Digital twin visualization method and system for digital metal structure processing

Abstract

The present invention provides a digital twin visualization method and system for digital metal structure processing. First, a real-time data set of the metal structure processing process is obtained, including processing equipment operation status data and metal structure feature data. Then, a digital twin basic model corresponding to the physical processing system is constructed, including a geometric feature module and a process association module. Then, the real-time data set is synchronized with the digital twin basic model to generate a dynamically updated digital twin model including real-time equipment operation status information and real-time structural morphology information. Then, visualization features are extracted from the dynamically updated digital twin model to obtain a visualization feature set including structural morphology features and process status features. Finally, visualization presentation content is generated based on the visualization feature set and output to an interactive terminal for display. This allows operators to intuitively understand the processing process in real time, improve processing quality, efficiency and accuracy, and reduce costs.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a digital twin visualization method and system applied to digital metal structure processing. Background Art

[0002] In the field of metal structure processing, traditional processing methods rely primarily on manual experience and pre-set processing parameters. During the processing, there is a lack of real-time, intuitive, and comprehensive monitoring of the actual processing status of the metal structure and the operating status of the processing equipment. Operators can usually only understand the equipment's operating status through regular equipment inspections and simple instrument readings. It is difficult to accurately grasp key information such as the metal structure's processing accuracy and morphological changes in real time.

[0003] While existing digital machining technologies have achieved a certain degree of digital control over the machining process, they primarily focus on the sending and execution of machining instructions, with limited visualization capabilities. This inability to intuitively display the real-time spatial form of the metal structure and the machining process status to operators makes it difficult to promptly identify and accurately diagnose problems that arise during machining, impacting machining quality and efficiency, and increasing production costs and scrap rates. Summary of the Invention

[0004] In view of the above-mentioned problems, in combination with the first aspect of the present invention, an embodiment of the present invention provides a digital twin visualization method for digital metal structure processing, the method comprising:

[0005] Acquire a real-time data set of a metal structure processing process, wherein the real-time data set includes processing equipment operation status data and metal structure characteristic data;

[0006] Construct a digital twin basic model corresponding to the physical processing system, the digital twin basic model including a geometric feature module and a process association module. The geometric feature module is used to represent the spatial morphological information of the metal structure, and the process association module is used to represent the mapping relationship between the processing technology and the structural characteristics.

[0007] Performing data synchronization processing on the real-time data set and the digital twin basic model to generate a dynamically updated digital twin model, wherein the dynamically updated digital twin model includes real-time device operation status information and real-time structural morphology information;

[0008] Performing visualization feature extraction processing on the dynamically updated digital twin model to obtain a visualization feature set including structural morphological features and process status features, wherein the structural morphological features reflect the current spatial form of the metal structure, and the process status features reflect the execution status of the processing technology;

[0009] Visual presentation content is generated based on the visualization feature set, and the visual presentation content is output to an interactive terminal for display.

[0010] In a possible implementation of the first aspect, constructing a digital twin basic model corresponding to the physical processing system includes:

[0011] Acquire design drawing data of the metal structure, wherein the design drawing data includes overall structural profile information, connection node position information, and key dimensional constraint information;

[0012] Constructing a geometric feature module based on the design drawing data, wherein the geometric feature module represents different components of the metal structure through a layered structure, and each layer of the structure contains contour boundary information and spatial position coordinate information of the corresponding part;

[0013] Acquiring standard process data of a processing technology, wherein the standard process data includes process execution sequence information, process operation parameter information, and process quality requirement information;

[0014] Building a process association module based on the standard process data, wherein the process association module represents the matching relationship between each process step and the corresponding component of the metal structure through an association relationship table, wherein the association relationship table includes a process step identifier, a corresponding structural component identifier, and process influencing parameter information;

[0015] The geometric feature module and the process association module are subjected to data fusion processing to generate an initial digital twin basic model. The initial digital twin basic model realizes a bidirectional query function of geometric features and process associations through a unified data interface.

[0016] In a possible implementation of the first aspect, constructing a geometric feature module based on the design drawing data includes:

[0017] Performing structural decomposition processing on the design drawing data to decompose the metal structure into a main frame portion, a connection node portion, and an auxiliary support portion;

[0018] Performing contour extraction processing on the main frame part to generate contour boundary information including vertex coordinate sequence and edge connection relationship;

[0019] Performing position positioning processing on the connection node part, extracting node center coordinates and radius information of the node coverage area as spatial position coordinate information;

[0020] Performing morphological description processing on the auxiliary support portion to generate contour boundary information including support direction vector and support length parameters;

[0021] The contour boundary information and spatial position coordinate information of the main frame part, the connection node part and the auxiliary support part are stored in a hierarchical relationship to generate a geometric feature module with a hierarchical structure, wherein the hierarchical relationship includes a step-by-step refinement relationship from the overall structure to the local components;

[0022] In a possible implementation of the first aspect, constructing a process association module based on the standard process data includes:

[0023] Performing step splitting processing on the standard process data to obtain a plurality of process step units arranged in chronological order, each process step unit including step name information and operation content description information;

[0024] Assigning a unique process step identifier to each process step unit, wherein the process step identifier includes step sequence number information and step type information;

[0025] Analyze the operation content description information of each process step unit, determine the metal structure components affected by the process step unit, and assign a corresponding structural part identifier to each process step unit. The structural part identifier corresponds one-to-one with the hierarchical structure identifier in the geometric feature module;

[0026] Extracting process influencing parameter information affecting metal structural features in each process step unit, wherein the process influencing parameter information includes temperature variation range information, pressure action position information, and processing time duration information;

[0027] The process step identifiers, corresponding structural part identifiers and process influencing parameter information are stored in rows to generate an association relationship table containing multiple rows of records. The association relationship table establishes data association with the geometric feature module through the structural part identifier.

[0028] In a possible implementation of the first aspect, synchronizing the real-time data set with the digital twin base model to generate a dynamically updated digital twin model includes:

[0029] Analyzing and processing the processing equipment operating status data in the real-time data set to obtain the equipment's current operating mode information, equipment component motion trajectory information, and equipment energy consumption information;

[0030] Collecting and processing the metal structure feature data in the real-time data set to obtain structure surface morphology information, structure connection node deformation information, and structure key position dimensional deviation information;

[0031] Matching the current operation mode information of the equipment with the process step identifier in the process association module to determine the currently executed process step unit;

[0032] updating the process influencing parameter information of the current process step unit in the process association module according to the motion trajectory information of the equipment component and the process influencing parameter information;

[0033] According to the structural surface morphology information, structural connection node deformation information and structural key position size deviation information, updating the contour boundary information and spatial position coordinate information of the corresponding structural part in the geometric feature module;

[0034] The updated geometric feature module and process association module are subjected to data fusion processing to generate a dynamically updated digital twin model that contains real-time equipment operation status information and real-time structural morphology information.

[0035] In a possible implementation of the first aspect, updating the contour boundary information and spatial position coordinate information of the corresponding structural part in the geometric feature module based on the structural surface morphology information, the structural connection node deformation information, and the structural key position size deviation information includes:

[0036] Extracting surface relief features from the surface topography information of the structure, and converting the surface relief features into vertex coordinate adjustment amounts of contour boundary information;

[0037] Extracting the node displacement direction and displacement distance from the deformation information of the structural connection node, and converting the displacement direction and displacement distance into the offset of the spatial position coordinates of the connection node portion;

[0038] Extracting the dimensional variation from the dimensional deviation information of the key position of the structure, and converting the dimensional variation into the side length adjustment of the outline boundary information of the main frame part or the auxiliary support part;

[0039] Obtain the original contour boundary information and original spatial position coordinate information of the corresponding structural part in the geometric feature module;

[0040] Superimposing the vertex coordinate adjustment amount with the vertex coordinate sequence of the original contour boundary information to generate updated contour boundary information;

[0041] Superimposing the offset with the node center coordinates of the original spatial position coordinate information to generate updated spatial position coordinate information of the connection node;

[0042] The side length adjustment amount is superimposed on the side length parameter of the original contour boundary information to generate updated contour boundary information of the main frame part or the auxiliary support part.

[0043] In a possible implementation of the first aspect, performing visualization feature extraction processing on the dynamically updated digital twin model to obtain a visualization feature set including structural morphological features and process state features includes:

[0044] Extracting updated contour boundary information and spatial position coordinate information of each structural part from the geometric feature module of the dynamically updated digital twin model as basic data of structural morphological features;

[0045] Performing visualization conversion processing on the basic data to generate structural morphology visualization data including a three-dimensional coordinate point cloud, wherein the point density of the three-dimensional coordinate point cloud is positively correlated with the importance of the structural part;

[0046] Extracting the process step identification, process influencing parameter information, and corresponding structural part identification of the currently executed process step unit from the process association module of the dynamically updated digital twin model as basic data of the process state characteristics;

[0047] Performing state annotation processing on the basic data of the process state characteristics to generate process state visualization data including step name information and parameter change trends, wherein the parameter change trends are represented by time series curves;

[0048] The structural morphology visualization data and the process status visualization data are fused to generate a visualization feature set including a spatial morphology display layer and a process status annotation layer. The spatial morphology display layer is used to present the current spatial morphology of the metal structure, and the process status annotation layer is used to annotate the process information that currently affects the current spatial morphology.

[0049] In a possible implementation of the first aspect, performing visualization conversion processing on the basic data to generate structural morphology visualization data including a three-dimensional coordinate point cloud includes:

[0050] Determine the importance level of each structural part in the geometric feature module, wherein the importance level is determined based on the load-bearing role of the structural part in the overall structure and the sensitivity of the processing error;

[0051] Assigning a corresponding point density parameter to each structural part, wherein the point density parameter is positively correlated with the importance level;

[0052] Extracting a vertex coordinate sequence from the updated contour boundary information of the corresponding structure part;

[0053] interpolating the vertex coordinate sequence according to the point density parameter, inserting a plurality of intermediate coordinate points between adjacent vertices to generate a target density coordinate point set;

[0054] Extracting node center coordinates and coverage area radius information from the updated spatial position coordinate information of the corresponding structural part;

[0055] Taking the node center coordinate as the center, generating uniformly distributed coordinate points in the coverage area according to the point density parameter to generate a node area coordinate point set;

[0056] The target density coordinate point set and the node area coordinate point set are merged to generate a three-dimensional coordinate point cloud containing the coordinate points of each structural part.

[0057] In a possible implementation of the first aspect, performing state annotation processing on the basic data of the process state characteristics to generate process state visualization data including step name information and parameter change trends includes:

[0058] Extracting step number information and step type information from the process step identifier, and combining the step name information to generate a process step annotation text;

[0059] extracting temperature variation range information, pressure action position information and processing time duration information from the process influencing parameter information;

[0060] Acquire historical parameter data of the current process step unit, wherein the historical parameter data includes temperature measured values, pressure measured values, and time accumulated values ​​at multiple time points in the past;

[0061] Comparing the measured temperature value with the temperature variation range information to generate a temperature variation trend curve;

[0062] Performing spatial mapping of the measured pressure value and the pressure action position information to generate a pressure distribution change trend curve;

[0063] Comparing the accumulated time value with the processing time duration information to generate a time progress change trend curve;

[0064] The process step annotation text is associated with the temperature change trend curve, the pressure distribution change trend curve, and the time progress change trend curve to store and generate process status visualization data.

[0065] In a possible implementation of the first aspect, generating visual presentation content based on the visualization feature set, and outputting the visual presentation content to an interactive terminal for display, includes:

[0066] Extracting a three-dimensional coordinate point cloud of a structural morphology display layer from the visualization feature set to generate a three-dimensional space visualization view, wherein the three-dimensional space visualization view supports rotation, scaling, and local magnification operations;

[0067] Extracting the process step annotation text and the parameter change trend curve of the process state annotation layer from the visualization feature set to generate a two-dimensional parameter visualization view, wherein the two-dimensional parameter visualization view includes a time axis and a parameter value coordinate axis;

[0068] Performing interface layout processing on the three-dimensional space visualization view and the two-dimensional parameter visualization view to generate a multi-view interface including a main view area and an auxiliary view area;

[0069] Adding an interactive control component to the multi-view interface, wherein the interactive control component includes a time progress slider, a view switching button, and a parameter filter drop-down menu;

[0070] Integrate the multi-view interface with the interactive control component to generate interactive visual presentation content;

[0071] The interactive visual presentation content is transmitted to an interactive terminal, so that the interactive terminal displays the interactive visual presentation content through a graphics rendering engine.

[0072] On the other hand, an embodiment of the present invention also provides a digital twin visualization system for digital metal structure processing, including a processor and a machine-readable storage medium, wherein the machine-readable storage medium is connected to the processor, the machine-readable storage medium is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the machine-readable storage medium to implement the above method.

[0073] Based on the above aspects, an embodiment of the present invention obtains a real-time data set of the metal structure processing process, which covers the operating status data of the processing equipment and the metal structure feature data, and constructs a digital twin basic model corresponding to the physical processing system, wherein the geometric feature module accurately represents the spatial morphological information of the metal structure, and the process association module clearly presents the mapping relationship between the processing technology and the structural features, so that the digital twin basic model can accurately reflect the characteristics of the physical processing system. The real-time data set and the digital twin basic model are synchronized to generate a dynamically updated digital twin model, which contains real-time equipment operating status information and real-time structural morphological information, realizing real-time dynamic simulation of the processing process. The dynamically updated digital twin model is subjected to visual feature extraction processing to obtain a visual feature set containing structural morphological features and process status features, which can comprehensively reflect the current spatial morphology of the metal structure and the execution status of the processing technology. Based on the visual feature set, visual presentation content is generated and output to the interactive terminal for display, so that operators can intuitively and in real time understand the processing process, promptly discover potential problems and make adjustments, thereby improving processing quality, efficiency and accuracy, and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a schematic diagram of the execution flow of the digital twin visualization method applied to digital metal structure processing provided by an embodiment of the present invention.

[0075] Figure 2 Schematic diagram of exemplary hardware and software components of a digital twin visualization system for digital metal structure processing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0076] The present invention will be described in detail below with reference to the accompanying drawings. Figure 1 This is a flow chart of a digital twin visualization method for digital metal structure processing provided by an embodiment of the present invention. The digital twin visualization method for digital metal structure processing is introduced in detail below.

[0077] Step S110: obtaining a real-time data set of the metal structure processing process, wherein the real-time data set includes processing equipment operation status data and metal structure feature data.

[0078] In the context of digital metal structure processing, comprehensive and accurate monitoring and analysis of the entire machining process requires real-time data collection. To obtain data on the operating status of machining equipment, various types of sensors are installed at key locations on the equipment. Power sensors installed in the equipment's power system provide real-time monitoring of the equipment's power consumption, indirectly reflecting its energy consumption, as there is a direct correlation between power and energy consumption. Displacement sensors and angle sensors are installed on the equipment's transmission components. Displacement sensors accurately measure the linear displacement of equipment components in space, while angle sensors measure the rotational angle of components. By integrating and analyzing the data from these two sensors, the motion trajectory of the equipment components can be determined. Furthermore, the equipment's built-in control system interface can be used to obtain operating instructions and feedback signals, thereby determining the equipment's current operating mode, such as whether it is in automatic machining mode, manual commissioning mode, or standby mode.

[0079] For the collection of characteristic data of metal structures, a 3D laser scanner can be used to perform an all-round scan of the surface of the metal structure. The laser beam emitted by the scanner is received after being reflected on the surface of the metal structure. By calculating information such as the propagation time and angle of the laser, the surface morphology of the metal structure can be accurately reconstructed, thereby obtaining the surface morphology information of the structure. Strain gauges are arranged at the connection nodes of the metal structure. The strain gauges can convert the strain changes at the nodes into electrical signals. By processing and analyzing the electrical signals, the deformation information of the structural connection nodes can be obtained. At the same time, high-precision measuring tools such as calipers and micrometers are used to regularly measure the key position dimensions of the metal structure, and the measurement results are compared with the design dimensions to obtain the dimensional deviation information of the key positions of the structure.

[0080] The processing equipment operating status data and metal structure characteristic data obtained through the above-mentioned various methods are summarized and sorted to obtain the required real-time data set.

[0081] Step S120: Construct a digital twin basic model corresponding to the physical processing system, wherein the digital twin basic model includes a geometric feature module and a process association module. The geometric feature module is used to represent the spatial morphological information of the metal structure, and the process association module is used to represent the mapping relationship between the processing technology and the structural features.

[0082] Building a digital twin foundational model is a key step in achieving digital visualization of metal structure processing. This model must accurately reflect the characteristics of the physical processing system. The following details the process of building the geometric feature module and the process-related module.

[0083] Step S121: obtaining design drawing data of the metal structure, wherein the design drawing data includes overall structure profile information, connection node position information, and key dimension constraint information.

[0084] In actual operation, it is necessary to obtain the design drawing data of the metal structure from the professional data management system of the design department. These design drawing data are stored in a set electronic format, such as CAD format. For the overall outline information of the structure, the design drawing will depict the shape of the metal structure in three-dimensional space with precise lines and curves. For example, for a large metal tower, the drawing will draw the overall shape of the tower in detail, including the inclination angle of the tower body, the diameter change at different heights, etc. The connection node position information will clearly mark the specific coordinates of each connection point on the drawing. These coordinates are determined based on the set coordinate system so that the nodes can be accurately located in subsequent modeling. The key dimensional constraint information will strictly stipulate the important dimensions of the structure, such as the diameter and wall thickness of the main members of the tower, and will also give the corresponding tolerance range to ensure the accuracy of processing.

[0085] Step S122: constructing a geometric feature module based on the design drawing data, wherein the geometric feature module represents different components of the metal structure through a layered structure, and each layer of the structure contains contour boundary information and spatial position coordinate information of the corresponding part.

[0086] Step S1221: performing structural decomposition processing on the design drawing data, and decomposing the metal structure into a main frame part, a connection node part and an auxiliary support part.

[0087] After obtaining the design drawing data, in-depth analysis and decomposition are required. As for the main frame part, it is the main load-bearing part of the metal structure, which determines the overall stability and mechanical properties of the structure. Taking the metal tower as an example, the main rods of the tower body constitute the main frame part. The connection node part is the key part where the various components are connected to each other, such as the welding points or bolt connection points between the tower rods. The auxiliary support part is used to enhance the stability and rigidity of the structure. The diagonal brace on the tower belongs to the auxiliary support part. During the decomposition process, it is necessary to accurately divide each part according to the mechanical principles and functional characteristics of the structure.

[0088] Step S1222: performing contour extraction processing on the main frame part to generate contour boundary information including vertex coordinate sequence and edge connection relationship.

[0089] Image processing and geometric analysis algorithms are required to extract the outline of the main frame. First, the line information of the main frame is extracted from the design drawings. Then, the positions of the vertices are determined by identifying the intersections of the lines. These vertices are arranged in a set order to form a vertex coordinate sequence. At the same time, the connection relationship between each vertex is analyzed to determine which vertices are connected by edges, thereby obtaining the edge connection relationship. During the extraction process, the accuracy and continuity of the lines need to be taken into account to ensure that the generated outline boundary information is accurate. For the main frame of the tower, the vertex coordinates and edge connection relationship of each member can clearly depict the shape and connection method of the member.

[0090] Step S1223: performing position positioning processing on the connection node part, extracting the node center coordinates and the radius information of the node coverage area as spatial position coordinate information.

[0091] When locating the connection node, it is necessary to combine the annotations in the design drawings with the actual physical characteristics. Calculate the center coordinates of the node based on the coordinate information on the drawing. For the radius information of the node coverage area, it is necessary to consider the actual size and connection method of the node. If it is a welded node, the width and impact range of the weld need to be considered; if it is a bolted connection node, the distribution of the bolts and the range of action of the tightening force need to be considered. Determine the radius of the node coverage area through precise measurement and calculation. For example, for a welded node on a tower, its center coordinates and coverage area radius can clearly define the specific position and impact range of the node in space.

[0092] Step S1224: performing morphological description processing on the auxiliary support part to generate contour boundary information including support direction vector and support length parameters.

[0093] To describe the auxiliary support's morphology, it's necessary to analyze its spatial extension direction and length. Through geometric calculations and vector analysis, the support direction vector is determined. This support direction vector represents the orientation of the auxiliary support in space and reflects the direction of its support for the main structure. Furthermore, based on the dimensions noted in the design drawings, the auxiliary support's length is accurately measured and used as the support length parameter. For the tower's diagonal braces, the support direction vector and support length parameters accurately describe their installation location and support effectiveness.

[0094] Step S1225: Store the contour boundary information and spatial position coordinate information of the main frame part, the connection node part and the auxiliary support part in a hierarchical relationship to generate a geometric feature module with a hierarchical structure, wherein the hierarchical relationship includes a step-by-step refinement relationship from the overall structure to the local components.

[0095] When storing this information, a reasonable hierarchical structure is necessary. The overall structure is the highest level, with the main frame, connection nodes, and auxiliary supports as components at the next level. Each component is further broken down into its specific components. For example, the main frame can be broken down into different rods, each with its own vertex coordinate sequence and edge connections. This hierarchical storage method forms a layered geometric feature module, enabling the model to clearly represent the spatial morphology of the metal structure.

[0096] Step S123: Acquire standard process data of the processing technology, wherein the standard process data includes process execution sequence information, process operation parameter information, and process quality requirement information.

[0097] Obtain detailed processing technology standard process data from the process design department. These data are derived from previous production experience, process tests and industry standards. The process execution sequence information will clearly specify the order of each process step. For example, for the processing of metal towers, the rods are cut first, then welded, and finally surface treated. The process operation parameter information will provide detailed descriptions of the key parameters in each process step, such as the cutting speed during cutting, the welding current and voltage during welding, etc. The process quality requirement information will strictly stipulate the quality standards of the processed metal structure, including requirements for dimensional accuracy, surface roughness, weld quality, etc.

[0098] Step S124: constructing a process association module based on the standard process data, wherein the process association module represents the matching relationship between each process step and the corresponding component of the metal structure through an association relationship table, wherein the association relationship table includes a process step identifier, a corresponding structural part identifier, and process influencing parameter information.

[0099] Step S1241: performing step splitting processing on the standard process data to obtain a plurality of process step units arranged in chronological order, each process step unit including step name information and operation content description information.

[0100] Perform detailed step-by-step breakdown of standard process data. Based on the process logic and operational characteristics, the entire machining process is broken down into multiple chronological process step units. Each process step unit has a clear step name, such as "cutting," "welding," "polishing," etc., and includes a detailed description of the specific operations and requirements required for that step. For example, in the "cutting" step, you can describe the cutting method (such as laser cutting, plasma cutting, etc.), the cutting location, and the required size.

[0101] Step S1242: Allocate a unique process step identifier to each process step unit, where the process step identifier includes step sequence number information and step type information.

[0102] Each process step unit is assigned a unique process step identifier, which includes the step sequence number and step type information. The step sequence number information is numbered according to the order in which the process steps are executed, ensuring that each step has a unique sequence number for easy subsequent management and query. The step type information is categorized according to the nature and function of the process step, such as "cutting type," "connection type," "surface treatment type," etc. This identification method clearly identifies the characteristics and function of each process step.

[0103] Step S1243: Analyze the operation content description information of each process step unit, determine the metal structure components affected by the process step unit, and assign a corresponding structural part identifier to each process step unit. The structural part identifier corresponds one-to-one to the hierarchical structure identifier in the geometric feature module.

[0104] The operation descriptions for each process step are thoroughly analyzed to determine which components of the metal structure are affected by each step. Based on this analysis, each process step is assigned a corresponding structural component identifier, which corresponds one-to-one with the hierarchical structure identifiers in the geometric feature module. For example, in the "Welding" step, if welding is performed on the main frame members of the tower, the structural component identifier corresponding to this step corresponds to the identifier of the main frame in the geometric feature module.

[0105] Step S1244: extracting process influencing parameter information affecting the metal structure characteristics in each process step unit, wherein the process influencing parameter information includes temperature variation range information, pressure action position information, and processing time duration information.

[0106] For each process step unit, it is necessary to extract the key parameter information that affects the characteristics of the metal structure. The temperature variation range information reflects the temperature variation range experienced by the metal structure during the process step. For example, during the welding process, the temperature around the weld will rise sharply and then gradually cool down. This temperature variation range needs to be recorded. The pressure action position information clarifies the position where the pressure acts on the metal structure. For example, in the forging process, the pressure will act on a specific part. The processing time duration information specifies the length of time required for the process step.

[0107] Step S1245: storing the process step identifier, the corresponding structural part identifier and the process influencing parameter information in rows, generating an association relationship table containing multiple rows of records, wherein the association relationship table establishes data association with the geometric feature module through the structural part identifier.

[0108] The process step identifiers, corresponding structural component identifiers, and process-influencing parameter information are stored row by row, forming a multi-row association table. Each row in the association table represents information related to a process step unit. Using the structural component identifiers, the association table establishes data associations with the geometric feature module, enabling the process association module to accurately represent the mapping between machining processes and structural features. For example, when querying a specific process step, the corresponding metal structural component and related process-influencing parameters can be found through the association table.

[0109] Step S125: Perform data fusion processing on the geometric feature module and the process association module to generate an initial digital twin basic model. The initial digital twin basic model realizes a bidirectional query function of geometric features and process association through a unified data interface.

[0110] When performing data fusion processing, it is necessary to ensure that the data format and structure of the geometric feature module and the process association module match. First, the data of the geometric feature module and the process association module are cleaned and preprocessed to remove redundant and erroneous information. Then, based on the structural part identifier in the association table, the process information in the process association module is associated with the corresponding structural part in the geometric feature module. By designing a unified data interface, a two-way query function for geometric feature and process association is realized. For example, the user can query the related process steps and process influencing parameters by entering the identifier of a component of the metal structure; or by entering the process step identifier, the structural part affected by the step and the related geometric feature information.

[0111] Step S130: Perform data synchronization processing on the real-time data set and the digital twin basic model to generate a dynamically updated digital twin model, wherein the dynamically updated digital twin model includes real-time equipment operation status information and real-time structural morphology information.

[0112] The purpose of synchronizing the real-time data set with the digital twin base model is to enable the digital twin model to reflect the actual operation of the physical processing system in real time. The following details the specific steps of data synchronization.

[0113] Step S131: Analyze and process the processing equipment operation status data in the real-time data set to obtain the equipment's current operation mode information, equipment component movement trajectory information, and equipment energy consumption information.

[0114] First, the collected device operation signals are decoded to extract key information. The device's current operating mode is determined by analyzing the device's control instructions and feedback signals. If the device receives automatic processing instructions and each component operates according to the preset program, the device can be determined to be in automatic processing mode. The motion trajectory of the device components is determined by combining data from the displacement sensors and angle sensors installed on the components. By processing and analyzing this sensor data, the position and posture changes of the components in three-dimensional space are calculated, thereby obtaining motion trajectory information. For device energy consumption information, the device's energy consumption is calculated by monitoring parameters such as current and voltage and combining them with the device's power characteristic curve.

[0115] Step S132: collecting and processing the metal structure feature data in the real-time data set to obtain structure surface morphology information, structure connection node deformation information, and structure key position dimensional deviation information.

[0116] For the collection and processing of metal structure characteristic data, special measurement equipment and data analysis methods are required. For structural surface morphology information, a three-dimensional laser scanner is used to scan the surface of the metal structure. The laser beam emitted by the scanner is received after being reflected on the surface of the metal structure. By calculating information such as the propagation time and angle of the laser, the surface morphology of the metal structure is reconstructed. For the deformation information of the structural connection nodes, strain gauges and displacement sensors are installed at the connection nodes. The strain gauges can measure the stress changes at the nodes, and the displacement sensors can measure the displacement of the nodes. By analyzing the data of these sensors, the deformation information of the connection nodes is obtained. For the dimensional deviation information of the key positions of the structure, high-precision measuring tools such as calipers and micrometers are used to regularly measure the dimensions of the key positions, compare them with the design dimensions, and calculate the dimensional deviation information.

[0117] Step S133: matching the current operation mode information of the equipment with the process step identifier in the process association module to determine the currently executed process step unit.

[0118] When matching the device's current operating mode information with the process step identifiers in the process association module, a matching rule base is required. Based on the device's operating mode and the process step requirements, the current process step is determined. If the device is in welding mode and the welding parameters match those of a welding process step in the process association module, the currently executing process step unit is determined to be that welding step. During the matching process, it is necessary to consider the flexibility of the device and the diversity of processes to ensure accurate matching.

[0119] Step S134: updating the process influencing parameter information of the current process step unit in the process association module according to the equipment component motion trajectory information and the process influencing parameter information.

[0120] Based on the motion trajectory information of the equipment component and the process-influencing parameter information, the process-influencing parameter information for the current process step unit in the process association module is updated. If the motion trajectory of the equipment component changes, it may affect parameters such as the pressure application position and processing time in the process step. Based on the changes in the motion trajectory, the pressure application position information and processing time duration information in the process-influencing parameter information are adjusted accordingly. For example, if the motion trajectory of the welding head shifts during the welding process, the pressure application position and welding time must be recalculated to ensure weld quality.

[0121] Step S135: updating the contour boundary information and spatial position coordinate information of the corresponding structural part in the geometric feature module according to the structural surface morphology information, structural connection node deformation information and structural key position size deviation information.

[0122] Step S1351: extracting surface relief features from the surface topography information of the structure, and converting the surface relief features into vertex coordinate adjustment values ​​of contour boundary information.

[0123] Extracting surface relief features from structural surface topography requires the use of image processing and feature extraction algorithms. Surface topography data acquired by a 3D laser scanner is filtered and denoised to extract surface convex and concave features. These surface relief features are converted into vertex coordinate adjustments for contour boundary information. If the surface is convex, the vertex coordinate value is increased accordingly; if it is concave, the vertex coordinate value is decreased accordingly.

[0124] Step S1352: extracting the node displacement direction and displacement distance from the deformation information of the structural connection node, and converting the displacement direction and displacement distance into the offset of the spatial position coordinates of the connection node part.

[0125] Extracting the node displacement direction and distance from structural connection node deformation information requires analyzing data from displacement sensors and strain gauges installed at the nodes. The node displacement direction and distance are determined by calculating the node displacement components in different directions. These displacement directions and distances are converted into offsets in the spatial coordinates of the connection node. Based on the displacement directions and distances, the node center coordinates of the connection node are adjusted.

[0126] Step S1353: extracting the dimensional variation in the dimensional deviation information of the key position of the structure, and converting the dimensional variation into the side length adjustment of the contour boundary information of the main frame part or the auxiliary support part.

[0127] When extracting dimensional changes from dimensional deviation information at key structural locations, the measured actual dimensions are compared with the designed dimensions to calculate the dimensional change. This dimensional change is then converted into side length adjustments for the outline boundary information of the main frame or auxiliary support sections. If the dimension increases, the corresponding side length is increased; if the dimension decreases, the side length is decreased.

[0128] Step S1354: Obtain the original contour boundary information and original spatial position coordinate information of the corresponding structural part in the geometric feature module.

[0129] The original contour boundary information and original spatial position coordinates of the corresponding structural part are obtained from the geometric feature module. This original contour boundary information and original spatial position coordinates are stored when the geometric feature module is constructed and represent the initial state of the metal structure during the design phase. By identifying the structural part, the corresponding original information can be accurately located.

[0130] Step S1355: superimposing the vertex coordinate adjustment amount with the vertex coordinate sequence of the original contour boundary information to generate updated contour boundary information.

[0131] When overlaying the vertex coordinate adjustment with the vertex coordinate sequence of the original contour boundary information, ensure the consistency of the coordinate system. Add the corresponding vertex coordinate adjustment to each vertex coordinate value to obtain the updated vertex coordinate sequence. Combine the updated vertex coordinate sequence with the edge connectivity to generate the updated contour boundary information.

[0132] Step S1356: superimpose the offset with the node center coordinates of the original spatial position coordinate information to generate updated spatial position coordinate information of the connection node.

[0133] When overlaying the offset with the original spatial coordinate information, the node center coordinates must be processed according to the coordinate calculation rules of three-dimensional space. Add the corresponding offset to each component of the node center coordinate to obtain the updated node center coordinates. Combine the updated node center coordinates with the radius of the node coverage area to generate the updated spatial coordinate information of the connected node.

[0134] Step S1357: Superimpose the side length adjustment amount and the side length parameter of the original contour boundary information to generate updated contour boundary information of the main frame part or the auxiliary support part.

[0135] When overlaying the edge length adjustment with the original contour boundary information, it's important to consider the edge connectivity and structural integrity. Add the corresponding edge length adjustment to each edge's length parameter to generate the updated edge length parameter. The updated vertex coordinate sequence and updated edge length parameters are combined to generate the updated contour boundary information for the main frame or auxiliary support portion.

[0136] Step S136: Perform data fusion processing on the updated geometric feature module and process association module to generate a dynamically updated digital twin model that includes real-time equipment operation status information and real-time structural morphology information.

[0137] The updated geometric feature module and process association module undergo another data fusion process. Based on the previously established association, the data from the geometric feature module and process association module are integrated. The structural information in the updated geometric feature module is associated with the corresponding process step information in the process association module to ensure consistency between the geometric features and process information in the model. This data fusion process generates a dynamically updated digital twin model that includes real-time equipment operating status information and real-time structural morphology information. This model accurately reflects the real-time status of the metal structure processing process.

[0138] Step S140: Perform visualization feature extraction processing on the dynamically updated digital twin model to obtain a visualization feature set including structural morphological features and process status features, wherein the structural morphological features reflect the current spatial form of the metal structure, and the process status features reflect the execution status of the processing technology.

[0139] In order to present the dynamically updated digital twin model to users in an intuitive manner, it is necessary to extract visual features from the dynamically updated digital twin model. This process mainly focuses on extracting structural morphological features and process state features to form a visual feature set.

[0140] Step S141: extracting the updated contour boundary information and spatial position coordinate information of each structural part from the geometric feature module of the dynamically updated digital twin model as basic data of the structural morphological features.

[0141] In the dynamically updated digital twin model, the geometric feature module records the spatial morphological information of each part of the metal structure in detail. In order to obtain the basic data of the structural morphological features, it is necessary to extract the updated contour boundary information and spatial position coordinate information of each structural part from the geometric feature module. In the previous step, the geometric feature module has been updated according to the real-time data, so the information extracted here is the latest data reflecting the current state of the metal structure. For the main frame part, its updated vertex coordinate sequence and edge connection relationship are extracted as contour boundary information, as well as the node center coordinates and coverage area radius information as spatial position coordinate information; for the connection node part, the updated node center coordinates and node coverage area radius information are extracted; for the auxiliary support part, the updated support direction vector and support length parameters are extracted as contour boundary information.

[0142] Step S142: performing visualization conversion processing on the basic data to generate structural morphology visualization data including a three-dimensional coordinate point cloud, wherein the point density of the three-dimensional coordinate point cloud is positively correlated with the importance of the structural part.

[0143] Step S1421: Determine the importance level of each structural part in the geometric feature module, where the importance level is determined based on the load-bearing role of the structural part in the overall structure and the sensitivity to machining errors.

[0144] When converting basic data into a visual representation, the first step is to determine the importance of each structural component within the geometric feature module. Each structural component's role in the overall structure and sensitivity to machining errors vary, resulting in varying degrees of importance. The main frame bears the primary load-bearing role within the structure, significantly impacting its stability and mechanical properties. Furthermore, machining errors can degrade the overall performance of the structure, thus accumulating a relatively high level of importance. Connecting nodes, which connect and transmit forces, significantly impact the joint strength and stability of the structure, thus also accumulating a relatively high level of importance. While auxiliary supports contribute to structural stability, their load-bearing role is less significant than that of the main frame and connecting nodes, and machining errors also have a relatively small impact on the overall structure. Therefore, their importance is relatively low. Based on these factors, the importance of each structural component is classified into different levels.

[0145] Step S1422: assigning a corresponding point density parameter to each structural part, where the point density parameter is positively correlated with the importance level.

[0146] Each structural component is assigned a corresponding point density parameter based on its importance level. Since the point density parameter is positively correlated with the importance level, higher-level structural components are assigned a larger point density parameter. The main frame, due to its high importance, is assigned a larger point density parameter; the connecting nodes are also assigned a relatively large point density parameter; and the auxiliary support components are assigned a relatively small point density parameter. As a result, when subsequently generating a 3D coordinate point cloud, more important structural components will have more coordinate points, allowing for a more detailed display of their structural morphology.

[0147] Step S1423: extracting the vertex coordinate sequence from the updated contour boundary information of the corresponding structural part.

[0148] Extract the vertex coordinate sequence from the updated contour boundary information of the corresponding structural part from the geometric feature module. For the main frame, obtain its updated coordinate values ​​based on the previously extracted vertex coordinate sequence. These vertex coordinate sequences are the key data for the main frame outline, reflecting its shape and size.

[0149] Step S1424: performing interpolation processing on the vertex coordinate sequence according to the point density parameter, inserting a plurality of intermediate coordinate points between adjacent vertices, and generating a target density coordinate point set.

[0150] Based on the point density parameters assigned to each structural component, the vertex coordinate sequence is interpolated. Multiple intermediate coordinate points are inserted between adjacent vertices to achieve the target point density. A larger point density parameter indicates that more intermediate coordinate points need to be inserted between adjacent vertices. An interpolation algorithm calculates the positions of the intermediate coordinate points based on the coordinate values ​​of adjacent vertices and the required point density. These inserted intermediate coordinate points are merged with the original vertex coordinate sequence to generate a set of coordinate points with the target density. This increases the number of coordinate points, improves the density of the point cloud, and more accurately represents the structure's morphology while maintaining the basic shape of the structure's outline.

[0151] Step S1425: extracting the node center coordinates and coverage area radius information from the updated spatial position coordinate information of the corresponding structural part.

[0152] Extract the node center coordinates and coverage radius information from the updated spatial position coordinates of the corresponding structural part from the geometric feature module. For the connection node part, obtain the updated node center coordinates and node coverage radius information. This information is used to determine the position and range of the connection node in space.

[0153] Step S1426: Taking the node center coordinate as the center, generate uniformly distributed coordinate points in the coverage area according to the point density parameter to generate a node area coordinate point set.

[0154] With the node center coordinate as the center, evenly distributed coordinate points are generated within the node coverage area according to the point density parameter. Based on the radius information and point density requirements of the node coverage area, the number of coordinate points to be generated within the area is determined. These coordinate points are evenly distributed within the coverage area to generate a node area coordinate point set, which can more fully display the structure and shape of the connected nodes.

[0155] Step S1427: merging the target density coordinate point set and the node area coordinate point set to generate a three-dimensional coordinate point cloud containing the coordinate points of each structural part.

[0156] The target density coordinate point set and the node region coordinate point set are merged. The coordinate points in the two sets are integrated to form a 3D coordinate point cloud containing the coordinate points of each structural component. This 3D coordinate point cloud can intuitively display the current spatial form of the metal structure. The different point densities of different structural components reflect their varying importance.

[0157] Step S143: extracting the process step identification, process influencing parameter information and corresponding structural part identification of the currently executed process step unit from the process association module of the dynamically updated digital twin model as basic data of the process state characteristics.

[0158] The relevant information of the currently executed process step unit is extracted from the process association module of the dynamically updated digital twin model as the basic data of the process state characteristics. In the previous data synchronization process, the currently executed process step unit has been determined. The process step identifier of the process step unit is extracted from the process association module, including the step sequence number information and the step type information, which can clarify which process step is currently being executed. At the same time, process influencing parameter information is extracted, such as temperature change range information, pressure action position information and processing time duration information. This information reflects the impact of the process step on the metal structure. It is also necessary to extract the corresponding structural part identifier to determine which parts of the metal structure are affected by the process step.

[0159] Step S144: performing state labeling processing on the basic data of the process state characteristics to generate process state visualization data including step name information and parameter change trends, wherein the parameter change trends are represented by time series curves.

[0160] Step S1441: extracting the step number information and step type information from the process step identifier, and generating process step annotation text in combination with the step name information.

[0161] The basic data of the process state characteristics is annotated. First, the step number and step type information are extracted from the process step identifier. Combined with the step name information determined in the previous step, the process step annotation text is generated. For example, if the step number is a certain number, the step type is welding, and the step name is a specific welding process name, this information is combined to form a clear process step annotation text to identify the currently executing process step.

[0162] Step S1442: extracting temperature variation range information, pressure action position information and processing time duration information from the process influencing parameter information.

[0163] The temperature range, pressure location, and processing time duration information are extracted from the process-influencing parameter information. These parameters are key data reflecting the process execution status. The temperature range describes the temperature variation range experienced by the metal structure during the process step, the pressure location specifies the location on the metal structure where pressure is applied, and the processing time duration specifies the duration of the process step.

[0164] Step S1443: Acquire historical parameter data of the current process step unit, wherein the historical parameter data includes temperature measured values, pressure measured values, and time accumulation values ​​at multiple time points in the past.

[0165] Obtain historical parameter data for the current process step unit. Through the data storage system, query the measured temperature, pressure, and time accumulation values ​​for the process step at multiple time points in the past. This historical parameter data is the basis for analyzing parameter change trends and can reflect the dynamic changes in parameters during process execution.

[0166] Step S1444: Compare the measured temperature value with the temperature variation range information to generate a temperature variation trend curve.

[0167] Compare and analyze the measured temperature values ​​with the temperature range information. Draw a temperature trend curve with time on the horizontal axis and the measured temperature value on the vertical axis. This curve allows you to visually see how the temperature changes over time during the current process step, whether it fluctuates within the specified temperature range, and whether the temperature trend is increasing, decreasing, or remaining stable.

[0168] Step S1445: spatially mapping the measured pressure value and the pressure action position information to generate a pressure distribution change trend curve.

[0169] The measured pressure values ​​are spatially mapped to the pressure application location information. Based on this pressure application location information, the point of pressure application on the metal structure is determined. A pressure distribution trend curve is generated, with time as the horizontal axis and the measured pressure values ​​as the vertical axis, combined with the pressure application location information. This curve not only reflects the change in pressure over time but also illustrates the distribution of pressure at different locations on the metal structure, helping to analyze the impact of pressure on the metal structure.

[0170] Step S1446: Compare the accumulated time value with the processing time duration information to generate a time progress change trend curve.

[0171] Compare the accumulated time value with the processing time duration information. Generate a time progress trend curve, with time as the horizontal axis and the proportion of the accumulated time value to the time specified in the processing time duration information as the vertical axis. This time progress trend curve allows you to intuitively see the execution progress of the current process step, whether it is proceeding according to the planned time, and whether there are any delays or advances.

[0172] Step S1447: the process step annotation text is associated with the temperature change trend curve, the pressure distribution change trend curve, and the time progress change trend curve to generate process status visualization data.

[0173] The process step annotation text is associated and stored with the temperature change trend curve, pressure distribution change trend curve, and time progress change trend curve. This information is integrated to form process status visualization data. This allows subsequent visualizations to simultaneously display the process step name and the changing trends of related parameters, providing users with a more comprehensive understanding of the process execution status.

[0174] Step S145: The structural morphology visualization data and the process status visualization data are fused to generate a visualization feature set including a spatial morphology display layer and a process status annotation layer. The spatial morphology display layer is used to present the current spatial morphology of the metal structure, and the process status annotation layer is used to annotate the process information that currently affects the current spatial morphology.

[0175] The structural morphology visualization data and the process status visualization data are fused. The structural morphology visualization data containing the three-dimensional coordinate point cloud is used as the spatial morphology display layer to present the current spatial morphology of the metal structure. The process status visualization data containing the step name information and parameter change trends is used as the process status annotation layer to annotate the process information that currently affects the current spatial morphology. The two layers of data are integrated through a fusion algorithm, so that while displaying the spatial morphology of the metal structure, the currently executed process steps and the related process parameter change trends can be annotated. For example, on the metal structure displayed by the three-dimensional coordinate point cloud, the name of the current process step and the corresponding parameter change curve are displayed through the set annotation method, allowing users to intuitively see the relationship between the process and the structural morphology.

[0176] Step S150: generating visual presentation content based on the visual feature set, and outputting the visual presentation content to an interactive terminal for display.

[0177] Step S151: extracting a three-dimensional coordinate point cloud of a structural morphology display layer from the visualization feature set to generate a three-dimensional space visualization view, wherein the three-dimensional space visualization view supports rotation, scaling, and local magnification operations.

[0178] The 3D coordinate point cloud representing the structural morphology is extracted from the visualization feature set, and a 3D spatial visualization view is generated using 3D visualization technology. The 3D coordinate point cloud is converted into intuitive 3D graphics using a 3D rendering engine. The generated 3D spatial visualization view provides rotation, scaling, and local zooming functions. Users can rotate the view using a mouse or other interactive device to observe the spatial morphology of the metal structure from different angles; zoom in and out to adjust the view size for a more comprehensive or detailed view of the structure; and zoom in to focus on specific areas of the metal structure for detailed inspection.

[0179] Step S152: extracting the process step annotation text and each parameter change trend curve of the process state annotation layer from the visualization feature set to generate a two-dimensional parameter visualization view, wherein the two-dimensional parameter visualization view includes a time axis and a parameter value coordinate axis.

[0180] The process step annotations and parameter trend curves from the process state annotation layer are extracted from the visualization feature set to generate a 2D parameter visualization. A time axis is created with time as the horizontal axis, and a parameter value axis is created with parameter values ​​as the vertical axis. The process step annotations and parameter trend curves are plotted within this 2D coordinate system. This allows users to clearly visualize the execution sequence of process steps and the changes in parameters over time.

[0181] Step S153: performing interface layout processing on the three-dimensional space visualization view and the two-dimensional parameter visualization view to generate a multi-view interface including a main view area and an auxiliary view area.

[0182] Layout the 3D spatial visualization view and the 2D parameter visualization view. Design a multi-view interface consisting of a primary view area and an auxiliary view area. Place the 3D spatial visualization view in the primary view area as the primary display window, allowing users to intuitively visualize the spatial form of the metal structure. Place the 2D parameter visualization view in the auxiliary view area as a secondary information display window, providing users with detailed information on process parameters. Through a reasonable layout, the two views complement each other, allowing users to easily view both the structural form and process parameter information simultaneously.

[0183] Step S154: adding an interactive control component to the multi-view interface, wherein the interactive control component includes a time progress slider, a view switching button, and a parameter filter drop-down menu.

[0184] Add interactive control components to the multi-view interface. Add a time progress slider. Users can drag the slider to view process parameters and structural morphology information at different time points, understanding the dynamic changes in the processing process. Add a view switching button. Users can click the button to switch between different view modes, such as switching to different perspectives or different parameter display methods. Add a parameter filter drop-down menu. Users can select different parameter options to only display the process parameter change trend curves of interest, improving information viewing efficiency.

[0185] Step S155: Integrate the multi-view interface with the interactive control component to generate interactive visual presentation content.

[0186] Integrate the multi-view interface with the interactive control component. By associating the interactive control component with the multi-view interface, users can influence the multi-view interface's display content in real time when operating the interactive control component. As the user drags the time progress slider, the 3D spatial visualization and 2D parameter visualization are synchronized to display information at the corresponding point in time. This integration generates interactive visual presentation content, enhancing user interactivity with the visual display.

[0187] Step S156: transmitting the interactive visual presentation content to the interactive terminal, so that the interactive terminal displays the interactive visual presentation content through a graphics rendering engine.

[0188] The interactive visualization content is transmitted to an interactive terminal, such as a computer monitor or tablet computer. After receiving the visualization content, the interactive terminal uses its built-in graphics rendering engine to render and display it. The graphics rendering engine converts data such as 3D coordinate point clouds and parameter trend curves into image signals, displaying a clear and intuitive visualization interface on the screen. Users can use the interactive terminal's input devices, such as a mouse or touch screen, to operate the interactive control components to interactively view the visualization content, thereby gaining a comprehensive and in-depth understanding of the real-time status of the digital metal structure processing process.

[0189] Figure 2 A schematic diagram illustrates exemplary hardware and software components of a digital twin visualization system 100 for digital metal structure processing, provided in some embodiments of the present application, that can implement the concepts of the present application. For example, the processor 120 can be used in the digital twin visualization system 100 for digital metal structure processing and perform the functions described in the present application.

[0190] The digital twin visualization system 100 for digital metal structure processing can be a general-purpose server or a special-purpose server, both of which can be used to implement the digital twin visualization method for digital metal structure processing described herein. Although only one server is shown herein, for convenience, the functions described herein can be implemented in a distributed manner on multiple similar platforms to balance the processing load.

[0191] For example, the digital twin visualization system 100 applied to digital metal structure processing may include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and different forms of storage media 140, such as a disk, ROM, or RAM, or any combination thereof. Exemplarily, the digital twin visualization system 100 applied to digital metal structure processing may also include program instructions stored in ROM, RAM, or other types of non-temporary storage media, or any combination thereof. The method of the present application can be implemented according to these program instructions. The digital twin visualization system 100 applied to digital metal structure processing also includes an I / O interface 150 between the computer and other input and output devices.

[0192] For ease of explanation, only one processor is described in the digital twin visualization system 100 applied to digital metal structure processing. However, it should be noted that the digital twin visualization system 100 applied to digital metal structure processing in the present application may also include multiple processors, so the steps performed by one processor described in the present application may also be performed jointly or individually by multiple processors. For example, if the processor of the digital twin visualization system 100 applied to digital metal structure processing executes step A and step B, it should be understood that step A and step B may also be performed jointly by two different processors or individually in one processor. For example, the first processor executes step A, the second processor executes step B, or the first processor and the second processor execute steps A and B together.

[0193] In addition, an embodiment of the present invention also provides a readable storage medium, in which computer-executable instructions are preset. When the processor executes the computer-executable instructions, the digital twin visualization method applied to digital metal structure processing as described above is implemented.

[0194] It should be noted that in order to simplify the description of the present invention and thus help understand one or more embodiments of the invention, in the foregoing description of the embodiments of the present invention, multiple features are sometimes combined into one embodiment, figure or description thereof.

Claims

1. A digital twin visualization method for digital metal structure processing, characterized in that: The method comprises: Acquire a real-time data set of a metal structure processing process, wherein the real-time data set includes processing equipment operation status data and metal structure characteristic data; Construct a digital twin basic model corresponding to the physical processing system, the digital twin basic model including a geometric feature module and a process association module. The geometric feature module is used to represent the spatial morphological information of the metal structure, and the process association module is used to represent the mapping relationship between the processing technology and the structural characteristics. Performing data synchronization processing on the real-time data set and the digital twin basic model to generate a dynamically updated digital twin model, wherein the dynamically updated digital twin model includes real-time device operation status information and real-time structural morphology information; Performing visualization feature extraction processing on the dynamically updated digital twin model to obtain a visualization feature set including structural morphological features and process status features, wherein the structural morphological features reflect the current spatial form of the metal structure, and the process status features reflect the execution status of the processing technology; Generating visual presentation content based on the visual feature set, and outputting the visual presentation content to an interactive terminal for display; The visual feature extraction process is performed on the dynamically updated digital twin model to obtain a visual feature set including structural morphological features and process state features, including: Extracting updated contour boundary information and spatial position coordinate information of each structural part from the geometric feature module of the dynamically updated digital twin model as basic data of structural morphological features; Performing visualization conversion processing on the basic data to generate structural morphology visualization data including a three-dimensional coordinate point cloud, wherein the point density of the three-dimensional coordinate point cloud is positively correlated with the importance of the structural part; Extracting the process step identification, process influencing parameter information, and corresponding structural part identification of the currently executed process step unit from the process association module of the dynamically updated digital twin model as basic data of the process state characteristics; Performing state annotation processing on the basic data of the process state characteristics to generate process state visualization data including step name information and parameter change trends, wherein the parameter change trends are represented by time series curves; The structural morphology visualization data and the process status visualization data are fused to generate a visualization feature set including a spatial morphology display layer and a process status annotation layer. The spatial morphology display layer is used to present the current spatial morphology of the metal structure, and the process status annotation layer is used to annotate the process information that currently affects the current spatial morphology.

2. The digital twin visualization method for digital metal structure processing according to claim 1 is characterized in that: The construction of a digital twin basic model corresponding to the physical processing system includes: Acquire design drawing data of the metal structure, wherein the design drawing data includes overall structural profile information, connection node position information, and key dimensional constraint information; Constructing a geometric feature module based on the design drawing data, wherein the geometric feature module represents different components of the metal structure through a layered structure, and each layer of the structure contains contour boundary information and spatial position coordinate information of the corresponding part; Acquiring standard process data of a processing technology, wherein the standard process data includes process execution sequence information, process operation parameter information, and process quality requirement information; Building a process association module based on the standard process data, wherein the process association module represents the matching relationship between each process step and the corresponding component of the metal structure through an association relationship table, wherein the association relationship table includes a process step identifier, a corresponding structural component identifier, and process influencing parameter information; The geometric feature module and the process association module are subjected to data fusion processing to generate an initial digital twin basic model. The initial digital twin basic model realizes a bidirectional query function of geometric features and process associations through a unified data interface.

3. The digital twin visualization method for digital metal structure processing according to claim 2 is characterized in that: The step of constructing a geometric feature module based on the design drawing data includes: Performing structural decomposition processing on the design drawing data to decompose the metal structure into a main frame portion, a connection node portion, and an auxiliary support portion; Performing contour extraction processing on the main frame part to generate contour boundary information including vertex coordinate sequence and edge connection relationship; Performing position positioning processing on the connection node part, extracting node center coordinates and radius information of the node coverage area as spatial position coordinate information; Performing morphological description processing on the auxiliary support portion to generate contour boundary information including support direction vector and support length parameters; The contour boundary information and spatial position coordinate information of the main frame part, the connection node part and the auxiliary support part are stored in a hierarchical relationship to generate a geometric feature module with a hierarchical structure, wherein the hierarchical relationship includes a step-by-step refinement relationship from the overall structure to the local components; Furthermore, the process association module is constructed based on the standard process data, including: Performing step splitting processing on the standard process data to obtain a plurality of process step units arranged in chronological order, each process step unit including step name information and operation content description information; Assigning a unique process step identifier to each process step unit, wherein the process step identifier includes step sequence number information and step type information; Analyze the operation content description information of each process step unit, determine the metal structure components affected by the process step unit, and assign a corresponding structural part identifier to each process step unit. The structural part identifier corresponds one-to-one with the hierarchical structure identifier in the geometric feature module; Extracting process influencing parameter information affecting metal structural features in each process step unit, wherein the process influencing parameter information includes temperature variation range information, pressure action position information, and processing time duration information; The process step identifiers, corresponding structural part identifiers and process influencing parameter information are stored in rows to generate an association relationship table containing multiple rows of records. The association relationship table establishes data association with the geometric feature module through the structural part identifier.

4. The digital twin visualization method for digital metal structure processing according to claim 2, characterized in that: The step of performing data synchronization processing on the real-time data set and the digital twin basic model to generate a dynamically updated digital twin model includes: Analyzing and processing the processing equipment operating status data in the real-time data set to obtain the equipment's current operating mode information, equipment component motion trajectory information, and equipment energy consumption information; Collecting and processing the metal structure feature data in the real-time data set to obtain structure surface morphology information, structure connection node deformation information, and structure key position dimensional deviation information; Matching the current operation mode information of the equipment with the process step identifier in the process association module to determine the currently executed process step unit; updating the process influencing parameter information of the current process step unit in the process association module according to the motion trajectory information of the equipment component and the process influencing parameter information; According to the structural surface morphology information, structural connection node deformation information and structural key position size deviation information, updating the contour boundary information and spatial position coordinate information of the corresponding structural part in the geometric feature module; The updated geometric feature module and process association module are subjected to data fusion processing to generate a dynamically updated digital twin model that contains real-time equipment operation status information and real-time structural morphology information.

5. The digital twin visualization method for digital metal structure processing according to claim 4 is characterized in that: The updating of the contour boundary information and spatial position coordinate information of the corresponding structural part in the geometric feature module according to the structural surface morphology information, the structural connection node deformation information and the structural key position size deviation information includes: Extracting surface relief features from the surface topography information of the structure, and converting the surface relief features into vertex coordinate adjustment amounts of contour boundary information; Extracting the node displacement direction and displacement distance from the deformation information of the structural connection node, and converting the displacement direction and displacement distance into the offset of the spatial position coordinates of the connection node portion; Extracting the dimensional variation from the dimensional deviation information of the key position of the structure, and converting the dimensional variation into the side length adjustment of the outline boundary information of the main frame part or the auxiliary support part; Obtain the original contour boundary information and original spatial position coordinate information of the corresponding structural part in the geometric feature module; Superimposing the vertex coordinate adjustment amount with the vertex coordinate sequence of the original contour boundary information to generate updated contour boundary information; Superimposing the offset with the node center coordinates of the original spatial position coordinate information to generate updated spatial position coordinate information of the connection node; The side length adjustment amount is superimposed on the side length parameter of the original contour boundary information to generate updated contour boundary information of the main frame part or the auxiliary support part.

6. The digital twin visualization method for digital metal structure processing according to claim 1, characterized in that: The step of performing visualization conversion processing on the basic data to generate structural morphology visualization data including a three-dimensional coordinate point cloud includes: Determine the importance level of each structural part in the geometric feature module, wherein the importance level is determined based on the load-bearing role of the structural part in the overall structure and the sensitivity of the processing error; Assigning a corresponding point density parameter to each structural part, wherein the point density parameter is positively correlated with the importance level; Extracting a vertex coordinate sequence from the updated contour boundary information of the corresponding structure part; interpolating the vertex coordinate sequence according to the point density parameter, inserting a plurality of intermediate coordinate points between adjacent vertices to generate a target density coordinate point set; Extracting node center coordinates and coverage area radius information from the updated spatial position coordinate information of the corresponding structural part; Taking the node center coordinate as the center, generating uniformly distributed coordinate points in the coverage area according to the point density parameter to generate a node area coordinate point set; The target density coordinate point set and the node area coordinate point set are merged to generate a three-dimensional coordinate point cloud containing the coordinate points of each structural part.

7. The digital twin visualization method for digital metal structure processing according to claim 1, characterized in that: The step of performing state annotation processing on the basic data of the process state characteristics to generate process state visualization data including step name information and parameter change trends includes: Extracting step number information and step type information from the process step identifier, and combining the step name information to generate a process step annotation text; extracting temperature variation range information, pressure action position information and processing time duration information from the process influencing parameter information; Acquire historical parameter data of the current process step unit, wherein the historical parameter data includes temperature measured values, pressure measured values, and time accumulated values ​​at multiple time points in the past; Comparing the measured temperature value with the temperature variation range information to generate a temperature variation trend curve; Performing spatial mapping of the measured pressure value and the pressure action position information to generate a pressure distribution change trend curve; Comparing the accumulated time value with the processing time duration information to generate a time progress change trend curve; The process step annotation text is associated with the temperature change trend curve, the pressure distribution change trend curve, and the time progress change trend curve to store and generate process status visualization data.

8. The digital twin visualization method for digital metal structure processing according to claim 1, characterized in that: Generating visual presentation content based on the visual feature set, and outputting the visual presentation content to an interactive terminal for display, includes: Extracting a three-dimensional coordinate point cloud of a structural morphology display layer from the visualization feature set to generate a three-dimensional space visualization view, wherein the three-dimensional space visualization view supports rotation, scaling, and local magnification operations; Extracting the process step annotation text and the parameter change trend curve of the process state annotation layer from the visualization feature set to generate a two-dimensional parameter visualization view, wherein the two-dimensional parameter visualization view includes a time axis and a parameter value coordinate axis; Performing interface layout processing on the three-dimensional space visualization view and the two-dimensional parameter visualization view to generate a multi-view interface including a main view area and an auxiliary view area; Adding an interactive control component to the multi-view interface, wherein the interactive control component includes a time progress slider, a view switching button, and a parameter filter drop-down menu; Integrate the multi-view interface with the interactive control component to generate interactive visual presentation content; The interactive visual presentation content is transmitted to an interactive terminal, so that the interactive terminal displays the interactive visual presentation content through a graphics rendering engine.

9. A digital twin visualization system for digital metal structure processing, characterized in that: It includes a processor and a memory, the memory is connected to the processor, the memory is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the memory to implement the digital twin visualization method applied to digital metal structure processing as described in any one of claims 1 to 8.

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