Model-driven steel structure welding system and method
The model-driven steel structure welding system utilizes BIM models and reverse modeling technology to automatically generate welding task data packages, collect actual dimensional information, and calculate welding process parameters. This solves the problems of low efficiency and low quality in steel structure welding, achieves automation and dynamic correction, and improves welding efficiency and quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NO 1 CONSTR ENG CO LTD OF CHINA CONSTR THIRD ENG BUREAU CO LTD
- Filing Date
- 2023-12-23
- Publication Date
- 2026-08-04
AI Technical Summary
Steel structure welding suffers from low efficiency and low quality. Existing technologies struggle to automate and intelligentize the process, requiring manual instruction and failing to effectively implement dynamic correction.
The model-driven steel structure welding system integrates welding process data using a BIM model platform and combines it with reverse modeling technology to automatically generate welding task data packages. It collects actual size information through a sensing module, constructs a reverse model, and compares it with the forward model to calculate welding process parameters, thereby realizing automated welding actions and dynamic correction.
It improved the efficiency of steel structure welding, met the requirements of flexible production, ensured welding quality, and realized the automation and dynamic monitoring of the welding process.
Smart Images
Figure CN117532233B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of industrialized processing and construction technology of building steel structures, and in particular to a model-driven steel structure welding system and method. Background Technology
[0002] In the engineering and construction industry, steel structure systems offer advantages such as high mechanization, short construction cycles, stable quality, and low carbon footprint. Focusing on steel structures to promote intelligent manufacturing and new-type building industrialization is a crucial development direction. Compared to manufacturing, steel structure production lines process single-piece, small-batch, and highly flexible products. Currently, the overall automation and intelligence levels of steel structure production lines are relatively low, making it difficult to meet the flexible production requirements of different products, resulting in high labor input and room for improvement in efficiency. Welding is one of the core processes in steel structure production; therefore, improving the automation and intelligence levels of welding has significant value in enhancing the efficiency of steel structure production.
[0003] BIM models for steel structures are still rarely used to provide data management services for steel structure production. Traditional steel structure welding operations involve production line workers manually welding according to 2D drawings, marking out positions, and specifying weld layers, weld bead sizes, welding current, voltage, and amplitude based on welding procedure qualification. While advanced steel structure production lines have introduced welding robots, production line workers still need to teach these robots, manually entering welding paths and process parameters. In recent years, advancements in machine vision and reverse modeling technologies have enabled welding robots to autonomously identify welding scenes and objects, laying the foundation for offline welding simulation. However, these products still require production line workers to select welding paths and enter welding process parameters from models generated through reverse modeling, resulting in low efficiency. Furthermore, because welding paths and process parameters must be preset, robots cannot effectively implement dynamic correction during welding, compromising welding quality. Summary of the Invention
[0004] The purpose of this application is to propose a model-driven steel structure welding method to solve the problems of low welding efficiency and low welding quality in related technologies.
[0005] To address the aforementioned technical issues, this application provides a model-driven steel structure welding system. The steel structure welding system includes a steel structure BIM model platform, a steel structure welding control device communicatively connected to the steel structure BIM model platform, and a steel structure welding robot communicatively connected to the steel structure welding control device. The steel structure BIM model platform includes a digital model management module and a welding task generation module. The steel structure welding control device includes a welding task parsing module, a reverse modeling module, and a dynamic adaptive planning module for welding process parameters. The steel structure welding robot includes a welding module and a perception module.
[0006] The digital model management module is used for the management of steel structure BIM models and their attribute data.
[0007] The welding task generation module is used to generate welding task data packages;
[0008] The welding task parsing module is used to parse the welding task data package to obtain the forward model data of the object to be welded; the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded.
[0009] The sensing module is used to collect the actual dimensional information of the object being welded during the actual welding process; the actual welding process includes the pre-welding, during-welding, and post-welding stages;
[0010] The reverse modeling module is used to construct a reverse model of the welding object based on the actual size information; the reverse model of the welding object represents a BIM model that reflects the actual state of the welding object.
[0011] The dynamic adaptive planning module for welding process parameters is used to generate welding process parameters based on the reverse and forward model data of the object to be welded.
[0012] The welding module is used to perform welding actions on the object to be welded according to the welding process parameters.
[0013] In some implementations, the steel structure product information includes the geometric dimensions and material properties of the components, and the location and length of the welds attached to the components; the welding process information includes the welding posture, joint type, bevel type, bevel size, weld size, weld layer and weld bead, welding current range, welding voltage range, welding speed range, shielding gas flow rate range, and swing range.
[0014] In some implementations, the BIM model reflecting the actual state of the object being welded includes the geometric dimensions and coordinate data of the object being welded, as well as the forming dimensions of the weld seam attached to the object being welded.
[0015] In some implementations, the welding process parameters include the world coordinates of the welding start point, the world coordinates of the welding path feature points, the target welding current, the target welding voltage, the target welding speed, the target shielding gas flow rate, and the target swing amplitude data.
[0016] In some implementations, the sensing module is used to acquire binocular images or point cloud images of the object being welded.
[0017] To address the aforementioned technical problems, this application provides a model-driven steel structure welding method, applied to a steel structure welding system, comprising the following steps:
[0018] Obtain welding task data packets;
[0019] Parse the welding task data package to obtain the forward model data of the object to be welded; the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded.
[0020] Obtain the actual dimensional information of the object to be welded during the actual welding process; wherein, the actual welding process includes the pre-welding, during-welding and post-welding stages of the object to be welded;
[0021] A reverse model of the object to be welded is constructed based on the actual size information; wherein, the reverse model of the object to be welded represents a BIM model that reflects the actual state of the object to be welded.
[0022] Welding process parameters are obtained by comparing and calculating the data from the reverse model and the forward model of the object to be welded.
[0023] Perform welding actions on the object to be welded according to the welding process parameters.
[0024] In some implementations, the reverse model and forward model data of the object to be welded are compared and analyzed to calculate the welding process parameters, including:
[0025] By matching the geometric dimensions of the components in the forward model data with the geometric dimensions and coordinate data of the welding object in the reverse model of the welding object, the position of the weld in the forward model data is converted into the coordinate point in the actual welding environment, and the world coordinates of the welding start point are obtained.
[0026] Compare the bevel type, bevel size, weld size, and weld layer / bead data in the forward model data with the weld forming size data in the reverse model of the object being welded, and adjust the subsequent weld layer / bead planning accordingly.
[0027] Based on the adjusted weld bead and weld layer plan, welding process parameter values are generated. These values include the world coordinates of the feature points of the welding path, as well as the specific target welding current, target welding voltage, target welding speed, target shielding gas flow rate, and target swing amplitude for each weld bead.
[0028] In some implementations, obtaining the actual dimensional information of the object to be welded during the actual welding process includes:
[0029] During each weld pass, the actual dimensional information of the object being welded is continuously collected; or...
[0030] After each one or more weld passes are completed, the actual dimensions of the object being welded are collected.
[0031] In some embodiments, the steel structure welding system includes a digital model management module of a steel structure BIM model platform. After performing welding actions on the object to be welded according to welding process parameters, the above method further includes:
[0032] After all welds are completed, obtain the current actual size information of the object being welded, construct a reverse model of the object being welded based on the current actual size information, and upload the reverse model of the object being welded to the digital model management module of the steel structure BIM model platform.
[0033] Compared with related technologies, the embodiments of this application have the following main advantages:
[0034] By parsing the welding task data package, the forward model data of the object to be welded is obtained. The forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded. Based on the actual size information of the object to be welded during the actual welding process, a reverse model of the object to be welded is constructed. The reverse model of the object to be welded represents the BIM model reflecting the actual state of the object to be welded. The reverse model of the object to be welded is compared and analyzed with the forward model data to calculate the welding process parameters. Welding actions are performed on the object to be welded according to the welding process parameters. That is, by integrating the welding process data of the component of the BIM model and combining it with reverse modeling technology, the automated operation of welding actions driven by the BIM model is realized. This avoids manual teaching or input of process parameters and welding paths, improves the efficiency of steel structure welding work, and can meet the requirements of flexible production. At the same time, the welding process is dynamically monitored through reverse modeling, and then the welding process is dynamically corrected through adaptive planning of welding process parameters, which effectively ensures the quality of automated welding. Attached Figure Description
[0035] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 This is an exemplary system architecture diagram to which this application can be applied;
[0037] Figure 2 A schematic flowchart of a model-driven steel structure welding method provided in an embodiment of this application;
[0038] Figure 3 This is a schematic diagram of the BIM model in the welding task data package of an embodiment of this application;
[0039] Figure 4 This is a schematic diagram of the point cloud of the object being welded after welding layer 1 and weld bead 1 in an embodiment of this application.
[0040] Figure 5This is a schematic diagram of the reverse welding model established after welding layer 1 and weld bead 1 in an embodiment of this application.
[0041] Figure 6 A schematic flowchart of a model-driven steel structure production welding method provided in an embodiment of this application;
[0042] Figure 7 This is a schematic diagram illustrating the adjustment of the starting position of weld bead 2 after welding layer 1 and weld bead 1 in an embodiment of this application. Detailed Implementation
[0043] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
[0044] To address the aforementioned technical issues, this application provides a model-driven steel structure welding system. The steel structure welding system includes a steel structure BIM model platform, a steel structure welding control device communicatively connected to the steel structure BIM model platform, and a steel structure welding robot communicatively connected to the steel structure welding control device. The steel structure BIM model platform includes a digital model management module and a welding task generation module. The steel structure welding control device includes a welding task parsing module, a reverse modeling module, and a dynamic adaptive planning module for welding process parameters. The steel structure welding robot includes a welding module and a perception module.
[0045] The digital model management module is used for the management of steel structure BIM models and their attribute data.
[0046] The welding task generation module is used to generate welding task data packages;
[0047] The welding task parsing module is used to parse the welding task data package to obtain the forward model data of the object to be welded; the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded.
[0048] The sensing module is used to collect the actual dimensional information of the object being welded during the actual welding process; the actual welding process includes the pre-welding, during-welding, and post-welding stages of the object being welded.
[0049] The reverse modeling module is used to construct a reverse model of the welding object based on the actual size information; the reverse model of the welding object represents a BIM model that reflects the actual state of the welding object.
[0050] The dynamic adaptive planning module for welding process parameters is used to generate welding process parameters based on the reverse and forward model data of the object to be welded.
[0051] The welding module is used to perform welding actions on the object to be welded according to the welding process parameters. For example... Figure 1 As shown, Figure 1 This is an exemplary system architecture diagram to which this application can be applied. Specifically, the system includes a steel structure BIM model platform 1, a steel structure welding control device 2, and a steel structure welding robot 3. The steel structure welding control device 2 is communicatively connected to the steel structure BIM model platform 1. The steel structure welding robot 3 is communicatively connected to the steel structure welding control device 2.
[0052] The steel structure BIM model platform 1 includes a data management module 11 and a welding task generation module 12. The data management module 11 is used for steel structure BIM model and data management, and the welding task generation module 12 is used to extract relevant data of the steel structure BIM model from the data management module 11 to generate welding task data packages.
[0053] The steel structure welding control device 2 includes a welding task parsing module 21, a reverse modeling module 22, and a welding process parameter dynamic adaptive planning module 23. The welding task parsing module 21 is used to receive and parse welding task data packets. The reverse modeling module 22 is used to establish a reverse model of the welding object and send the reverse model of the welding object to the data management module 11 for storage. The welding process parameter dynamic adaptive planning module 23 is used to generate welding process parameters based on the forward model data of the welding task data packet and the reverse model of the welding object.
[0054] The steel structure welding robot 3 includes a welding module 31 and a sensing module 32. The welding module 31 is used to execute welding actions according to welding process parameters. The welding module 31 can be composed of devices such as the EFORT ER10-2000 robotic arm, the Aotai welding power supply NBC-500RP plus, and the Telma TRM605W water-cooled welding torch. The sensing module 32 is used to collect the actual geometric dimension data of the object to be welded and send the collected actual geometric dimension data of the object to be welded to the reverse modeling module 22. The sensing module 32 can be a FARO Orbis laser point cloud scanning device.
[0055] This application uses BIM model to integrate welding process data, and combines reverse modeling technology to realize model-driven automated flexible welding, and realize dynamic correction of welding process and digital management of welding quality.
[0056] In the embodiments of this application, such as Figure 2 As shown, Figure 2 This is a schematic flowchart of the model-driven steel structure welding method provided in this application embodiment. The model-driven steel structure welding method is applied to the above-mentioned steel structure welding system, and its specific implementation includes:
[0057] S201: Obtain welding task data package.
[0058] Specifically, the steel structure BIM model and its attribute data are selected from the digital model management module. The selected steel structure product information and welding process information are packaged together to generate a welding task data package.
[0059] S202: Parse the welding task data package to obtain the forward model data of the object to be welded; the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded.
[0060] The welding task data package includes, but is not limited to: BIM models of steel structure components, their geometric dimensions and material properties, attribute data such as the position and length of welds attached to the components, and welding process attribute data such as welding posture, joint type, bevel type, bevel size, weld size, weld layer and weld bead, welding current range, welding voltage range, welding speed range, shielding gas flow rate range, and swing range. Figure 3 As shown, Figure 3 This is a schematic diagram of the BIM model in the welding task data package of this application embodiment. The BIM model includes H-beam 301, weld 302, and single-plate corbel 303. The BIM model can be stored in IFC format. For example, the content of an IFC file is shown below:
[0061] #156=IFCFASTENER('1quL1td0H00Qza$jFgkXuy',$,'WELD',$,$,#142,#155,$,$);
[0062] In this table, #156 is the object number, IFCFASTENER indicates the connector category, '1quL1td0H00Qza$jFgkXuy' is the globally unique identifier (GlobalId), the first $ indicates the owner history, 'WELD' indicates that the object is a weld (ObjectType), the second $ is the description, the third $ is the name, #142 is the connection start object number, #155 is the connection end object number, the fourth $ is the attribute (Representation), and the fifth $ is the tag (TAG).
[0063] In this embodiment of the application, an equal-area weld filling strategy with the same number of weld layers and weld passes is adopted. The content of the welding task data package includes some task attribute data as shown in Table 1 below.
[0064] Table 1
[0065]
[0066]
[0067] Task attribute data can be stored in XML format, for example, as shown below:
[0068]
[0069] It should be noted that the welding process information obtained from the forward model data of the object to be welded by parsing the welding task data package represents the standard welding scheme and provides the range of welding process parameters, such as the welding current range of 200A-300A.
[0070] S203: Obtain the actual dimensional information of the object to be welded during the actual welding process.
[0071] The actual welding process includes the pre-welding, during-welding, and post-welding stages of the object being welded.
[0072] In some implementations, obtaining the actual dimensional information of the object to be welded during the actual welding process includes:
[0073] During each weld pass, the actual dimensional information of the object being welded is continuously collected; or...
[0074] After each or more weld passes are completed, the actual dimensions of the object being welded are collected. Specifically, the actual dimensions of the object being welded are collected by sensing sensors, and the actual dimensions can be in the form of binocular images, point clouds, etc.
[0075] The sensing module may include, but is not limited to, laser scanners, cameras, and current and voltage sensors.
[0076] like Figure 4 The diagram shown is a point cloud of the object being welded after welding layer 1 and weld bead 1. The actual geometric dimension data of the object being welded is collected by the sensing module. In this embodiment, it is a point cloud collected after welding layer 1 and weld bead 1.
[0077] S204: Construct a reverse model of the object to be welded based on actual size information; wherein, the reverse model of the object to be welded represents a BIM model that reflects the actual state of the object to be welded.
[0078] Specifically, the reverse model of the welding object stores the geometric dimensions and coordinate data of the welding object in the form of an actual BIM model, including the forming dimension data of the weld seam attached to the welding object. For example... Figure 5 As shown, Figure 5This is a schematic diagram of the reverse welding model established after welding layer 1 and weld bead 1 in this embodiment of the application. Based on the geometric dimensions of the model, the actual cross-sectional area of the weld bead is calculated to be 38.5 mm². 2 .
[0079] S205: Compare and analyze the reverse model and forward model data of the object to be welded to calculate the welding process parameters.
[0080] The welding process parameters generated by the dynamic adaptive planning of welding process parameters include the world coordinates of the welding start point, the world coordinates of the characteristic points of the welding path, and data such as the target welding current, target welding voltage, target welding speed, target shielding gas flow rate, and target swing amplitude. Since the forward model data provides the range values of standard welding process parameters, the actual size information of the reverse model is adjusted based on the range values of standard welding process parameters to approximate the size information of the standard forward model.
[0081] For example, after the welding of weld layer 1 and weld bead 1 in this embodiment is completed, the welding process parameters of weld layer 2 and weld bead 2 are further generated through dynamic adaptive planning of welding process parameters. The specific values of the welding process parameters are: welding current 220A, welding voltage 30V, welding speed 22cm / min, shielding gas flow rate 18L / min, and cross-sectional area 37.1mm2.
[0082] In some implementations, the reverse model and forward model data of the object to be welded are compared and analyzed to calculate the welding process parameters, including:
[0083] By matching the geometric dimensions of the components in the forward model data with the geometric dimensions and coordinate data of the welding object in the reverse model of the welding object, the position of the weld in the forward model data is converted into the coordinate point in the actual welding environment, and the world coordinates of the welding start point are obtained.
[0084] Compare the bevel type, bevel size, weld size, and weld layer / bead data in the forward model data with the weld forming size data in the reverse model of the object being welded, and adjust the subsequent weld layer / bead planning accordingly.
[0085] Based on the adjusted weld bead and weld layer plan, welding process parameter values are generated. These values include the world coordinates of the welding path feature points, as well as the target welding current, target welding voltage, target welding speed, target shielding gas flow rate, and target swing amplitude for each weld bead.
[0086] S206: Perform welding actions on the object to be welded according to the welding process parameters.
[0087] In some embodiments, after performing welding operations on the object to be welded according to welding process parameters, the above method further includes:
[0088] After all welds are completed, obtain the current actual size information of the object being welded, construct a reverse model of the object being welded based on the current actual size information, and upload the reverse model of the object being welded to the digital model management module of the steel structure BIM model platform.
[0089] Understandably, adding production process data (including actual weld dimensions) to the BIM model platform to form a data loop for the welding process helps improve the quality management level of steel structure production welding.
[0090] By parsing the welding task data package, the forward model data of the object to be welded is obtained. The forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded. Based on the actual size information of the object to be welded during the actual welding process, a reverse model of the object to be welded is constructed. The reverse model of the object to be welded represents the BIM model reflecting the actual state of the object to be welded. The reverse model of the object to be welded is compared and calculated with the forward model data to obtain the welding process parameters. Welding actions are performed on the object to be welded according to the welding process parameters. That is, by integrating the welding process data of the component of the BIM model and combining it with reverse modeling technology, the automated operation of welding actions driven by the BIM model is realized. This avoids manual teaching or input of process parameters and welding paths, improves the efficiency of steel structure welding work, and can meet the requirements of flexible production. At the same time, the welding process is dynamically monitored through reverse modeling, and then the welding process is dynamically corrected through adaptive planning of welding process parameters, which effectively ensures the quality of automated welding.
[0091] like Figure 6 As shown, this application also proposes a BIM model-driven steel structure production and welding method based on the aforementioned steel structure production and welding system, comprising the following steps:
[0092] Step S61: The steel structure BIM model platform generates a welding task data package and sends it to the steel structure welding control device.
[0093] Step S62: The steel structure welding control device sends a modeling and perception command to the steel structure welding robot;
[0094] Step S63: The steel structure welding robot collects the actual geometric dimension data of the object to be welded based on the modeling and perception instructions, and sends it to the steel structure welding control device;
[0095] Step S64: The steel structure welding control device performs reverse modeling based on the received actual geometric dimension data of the object to be welded, and obtains the reverse model of the object to be welded.
[0096] Step S65: The steel structure welding control device compares the parsing results of the welding task data packet with the data in the reverse model of the object to be welded, and calculates and generates welding process parameters.
[0097] Step S66: The steel structure welding robot performs welding actions according to the welding process parameters;
[0098] Step S67: After each weld is completed, the steel structure welding robot collects the actual geometric dimension data of the object to be welded, sends it to the steel structure welding control device, and returns to step S64.
[0099] Step S68: After welding is completed, the steel structure welding robot collects the actual geometric dimension data of the object being welded and sends it to the steel structure welding control unit.
[0100] Step S69: The steel structure welding control device performs reverse modeling based on the received actual geometric dimension data of the object to be welded, obtains the reverse model of the object to be welded, and sends it to the steel structure BIM model platform.
[0101] Step S610: The steel structure BIM model platform receives and stores the reverse model of the object to be welded.
[0102] In this embodiment of the application, step S65, which calculates and generates welding process parameters, includes the following steps:
[0103] Step S651: Perform feature matching between the geometric contour and dimensions of the component BIM model obtained from the welding task analysis and the geometric contour and dimensions of the reverse model of the welding object, thereby converting the weld position attached in the component BIM model into coordinate points in the actual welding environment and obtaining the world coordinates of the welding start point; preferably, feature matching specifically uses OpenCV's 3D surface feature matching tool PPF3DDetector to construct feature vector sets for the component BIM model and the reverse model respectively, and finds the rotation matrix that maximizes the matching degree of the two feature vector sets, thereby achieving pose matching of the two types of models.
[0104] Step S652: Compare the groove size, weld layer and weld bead data included in the welding process data obtained from the welding task analysis with the actual groove size and weld formation size data in the reverse model of the welding object, and adjust the subsequent weld layer and weld bead planning to correct the differences; for example, in this embodiment, when the cross-sectional area of the completed weld layer 1 and weld bead 1 is larger than the original welding process data design value, reduce the design value of the cross-sectional area of the subsequent weld bead.
[0105] Step S653: Based on the new weld layer and weld bead planning, generate the world coordinates of the welding path feature points, and the welding process parameter values such as the target welding current, target welding voltage, target welding speed, target shielding gas flow rate, and target swing amplitude for each weld bead; preferably, the method for determining the welding process parameter values for a specific weld bead is to perform matching and interpolation calculations with cases in the welding process case library. For example... Figure 7 As shown, in this embodiment, the starting position of the welding of the weld layer 2 and the weld bead 2 is adjusted according to the actual forming contour of the weld layer 1 and the specific values of its welding process parameters are generated as follows: welding current 220A, welding voltage 30V, welding speed 22cm / min, shielding gas flow rate 18L / min, and cross-sectional area 37.1mm2.
[0106] Regarding the steel structure welding system in the above embodiments, the specific methods by which each module performs its operations have been described in detail in the embodiments related to the method, and will not be elaborated upon here.
[0107] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.
Claims
1. A model-driven steel structure welding system, characterized in that, The steel structure welding system includes a steel structure BIM model platform, a steel structure welding control device communicatively connected to the steel structure BIM model platform, and a steel structure welding robot communicatively connected to the steel structure welding control device. The steel structure BIM model platform includes a digital model management module and a welding task generation module. The steel structure welding control device includes a welding task parsing module, a reverse modeling module, and a dynamic adaptive planning module for welding process parameters. The steel structure welding robot includes a welding module and a perception module. The digital model management module is used for the management of the steel structure BIM model and the attribute data of the steel structure BIM model. The welding task generation module is used to generate welding task data packets; The welding task parsing module is used to parse the welding task data packet to obtain the forward model data of the object to be welded; wherein, the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded; The sensing module is used to collect the actual dimensional information of the object to be welded during the actual welding process; wherein, the actual welding process includes the stages of pre-welding, welding, and post-welding. The reverse modeling module is used to construct a reverse model of the welding object based on the actual size information; wherein, the reverse model of the welding object represents a BIM model reflecting the actual state of the welding object; The dynamic adaptive planning module for welding process parameters is used to generate welding process parameters based on the inverse model and the forward model data of the object to be welded; wherein, the dynamic adaptive planning module for welding process parameters is used for: The geometric dimensions of the components in the forward model data are matched with the geometric dimensions and coordinate data of the welding object in the reverse model of the welding object, thereby converting the position of the weld in the forward model data into coordinate points in the actual welding environment and obtaining the world coordinates of the welding start point. The groove type, groove size, weld size, and weld layer / bead data in the forward model data are compared with the weld forming size data in the reverse model of the object to be welded, and the subsequent weld layer / bead planning is adjusted accordingly. Based on the adjusted weld layer and weld bead plan, the welding process parameter values are generated; The welding module is used to perform welding actions on the object to be welded according to the welding process parameters.
2. The model-driven steel structure welding system according to claim 1, characterized in that, The steel structure product information includes the geometric dimensions and material properties of the components, as well as the position and length of the welds attached to the components; the welding process information includes the welding posture, joint type, bevel type, bevel size, weld size, weld layer and weld bead, welding current range, welding voltage range, welding speed range, shielding gas flow rate range, and swing range.
3. The model-driven steel structure welding system according to claim 1, characterized in that, The BIM model reflecting the actual state of the object being welded includes the geometric dimensions and coordinate data of the object being welded, as well as the forming dimensions of the weld seam attached to the object being welded.
4. The model-driven steel structure welding system according to claim 1, characterized in that, The welding process parameters include the world coordinates of the welding start point, the world coordinates of the characteristic points of the welding path, the target welding current, the target welding voltage, the target welding speed, the target shielding gas flow rate, and the target swing amplitude data.
5. The model-driven steel structure welding system according to claim 1, characterized in that, The sensing module is used to acquire binocular images or point cloud images of the object being welded.
6. A model-driven steel structure welding method, characterized in that, Applied to the steel structure welding system according to any one of claims 1-5, the model-driven steel structure welding method includes: Obtain welding task data packets; The welding task data packet is parsed to obtain the forward model data of the object to be welded; wherein, the forward model data includes the steel structure product information and welding process information of the BIM model of the corresponding component of the object to be welded; Obtain the actual dimensional information of the object to be welded during the actual welding process; wherein, the actual welding process includes the stages before welding, during welding, and after welding; A reverse model of the object to be welded is constructed based on the actual size information; wherein, the reverse model of the object to be welded represents a BIM model reflecting the actual state of the object to be welded; The geometric dimensions of the components in the forward model data are matched with the geometric dimensions and coordinate data of the welding object in the reverse model of the welding object, thereby converting the position of the weld in the forward model data into coordinate points in the actual welding environment and obtaining the world coordinates of the welding start point. The groove type, groove size, weld size, and weld layer / bead data in the forward model data are compared with the weld forming size data in the reverse model of the object to be welded, and the subsequent weld layer / bead planning is adjusted accordingly. Based on the adjusted weld layer and weld bead plan, the welding process parameter values are generated; the welding action is performed on the object to be welded according to the welding process parameters.
7. The model-driven steel structure welding method according to claim 6, characterized in that, The welding process parameters include the world coordinates of the welding start point, the world coordinates of the characteristic points of the welding path, the target welding current, the target welding voltage, the target welding speed, the target shielding gas flow rate, and the target swing amplitude data.
8. The model-driven steel structure welding method according to claim 6, characterized in that, The acquisition of the actual dimensional information of the object to be welded during the actual welding process includes: During each weld pass, the actual dimensional information of the object being welded is continuously collected; or... After each one or more weld passes are completed, the actual dimensions of the object being welded are collected.
9. The model-driven steel structure welding method according to any one of claims 6-8, characterized in that, The steel structure welding system includes a digital model management module of a steel structure BIM model platform. After performing welding actions on the object to be welded according to the welding process parameters, the method further includes: After all welds are completed, the current actual size information of the object being welded is obtained. Based on the current actual size information, a reverse model of the object being welded is constructed, and the reverse model of the object being welded is uploaded to the digital model management module of the steel structure BIM model platform.