welding posture, and welding parameter, and is stored in a structured manner to obtain a water purifier historical welding control database. The water purifier historical welding control database includes control parameters such as current, voltage, wire feed speed, welding speed, and welding heat input, as well as corresponding welding effect records. The welding effect records include weld penetration deviation, weld width deviation, welding heat input, welding speed stability, and spatter control amount.

[0028] Next, the attribute parameter set of the N robot welding work areas is traversed in the water purifier historical welding control database. In this process, first, the attribute parameter set of the N robot welding work areas is classified by dimension to form a welding work area attribute parameter dimension set. Then, the water purifier historical welding control database is classified and integrated according to the welding work area attribute parameter dimension set to obtain a water purifier welding control dimension database. Next, the attribute parameter set is traversed in the welding control dimension database for similarity matching to obtain N water purifier welding control matching data sets. Finally, the matching data sets are globally optimized for parameters to generate N initial robot welding control parameters.

[0029] Further, the method provided by the application embodiment further comprises: The attribute parameter set of the N robot welding work areas is classified by dimension to obtain a welding work area attribute parameter dimension set. The water purifier historical welding control database is classified and integrated according to the welding work area attribute parameter dimension set to obtain a water purifier welding control dimension database. The attribute parameter set of the N robot welding work areas is traversed in the water purifier welding control dimension database for similarity matching to obtain N water purifier welding control matching data sets. The N water purifier welding control matching data sets are respectively globally optimized for parameters to generate N initial robot welding control parameters.

[0030] In the application embodiment, first, the attribute parameter set of the N robot welding work areas is classified by dimension. The attribute parameter set includes weld length, groove angle, weld type, spatial position, attitude information, and material attribute. The parameter dimension division method is used to divide these parameters into geometric dimension, process dimension, and material dimension according to their physical attributes and process characteristics, thereby forming a welding work area attribute parameter dimension set with clear structure and corresponding relationship.

[0031] Next, the water purifier historical welding control database is classified and integrated according to the welding work area attribute parameter dimension set. The original historical welding control data in the water purifier historical welding control database is reorganized and indexed according to the geometric dimension, process dimension, and material dimension by using the hierarchical archiving method. The historical control parameters such as current, voltage, wire feed speed, welding speed, and heat input are one-to-one corresponding to the corresponding attribute dimensions to construct a structured data index system, thereby obtaining a water purifier welding control dimension database.

[0032] Subsequently, traversal similarity matching is performed based on the attribute parameter set of the N robot to-be-welded work area. In this process, a similarity calculation method based on the Euclidean distance is adopted to calculate the similarity between the attribute parameter vector of each welding area and each historical record in the database, and filtering is performed according to a preset similarity threshold, so that a historical data set closest to the current welding area in terms of weld characteristics, material properties and spatial position is obtained, and N water purifier welding control matching data sets are formed.

[0033] Finally, parameter global optimization is performed on the N water purifier welding control matching data sets respectively. In this process, a welding effect multi-objective function is first constructed according to the water purifier welding effect requirement. Then, welding effect evaluation is performed on the N water purifier welding control matching data sets according to the welding effect multi-objective function, and N water purifier welding control effect sets are obtained. Finally, parameter global optimization is performed on the N water purifier welding control matching data sets based on the N welding control effect sets, and N initial robot welding control parameters are determined.

[0034] Further, the method provided by the application embodiment further comprises the following steps: According to the water purifier welding effect requirement, a welding effect multi-objective function is constructed. Welding effect evaluation is performed on the N water purifier welding control matching data sets according to the welding effect multi-objective function, and N water purifier welding control effect sets are obtained. Parameter global optimization is performed on the N water purifier welding control matching data sets based on the N welding control effect sets, and N initial robot welding control parameters are determined.

[0035] In the application embodiment, a welding effect multi-objective function is first constructed according to the water purifier welding effect requirement. The index standardization and weighted summation method is adopted, and the penetration deviation, weld width deviation, welding heat input, welding speed stability and spatter control amount are selected as the main evaluation indexes. Through range standardization, indexes of different dimensions are converted to the interval of 0 to 1, and the direction is unified to be smaller the better. The welding effect multi-objective function can be expressed as . Wherein, represents the penetration deviation, represents the weld width deviation, represents the heat input, represents the welding speed fluctuation, represents the spatter amount, , , , , is a pre-set weight.

[0036] Next, the N water purifier welding control matching data sets are evaluated according to the welding effect multi-objective function. For each set of welding control parameters, including current, voltage, wire feed speed, welding speed and protective gas flow, process boundary check is performed first, and records that do not meet the heat input or arc stability constraints are removed. Then, according to the corresponding index values, standardization processing is performed and substituted into the multi-objective function to obtain the function value F corresponding to each set of parameters, forming the N water purifier welding control effect set.

[0037] Finally, the N water purifier welding control matching data sets are subjected to parameter global optimization based on the N water purifier welding control effect set. In this process, first, the N water purifier welding control matching data sets are subjected to control parameter optimization according to the N water purifier welding control effect set, obtaining N parent robot welding control parameters. Then, based on the parent robot welding control parameters, cross variation expansion is performed to construct N robot welding control parameter spaces. Finally, global optimization is performed in the N robot welding control parameter spaces using the welding effect multi-objective function to determine the N initial robot welding control parameters.

[0038] Further, the method provided by the application embodiment further comprises: The N water purifier welding control matching data sets are subjected to control parameter optimization according to the N water purifier welding control effect set, obtaining N parent robot welding control parameters. Then, based on the N parent robot welding control parameters, cross variation expansion is performed to construct N robot welding control parameter spaces. Finally, global optimization is performed in the N robot welding control parameter spaces using the welding effect multi-objective function to determine the N initial robot welding control parameters.

[0039] In the application embodiment, first, the N water purifier welding control matching data sets are subjected to control parameter optimization according to the N water purifier welding control effect set. By performing multi-objective function calculation and sorting on the welding control parameter combinations in each water purifier welding control matching data set, parameter combinations that meet the heat input range, upper limit of penetration deviation, upper limit of weld width deviation, speed stability threshold and spatter control requirements are selected. According to the order from small to large of the multi-objective function values, the optimal parameter combination of each welding work area is selected, and N parent robot welding control parameters are obtained.

[0040] Next, based on the N parent robot welding control parameters, cross mutation expansion is performed, and the parameter range is expanded through cross and mutation operations. The cross operation randomly exchanges part of the parameter values in different parent parameters to generate new parameter combinations; the mutation operation introduces small perturbations within the allowed range of key parameters such as current, voltage, wire feed speed, welding speed, and protective gas flow, to enhance the coverage and diversity of the search. A large set of candidate parameters is obtained through cross and mutation, and the N robot welding control parameter space is constructed.

[0041] Subsequently, for each set of candidate control parameters in the robot welding control parameter space, the evaluation indicators in the welding effect multi-objective function are calculated by the simulation method. The penetration deviation is obtained by comparing the theoretical penetration calculated by the heat input and the penetration empirical model with the target value; the weld width deviation is obtained by comparing the width estimated by the geometric shaping model with the design width; the heat input is directly calculated by voltage, current, and welding speed; the welding speed stability is obtained by analyzing the fluctuation of the speed time sequence; and the spatter amount is obtained by simulating the voltage and current fluctuations. After standardizing the above indicators, they are input into the welding effect multi-objective function for calculation. After calculating the objective function values of all candidate parameters, global optimization is performed. According to the function value from small to large, the parameter combinations that do not meet the constraint conditions are eliminated, such as heat input exceeding the upper limit, welding speed fluctuation exceeding the limit, or spatter amount being unqualified. For the remaining parameter combinations, in the case of the same function value, the penetration deviation, weld width deviation, and speed stability are compared in turn, and the unique optimal solution is selected. Finally, the optimal control parameters for each welding work area are determined, and N initial robot welding control parameters are obtained.

[0042] Step S300: The posture and position information of the target water purifier cylinder and end cover is recognized by the visual sensor, and the N initial robot welding control parameters are cooperatively optimized based on the posture and position information to determine the robot welding cooperative control parameters.

[0043] In the embodiments of the present application, first, the posture and position information of the target water purifier cylinder and end cover is recognized by the visual sensor. The image information and contour information of the target water purifier cylinder and end cover are collected by a multi-view industrial camera and a laser contour sensor, and the correspondence between the sensor coordinates and the robot base coordinates is established using a calibration method. Then, through feature extraction and three-dimensional reconstruction, the translation deviation and rotation deviation of the target water purifier cylinder and end cover are calculated to obtain the posture and position information.

[0044] Next, the N initial robot welding control parameters are cooperatively optimized based on the pose position information. In this process, first, the N initial robot welding control parameters are mapped, adjusted and corrected based on the pose position information to obtain N robot welding correction control parameters; then, the N robot welding correction control parameters are cooperatively optimized based on the welding effect multi-objective function according to the N space operation constraint parameters of the N welding robots, and finally the robot welding cooperative control parameters are determined.

[0045] Further, the method provided in the application embodiment further comprises: The N initial robot welding control parameters are mapped, adjusted and corrected based on the pose position information to determine the N robot welding correction control parameters; the N robot welding correction control parameters are cooperatively optimized based on the welding effect multi-objective function according to the N space operation constraint parameters of the N welding robots to determine the robot welding cooperative control parameters.

[0046] In the application embodiment, when the N initial robot welding control parameters are mapped, adjusted and corrected based on the pose position information, first, the pose data and the corresponding robot welding control data of the water purifier cylinder and the end cover are extracted from the water purifier historical welding control database. Then, the extracted data are associated, mapped and fitted to establish a segmented adjustment model between the pose deviation and the welding parameters. Finally, the model is used to adjust and correct the N initial robot welding control parameters in combination with the pose position information to determine the N robot welding correction control parameters.

[0047] Next, the N robot welding correction control parameters are cooperatively optimized based on the welding effect multi-objective function according to the N space operation constraint parameters of the N welding robots. The space operation constraint parameters include the reachable space of each robot, the joint motion range, the path safety distance, the operation time sequence and the welding trajectory interference condition. By calculating the objective function value of each correction control parameter combination within the constraint range, the combinations with excessive heat input, excessive welding speed fluctuation and excessive weld deviation are eliminated, and the remaining combinations are sorted in ascending order of the welding effect multi-objective function value, and the combination with the optimal welding effect is preferentially selected, and the corresponding robot welding correction control parameter is determined as the robot welding cooperative control parameter.

[0048] Further, the method provided in the application embodiment further comprises: According to the water purifier historical welding control database, the water purifier cylinder and end cover pose data and the corresponding robot welding control data are extracted; based on the water purifier cylinder and end cover pose data and the corresponding robot welding control data, the pose deviation-welding parameter segmented adjustment model is established; the pose deviation-welding parameter segmented adjustment model is used to adjust and correct N initial robot welding control parameters based on the attitude position information, and N robot welding correction control parameters are determined.

[0049] In the embodiments of the present application, first, according to the water purifier historical welding control database, the water purifier cylinder and end cover pose data and the corresponding robot welding control data are extracted. The water purifier historical welding control database contains the attitude information of the water purifier cylinder and end cover under different clamping states, and the control parameters corresponding to these attitudes, such as current, voltage, wire feeding speed, welding speed and welding torch angle. In this process, by performing a structured query on the water purifier historical welding control database, the records are matched according to batch identification, timestamp and weld number, and the pose data and welding control data under different attitude conditions are extracted one by one. The pose data includes translation information and rotation information, and the welding control data includes current, voltage, wire feeding speed, welding speed, welding torch angle, swing amplitude, swing frequency and other contents.

[0050] Next, based on the extracted pose data and welding control data, the pose deviation-welding parameter segmented adjustment model is established. By fitting and analyzing the data in different deviation intervals, the pose deviation is divided into small deviation zone, medium deviation zone and large deviation zone, and the mapping relationship between the deviation and the trajectory coordinate compensation, welding speed correction, welding torch angle correction and swing amplitude correction is established. In the fitting process, the segmented linear regression method is used to calculate the correction coefficients in different intervals, and the interval boundaries and coefficient matrix are determined by breakpoint search and least squares method. After fitting and verification, the pose deviation-welding parameter segmented adjustment model for parameter correction is formed.

[0051] Finally, the established pose deviation-welding parameter segmented adjustment model is used to adjust and correct N initial robot welding control parameters combined with the attitude position information. In this process, according to the translation deviation and rotation deviation in the attitude position information, the corresponding parameter interval is selected, the trajectory coordinate compensation, welding torch angle correction, current and welding speed adjustment, wire feeding speed and swing parameter adjustment are calculated, and these correction amounts are added to the initial control parameters. After completing the parameter correction, the correction results are checked for reachability, joint limit, path safety distance and heat input upper limit, and the correction amounts exceeding the allowed range are trimmed. After this process, N robot welding correction control parameters are obtained.

[0052] Step S400: Start N welding robots to perform collaborative welding operation and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters.

[0053] Further, the method provided by the application embodiment further comprises: The N welding robots perform collaborative welding operation and state feedback monitoring on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters to obtain the current welding state parameters of the water purifier; the PID controller compensates and analyzes the robot welding collaborative control parameters based on the deviation value between the water purifier welding desired effect parameters and the current welding state parameters of the water purifier, and performs closed-loop welding control on the water purifier through the compensated robot welding collaborative control parameters.

[0054] In the application embodiment, when the N welding robots perform collaborative welding operation and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters, first, the N welding robots are started to perform collaborative welding operation on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters. Each welding robot synchronously performs the welding task according to the predetermined control parameters such as trajectory position, welding current, welding voltage, welding speed, and wire feeding speed, to realize parallel processing of multiple welds. In the welding process, the motion rhythm and parameter execution sequence of each welding robot are coordinated to ensure that the welding process of multiple robots on the same workpiece is stable and synchronized.

[0055] During the welding operation, state feedback monitoring is performed to collect the welding state of the target water purifier cylinder and end cover in real time. Through arc sensors, voltage and current sensors, and visual sensors, real-time parameters such as welding current, welding voltage, welding speed, penetration, weld width, heat input, and spatter amount are obtained to form the current welding state parameters of the water purifier.

[0056] Subsequently, the PID controller is used to compensate and analyze the robot welding collaborative control parameters based on the deviation value of the water purifier welding desired effect parameters and the current welding state parameters of the water purifier. In this process, the preset water purifier welding desired effect parameters are compared with the current welding state parameters of the water purifier, the deviation value is calculated, and the compensation amount is obtained through proportional, integral and differential operations respectively. The compensation amount is applied to the original robot welding collaborative control parameters, and the welding current, welding voltage, welding speed and welding torch angle and other parameters are corrected in real time to reduce the deviation value. After completing the compensation analysis, the water purifier cylinder and end cover are controlled by closed-loop welding using the compensated robot welding collaborative control parameters. As the welding process proceeds, the feedback parameters are continuously updated, and the control parameters are continuously adjusted according to the deviation, achieving dynamic correction and stable control of the welding state. Finally, the welding deviation is effectively suppressed, and the closed-loop welding control of the water purifier is completed.

[0057] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects: The present application obtains N welding robots, distributes the welding area of the target water purifier cylinder and end cover based on the N welding robots, obtains N robot welding work area to be welded, constructs a water purifier historical welding control database, traverses and optimizes in the water purifier historical welding control database according to the attribute parameter set of the N robot welding work area to be welded, generates N initial robot welding control parameters, identifies the posture position information of the target water purifier cylinder and end cover using a visual sensor, optimizes the N initial robot welding control parameters based on the posture position information, determines the robot welding collaborative control parameters, and starts the N welding robots to perform collaborative welding work and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters. The present application solves the technical problem that the existing welding work is difficult to realize efficient collaborative work of multiple robots, and achieves the technical effect of efficient collaborative welding of multiple robots by reasonably distributing the welding area, generating initial control parameters based on the historical welding database, realizing posture recognition using a visual sensor and optimizing the control parameters, and introducing feedback compensation control in the welding process.

[0058] Embodiment two, based on the same inventive concept as the robot collaborative welding control method of the water purifier cylinder and end cover in the foregoing embodiments, as shown in Figure 2 The present application provides a robot collaborative welding control system for a water purifier cylinder and end cover, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. The system comprises: The welding area distribution module 11 is used to obtain N welding robots, and welding area distribution of the target water purifier cylinder and end cover is performed based on the N welding robots to obtain N robot welding work areas; the traversal optimization module 12 is used to construct a water purifier historical welding control database, and traversal optimization is performed in the water purifier historical welding control database according to attribute parameter sets of the N robot welding work areas to generate N initial robot welding control parameters; the collaborative optimization module 13 is used to identify posture position information of the target water purifier cylinder and end cover by using a visual sensor, and collaborative optimization is performed on the N initial robot welding control parameters based on the posture position information to determine robot welding collaborative control parameters; and the welding control module 14 is used to start the N welding robots to perform collaborative welding work and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters.

[0059] Further, the system is also used to implement the following functions: Three-dimensional modeling is performed based on structure design data and material attribute data of the target water purifier cylinder and end cover to generate a water purifier cylinder and end cover three-dimensional model; welding area identification is performed on the water purifier cylinder and end cover three-dimensional model according to welding work targets to obtain a water purifier welding area; N welding capability constraint parameters of the N welding robots are evaluated and obtained; and work area distribution is performed on the water purifier welding area based on the N welding capability constraint parameters to obtain N robot welding work areas.

[0060] Further, the system is also used to implement the following functions: Welding seam, material, and position features are extracted from the water purifier welding area to obtain a water purifier welding area multi-dimensional feature set; clustering analysis and area division are performed based on the water purifier welding area multi-dimensional feature set to obtain a water purifier clustering welding area set; preliminary matching is performed on the water purifier clustering welding area set according to the N welding capability constraint parameters to determine N preliminary robot welding areas; conflict detection and load balancing optimization are performed on the N preliminary robot welding areas to obtain N robot welding work areas.

[0061] Further, the system is also used to implement the following functions: Dimension classification is performed on attribute parameter sets of the N robot welding work areas to obtain welding work area attribute parameter dimension sets; the water purifier historical welding control database is classified and integrated according to the welding work area attribute parameter dimension sets to obtain a water purifier welding control dimension database; traversal similarity matching is performed in the water purifier welding control dimension database based on the attribute parameter sets of the N robot welding work areas to obtain N water purifier welding control matching data sets; parameter global optimization is respectively performed on the N water purifier welding control matching data sets to generate N initial robot welding control parameters.

[0062] Further, the system is also used to realize the following functions: According to the welding effect demand of the water purifier, a welding effect multi-objective function is constructed; welding effect evaluation is performed on the N water purifier welding control matching data sets according to the welding effect multi-objective function, and N water purifier welding control effect sets are obtained; parameter global optimization is performed on the N water purifier welding control matching data sets based on the N water purifier welding control effect sets, and N initial robot welding control parameters are determined.

[0063] Further, the system is also used to realize the following functions: Control parameter optimization is performed on the N water purifier welding control matching data sets according to the N water purifier welding control effect sets, and N parent robot welding control parameters are obtained; cross variation expansion is performed based on the N parent robot welding control parameters, and N robot welding control parameter spaces are constructed; global optimization is performed in the N robot welding control parameter spaces by using the welding effect multi-objective function, and N initial robot welding control parameters are determined.

[0064] Further, the system is also used to realize the following functions: Mapping adjustment and correction are performed on the N initial robot welding control parameters based on the pose position information, and N robot welding correction control parameters are determined; collaborative optimization is performed on the N robot welding correction control parameters based on the welding effect multi-objective function according to the N space operation constraint parameters of the N welding robots, and robot welding collaborative control parameters are determined.

[0065] Further, the system is also used to realize the following functions: According to the water purifier historical welding control database, water purifier cylinder and end cover pose data and corresponding robot welding control data are extracted; association mapping fitting is performed based on the water purifier cylinder and end cover pose data and corresponding robot welding control data, and a pose deviation-welding parameter segmented adjustment model is established; adjustment and correction are performed on the N initial robot welding control parameters based on the pose position information by using the pose deviation-welding parameter segmented adjustment model, and N robot welding correction control parameters are determined.

[0066] Further, the system is also used to realize the following functions: N welding robots are started based on the robot welding collaborative control parameters to perform collaborative welding operation and state feedback monitoring on the target water purifier cylinder and end cover, and water purifier current welding state parameters are obtained; compensation analysis is performed on the robot welding collaborative control parameters based on the deviation value of the water purifier welding expected effect parameters and the water purifier current welding state parameters by using a PID controller, and closed-loop welding control of the water purifier is performed through the compensated robot welding collaborative control parameters.

[0067] It should be noted that the above-mentioned order of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0068] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content without departing from the scope of the technical solution of the present application, and any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application are still within the scope of the technical solution of the present application.

Claims

1. A robot collaborative welding control method for a water purifier cylinder and an end cover, characterized in that the method The method comprises the following steps: Obtain N welding robots, and perform welding area distribution on the target water purifier cylinder and end cover based on the N welding robots to obtain N robot welding work areas; Construct a water purifier historical welding control database, and perform traversal optimization in the water purifier historical welding control database according to the attribute parameter set of the N robot welding work areas to generate N initial robot welding control parameters; Identify the posture position information of the target water purifier cylinder and end cover by using a visual sensor, and perform collaborative optimization on the N initial robot welding control parameters based on the posture position information to determine robot welding collaborative control parameters; Start the N welding robots to perform collaborative welding work and feedback compensation control on the target water purifier cylinder and end cover based on the robot welding collaborative control parameters.

2. The robot collaborative welding control method of a water purifier cylinder and an end cover according to claim 1, characterized in that, Obtain N robot welding work areas, comprising: Based on the structure design data and material attribute data of the target water purifier cylinder and end cover, perform three-dimensional modeling to generate a water purifier cylinder and end cover three-dimensional model; Perform welding area marking on the water purifier cylinder and end cover three-dimensional model according to the welding work target to obtain a water purifier welding area; Evaluate N welding capability constraint parameters of the obtained N welding robots; Based on the N welding capability constraint parameters, perform work area distribution on the water purifier welding area to obtain N robot welding work areas.

3. The robot collaborative welding control method of a water purifier cylinder and an end cap according to claim 2, characterized in that, Based on the N welding capability constraint parameters, perform work area distribution on the water purifier welding area to obtain N robot welding work areas, comprising: Extract the weld, material, and position features of the water purifier welding area to obtain a water purifier welding area multi-dimensional feature set; Perform clustering analysis and area division based on the water purifier welding area multi-dimensional feature set to obtain a water purifier clustering welding area set; According to the N welding capability constraint parameters, perform preliminary matching on the water purifier clustering welding area set to determine N preliminary robot welding areas; Perform conflict detection and load balancing optimization on the N preliminary robot welding areas to obtain N robot welding work areas.

4. The robot collaborative welding control method of a water purifier cylinder and an end cover according to claim 1, characterized in that, Generate N initial robot welding control parameters, comprising: Classify the attribute parameter set of the N robot welding work areas by dimension to obtain a welding work area attribute parameter dimension set; Classify and integrate the water purifier historical welding control database according to the welding work area attribute parameter dimension set to obtain a water purifier welding control dimension database; Perform traversal similarity matching in the water purifier welding control dimension database based on the attribute parameter set of the N robot welding work areas to obtain N water purifier welding control matching data sets; Perform parameter global optimization on the N water purifier welding control matching data sets respectively to generate N initial robot welding control parameters.

5. The robot collaborative welding control method of a water purifier cylinder and an end cap according to claim 4, characterized in that, Perform parameter global optimization on the N water purifier welding control matching data sets respectively to generate N initial robot welding control parameters, comprising: According to the water purifier welding effect requirement, construct a welding effect multi-objective function; Perform welding effect evaluation on the N water purifier welding control matching data sets according to the welding effect multi-objective function to obtain N water purifier welding control effect sets; Based on the N water purifier welding control effect set, the N water purifier welding control matching data set is subjected to parameter global optimization, and N initial robot welding control parameters are determined.

6. The robot collaborative welding control method of a water purifier cylinder and an end cover according to claim 5, characterized in that, The N initial robot welding control parameters are determined, including: According to the N water purifier welding control effect set, the N water purifier welding control matching data set is subjected to control parameter optimization, and N parent robot welding control parameters are obtained. Based on the N parent robot welding control parameters, cross variation expansion is carried out to construct an N robot welding control parameter space. Global optimization is carried out in the N robot welding control parameter space by using the welding effect multi-objective function to determine the N initial robot welding control parameters.

7. The robot collaborative welding control method of a water purifier cylinder and an end cap according to claim 5, characterized in that, The robot welding collaborative control parameters are determined, including: Based on the posture position information, the N initial robot welding control parameters are mapped, adjusted and corrected to determine the N robot welding correction control parameters. According to the N space operation constraint parameters of the N welding robots, the N robot welding correction control parameters are collaboratively optimized based on the welding effect multi-objective function to determine the robot welding collaborative control parameters.

8. The robot collaborative welding control method of a water purifier cylinder and an end cap according to claim 7, characterized in that, The N robot welding correction control parameters are determined, including: According to the water purifier historical welding control database, the water purifier cylinder and end cover pose data and the corresponding robot welding control data are extracted. Based on the water purifier cylinder and end cover pose data and the corresponding robot welding control data, an association mapping fitting is carried out to establish a pose deviation-welding parameter segmented adjustment model. The pose deviation-welding parameter segmented adjustment model is used to adjust and correct the N initial robot welding control parameters based on the posture position information to determine the N robot welding correction control parameters.

9. The robot collaborative welding control method of a water purifier cylinder and an end cap according to claim 1, characterized in that, The N welding robots are started based on the robot welding collaborative control parameters to perform collaborative welding operation and feedback compensation control on the target water purifier cylinder and end cover, including: The N welding robots are started based on the robot welding collaborative control parameters to perform collaborative welding operation and state feedback monitoring on the target water purifier cylinder and end cover to obtain the current water purifier welding state parameters. A PID controller is used to compensate and analyze the robot welding collaborative control parameters based on the deviation value between the water purifier welding desired effect parameters and the water purifier current welding state parameters, and the water purifier closed-loop welding control is performed through the compensated robot welding collaborative control parameters.

10. A robot collaborative welding control system for a water purifier cylinder and end cap, characterized by, The system is used to perform the robot collaborative welding control method of the water purifier cylinder and end cover as claimed in any one of claims 1-9, and the system comprises: A welding area distribution module is used to obtain N welding robots, and based on the N welding robots, a welding area distribution is performed on the target water purifier cylinder and end cover to obtain N robot welding operation areas. A traversal optimization module is used to construct a water purifier historical welding control database, and according to the attribute parameter set of the N robot welding operation areas, a traversal optimization is performed in the water purifier historical welding control database to generate N initial robot welding control parameters. A collaborative optimization module is used to identify the posture position information of the target water purifier cylinder and end cover by using a visual sensor, and based on the posture position information, a collaborative optimization is performed on the N initial robot welding control parameters to determine the robot welding collaborative control parameters. The welding control module is used for starting N welding robots to cooperatively weld a target water purifier cylinder and an end cover based on robot welding cooperative control parameters and feedback compensation control.

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