A digital-twin-based automobile component die-casting design method, device and medium

Abstract

The application discloses a kind of based on digital twinning automobile component die casting design method, equipment and medium, it is related to die casting design technical field, including: reading three-dimensional design model, mould cavity model and historical trial production detection record, establish die casting feature mapping table, generate automobile component die casting design digital twin object;Current die casting defect risk area and risk formation path record are generated, historical position deviation data are collected, simulation deviation vector is calculated, and calibrated die casting defect risk area is generated;Register pending attribution risk area, calculate overlap ownership and path overlap ownership, determine the design feature where defect is and defect cause design feature, generate the cause separation record or the cause coincidence record where it is;Generation revision task list, determine specific revision object, generate die casting adaptation automobile component design version and digital twin write-back record, to improve die casting design revision pertinence and version reinspection consistency.

Description

Technical Field

[0001] This invention relates to the field of die casting design technology, and in particular to a method, equipment and medium for die casting design of automotive parts based on digital twins. Background Technology

[0002] Die-casting design of automotive parts is typically based on 3D design models and mold cavity models. It combines material grade, gate location, overflow and venting location, cooling channel location, and demolding direction to conduct process adaptation analysis. In conventional methods, designers identify risks of porosity, air entrapment, cold shuts, and deformation through filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis. Based on the results of trial production and testing, structural parameters or die-casting process boundary conditions are iteratively modified.

[0003] However, conventional methods still have room for improvement in handling risk areas. On the one hand, the historical spatial deviation between the simulated risk center location and the trial production defect center location often relies on design experience for correction, and there may still be corresponding deviations between the die casting defect risk area in the current design version and the actual trial production defect location. On the other hand, conventional methods often determine the correction location based on the location of the defect, without fully tracing the risk formation location in the processes of feeding, filling, venting, cooling, and demolding, which can easily lead to inconsistencies between the correction object and the actual cause. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a digital twin-based die-casting design method for automotive parts to solve the problems of inaccurate correspondence between simulation risk areas and trial production defect locations, as well as the inability to distinguish between defect locations and defect causes in existing technologies.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, this invention provides a digital twin-based method for die-casting automotive components, comprising: reading a 3D design model, a mold cavity model, and historical trial production and testing records; unifying the die-casting design coordinate system; extracting automotive component design features; generating a die-casting simulation mesh; establishing a die-casting feature mapping table; and generating a digital twin object for the automotive component die-casting design. Based on the digital twin object, it performs filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis to generate current die-casting defect risk areas and risk formation path records, collects historical position deviation data, calculates simulation deviation vectors, and generates calibrated die-casting defect risk areas. The system records the risk areas and risk formation paths of die casting defects, as well as the die casting feature mapping table. It registers the risk areas to be attributed, calculates the overlap and path overlap values, determines the design features where the defects are located and the design features that cause the defects, and generates separate or coincident records of the causes. It reads the design feature records of the causes of defects, combines the separate and coincident records of the causes, generates a correction task list, registers the objects to be corrected and protected, determines the specific objects to be corrected, generates correction values ​​for structural parameters and correction values ​​for die casting process boundary conditions, writes back and verifies the corrected automotive component design version, and generates a die casting-compatible automotive component design version and a digital twin write-back record.

[0007] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the extraction of automotive component design features includes: reading the 3D design model, mold cavity model, and historical trial production inspection records; analyzing the 3D design boundary, cavity boundary, and historical trial production inspection content to generate 3D design boundary data, cavity boundary data, historical trial production inspection data, and installation connection area; constructing a die-casting design coordinate system based on the installation connection area, connection hole center, and demolding direction; converting the 3D design model, mold cavity model, and historical trial production inspection data to the die-casting design coordinate system to generate coordinate transformation records; reading the 3D design boundary data; extracting automotive component design features according to closed boundaries, adjacent surface connection relationships, and structural uses to generate an automotive component design feature list.

[0008] As a preferred embodiment of the automotive component die-casting design method based on digital twins described in this invention, the step of establishing a die-casting feature mapping table and generating a digital twin object for automotive component die-casting design includes: generating a die-casting simulation mesh based on a 3D design model and a mold cavity model; establishing a correspondence between automotive component design features and cavity areas and die-casting simulation mesh areas based on an automotive component design feature list and cavity boundary data; generating corresponding records for design feature cavities and design feature meshes; generating historical trial production inspection area records based on historical trial production inspection data, corresponding records for design feature meshes, and coordinate transformation records; and generating a die-casting feature mapping table and a digital twin object for automotive component die-casting design by combining the automotive component design feature list, corresponding records for design feature cavities, and corresponding records for design feature meshes.

[0009] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the step of generating the current die-casting defect risk area and risk formation path record includes: based on the digital twin object of the automotive component die-casting design, performing filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis to generate simulation analysis results; based on the simulation analysis results, identifying porosity risk areas, air entrapment risk areas, cold shut risk areas, and deformation deviation risk areas, registering the defect type, risk area center location, belonging die-casting simulation grid area, and belonging historical trial production detection area to generate the current die-casting defect risk area; based on the current die-casting defect risk area and simulation analysis results, tracing back along the feeding connection relationship, the area traversed by the molten metal front, the connected grid area obtained from the venting path analysis, the cooling channel influence area, and the demolding direction related area, to the feeding source direction, gate location, overflow venting location, cooling channel influence area direction, and demolding direction related area direction to generate a risk formation path record.

[0010] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the generation of the calibrated die-casting defect risk area includes: based on the current die-casting defect risk area, the die-casting feature mapping table, and historical trial production inspection area records, collecting the trial defect center position and simulation risk center position of the same defect type within the same historical trial production inspection area to generate historical position deviation data; based on the historical position deviation data, calculating the simulation deviation vector, applying the simulation deviation vector to the current die-casting defect risk area to generate the calibrated die-casting defect risk area, and generating an uncalibrated risk area for the current die-casting defect risk area lacking historical position deviation data.

[0011] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the generation of the cause separation record or cause overlap record includes: reading the calibrated die-casting defect risk area, uncalibrated risk area, risk formation path record, and die-casting feature mapping table; registering the risk areas to be attributed according to the defect type, risk area center location, historical trial production inspection area, and die-casting simulation grid area; generating the risk areas to be attributed; based on the risk areas to be attributed and the spatial boundary of automotive component design features, screening automotive component design features that have spatial intersection, forming a candidate design feature set, calculating the overlap attribution value, determining the design feature where the defect is located, and generating the design feature record where the defect is located; according to The system records the risk regions to be attributed and the risk formation paths. It reads the die-casting simulation mesh regions traversed by the risk formation paths and converts them into automotive component design features through a die-casting feature mapping table, generating a set of candidate design features for causes. Based on the set of candidate design features for causes and the risk formation path records, it calculates the path overlap attribution value and determines the defect cause design features according to the defect types corresponding to the porosity risk region, air entrapment risk region, cold shut risk region, and deformation deviation risk region, generating a record of defect cause design features. Based on the design feature record where the defect is located and the design feature record of defect cause, it compares the design feature where the defect is located and the design feature record of defect cause, generating a record of separation of causes or a record of overlap of causes, and writes it into the digital twin object of automotive component die-casting design.

[0012] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the step of registering the correction protection object and the correction object, and determining the specific correction object includes: reading the defect cause design feature record, the cause separation record, and the cause coincidence record; extracting the defect type, risk formation path, the design feature where the defect is located, and the defect cause design feature; generating a correction task list; registering the assembly reference surface, connection hole position, stress connection area, and tolerance control surface of the design feature where the defect is located in the correction task list; generating the correction protection object; and determining the defect cause design feature as the correction object; and determining the structural parameters or die-casting process boundary conditions based on the correction object, defect type, risk formation path record, and die-casting feature mapping table; and generating the specific correction object.

[0013] As a preferred embodiment of the digital twin-based automotive component die-casting design method of the present invention, the generation of the die-casting-adapted automotive component design version and the digital twin write-back record includes: based on the specific correction object, distinguishing between structural parameter correction and die-casting process boundary condition correction; generating structural parameter correction values ​​by referring to the design feature set; generating die-casting process boundary condition correction values ​​by using the risk formation path and adjacent cavity regions; writing the structural parameter correction values ​​and die-casting process boundary condition correction values ​​into the automotive component design version to be written back, thereby generating the corrected automotive component design version; re-performing simulation calibration and defect attribution on the corrected automotive component design version; comparing the defect cause design feature records before and after correction; and generating the die-casting-adapted automotive component design version and the digital twin write-back record.

[0014] In a second aspect, the present invention provides a computer device including a memory and a processor, the memory storing a computer program, wherein the computer program, when executed by the processor, implements any step of the digital twin-based automotive component die-casting design method described in the first aspect of the present invention.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements any step of the digital twin-based automotive component die-casting design method described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: by collecting historical position deviation data and calculating simulation deviation vectors, a calibrated die-casting defect risk area is generated, providing traceable position calibration basis for the porosity risk area, air entrapment risk area, cold shut risk area, and deformation deviation risk area; by combining the risk formation path record and the die-casting feature mapping table, the design features where the defect is located and the design features that cause the defect are determined respectively, providing an attribution basis for determining the correction object and registering the correction protection object, thereby improving the pertinence of die-casting design correction and the consistency of version verification. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a digital twin-based die-casting design method for automotive parts.

[0019] Figure 2 A flowchart for calibrating the risk area of ​​die casting defects.

[0020] Figure 3 A flowchart for performing defect attribution.

[0021] Figure 4 A flowchart for rewriting and retesting the design version of automotive components.

[0022] Figure 5 Calibrate the risk area map.

[0023] Figure 6 To rewrite and verify the risk map. Detailed Implementation

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0025] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0027] Reference Figures 1-6 As one embodiment of the present invention, this embodiment provides a method for die-casting automotive components based on digital twins, comprising the following steps: S1. Read the 3D design model, mold cavity model, and historical trial production and testing records, unify the die casting design coordinate system, extract the design features of automotive parts, generate a die casting simulation mesh, establish a die casting feature mapping table, and generate a digital twin object of automotive part die casting design.

[0028] Read the 3D design model, mold cavity model, and historical trial production and inspection records; analyze the 3D design boundary, cavity boundary, and historical trial production and inspection content; and generate 3D design boundary data, cavity boundary data, historical trial production and inspection data, and installation and connection area.

[0029] Based on the installation connection area, the center of the connection hole, and the demolding direction, a die-casting design coordinate system is constructed. The three-dimensional design model, mold cavity model, and historical trial production and testing data are converted to the die-casting design coordinate system, and a coordinate transformation record is generated.

[0030] Furthermore, the 3D design model and material grade of the automotive component to be designed are read, and the solid boundaries, curved surface boundaries, hole boundaries, stiffener boundaries, boss boundaries, mounting ear boundaries, thickness transition zone boundaries, corner fillet boundaries, weight reduction hole boundaries, and local draft surface boundaries in the 3D design model are analyzed to generate 3D design boundary data; based on the mounting ear boundaries and hole boundaries, the mounting connection area is generated.

[0031] Read the mold cavity model, analyze the cavity surface, parting boundary, gate location, overflow and venting location, cooling channel location, and demolding direction in the mold cavity model, and generate cavity boundary data.

[0032] Read historical prototype testing records, parse historical design version number, defect type, prototype defect center location, and simulation risk center location within the same historical design version, and generate historical prototype testing data.

[0033] It should be noted that when there are no historical trial production test records, empty historical trial production test data is generated. Empty historical trial production test data only retains the location where subsequent trial production test results are written.

[0034] Furthermore, the installation connection area in the 3D design boundary data is read to identify the installation plane used for the installation connection between the automotive component and the body or assembly; when there are multiple installation planes, the installation plane with the largest area is selected as the assembly reference plane.

[0035] Extract all the centers of the connecting holes on the assembly reference surface, calculate the distance between any two connecting hole centers, select the two connecting hole centers with the largest distance, and take the direction of the line connecting the two connecting hole centers as the first direction of the die casting design coordinate system.

[0036] When there are fewer than two connection hole centers on the assembly reference surface, read all connection hole centers within the installation connection area; when there are still fewer than two connection hole centers within the installation connection area, read the outer contour boundary of the assembly reference surface, select the two boundary points with the largest distance in the outer contour boundary, and take the direction of the line connecting the two boundary points as the first direction of the die casting design coordinate system.

[0037] Read the demolding direction in the mold cavity model, project the demolding direction onto a plane perpendicular to the first direction, and obtain the third direction; when the demolding direction is parallel to the first direction, select the normal direction of the assembly reference plane as the third direction.

[0038] The second direction is generated by performing a cross product operation on the first direction vector and the third direction vector. The first direction, the second direction and the third direction are then orthogonally normalized to form the die-casting design coordinate system.

[0039] All 3D design models, mold cavity models, and historical trial production and testing data are converted into the die casting design coordinate system, generating coordinate transformation records. The coordinate transformation records include the model source, coordinates before transformation, coordinates after transformation, and corresponding data types.

[0040] Read the 3D design boundary data, extract the design features of automotive components according to the closed boundary, the connection relationship between adjacent surfaces and the structural purpose, and generate a list of automotive component design features.

[0041] Based on the 3D design model and mold cavity model, a die-casting simulation mesh is generated. Based on the automotive component design feature list and cavity boundary data, the correspondence between automotive component design features and cavity regions and die-casting simulation mesh regions is established, generating corresponding records for design feature cavities and design feature meshes.

[0042] Based on historical trial production and testing data, corresponding records of design feature grids, and coordinate transformation records, historical trial production and testing area records are generated. Combined with the automotive component design feature list, corresponding records of design feature cavities, and corresponding records of design feature grids, a die casting feature mapping table and a digital twin object of automotive component die casting design are generated.

[0043] Furthermore, based on the die-casting design coordinate system, the three-dimensional design boundary data is read, and the design features of automotive components are extracted according to the closed boundary, the connection relationship between adjacent surfaces, and the structural purpose.

[0044] Among them, the design features of automotive components include wall panels, reinforcing ribs, mounting ears, post holes, bosses, corner fillets, thickness transition zones, weight reduction hole boundaries, and local draft surfaces.

[0045] Register the design feature name, design feature type, design feature spatial boundary, adjacent design features, corresponding assembly reference surface, corresponding connection hole position, corresponding stress connection area and corresponding tolerance control surface for each automotive component design feature, and generate an automotive component design feature list.

[0046] Furthermore, based on the list of automotive component design features, the cavity boundary data is read, and the spatial boundary of each automotive component design feature is projected onto the cavity surface in the mold cavity model that fits with the spatial boundary of the automotive component design features.

[0047] Specifically, the wall panel corresponds to the wall panel cavity area, the reinforcing rib corresponds to the reinforcing rib cavity area, the mounting ear corresponds to the mounting ear cavity area, the hole post corresponds to the hole post cavity area, the boss corresponds to the boss cavity area, the corner fillet corresponds to the corner fillet cavity area, the thickness transition area corresponds to the thickness transition cavity area, the weight reduction hole boundary corresponds to the weight reduction hole cavity area, and the local draft surface corresponds to the draft mold cavity area.

[0048] For each cavity area, register the corresponding automotive component design features, adjacent cavity areas, associated gate locations, associated overflow and vent locations, associated cooling channel locations, and associated demolding directions to generate a record corresponding to the design feature cavity.

[0049] Furthermore, based on the 3D design model and the mold cavity model, a die-casting simulation mesh is generated in the die-casting design coordinate system.

[0050] The die-casting simulation mesh covers the solid area of ​​the automotive part and the cavity area of ​​the mold, preserving the mesh center position, mesh boundary, and mesh adjacency relationship.

[0051] Read the center position, boundary, and design feature space boundary of each grid. Attach the grids whose center position is within the design feature space boundary of the vehicle component and whose boundaries do not cross the design feature space boundaries of other vehicle components to the corresponding vehicle component design feature. Attach the grids whose boundaries intersect with the design feature space boundaries of two vehicle components to the corresponding boundary area. Simultaneously register two adjacent vehicle component design features to generate corresponding records for the design feature grids.

[0052] It should be noted that the corresponding record for the design feature grid includes the design feature name, design feature type, internal grid area, boundary grid area, and adjacent grid area.

[0053] Furthermore, based on historical trial production and testing data, the center location of the trial production defect and the center location of the simulation risk in the same historical design version are read. According to the coordinate transformation record, the center location of the trial production defect and the center location of the simulation risk in the same historical design version are transformed into the die casting design coordinate system.

[0054] Read the grid to which the center of the defect in the prototype belongs after conversion, and determine the design feature of the automotive component and the historical prototype inspection area according to the corresponding record of the design feature grid.

[0055] Read the grid to which the simulated risk center location belongs after conversion, and determine the corresponding automotive component design features and corresponding historical prototype testing areas based on the corresponding records of the design feature grid.

[0056] Write the same historical design version number, the same defect type, the center location of the prototype defect, and the center location of the simulation risk into the same historical prototype inspection area to generate a historical prototype inspection area record; when the historical prototype inspection data is empty, generate an empty historical prototype inspection area record for each automotive component design feature, waiting for subsequent prototype inspection results to be written.

[0057] Furthermore, based on the automotive component design feature list, design feature cavity corresponding records, design feature grid corresponding records, and historical trial production inspection area records, a die casting feature mapping table is generated.

[0058] The die casting feature mapping table registers the design feature name, design feature type, design feature spatial boundary, corresponding cavity area, corresponding die casting simulation mesh area, corresponding historical trial production inspection area, corresponding defect type, trial production defect center location, simulation risk center location, gate location, overflow and venting location, cooling channel location, and demolding direction.

[0059] It should be noted that the location of the trial production defect center and the location of the simulation risk center are only written when historical trial production test data exists; the corresponding writing location is retained when historical trial production test data is empty.

[0060] Furthermore, the 3D design model, material grade, mold cavity model, gate location, overflow and venting location, cooling channel location, demolding direction, coordinate transformation record, automotive component design feature list, and die casting feature mapping table are written into the same data object to generate a digital twin object for automotive component die casting design.

[0061] It should be noted that in the digital twin object of automotive component die casting design, each automotive component design feature can be queried for its corresponding cavity area, corresponding die casting simulation grid area, and corresponding historical trial production inspection area; each historical trial production inspection area can be queried for the location of the trial production defect center and the location of the simulation risk center; each die casting simulation grid area can be queried for its own automotive component design feature and adjacent automotive component design features.

[0062] S2. Based on the digital twin object of automotive component die casting design, perform filling simulation, solidification simulation, exhaust path analysis, cooling analysis and deformation analysis, generate current die casting defect risk area and risk formation path record, collect historical position deviation data, calculate simulation deviation vector, and generate calibrated die casting defect risk area.

[0063] Based on the digital twin object of automotive component die casting design, the system performs filling simulation, solidification simulation, exhaust path analysis, cooling analysis, and deformation analysis to generate simulation analysis results.

[0064] Based on the simulation analysis results, the risk areas of porosity, air entrapment, cold shut, and deformation deviation are identified. The defect type, center location of the risk area, the die casting simulation grid area to which it belongs, and the historical trial production and inspection area to which it belongs are registered, and the current die casting defect risk area is generated.

[0065] Based on the current die-casting defect risk areas and simulation analysis results, the risk formation path record is generated by tracing back to the direction of the feeding source, gate location, overflow venting location, direction of the cooling channel influence area, and direction of the demolding direction associated with the connected mesh area obtained from the feeding connection relationship, the area through which the molten metal front passes, the connected mesh area obtained from the venting path analysis, the area affected by the cooling channel, and the direction of the demolding direction associated with the demolding direction.

[0066] Furthermore, based on the current automotive component design version, material grade, mold cavity model, gate location, overflow and venting location, cooling channel location, demolding direction, and die-casting simulation mesh area, conventional die-casting simulation functions are invoked to perform filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis, and the simulation analysis results are output. Conventional die-casting simulation functions include filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis.

[0067] The filling simulation records the die-casting simulation grid areas and filling arrival sequence that the molten metal passes through after entering the mold cavity from the gate position. It also records the filling arrival time, the molten metal front convergence position, and the molten metal front convergence state of each die-casting simulation grid area.

[0068] The solidification simulation records the solidification sequence and feeding connectivity of molten metal within the die-casting simulation grid area, and records the solidification completion time, adjacent feeding connectivity grids, and solidification end grids for each die-casting simulation grid area.

[0069] The exhaust path analysis records the connected grid region pointing from the molten metal front to the overflow exhaust position after reaching the end region, and records the connectivity between the gas stagnation grid region and the overflow exhaust position.

[0070] The cooling analysis records the cavity area and die-casting simulation mesh area affected by the location of the cooling channel, and records the cooling sequence relationship of each die-casting simulation mesh area within the area affected by the cooling channel.

[0071] Deformation analysis records the demolding direction-related area and the deformation-out-of-tolerance area, and records the offset direction, offset position, and deformation offset amount of the deformation-out-of-tolerance area in the die-casting design coordinate system. When the deformation offset amount exceeds the form and position tolerance in the automotive part design drawings, the allowable offset of the assembly datum surface, or the allowable offset amount in the historical trial production inspection specifications, the corresponding die-casting simulation mesh area is registered as a deformation-out-of-tolerance area. When the deformation offset amount is equal to the form and position tolerance in the automotive part design drawings, the allowable offset of the assembly datum surface, or the allowable offset amount in the historical trial production inspection specifications, the corresponding die-casting simulation mesh area is not registered as a deformation-out-of-tolerance area.

[0072] Based on the simulation analysis results output from filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis, the current die-casting defect risk area is generated.

[0073] Specifically, in the solidification simulation output, the grid region that is disconnected from the adjacent feeding connected grid in the solidification end grid is registered as a porosity risk region; the grid region where the gas stagnation is surrounded by the molten metal front and cannot be connected to the overflow venting position, which is jointly output by the filling simulation and the venting path analysis, is registered as a gas entrapment risk region; the grid region where the two molten metal fronts in the filling simulation converge in the same grid region but do not form a continuous filling connection is registered as a cold shut risk region; and the grid region where the form and position shift occurs in the demolding direction associated region, which is output by the deformation analysis, is registered as a deformation deviation risk region.

[0074] Currently, die-casting defect risk areas are registered according to defect type, risk area center location, die-casting simulation grid area to which they belong, and historical trial production and testing area to which they belong.

[0075] The center location of the risk area is determined by the geometric center of all grid centers within the current die-casting defect risk area; when the current die-casting defect risk area is formed by a single grid, the center location of the risk area is the center location of that single grid.

[0076] Furthermore, based on the current die-casting defect risk area, a risk formation path record is generated.

[0077] Specifically, for the porosity risk region, along the feeding connection relationship obtained from the solidification simulation, the continuous die casting simulation mesh region is registered as the solidification feeding path by tracing back from the porosity risk region to the feeding source direction; the starting direction of the solidification feeding path is the feeding source direction, and the ending direction of the solidification feeding path is the porosity risk region direction.

[0078] For areas with high risk of entrapment, the molten metal front obtained from the filling simulation is traced back to the gate position, and the continuous die casting simulation grid area is registered as the filling path; the connected grid area obtained from the venting path analysis is traced back to the overflow venting position, and the continuous die casting simulation grid area is registered as the venting path; the starting direction of the filling path is the gate position direction, and the starting direction of the venting path is the overflow venting position direction.

[0079] For areas with cold shut risk, the molten metal front obtained from the filling simulation is traced back to the gate position, and the continuous die casting simulation mesh area is registered as the filling path; the starting direction of the filling path corresponding to the cold shut risk area is the direction of the gate position.

[0080] For areas with deformation exceeding tolerance risk, read the cooling channel influence area obtained from cooling analysis and the demolding direction related area obtained from deformation analysis, and register the cooling channel influence area and the demolding direction related area as deformation risk formation paths; the starting direction of the deformation risk formation path includes the direction of the cooling channel influence area and the direction of the demolding direction related area.

[0081] Risk formation path records are registered according to defect type, historical trial production and testing area, grid area traversed by the path, and starting direction of the path.

[0082] Based on the current die-casting defect risk area, the die-casting feature mapping table, and historical trial production inspection area records, the trial production defect center location and simulation risk center location of the same defect type within the same historical trial production inspection area are collected to generate historical position deviation data.

[0083] Based on historical position deviation data, a simulation deviation vector is calculated and applied to the current die-casting defect risk area to generate a calibrated die-casting defect risk area. For the current die-casting defect risk area lacking historical position deviation data, an uncalibrated risk area is generated.

[0084] Furthermore, the center location of the current die-casting defect risk area is read, and the historical trial production inspection area to which the center location of the risk area belongs is determined according to the die-casting feature mapping table.

[0085] When the current die-casting defect risk area covers multiple historical trial production and inspection areas, the spatial intersection range between the current die-casting defect risk area and each historical trial production and inspection area is calculated, and the historical trial production and inspection area with the largest spatial intersection range is selected as the historical trial production and inspection area to which the current die-casting defect risk area belongs.

[0086] It should be noted that the spatial intersection range is calculated by volume in the porosity risk area, air entrapment risk area, and deformation deviation risk area, and by area in the cold shut risk area.

[0087] Furthermore, read historical trial production inspection records with the same defect type within the corresponding historical trial production inspection area, extract the center location of the trial production defect and the simulation risk center location in the same historical design version, and form historical position deviation data within the same historical trial production inspection area.

[0088] It should be noted that historical position deviation data are collected separately according to defect type and historical trial production inspection area. Different defect types are not mixed in the calculation, and different historical trial production inspection areas are not mixed in the calculation.

[0089] Furthermore, based on historical positional deviation data within the same historical trial production and testing area, a simulation deviation vector is calculated.

[0090] Specifically, the simulation deviation vector is represented as: ; in, Indicates the first Die-casting defect risk in the first Simulation deviation vector within a historical trial production testing area. This indicates the die-casting defect type number. Indicates the historical trial production and testing area number. This indicates the historical trial production and testing record number. Indicates the first The horizontal coordinate of the center location of the trial production defect in the historical trial production inspection record in the die casting design coordinate system. Indicates the first The longitudinal coordinate of the center location of the trial production defect in the historical trial production inspection record in the die casting design coordinate system. Indicates the first The height coordinates of the center location of the trial production defect in the die casting design coordinate system in the historical trial production inspection record. This represents the horizontal coordinate of the simulation risk center location in the die-casting design coordinate system within the same historical design version. This represents the vertical coordinate of the simulation risk center location in the die-casting design coordinate system within the same historical design version. This indicates the height coordinates of the simulation risk center location in the die-casting design coordinate system within the same historical design version.

[0091] It should be noted that when the number of historical position deviation data is odd, the median value after sorting is taken; when the number of historical position deviation data is even, the arithmetic mean of the two median values ​​after sorting is taken.

[0092] It should be noted that within the same historical trial production inspection area, there is a repeatable spatial deviation between the center position of the trial production defect of the same defect type and the center position of the simulation risk; using the median result can reduce the impact of single trial production inspection error or single simulation discrete error on the current die casting defect risk area position calibration; the unit of the simulation deviation vector is consistent with the die casting design coordinate system.

[0093] If there is no historical position deviation data within the same historical trial production and testing area, the simulation deviation vector is not calculated. The current die casting defect risk area is registered as an uncalibrated risk area, and the original position of the current die casting defect risk area is retained for subsequent processes. The uncalibrated risk area continues to retain the risk formation path record and participates in the simulation deviation vector update after the trial production and testing results are obtained.

[0094] When historical position deviation data exist within the same historical trial production and testing area, the simulation deviation vector is read to calibrate the position of the current die-casting defect risk area.

[0095] Specifically, the calibrated die-casting defect risk area is represented as follows: ; in, Indicates the first before calibration Die-casting defect risk in the first Risk areas within historical trial production and testing areas Indicates the first Die-casting defect risk in the first Calibrated die-casting defect risk areas within the historical trial production and testing areas. This indicates the location point within the risk area before calibration, and ∈ indicates that it belongs to.

[0096] It should be noted that the current die-casting defect risk area and historical position deviation data are both located in the die-casting design coordinate system. The simulation deviation vector represents the correction offset of the center position of the same type of trial defect in the same historical trial inspection area relative to the simulation risk center position. Applying the simulation deviation vector to each position point in the current die-casting defect risk area can keep the shape and size of the current die-casting defect risk area unchanged, and only correct the position of the current die-casting defect risk area in the die-casting design coordinate system.

[0097] Furthermore, the risk areas obtained according to the calibrated die-casting defect risk area formula will be registered as calibrated die-casting defect risk areas; the current die-casting defect risk areas that have not undergone position calibration will be registered as uncalibrated risk areas.

[0098] The simulation deviation vector, the calibrated die-casting defect risk area, the uncalibrated risk area, and the risk formation path record are written into the digital twin object of automotive component die-casting design.

[0099] S3. Based on the calibrated die-casting defect risk area, risk formation path record, and die-casting feature mapping table, register the risk area to be attributed, calculate the overlap attribution value and path overlap attribution value, determine the design feature where the defect is located and the design feature of the defect cause, and generate the cause separation record or the cause coincidence record.

[0100] Read the calibrated die-casting defect risk area, uncalibrated risk area, risk formation path record, and die-casting feature mapping table. Register the risk areas to be attributed according to the defect type, risk area center location, historical trial production and testing area, and die-casting simulation grid area, and generate the risk areas to be attributed.

[0101] Based on the risk region to be attributed and the spatial boundary of automotive component design features, automotive component design features that have spatial intersection are screened to form a set of candidate design features, the overlap attribution value is calculated, the design feature where the defect is located is determined, and the design feature record where the defect is located is generated.

[0102] Based on the risk region to be attributed and the risk formation path record, the die-casting simulation mesh region through which the risk formation path passes is read, converted into automotive part design features through the die-casting feature mapping table, and a set of candidate design features for causes is generated.

[0103] Furthermore, the calibrated die-casting defect risk area, uncalibrated risk area, risk formation path record, and die-casting feature mapping table are read from the digital twin object of automotive component die-casting design; the design feature name, design feature type, design feature spatial boundary, corresponding die-casting simulation mesh area, and corresponding historical trial production detection area are read from the die-casting feature mapping table.

[0104] It should be noted that each calibrated die-casting defect risk area is registered as a risk area to be attributed according to the defect type, the center location of the risk area, the historical trial production and testing area to which it belongs, and the die-casting simulation grid area to which it belongs; uncalibrated risk areas are registered as risk areas to be attributed at the same time, and the uncalibrated mark is retained; the original location of the uncalibrated risk area is used as the location basis for participating in the attribution.

[0105] Furthermore, based on the risk area to be attributed, the spatial boundary of automotive component design features within the same historical prototype testing area is read, and automotive component design features that spatially intersect with the risk area to be attributed are selected to form a set of candidate design features.

[0106] It should be noted that if the risk area to be attributed does not spatially intersect with the spatial boundary of the automotive component design feature, the die-casting simulation mesh area to which the risk area to be attributed belongs is read, and the automotive component design feature to which it belongs is found according to the die-casting feature mapping table to form the candidate design feature set. By reverse-checking the automotive component design feature through the die-casting simulation mesh area, the situation where the risk area is located in the design feature boundary area or the mesh boundary area can be handled.

[0107] Furthermore, an overlap assignment value is calculated for each automotive component design feature in the candidate design feature set.

[0108] Specifically, the overlap attribution value is represented as: ; in, Indicates the first Die-casting defect risk in the first Within the historical trial production testing area, the first Overlapping attribution values ​​of design features of individual automotive components Indicates the design feature number of an automotive component. Indicates the first The spatial region of an automotive component design feature in the die-casting design coordinate system This indicates a measurement operator, where the measurement object is a three-dimensional die-casting defect risk region. Take the volume; when the measurement object is a two-dimensional die-casting defect risk area. Take the area; when the measurement object is a linear risk formation path, Take the path length; when the measurement object is a regional risk formation path. Take the area of ​​the region. This represents the spatial intersection operation.

[0109] The design features where the defects are located are used to characterize the automotive component design features where the die-casting defect risk actually falls. Therefore, the attribution is determined by the overlap ratio between the risk area to be attributed and the spatial area of ​​the automotive component design features. The numerator represents the range of the risk area carried by the automotive component design features, and the denominator represents the range of the risk area to be attributed.

[0110] It should be noted that the overlap attribution value ranges from [0, 1]. A value of 0 indicates that there is no spatial overlap between the corresponding automotive component design feature and the currently calibrated die-casting defect risk area; a value of 1 indicates that the currently calibrated die-casting defect risk area is entirely located within the spatial area of ​​the corresponding automotive component design feature.

[0111] Furthermore, the candidate design feature set is arranged in descending order of overlap attribution value, and the automotive component design feature with the highest overlap attribution value is registered as the design feature where the defect is located; a design feature record of the defect location is formed, which includes the defect type, the calibrated die-casting defect risk area, the center location of the risk area, the design feature where the defect is located, the overlap attribution value, and the uncalibrated mark.

[0112] It should be noted that if multiple automotive component design features have the same overlapping attribution value, the center position of the risk area and the geometric center position of the spatial boundary of the automotive component design feature are read, the distance from the center position of the risk area to each geometric center position is calculated, and the automotive component design feature with the lowest distance value is registered as the design feature where the defect is located.

[0113] Furthermore, the risk formation path records corresponding to the risk area to be attributed are read.

[0114] Specifically, the solidification and feeding path is read in the porosity risk area; the filling and venting paths are read in the air entrapment risk area; the filling path is read in the cold shut risk area; and the deformation risk path is read in the deformation risk area.

[0115] Furthermore, the die-casting simulation mesh area traversed by the risk formation path is converted into the corresponding automotive component design features according to the die-casting feature mapping table, forming a set of causal candidate design features; if the die-casting simulation mesh area traversed by the risk formation path is located at the intersection of two automotive component design features, then the design features of the two adjacent automotive components are read simultaneously and added to the set of causal candidate design features.

[0116] Based on the candidate design feature set and risk formation path record, the path overlap attribution value is calculated, and the defect cause design features are determined according to the defect types corresponding to the pore risk area, air entrapment risk area, cold shut risk area and deformation deviation risk area, and defect cause design feature record is generated.

[0117] Based on the design feature record of the defect location and the design feature record of the defect cause, compare the design features of the defect location and the design features of the defect cause, generate a separate record of the cause or a record of the cause overlap, and write it into the digital twin object of the automotive component die casting design.

[0118] Furthermore, the path overlap attribution value is calculated for each automotive component design feature in the candidate design feature set.

[0119] It should be noted that when the same risk area to be attributed corresponds to two or more risk formation paths, the two or more risk formation paths will be merged and registered as the same risk formation path record, and the merged risk formation path record will be used as the risk formation path in the calculation of the path overlap attribution value.

[0120] Specifically, the path overlap attribution value is represented as: ; in, Indicates the first Die-casting defect risk in the first Within the historical trial production testing area, the first The path overlap attribution value of design features of individual automotive components Indicates the first Die-casting defect risk in the first Risk formation paths within a historical trial production testing area are used. When the risk formation path is a linear path, the path length is used; when the risk formation path is a regional path, the regional area is used.

[0121] The design features for defect formation are used to characterize the automotive component design features that pass through or constrain the risk formation path during the formation of die-casting defect risks. Therefore, the overlap ratio between the risk formation path and the spatial region of the automotive component design features is used to determine the attribution. The numerator represents the range of the automotive component design features participating in the risk formation path, and the denominator represents the complete range of the risk formation path.

[0122] It should be noted that the path overlap attribution value ranges from [0, 1]. A value of 0 indicates that the corresponding automotive component design feature does not overlap with the risk formation path corresponding to the current die-casting defect risk area; a value of 1 indicates that all risk formation paths corresponding to the current die-casting defect risk area are located within the spatial area of ​​the corresponding automotive component design feature.

[0123] Furthermore, the set of candidate design features for cause is arranged from high to low according to the path overlap attribution value, and the automotive component design feature with the highest path overlap attribution value is registered as the candidate design feature for defect cause.

[0124] It should be noted that if multiple automotive component design features have the same path overlap attribution value, then according to the path starting direction and the order of the grid areas traversed by the path in the risk formation path record, the grid areas traversed by the path are arranged along the path starting direction to the risk area to be attributed, and the automotive component design feature that first overlaps with the risk formation path is selected and registered as a candidate design feature for defect cause.

[0125] Furthermore, design features for determining the causes of defects are determined according to the type of defect.

[0126] Specifically, in the porosity risk region, candidate design features for defect causation along the solidification feeding path are registered as design features for defect causation.

[0127] The candidate design features for defect causes are read from the filling path and the exhaust path of the air-entraining risk area. The length of the connecting path from the air-entraining risk area to the starting direction of the filling path and the length of the connecting path from the air-entraining risk area to the starting direction of the exhaust path are calculated. The automotive component design feature corresponding to the path with the lowest connecting path length is registered as the design feature for defect causes.

[0128] It should be noted that when the connected path length values ​​are the same, the design feature of the automotive component corresponding to the exhaust path is registered as the defect cause design feature; the connected path length is determined by connecting the paths in the risk formation path record sequentially through the center of the grid area, and the unit of connected path length is consistent with the die casting design coordinate system; the connected path length is used to distinguish whether the entrapment risk area is closer to the filling and surrounding source or closer to the exhaust obstruction source.

[0129] In the cold shut risk area, candidate design features for defect causes along the filling path are registered as design features for defect causes.

[0130] The deformation out-of-tolerance risk area registers the candidate design features for the cause of defects on the path to the formation of deformation risk as design features for the cause of defects.

[0131] Furthermore, read the design feature record where the defect is located and the design feature record of the cause of the defect, and compare the design feature where the defect is located and the design feature of the cause of the defect.

[0132] When the design feature where the defect is located and the design feature that causes the defect do not belong to the same automotive component design feature, a cause separation record is generated. The cause separation record includes the defect type, the calibrated die-casting defect risk area, the center location of the risk area, the historical trial production inspection area, the risk formation path, the design feature where the defect is located, the design feature that causes the defect, the overlap assignment value, the path overlap assignment value, and the uncalibrated mark.

[0133] When the design feature where the defect is located and the design feature that causes the defect belong to the same automotive component design feature, a cause overlap record is generated. The cause overlap record includes the defect type, the calibrated die-casting defect risk area, the center location of the risk area, the historical trial production inspection area, the risk formation path, the design feature where the defect is located, the design feature that causes the defect, the overlap assignment value, the path overlap assignment value, and the uncalibrated mark.

[0134] Record the design features where the defect is located, the design features that cause the defect, the separation record of the cause, and the overlap record of the cause in the digital twin object of the die casting design of the automotive component.

[0135] S4. Read the defect cause design feature record, combine the cause separation record and the cause overlap record, generate a correction task list, register the correction protection object and the correction object, determine the specific correction object, generate structural parameter correction value and die casting process boundary condition correction value, write back and verify the corrected automotive part design version, and generate the die casting adapted automotive part design version and digital twin write back record.

[0136] Read the defect cause design feature record, the cause separation record, and the cause overlap record, extract the defect type, risk formation path, the design feature where the defect is located, and the defect cause design feature, and generate a correction task list.

[0137] Register the assembly reference surface, connection hole position, stress connection area and tolerance control surface of the design feature where the defect is located in the correction task list, generate the correction protection object, and determine the design feature that causes the defect as the correction object.

[0138] Furthermore, the cause separation record is read, and the defect type, calibrated die-casting defect risk area, risk area center location, historical trial production inspection area, risk formation path, design features of the defect, defect cause design features, overlap assignment value, path overlap assignment value, and uncalibrated mark are extracted to generate a cause priority correction task.

[0139] Read the corresponding cause overlap record, extract the defect type, calibrated die-casting defect risk area, risk area center location, historical trial production inspection area, risk formation path, design features where the defect is located, defect cause design features, overlap assignment value, path overlap assignment value, and uncalibrated mark, and generate an overlap linkage correction task.

[0140] Read the defect type, its historical prototype testing area, path overlap value, risk area center location, and uncalibrated marker from the cause-priority correction task and overlapping linkage correction task. Based on the historical prototype testing area records, count the number of historical prototype testing records of the same defect type in the same historical prototype testing area, and generate the number of defect type records.

[0141] The cause-priority correction tasks and overlapping linkage correction tasks are arranged according to the uncalibrated marker, the number of defect type records, the path overlap attribution value, and the center location of the risk area to generate a correction task list.

[0142] Specifically, correction tasks without uncalibrated markers are scheduled before those with uncalibrated markers; under the same uncalibrated marker state, they are arranged from high to low according to the number of defect type records; when the number of defect type records is the same, they are arranged from high to low according to the path overlap attribution value; when the path overlap attribution values ​​are the same, they are arranged in sequence according to the horizontal coordinate, vertical coordinate, and height coordinate of the risk area center location in the die-casting design coordinate system.

[0143] Furthermore, read the cause-priority correction tasks in the correction task list, register the assembly reference surface, corresponding connection hole position, corresponding stress connection area and corresponding tolerance control surface corresponding to the design feature where the defect is located as correction protection objects, and register the design feature that causes the defect as correction objects.

[0144] Furthermore, read the overlapping linkage correction tasks in the correction task list, register the assembly reference surface, corresponding connection hole position, corresponding stress connection area and corresponding tolerance control surface corresponding to the design feature where the defect is located as correction protection objects, and register the structural parameters of the design feature of the defect cause and the die casting process boundary conditions corresponding to the design feature of the defect cause as correction objects.

[0145] It should be noted that the boundary conditions of the die casting process include the gate position, overflow and venting position, cooling channel position, and demolding direction associated area in the record corresponding to the design feature cavity.

[0146] Based on the object to be corrected, the defect type, the risk formation path record, and the die casting feature mapping table, determine the structural parameters or die casting process boundary conditions, and generate specific objects to be corrected.

[0147] Based on the specific object to be corrected, structural parameter correction and die-casting process boundary condition correction are distinguished. By referring to the design feature set, structural parameter correction values ​​are generated. By using the risk formation path and adjacent cavity regions, die-casting process boundary condition correction values ​​are generated. The structural parameter correction values ​​and die-casting process boundary condition correction values ​​are written into the automotive component design version to be written back, thus generating the corrected automotive component design version.

[0148] The simulation calibration and defect attribution are re-performed on the revised automotive component design version. The defect cause design feature records before and after the revision are compared to generate a die-casting adapted automotive component design version and a digital twin write-back record.

[0149] Furthermore, the specific object to be corrected is determined by reading the correction object, defect type, risk formation path, and die-casting feature mapping table.

[0150] When the defect type is a porosity risk area, if the defect cause design feature is a thick-thin transition zone, the transition length corresponding to the boundary of the thick-thin transition zone shall be registered as a specific correction object; if the defect cause design feature is a reinforcing rib, the transition radius of the reinforcing rib root corresponding to the boundary of the reinforcing rib shall be registered as a specific correction object; if the defect cause design feature is a hole column, the transition radius of the hole column root corresponding to the boundary of the hole column shall be registered as a specific correction object; if the risk formation path passes through the cavity area corresponding to the location of the cooling channel, the location of the cooling channel shall be registered as a specific correction object.

[0151] When the defect type is a gas entrapment risk area, if the defect cause design feature is a corner fillet, the corner fillet radius corresponding to the corner fillet boundary shall be registered as a specific correction object; if the risk formation path passes through the cavity area corresponding to the overflow venting position, the overflow venting position shall be registered as a specific correction object; if the risk formation path passes through the cavity area corresponding to the gate position, the gate position shall be registered as a specific correction object.

[0152] When the defect type is a cold shut risk area, if the defect cause design feature is a wall panel or a thickness transition zone, register the wall thickness transition boundary formed by the wall panel boundary and the thickness transition zone boundary as a specific correction object; if the defect cause design feature is a corner fillet, register the corner fillet radius as a specific correction object; if the defect cause design feature is a local draft surface, register the included angle of the local draft surface relative to the demolding direction as a specific correction object; if the risk formation path passes through the cavity area corresponding to the gate location, register the gate location as a specific correction object.

[0153] When the defect type is a deformation excess risk area, if the defect cause design feature is a wall panel or a thickness transition zone, the wall thickness gradient formed by the wall panel boundary and the thickness transition zone boundary should be registered as a specific correction object; if the defect cause design feature is a reinforcing rib, the reinforcing rib centerline corresponding to the reinforcing rib boundary and the spacing between adjacent reinforcing ribs should be registered as specific correction objects; if the risk formation path passes through the cavity area corresponding to the cooling channel location, the cooling channel location should be registered as a specific correction object; if the risk formation path passes through the demolding direction associated area, the local draft surface within the demolding direction associated area should be registered as a specific correction object.

[0154] Furthermore, the specific correction object and the die-casting feature mapping table are read to generate structural parameter correction values.

[0155] When the specific object to be corrected belongs to a structural parameter, the design features centered on the defect cause design features are read from the automotive component design feature list. Automotive component design features that are not registered as the same type of defect cause design features, do not contain correction protection objects, and have the same structural parameter are selected to generate a reference design feature set.

[0156] Extract structural parameters with the same name from the reference design feature set, arrange them in ascending order of value, and use the median result as the structural parameter correction value.

[0157] For example, when the specific object to be corrected is the transition radius at the root of the reinforcing rib, the transition radius at the root of the reinforcing rib is extracted from the reference design feature set and the median result is taken; when the specific object to be corrected is the angle between the local draft surface and the demolding direction, the same angle is extracted from the reference design feature set and the median result is taken.

[0158] It should be noted that when the reference design feature set is empty, the automotive component design features passed through are read along the path from the starting direction of the risk formation path to the center of the risk area. The first automotive component design feature that is not registered as a design feature of the same type of defect cause, does not contain a correction protection object, and has the same structural parameter is selected. The selected same structural parameter is used as the structural parameter correction value.

[0159] If the same structural parameter is still not obtained, retain the original value of the structural parameter and transfer the same correction task to the die casting process boundary condition correction; write the original value of the structural parameter, the corrected value of the structural parameter, and the reference design feature set into the genetic design feature correction record.

[0160] Furthermore, the system reads the specific correction object, the risk formation path, the corresponding record of the design feature cavity, and the corresponding record of the design feature mesh to generate the correction value of the die casting process boundary conditions.

[0161] Specifically, when the specific correction target is the gate location, the grid area passed through by the path is read from the starting direction of the filling path to the center of the risk area. Adjacent cavity areas are found by corresponding records of design feature grids and design feature cavities. Adjacent cavity areas that do not correspond to the same type of defect cause design features are filtered out, and a set of gate candidate cavity areas is generated.

[0162] It should be noted that when the set of candidate gating cavity regions contains only one adjacent cavity region, the intersection center of the adjacent cavity region and the filling path is registered as the corrected gating position; when the set of candidate gating cavity regions contains multiple adjacent cavity regions, the filling path length between the intersection center formed by each adjacent cavity region and the filling path and the center of the risk area is calculated, and the intersection center with the lowest filling path length value is registered as the corrected gating position; when the filling path length values ​​are the same, they are sorted from low to high according to the horizontal coordinate, vertical coordinate, and height coordinate in the die casting design coordinate system, and the intersection center with the highest ranking is registered as the corrected gating position.

[0163] When the specific target for correction is the overflow exhaust location, the path is read along the starting direction of the exhaust path to the center of the risk area, and the grid area passed through is read. Adjacent cavity areas are found by matching the design feature grid records and the design feature cavity records. Adjacent cavity areas that do not correspond to the same type of defect cause design features are filtered out, and a set of exhaust candidate cavity areas is generated.

[0164] It should be noted that when the set of candidate venting cavity regions contains only one adjacent cavity region, the intersection center of the adjacent cavity region and the venting path is registered as the corrected overflow venting position; when the set of candidate venting cavity regions contains multiple adjacent cavity regions, the length of the venting path between the intersection center formed by each adjacent cavity region and the venting path and the center of the risk area is calculated, and the intersection center with the lowest venting path length value is registered as the corrected overflow venting position; when the venting path length values ​​are the same, they are sorted from low to high according to the horizontal coordinate, vertical coordinate, and height coordinate in the die casting design coordinate system, and the intersection center with the highest ranking is registered as the corrected overflow venting position.

[0165] When the specific target for correction is the location of the cooling channel, the adjacent cavity regions are read along the boundary of the cooling channel's influence area, and adjacent cavity regions that do not correspond to the design features of the same type of defect cause are selected to generate a set of cooling candidate cavity regions.

[0166] It should be noted that when the set of candidate cooling cavity regions contains only one adjacent cavity region, the boundary center of the adjacent cavity region and the boundary of the cooling channel influence area is registered as the corrected cooling channel location; when the set of candidate cooling cavity regions contains multiple adjacent cavity regions, the boundary distance between the boundary center formed by each adjacent cavity region and the boundary of the cooling channel influence area and the center of the risk area is calculated, and the boundary center with the lowest boundary distance value is registered as the corrected cooling channel location; when the boundary distance values ​​are the same, they are sorted from low to high according to the horizontal coordinate, vertical coordinate, and height coordinate in the die casting design coordinate system, and the boundary center with the highest ranking is registered as the corrected cooling channel location.

[0167] When the specific object to be corrected is a local draft surface in the area associated with the demolding direction, the design features of the automotive parts adjacent to the local draft surface are read, and the design features of the automotive parts that have not been registered as the cause of the same type of defect, do not contain the object to be corrected and protected, and have a local draft surface are selected to generate a set of candidate draft design features.

[0168] It should be noted that when the draft candidate design feature set contains only one automotive component design feature, the angle between the local draft surface of the automotive component design feature and the demolding direction is used as the corrected local draft angle. When the draft candidate design feature set contains multiple automotive component design features, the distance between the geometric center of the local draft surface of each automotive component design feature and the center of the risk area is calculated, and the angle between the local draft surface with the lowest distance value and the demolding direction is used as the corrected local draft angle. When the distance values ​​are the same, the local draft surfaces are sorted from low to high according to the horizontal coordinate, vertical coordinate, and height coordinate of the geometric center of the local draft surface in the die-casting design coordinate system, and the angle between the local draft surface with the highest ranking value and the demolding direction is used as the corrected local draft angle.

[0169] Furthermore, the system reads the structural parameter correction values, die-casting process boundary condition correction values, correction protection objects, and the current automotive component design version. It then copies the current automotive component design version into the automotive component die-casting design digital twin object to generate the automotive component design version to be written back.

[0170] It should be noted that before the structural parameter correction values ​​and die-casting process boundary condition correction values ​​are written into the automotive component design version to be written back, the structural parameter correction values ​​and die-casting process boundary condition correction values ​​are verified based on the correction protection object. If the structural parameter correction values ​​or die-casting process boundary condition correction values ​​cause changes in the assembly reference surface, connection hole position, stress connection area, or tolerance control surface corresponding to the correction protection object, the structural parameter correction values ​​or die-casting process boundary condition correction values ​​will not be written into the automotive component design version to be written back, and a correction protection object conflict record will be generated.

[0171] Specifically, for the cause-priority correction task, the structural parameters or die-casting process boundary conditions corresponding to the defect cause design features are replaced in the automotive component design version to be written back, while keeping the assembly reference surface, connection hole position, stress connection area and tolerance control surface corresponding to the correction and protection object unchanged.

[0172] For overlapping linkage correction tasks, replace the structural parameters and die-casting process boundary conditions corresponding to the defect cause design features in the automotive component design version to be written back, while keeping the assembly reference surface, connection hole position, stress connection area and tolerance control surface corresponding to the correction and protection object unchanged.

[0173] Furthermore, after the replacement is completed, the 3D design boundary data and cavity boundary data are re-analyzed based on the automotive component design version to be written back, the die-casting simulation mesh of the changed area is regenerated, the automotive component design feature list, the corresponding records of design feature cavities, the corresponding records of design feature meshes, and the die-casting feature mapping table are updated, and the corrected automotive component design version is generated.

[0174] Furthermore, the revised automotive component design version is written back to the digital twin object of the automotive component die-casting design, and filling simulation, solidification simulation, venting path analysis, cooling analysis, and deformation analysis are performed to generate simulation analysis results corresponding to the revised version. Based on the simulation analysis results corresponding to the revised version, porosity risk areas, air entrapment risk areas, cold shut risk areas, and deformation deviation risk areas are identified, generating the current die-casting defect risk areas corresponding to the revised version. Risk formation path records corresponding to the revised version are generated along the feeding connectivity, the area traversed by the molten metal front, the connected mesh area obtained from the venting path analysis, the cooling channel influence area, and the demolding direction related area. The simulation deviation vector corresponding to the revised version is calculated to generate the calibrated die-casting defect risk areas and uncalibrated risk areas corresponding to the revised version.

[0175] Read the calibrated die-casting defect risk area, uncalibrated risk area, risk formation path record, and die-casting feature mapping table corresponding to the revised version, and register the risk area to be attributed to the revised version; filter the automotive component design features that have spatial intersection, calculate the overlap attribution value, and generate the design feature record of the defect corresponding to the revised version; calculate the path overlap attribution value, and determine the defect cause design feature record corresponding to the revised version according to the defect type; generate the cause separation record and cause overlap record corresponding to the revised version.

[0176] Furthermore, the defect cause design feature records before and after the correction are read and compared according to the same defect type, the same historical trial production and testing area, and the same risk formation path.

[0177] When the revised defect cause design feature record no longer contains the original defect cause design features, and when the revised cause separation record and the revised cause overlap record do not contain any new defect cause design features corresponding to the same defect type, the same historical trial production inspection area, and the same risk formation path, the revised automotive component design version will be registered as the die-casting compatible automotive component design version.

[0178] If the revised defect cause design feature record still contains the defect cause design feature from before the revision, or if the revised cause separation record and the revised cause overlap record contain new defect cause design features corresponding to the same defect type, the same historical trial production testing area, and the same risk formation path, then the revised defect cause design feature record, the revised cause separation record, and the revised cause overlap record will be used as the input for the next round of revision, and the revision task list will be established.

[0179] Furthermore, the design version of the die-casting adapted automotive component, the cause design feature correction record, the corrected die-casting feature mapping table, the corrected defect cause design feature record, the corrected cause separation record, and the corrected cause overlap record are written into the digital twin object of the automotive component die-casting design to generate a digital twin write-back record.

[0180] It should be noted that when the next round of correction input does not form a specific correction object, a write-back verification anomaly record will be generated, and the corrected automotive component design version will not be registered as a die-casting compatible automotive component design version.

[0181] After obtaining the trial production and testing results of the die-cast automotive component design version, the center location of the trial production defect, the defect type, the corresponding historical design version number, and the simulation risk center location in the same automotive component design version are read. The center location of the trial production defect and the simulation risk center location are written into the historical trial production and testing area record, so that the newly added historical trial production and testing area record can participate in the next round of historical position deviation data collection and simulation deviation vector calculation.

[0182] Furthermore, the beneficial effects of this embodiment are verified through simulation experiments. Specifically, the simulation experiments are conducted in a digital twin environment for automotive component die casting design. The test object is the transmission housing of a new energy vehicle, and the material grade is ADC12. The experimental materials include a three-dimensional design model, a mold cavity model, historical trial production test records, gate location, overflow and vent location, cooling channel location, demolding direction, automotive component design feature list, die casting simulation mesh, die casting feature mapping table, and historical trial production test area records. The automotive component design features include wall panels, reinforcing ribs, mounting ears, hole pillars, bosses, corner fillets, thickness transition zones, weight reduction hole boundaries, and local draft surfaces.

[0183] The simulation experiment used the average injection speed of 3.8 m / s, the average pouring temperature of 680℃, the average mold temperature of 210℃, the average boosting pressure of 68 MPa, and the average cooling channel inlet temperature of 22℃ as non-variable conventional process data. The non-variable conventional process data were taken from the average values ​​of the simulation working conditions of the same material grade and the same type of automotive parts. The number of gate positions, the number of overflow vent positions, the number of cooling channels, and the number of demolding directions were kept constant. Simulation calibration, defect attribution, and write-back verification were performed on the porosity risk area, air entrapment risk area, cold shut risk area, and deformation deviation risk area, respectively.

[0184] Figure 5 The effect of the number of historical position deviation data on the position calibration effect of the calibrated die-casting defect risk area was verified. Specifically, the simulation experiment read the center position of the trial defect and the simulated risk center position corresponding to the same historical trial inspection area and the same defect type from the historical trial inspection records, forming 3, 6, 9 and 12 historical position deviation data, respectively. For each defect type, 18 repeated simulations were performed under each number of historical position deviation data, resulting in a total of 288 die-casting defect risk area calibration records. The simulation deviation vector was calculated based on each set of historical position deviation data and applied to the current die-casting defect risk area to generate the calibrated die-casting defect risk area. The center position deviation before and after calibration of the porosity risk area, air entrapment risk area, cold shut risk area and deformation deviation risk area were recorded respectively.

[0185] It should be noted that the center position deviation before calibration is the spatial distance between the center position of the current die-casting defect risk area and the center position of the trial production defect, and the center position deviation after calibration is the spatial distance between the center position of the die-casting defect risk area after calibration and the center position of the trial production defect. The unit of spatial distance is millimeters. The calibration record of the die-casting defect risk area includes the defect type, historical trial production detection area, number of historical position deviation data, horizontal component of the simulation deviation vector, vertical component of the simulation deviation vector, height component of the simulation deviation vector, center position deviation before calibration, center position deviation after calibration, and the amount of reduction in center position deviation.

[0186] Figure 5 The solid line represents the center position deviation before calibration, and the dashed line represents the center position deviation after calibration; different curves correspond to different defect types; experimental results show that after the number of historical position deviation data points increased from 3 to 12, the average center position deviation after calibration decreased from 3.295 mm to 2.003 mm, and the average reduction rate of center position deviation increased from 21.839% to 52.463%, indicating that the simulated deviation vector can provide a traceable position calibration basis for the risk area of ​​die casting defects.

[0187] Figure 6The changes in risk areas during the write-back and re-inspection process of automotive component design versions after performing corrections based on the design features of the defect causes were verified. Simulation experiments read the design feature records of the defect causes, the records of the separation of the causes, and the records of the overlap of the causes, and generated correction task lists using two methods: "correction based only on the design features where the defect is located" and "correction based on the design features of the defect causes".

[0188] Among them, "correction based solely on the design features where the defect is located" is used as a comparison method, with the correction object taken from the design features where the defect is located; "correction based on the design features that cause the defect" is used as the method in this embodiment, with the correction object taken from the design features that cause the defect, and the assembly reference surface, connection hole position, stress connection area and tolerance control surface are simultaneously registered as correction protection objects.

[0189] The experiment performed three rounds of write-and-re-inspection on the porosity risk area, air entrapment risk area, cold shut risk area, and deformation deviation risk area. In each round of write-and-re-inspection, simulation calibration and defect attribution were re-executed, and the number of risk areas after correction was recorded. For each defect type, each correction method, and each round of write-and-re-inspection, 14 repeated simulations were performed, resulting in a total of 336 write-and-re-inspection records for automotive component design versions. The write-and-re-inspection records for automotive component design versions include defect type, inspection round, correction method, type of correction object, correction object, correction protection object, number of risk areas after correction, offset of assembly datum surface, offset of connection hole position, offset of stress connection area, offset of tolerance control surface, and inspection conclusion.

[0190] Figure 6 Different curves correspond to different combinations of defect types and correction methods. Experimental results show that when correcting based on design features of defect causes, the number of risk areas after correction is lower than that of correction based solely on the design features of the defect as the number of retesting rounds increases. This indicates that risk formation path records and die-casting feature mapping tables can provide an attribution basis for determining correction targets, thereby improving the pertinence of die-casting design corrections and the consistency of version retesting.

[0191] This embodiment also provides a computer device applicable to the digital twin-based automotive component die-casting design method, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the digital twin-based automotive component die-casting design method proposed in the above embodiment.

[0192] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0193] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the digital twin-based automotive component die-casting design method proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0194] In summary, this invention generates calibrated die-casting defect risk areas by collecting historical position deviation data and calculating simulation deviation vectors, providing traceable position calibration basis for porosity risk areas, air entrapment risk areas, cold shut risk areas, and deformation deviation risk areas. By combining risk formation path records and die-casting feature mapping tables, the design features where defects are located and the design features that cause defects are determined respectively, providing an attribution basis for determining the correction objects and registering the correction protection objects, thereby improving the pertinence of die-casting design corrections and the consistency of version verification.

[0195] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for die-casting automotive components based on digital twins, characterized in that, include: Read the 3D design model, mold cavity model and historical trial production test records, unify the die casting design coordinate system, extract the design features of automotive parts, generate the die casting simulation mesh, establish the die casting feature mapping table, and generate digital twin objects of automotive part die casting design; Based on the digital twin object of automotive component die casting design, the filling simulation, solidification simulation, exhaust path analysis, cooling analysis and deformation analysis are performed to generate the current die casting defect risk area and risk formation path record, collect historical position deviation data, calculate the simulation deviation vector, and generate the calibrated die casting defect risk area. Based on the calibrated die casting defect risk area, risk formation path record and die casting feature mapping table, register the risk area to be attributed, calculate the overlap and path overlap values, determine the design feature where the defect is located and the design feature of the defect cause, and generate the cause separation record or the cause coincidence record. Read the design feature record of defect cause, combine it with the cause separation record and cause overlap record, generate a correction task list, register the correction protection object and the correction object, determine the specific correction object, generate structural parameter correction value and die casting process boundary condition correction value, write back and verify the corrected automotive part design version, and generate die casting adapted automotive part design version and digital twin write back record.

2. The automotive component die-casting design method based on digital twins as described in claim 1, characterized in that, The extracted automotive component design features include: Read the 3D design model, mold cavity model, and historical trial production and inspection records; analyze the 3D design boundary, cavity boundary, and historical trial production and inspection content; and generate 3D design boundary data, cavity boundary data, historical trial production and inspection data, and installation and connection area. Based on the installation connection area, the center of the connection hole and the demolding direction, a die casting design coordinate system is constructed. The three-dimensional design model, mold cavity model and historical trial production test data are converted to the die casting design coordinate system, and a coordinate transformation record is generated. Read the 3D design boundary data, extract the design features of automotive components according to the closed boundary, the connection relationship between adjacent surfaces and the structural purpose, and generate a list of automotive component design features.

3. The automotive component die-casting design method based on digital twins as described in claim 1 or 2, characterized in that, The process of establishing a die-casting feature mapping table and generating a digital twin object for the die-casting design of automotive parts includes: Based on the 3D design model and mold cavity model, a die-casting simulation mesh is generated. Based on the automotive component design feature list and cavity boundary data, the correspondence between automotive component design features and cavity regions and die-casting simulation mesh regions is established, and corresponding records of design feature cavities and design feature meshes are generated. Based on historical trial production and testing data, corresponding records of design feature grids, and coordinate transformation records, historical trial production and testing area records are generated. Combined with the automotive component design feature list, corresponding records of design feature cavities, and corresponding records of design feature grids, a die casting feature mapping table and a digital twin object of automotive component die casting design are generated.

4. The automotive component die-casting design method based on digital twins as described in claim 1, characterized in that, The process of generating current die-casting defect risk areas and risk formation path records includes: Based on the digital twin object of automotive component die casting design, the filling simulation, solidification simulation, exhaust path analysis, cooling analysis and deformation analysis are performed to generate simulation analysis results. Based on the simulation analysis results, identify the risk areas of porosity, air entrapment, cold shut, and deformation deviation, and register the defect type, the center location of the risk area, the die casting simulation grid area to which it belongs, and the historical trial production detection area to which it belongs, and generate the current die casting defect risk area. Based on the current die-casting defect risk areas and simulation analysis results, the risk formation path record is generated by tracing back to the direction of the feeding source, gate location, overflow venting location, direction of the cooling channel influence area, and direction of the demolding direction associated with the connected mesh area obtained from the feeding connection relationship, the area through which the molten metal front passes, the connected mesh area obtained from the venting path analysis, the area affected by the cooling channel, and the direction of the demolding direction associated with the demolding direction.

5. The automotive component die-casting design method based on digital twins as described in claim 4, characterized in that, The generated and calibrated die-casting defect risk area includes: Based on the current die casting defect risk area, die casting feature mapping table and historical trial production inspection area records, the trial production defect center position and simulation risk center position of the same defect type in the same historical trial production inspection area are collected to generate historical position deviation data. Based on historical position deviation data, a simulation deviation vector is calculated and applied to the current die-casting defect risk area to generate a calibrated die-casting defect risk area. For the current die-casting defect risk area lacking historical position deviation data, an uncalibrated risk area is generated.

6. The automotive component die-casting design method based on digital twins as described in claim 5, characterized in that, The generated causality separation record or causality overlap record includes: Read the calibrated die casting defect risk area, uncalibrated risk area, risk formation path record and die casting feature mapping table, register the risk areas to be attributed according to the defect type, risk area center location, historical trial production detection area, and die casting simulation grid area, and generate the risk areas to be attributed. Based on the risk area to be attributed and the spatial boundary of automotive component design features, automotive component design features that have spatial intersection are screened to form a set of candidate design features, the overlap attribution value is calculated, the design feature where the defect is located is determined, and a record of the design feature where the defect is located is generated. Based on the risk region to be attributed and the risk formation path record, the die-casting simulation mesh region through which the risk formation path passes is read, and converted into automotive part design features through the die-casting feature mapping table to generate a set of candidate design features for causes. Based on the set of candidate design features for causes and risk formation path records, the path overlap attribution value is calculated, and the defect cause design features are determined according to the defect types corresponding to the pore risk area, air entrapment risk area, cold shut risk area and deformation deviation risk area, and defect cause design feature records are generated. Based on the design feature record of the defect location and the design feature record of the defect cause, compare the design features of the defect location and the design features of the defect cause, generate a separate record of the cause or a record of the cause overlap, and write it into the digital twin object of the automotive component die casting design.

7. The automotive component die-casting design method based on digital twins as described in claim 1, characterized in that, The registration and amendment of the protected object and the object to be amended, and the determination of the specific object to be amended, include: Read the defect cause design feature record, the cause separation record and the cause overlap record, extract the defect type, risk formation path, the design feature where the defect is located and the defect cause design feature, and generate a correction task list. Register the assembly reference surface, connection hole, stress connection area and tolerance control surface of the design feature where the defect is located in the correction task list, generate the correction protection object, and determine the design feature that causes the defect as the correction object. Based on the object to be corrected, the defect type, the risk formation path record, and the die casting feature mapping table, determine the structural parameters or die casting process boundary conditions, and generate specific objects to be corrected.

8. The automotive component die-casting design method based on digital twins as described in claim 7, characterized in that, The generation of die-casting-adapted automotive component design versions and digital twin write-back records includes: Based on the specific object to be corrected, structural parameter correction and die-casting process boundary condition correction are distinguished. By referring to the design feature set, structural parameter correction values ​​are generated. By using the risk formation path and adjacent cavity areas, die-casting process boundary condition correction values ​​are generated. The structural parameter correction values ​​and die-casting process boundary condition correction values ​​are written into the automotive part design version to be written back, and the corrected automotive part design version is generated. The simulation calibration and defect attribution are re-performed on the revised automotive component design version. The defect cause design feature records before and after the revision are compared to generate a die-casting adapted automotive component design version and a digital twin write-back record.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the digital twin-based automotive component die-casting design method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the digital twin-based automotive component die-casting design method as described in any one of claims 1 to 8.

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