Machine tool component structure optimization design method, device, equipment and storage medium

Abstract

This invention relates to a method, apparatus, equipment, and storage medium for optimizing the structure of machine tool components. The method includes the following steps: scanning the machine tool component to obtain a 3D model, and disassembling it into multiple sub-component models; calculating the dimensions of each sub-component, establishing a dimensional parameter table, simulating assembly relationships to generate an assembly simulation model, and identifying and adjusting spatial interference areas to optimize the model; performing material matching analysis based on this model to obtain a material combination scheme, and calculating the load-bearing capacity accordingly; combining the load-bearing capacity and material scheme to optimize the structure and materials of the machine tool component; determining reinforcement requirements through marking key stress areas and evaluating stress concentration factors; and implementing structural reinforcement measures for high-stress areas, such as increasing wall thickness or adding reinforcing rings, ultimately achieving optimized design of the entire machine tool component. This invention solves the technical problems commonly found in existing design processes, such as the disconnect between the model and the physical object, and the lag in verifying the assembly relationships between sub-components.

Description

Technical Field

[0001] This invention relates to the field of machine tool technology, and in particular to a method, apparatus, equipment, and storage medium for optimizing the structure of machine tool components. Background Technology

[0002] As modern manufacturing demands increasingly higher precision, efficiency, and reliability in machine tool processing, the structural design of machine tool components directly determines the overall performance of the machine.

[0003] However, existing design processes commonly suffer from problems such as a disconnect between the model and the physical prototype, and delayed verification of assembly relationships between sub-components. In actual development, structural issues such as interference or poor fit are often only discovered during the physical prototype assembly stage, leading to frequent design rework and extended development cycles. Summary of the Invention

[0004] The main objective of this invention is to provide a method for optimizing the design of machine tool component structures, which solves the technical problems of disconnect between models and physical objects and the lag in verifying the assembly relationship between sub-components that are common in existing design processes.

[0005] To achieve the above objectives, the present invention provides a method for optimizing the structure of machine tool components, comprising the following steps: Scan the machine tool component entity to obtain a 3D model of the component, and then disassemble the 3D model of the component to obtain multiple 3D models of sub-components. Calculate the dimensions of each sub-component in the 3D model of the sub-components to obtain a sub-component dimension parameter table. Based on the sub-component dimension parameter table, simulate the assembly relationship of each sub-component to obtain an assembly simulation model. When the assembly simulation model has spatial interference regions, adjust the assembly simulation model according to the spatial interference regions to obtain an adjusted assembly simulation model. Based on the adjusted assembly simulation model, perform material matching analysis on each sub-component to obtain a material combination scheme, and calculate the load-bearing capacity based on the material combination scheme. Optimize the entire machine tool component entity based on the load-bearing capacity and the material combination scheme to obtain an optimized machine tool component entity.

[0006] Furthermore, the scanning machine tool component entity is used to obtain a three-dimensional model of the component, and the three-dimensional model of the component is structurally disassembled to obtain multiple sub-component three-dimensional models, including: The machine tool component is scanned from all angles using a 3D laser scanner to obtain the original point cloud of the component. Redundant points in the original point cloud are then filtered to obtain a simplified point cloud image. Based on the simplified point cloud map, the connection features of the machine tool component entity are identified and labeled, and the simplified point cloud map is reconstructed into a surface according to the connection features to obtain a three-dimensional model of the component. Based on the connection features, the sub-component splitting boundary lines are determined, and the 3D model of the component is cut and separated according to the sub-component splitting boundary lines to obtain multiple sub-component 3D models.

[0007] Furthermore, the calculation of the dimensions of each sub-component in the 3D model of the sub-component to obtain a sub-component dimension parameter table includes: The three-dimensional models of the multiple sub-components are grouped according to their assembly relationships to obtain sub-component association groups. The dimensions of each sub-component within the sub-component association group are calculated to obtain a sub-component dimension parameter table that includes the sub-component name, association group number, and mating dimensions.

[0008] Furthermore, the assembly simulation model obtained by simulating the assembly relationship of each sub-component based on the sub-component size parameter table includes: Based on the sub-component size parameter table, the connection interface size of each sub-component is extracted, and the matching of the connection interface size is verified to obtain an interface matching table; Based on the interface matching table, a list of connection methods between sub-components is determined, and the corresponding assembly direction is marked on the list of connection methods; Based on the assembly direction, each sub-component is sequentially positioned and simulated in three-dimensional space according to the interface matching relationship to obtain an assembly simulation model.

[0009] Furthermore, adjusting the assembly simulation model based on the spatial interference region to obtain the adjusted assembly simulation model includes: Extract the three-dimensional contour data of the interferometric sub-components in the spatial interferometric region, and measure the overlap volume and overlap position coordinates of the three-dimensional contour data to obtain the interferometric parameter table; Based on the interference parameter table, the interference type is determined, and an adjustment scheme list is formulated according to the interference type; Based on the adjustment scheme list, the dimensions or spatial orientation of the interfering sub-components in the assembly simulation model are modified to obtain the adjusted pre-assembly. The spatial interference of the adjusted pre-assembly is then re-inspected to obtain the interference re-inspection result. When the interference re-inspection result shows no spatial interference area, the adjusted assembly simulation model is obtained.

[0010] Furthermore, the process of performing material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculating the load-bearing capacity based on the material combination scheme, includes: The force points and directions of each sub-component in the adjusted assembly simulation model are marked to obtain a force marking diagram, and the load type of each sub-component is determined based on the force marking diagram; Based on the load type, suitable candidate materials are selected, and the candidate materials are subjected to pairing compatibility testing to obtain a material matching degree table. Based on the material matching degree table, the combination with the highest matching degree is selected to obtain the material combination scheme, and stress and strain calculations are performed on each sub-component in the material combination scheme to obtain the load-bearing capacity value.

[0011] Furthermore, the optimization of the entire machine tool component entity based on the load-bearing capacity and material combination scheme to obtain the optimized machine tool component entity includes: Based on the load-bearing capacity values, key stress areas are marked for each sub-component in the adjusted assembly simulation model to obtain a key stress area diagram. Stress concentration factors are calculated for each sub-component in the key stress area diagram to obtain a stress concentration factor table. Structural reinforcement design is performed on the key stress areas of each sub-component using the stress concentration factor table to obtain a structural reinforcement scheme. The assembly simulation model is then updated based on the structural reinforcement scheme to obtain an updated assembly simulation model. Weight distribution is calculated for each sub-component in the updated assembly simulation model based on the material combination scheme to obtain a sub-component weight distribution table. The center of gravity position is calculated for the updated assembly simulation model using the sub-component weight distribution table to obtain the center of gravity coordinates. Overall balance adjustment is performed on the updated assembly simulation model based on the center of gravity coordinates to obtain a balance adjustment scheme. The entire machine tool component entity is then optimized based on the balance adjustment scheme to obtain an optimized machine tool component entity.

[0012] The present invention also provides a machine tool component structure optimization design device, comprising: The system comprises the following modules: a scanning module for scanning the machine tool component entity to obtain a 3D model of the component, and a calculation module for calculating the dimensions of each sub-component in the sub-component 3D model to obtain a sub-component dimension parameter table; a simulation module for simulating the assembly relationship of each sub-component based on the sub-component dimension parameter table to obtain an assembly simulation model, and adjusting the assembly simulation model according to the spatial interference region when the assembly simulation model has such a region to obtain an adjusted assembly simulation model; an analysis module for performing material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculating the load-bearing capacity based on the material combination scheme; and an optimization module for optimizing the entire machine tool component entity based on the load-bearing capacity and the material combination scheme to obtain an optimized machine tool component entity.

[0013] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0015] This invention provides a machine tool component structure optimization design method, comprising the following steps: scanning the machine tool component entity to obtain a three-dimensional model of the component, and structurally disassembling the three-dimensional model of the component to obtain multiple sub-component three-dimensional models; calculating the dimensions of each sub-component in the sub-component three-dimensional model to obtain a sub-component dimension parameter table; simulating the assembly relationship of each sub-component based on the sub-component dimension parameter table to obtain an assembly simulation model; when the assembly simulation model has a spatial interference region, adjusting the assembly simulation model according to the spatial interference region to obtain an adjusted assembly simulation model; performing material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculating the load-bearing capacity based on the material combination scheme; optimizing the entire machine tool component entity based on the load-bearing capacity and the material combination scheme to obtain an optimized machine tool component entity. This method solves the technical problems of model-physical disconnect and delayed verification of assembly relationships between sub-components that are common in existing design processes, achieving precise matching of material performance and structural requirements, and improving overall reliability and economy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating the steps of a machine tool component structure optimization design method in one embodiment of the present invention; Figure 2 This is a structural block diagram of a machine tool component structure optimization design device according to an embodiment of the present invention; Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0020] like Figure 1 As shown, Figure 1 This invention provides a method for optimizing the structure of machine tool components, comprising the following steps: Step S1: Scan the machine tool component entity to obtain a 3D model of the component, and disassemble the 3D model of the component to obtain multiple sub-component 3D models.

[0021] Specifically, the machine tool component is scanned to obtain a 3D model. This 3D model is then structurally disassembled to obtain multiple sub-component 3D models. This process begins by using a 3D laser scanner or structured light scanner to collect comprehensive data from the actual machine tool component, acquiring dense point cloud data of its surface. This point cloud data is then registered and stitched together to generate a complete 3D model of the component. This 3D model accurately reflects the geometry and spatial structure of the original component. Subsequently, this 3D model is imported into a 3D modeling software environment. Based on the actual assembly relationships and functional divisions of the component, virtual segmentation is performed along the original assembly contact surfaces or connection interfaces to identify and separate components with independent structural features. The process involves disassembling the 3D model of a component, maintaining the geometric integrity and topological relationships of each part, and ultimately forming multiple sub-component 3D models. These sub-component 3D models correspond to the actual functional units in the machine tool, such as the spindle box, slide, and guide rail support. Taking the bed component of a certain type of CNC milling machine as an example, the overall bed 3D model obtained after scanning can be disassembled into multiple sub-component 3D models along the bolt connection surface and functional area boundaries, such as the base, column mounting area, and transverse slide support area. This provides a structural basis for subsequent dimensional parameter extraction and assembly simulation. The entire process relies on the collaborative operation of high-precision scanning technology and professional modeling tools to ensure that the disassembly results truly reflect the physical structure.

[0022] Step S2: Calculate the dimensions of each sub-component in the 3D model of the sub-component to obtain the sub-component dimension parameter table.

[0023] Specifically, based on obtaining multiple 3D models of sub-components, the measurement and analysis functions of 3D modeling software are used to extract dimensions of the geometric features of each sub-component in the 3D model. First, the main structural elements of each sub-component are identified, including outer contour boundaries, mounting holes, mating surfaces, wall thickness areas, and key transition fillets. Geometric parameters such as length, width, height, diameter, hole spacing, angle, and curvature are obtained using the software's built-in dimensioning tools or automatic feature recognition module. These parameters are then categorized and recorded according to a unified format. For sub-components with symmetrical or repetitive structures, an instantiated measurement method is used to reduce repetitive operations. Simultaneously, for mating dimensions with tolerance requirements, their dimensions are annotated based on the design intent or actual assembly needs. The scope of data collection involves organizing and summarizing all collected dimensional data into a structured data table, namely the sub-component dimension parameter table. Each data item in this table is associated with the corresponding 3D model of the sub-component, ensuring data traceability. Taking the 3D model of the slide sub-component disassembled from the CNC milling machine bed as an example, when calculating its dimensions, it is necessary to measure specific parameters such as the overall length, width, and height of the slide, the flatness and relative position of the guide rail mounting surface, the distribution spacing and thickness of the internal reinforcing ribs, and the position and depth of the threaded hole connected to the lead screw nut seat. These parameters are then filled into the sub-component dimension parameter table to provide accurate data support for subsequent assembly relationship simulation based on this parameter table. The entire process relies on the accurate measurement capabilities of the modeling software and the accurate judgment of the structural features by the engineers.

[0024] Step S3: Based on the sub-component size parameter table, perform assembly relationship simulation on each sub-component to obtain an assembly simulation model. When the assembly simulation model has a spatial interference region, adjust the assembly simulation model according to the spatial interference region to obtain an adjusted assembly simulation model.

[0025] Specifically, based on the geometric data recorded in the sub-component dimension parameter table, the aforementioned multiple sub-component 3D models are imported into the assembly simulation software environment. Following the actual assembly sequence and connection method of the machine tool, and based on the installation position, fit tolerances, and relative relationships provided in the dimension parameter table, the 3D models of each sub-component are virtually assembled. By setting constraints such as fitting, concentricity, fixed distance, or angular alignment, the precise spatial alignment of each sub-component 3D model is achieved, forming a complete assembly simulation model. After the assembly simulation model is generated, the software's interference check function is activated to perform global collision and gap analysis on the entire assembly. The system automatically identifies areas where geometric overlap occurs between different sub-component 3D models, which are the spatial interference areas. For the detected spatial interference areas, combined with the dimensions... Based on the design parameters in the parameter table and the actual assembly requirements, the structural features of the 3D model of the interfering sub-components are locally modified. For example, the mounting hole positions are adjusted, the mating surface contours are corrected, or the layout of the reinforcing ribs is optimized. After the modifications are completed, the assembly relationship simulation is re-performed, and the interference check is performed again until the spatial interference area is completely eliminated. Finally, an interference-free adjusted assembly simulation model is obtained. Taking the assembly of the slide and the guide rail bracket in a CNC milling machine as an example, if a spatial interference area is found between the reinforcing rib at the bottom of the slide and the bolt boss on the guide rail bracket during the assembly relationship simulation, the reinforcing rib of the slide is designed with a cut to avoid interference or the bolt hole position of the bracket is adjusted according to the specific location and range of the interference area to ensure assembly feasibility. The whole process relies on the collaboration of the dimension parameter table and the 3D model to achieve accurate virtual assembly and structural optimization.

[0026] Step S4: Based on the adjusted assembly simulation model, perform material matching analysis on each sub-component to obtain a material combination scheme, and calculate the load-bearing capacity based on the material combination scheme.

[0027] Specifically, based on the adjusted assembly simulation model, finite element analysis software is used to simulate the stress state of each sub-component under actual working conditions. The adjusted assembly simulation model is imported into the analysis environment, meshed, and boundary conditions and loads are applied. Based on the multi-physics field effects such as cutting force, inertial force, and thermal deformation experienced by each sub-component during machine tool operation, the stress distribution, strain degree, and displacement deformation in the three-dimensional model of each sub-component are analyzed. Combining the mechanical property parameters of different metallic materials in the material database, such as elastic modulus, yield strength, density, and fatigue limit, material matching analysis is performed based on the stress characteristics of each sub-component's location. High-strength alloy steel or cast iron is preferentially selected for high-stress concentration areas, while aluminum alloy or engineering composite materials can be selected for non-critical load-bearing parts or parts requiring weight reduction. By comparing the simulation responses of different materials under the same working conditions, a material combination scheme that meets the performance and process requirements is selected. The material combination scheme clearly specifies the material type corresponding to the 3D model of each sub-component. Then, based on the material combination scheme, the 3D model of each sub-component is assigned the corresponding material properties, and the structural mechanics simulation calculation is performed again to obtain the overall deformation trend of the entire assembly under rated working conditions and the stress level of key parts. This allows for the assessment of its ability to resist external loads and the quantitative calculation of load-bearing capacity. Taking the slide and guide rail bracket of a CNC milling machine as an example, in the material matching analysis, if the slide mainly bears the periodic cutting load, high-strength cast iron is selected to ensure stiffness and damping performance. If the guide rail bracket is sensitive to weight and has a small force, aluminum alloy material can be matched. After assigning the corresponding material properties, the maximum deformation and safety factor under the maximum cutting force are calculated through simulation to obtain an accurate load-bearing capacity assessment result. The entire process relies on the collaborative analysis of the adjusted assembly simulation model and the material database to achieve scientific material selection and performance verification.

[0028] Step S5: Optimize the entire machine tool component entity based on the load-bearing capacity and material combination scheme to obtain the optimized machine tool component entity.

[0029] Specifically, the entire machine tool component entity is optimized based on the load-bearing capacity and material combination scheme to obtain the optimized machine tool component entity. This process first combines the load-bearing capacity value calculated in step S4 with the material configuration of each sub-component in the material combination scheme. For the slide sub-component in the CNC milling machine that bears high stress, based on the use of HT300 cast iron material, and considering that the local stress is close to the material limit as shown by the load-bearing capacity analysis, the internal stiffener layout of the slide three-dimensional model is topologically optimized, the stiffener density on the key force transmission path is increased, and the transition fillet radius is increased from R5 to R8 to reduce stress concentration. At the same time, the wall thickness of non-major load-bearing areas is reduced to achieve lightweighting. After completing the geometric modification, the updated sub-component is reassembled into the adjusted assembly simulation model, keeping the material combination scheme unchanged, and finite element simulation calculation is performed again to verify whether its load-bearing capacity has been improved. If the simulation results show that the maximum stress has decreased and the safety factor meets the design requirements, the structural improvement is confirmed to be effective, and finally, an optimized machine tool component entity with higher stiffness, better quality distribution, and stronger deformation resistance is formed.

[0030] In a specific embodiment, the scanning machine tool component entity is used to obtain a three-dimensional model of the component, and the three-dimensional model of the component is structurally disassembled to obtain multiple sub-component three-dimensional models, including: The machine tool component is scanned from all angles using a 3D laser scanner to obtain the original point cloud of the component. Redundant points in the original point cloud are then filtered to obtain a simplified point cloud image. Based on the simplified point cloud map, the connection features of the machine tool component entity are identified and labeled, and the simplified point cloud map is reconstructed into a surface according to the connection features to obtain a three-dimensional model of the component. Based on the connection features, the sub-component splitting boundary lines are determined, and the 3D model of the component is cut and separated according to the sub-component splitting boundary lines to obtain multiple sub-component 3D models.

[0031] Specifically, a 3D laser scanner is used to perform a full-range scan of the machine tool component to obtain the original point cloud of the component. Redundant points in the original point cloud are then filtered to obtain a simplified point cloud image. This step first requires fixing the machine tool component to be scanned on a rotating platform or stable support to ensure that the component does not move during the scanning process. Then, the 3D laser scanner is started to collect data around the component from multiple angles and with full coverage, obtaining densely distributed point cloud data on its surface, i.e., the original point cloud of the component. Since a large number of redundant and noise points may be introduced during the scanning process due to environmental interference, reflection differences, or multiple overlapping scans, the original point cloud of the component needs to be preprocessed. Algorithms based on statistical filtering or voxel mesh downsampling are used to denoise and simplify the point cloud data, remove isolated outliers, and homogenize the point density, thereby obtaining a simplified point cloud image with a clear structure and a moderate amount of data, providing a high-quality data foundation for subsequent modeling. Based on the simplified point cloud map, the connection features of machine tool components are identified and labeled. Then, the simplified point cloud map is reconstructed into a surface based on these connection features to obtain a 3D model of the component. Specifically, the simplified point cloud map needs to be imported into 3D modeling software. Key connection features on the component are automatically detected using feature recognition algorithms or manually labeled. These connection features include, but are not limited to, bolt hole arrays, flange mating surfaces, pin positioning holes, slot structures, and weld marks. They reflect the assembly method and mechanical transmission path of the component in actual assembly. By marking and classifying the spatial location, geometric shape, and distribution pattern of these connection features, the assembly boundaries between sub-components can be clearly defined. Subsequently, based on the labeled connection features, a surface fitting process is guided. NURBS surface fitting or triangular mesh reconstruction technology is used to reconstruct the surface of the simplified point cloud map, ensuring that the generated 3D model of the component not only accurately restores the original component's outer contour shape but also retains the geometric details of all key connection features, ensuring the model's engineering usability.Based on the connection features, the sub-component splitting boundary lines are determined, and the 3D model of the component is cut and separated according to the sub-component splitting boundary lines to obtain multiple sub-component 3D models. This process requires combining the physical meaning and spatial distribution of the connection features to divide areas with independent assembly functions into splitting units. For example, in the bed component of a certain type of CNC milling machine, its bottom is connected to the base through an array of bolt holes, its side has a flange surface for mounting columns, and its interior contains a guide rail mounting area for supporting the slide. These connection features together constitute the natural boundary between sub-components, based on which the sub-component splitting boundary lines can be defined. These boundary lines are usually along bolt connection surfaces, mating contact surfaces, or structural... The mutation region extends, and then Boolean cutting or patch segmentation operations are performed on the 3D model of the component along the sub-component split boundary line in the 3D modeling environment. The overall model is decomposed into several independent geometries, each corresponding to a functionally defined sub-component, such as the base, column mounting area, and transverse slide support area. During the cutting process, it is necessary to ensure the geometric integrity and topological consistency of each sub-component's 3D model to avoid broken surfaces, gaps, or overlapping surfaces. The final output of multiple sub-component 3D models not only maintains a high degree of consistency with the original entity, but also has the feasibility of independent modeling and subsequent analysis, providing a structural foundation for dimension extraction, assembly simulation, and material optimization.

[0032] In a specific embodiment, calculating the dimensions of each sub-component in the three-dimensional model of the sub-component to obtain a sub-component dimension parameter table includes: The three-dimensional models of the multiple sub-components are grouped according to their assembly relationships to obtain sub-component association groups. The dimensions of each sub-component within the sub-component association group are calculated to obtain a sub-component dimension parameter table that includes the sub-component name, association group number, and mating dimensions.

[0033] Specifically, multiple sub-component 3D models are grouped according to their assembly relationships to obtain sub-component association groups. The dimensions of each sub-component within each association group are then calculated, resulting in a sub-component dimensional parameter table including the sub-component name, association group number, and mating dimensions. This process first requires loading the disassembled 3D models of multiple sub-components into the 3D modeling software environment. Based on the assembly logic and spatial connection methods of each sub-component in the actual machine tool structure, their assembly relationships are determined. These relationships originate from the connection features identified in step S1, such as bolted connections, flange fits, shaft-hole fits, or guide rail sliding fits. The analysis of the contact surface types between sub-components further supports this process. Based on the distribution of fasteners and motion constraints, multiple sub-components with direct assembly relationships are grouped into the same set, thus forming sub-component association groups. For example, in the bed structure of a certain type of CNC milling machine, the slide and the guide rail bracket are fixed by bolts and slide along the guide rail surface, forming a clear assembly unit. Therefore, the 3D model of the slide and the 3D model of the guide rail bracket are assigned to the same sub-component association group and given a unique association group number, such as "CG-01". The base and the column mounting area are connected by anchor bolts and share the same reference plane, so they are assigned to another sub-component association group, numbered "CG-02". This process is repeated to complete the grouping operation of all sub-component 3D models. After completing the sub-component association group division, dimensional calculations are performed sequentially on the 3D models of each sub-component within each association group. This operation is based on the measurement tools built into the 3D modeling software or automated scripts. First, the basic geometric parameters of each sub-component's 3D model are extracted, including independent dimensions such as overall length, width, height, wall thickness, and fillet radius. Simultaneously, the mating dimensions related to assembly are measured, encompassing the relative positional relationships between sub-components, such as the distance between the mating surfaces of two components, bolt hole center distance, hole diameter, pin hole coaxiality, and the parallelism and flatness of the guide rail mounting surface. All measurement results are associated with the corresponding sub-component name and its associated group number. For example, in the sub-component associated group "CG-01", the guide rail mounting surface width of the slide 3D model is 320mm, the hole spacing of the four threaded holes on it is 280mm×200mm, and the hole diameter is M12. The through hole position on the corresponding mounting surface of the guide rail bracket 3D model is exactly the same, and is also recorded as hole spacing 280mm×200mm and hole diameter Φ13.5mm. The above data, along with the sub-component names "slide", "guide rail bracket" and associated group number "CG-01", are entered into the data table.Finally, the measurement results of all sub-components in the associated group are summarized and organized to form a structured sub-component size parameter table. Each row of the table records the size information of a sub-component, and the columns include the sub-component name, associated group number, independent size and mating size. This ensures that the subsequent assembly simulation can accurately restore the spatial arrangement relationship between each sub-component based on this table. The entire process strictly relies on the three-dimensional model of the sub-components and the connection feature annotations obtained from the previous disassembly to ensure the accuracy of size extraction and engineering traceability.

[0034] In a specific embodiment, the step of simulating the assembly relationship of each sub-component based on the sub-component size parameter table to obtain an assembly simulation model includes: Based on the sub-component size parameter table, the connection interface size of each sub-component is extracted, and the matching of the connection interface size is verified to obtain an interface matching table; Based on the interface matching table, a list of connection methods between sub-components is determined, and the corresponding assembly direction is marked on the list of connection methods; Based on the assembly direction, each sub-component is sequentially positioned and simulated in three-dimensional space according to the interface matching relationship to obtain an assembly simulation model.

[0035] Specifically, the connection interface dimensions of each sub-component are extracted based on the sub-component size parameter table, and the matching of these dimensions is verified to obtain an interface matching table. This process first reads the names of each sub-component belonging to the same sub-component association group and their corresponding mating dimensions from the sub-component size parameter table. The focus is on extracting the geometric feature data related to the assembly connection, i.e., the connection interface dimensions. These dimensions include the diameter of bolt holes, hole center coordinates, number of holes, hole distribution pitch circle diameter, flange width and thickness, keyway width and depth, and guide rail mating surface length and height. For example, in the sub-component association group "CG-01" of the CNC milling machine, the connection interface dimensions of the slide 3D model include the position coordinates and hole diameters of its four M12 threaded holes at the bottom, while the corresponding connection interface dimensions of the guide rail bracket 3D model... The dimensions of the opening are the position coordinates and diameters of the four Φ13.5mm through holes at the top. The dimensions of these two sets of connection interfaces are compared item by item to verify whether they meet the basic matching conditions of mechanical assembly, namely, whether the diameter of the through hole is greater than or equal to the diameter of the threaded hole, whether the center coordinate deviation of the two sets of holes is within the allowable tolerance range (such as ±0.1mm), and whether the hole distribution pattern is consistent (such as rectangular array or circular array). If all interface dimensions meet the preset matching rules, the docking relationship is determined to be assembleable, and the verification results are recorded in the interface matching table. Each item in the interface matching table includes the name of the paired sub-component, the associated group number, the connection interface type, the measured dimension value, and the matching status, such as "slide base-guide rail bracket, CG-01, bolt connection, M12×Φ13.5, matching passed". Based on the interface matching table, a list of connection methods between sub-components is determined, and the corresponding assembly direction is marked on the list of connection methods. This step clarifies the physical connection form used between each sub-component according to the connection interface type in the interface matching table, such as bolt connection, pin positioning, planar fitting, sliding fit, or interference fit, and summarizes these connection forms into a connection method list. At the same time, combined with the actual assembly process of the CNC machine tool, the assembly direction in three-dimensional space is specified for each connection method. The assembly direction is determined by the spatial orientation of the connection interface, usually represented by the coordinate axis direction, such as positive Z-axis (pressing from top to bottom), negative X-axis (horizontal pushing in), or bidirectional sliding Y-axis, etc. For example, the bolt connection between the slide and the guide rail bracket requires the application of a tightening force in the positive Z-axis direction to complete the assembly, so its assembly direction is marked as "+Z". The process of sliding the slide along the guide rail surface on the guide rail bracket corresponds to the movement in the X-axis direction, and the assembly direction is marked as "±X". This connection method list not only lists the connection types of each sub-component, but also includes assembly sequence suggestions and direction vector information, providing operational guidance for subsequent spatial positioning.Based on the assembly direction, each sub-component is sequentially positioned and simulated in three-dimensional space according to the interface matching relationship to obtain an assembly simulation model. In specific execution, the three-dimensional models of all sub-components are imported into the assembly simulation software environment. A certain reference sub-component (such as the guide rail bracket) is used as the assembly origin to fix its position. Then, according to the assembly direction indication in the connection method list, other sub-components are moved along the specified direction and brought close to the connection interface. The software's constraint alignment function is used to automatically align the dimensions of the connection interface between the two sub-components. For example, the center of the threaded hole of the slide block is aligned with the center of the through hole of the guide rail bracket on the XY plane, and then translated downward along the +Z direction until the mating surfaces are in complete contact, completing the virtual assembly. This process strictly follows the dimensional matching relationship confirmed in the interface matching table and the assembly direction defined in the connection method list to ensure that the relative position of each sub-component in space is consistent with the actual machine tool assembly. Finally, after all sub-components are assembled in sequence, a complete assembly simulation model is formed. This model truly reflects the spatial layout and connection status of each sub-component in the physical machine tool, providing an accurate geometric basis for subsequent interference checks and structural optimization.

[0036] In a specific embodiment, adjusting the assembly simulation model according to the spatial interference region to obtain the adjusted assembly simulation model includes: Extract the three-dimensional contour data of the interferometric sub-components in the spatial interferometric region, and measure the overlap volume and overlap position coordinates of the three-dimensional contour data to obtain the interferometric parameter table; Based on the interference parameter table, the interference type is determined, and an adjustment scheme list is formulated according to the interference type; Based on the adjustment scheme list, the dimensions or spatial orientation of the interfering sub-components in the assembly simulation model are modified to obtain the adjusted pre-assembly. The spatial interference of the adjusted pre-assembly is then re-inspected to obtain the interference re-inspection result. When the interference re-inspection result shows no spatial interference area, the adjusted assembly simulation model is obtained.

[0037] Specifically, the three-dimensional contour data of the interfering sub-components in the spatial interference region are extracted, and the overlapping volume and coordinates of the overlapping position are measured to obtain an interference parameter table. This process is performed after the assembly simulation model completes the initial virtual assembly. The interference check function in the assembly simulation software is used to perform a global collision analysis on the entire assembly. The system automatically identifies the areas where geometric overlap occurs between the three-dimensional models of different sub-components, which are the spatial interference regions. Subsequently, for each detected spatial interference region, the software extracts the three-dimensional contour data of two or more interfering sub-components involved in the interference. This three-dimensional contour data includes the patch mesh, boundary line segments, and vertex coordinate information corresponding to the interference region. The intersection operation in Boolean operations is used to calculate the geometry of the overlapping part, and its volume, i.e., the overlapping volume, is calculated based on this geometry. At the same time, the coordinates of the overlapping geometry in the global coordinate system are recorded. The three-dimensional coordinates of the center position, maximum extension range, and key points under the standard system, i.e., the coordinates of the overlapping position, are all quantitative data. These data, along with the names of the interfering sub-components and their associated group numbers, are summarized to form an interference parameter table. For example, in the assembly simulation model of a CNC milling machine, after the slide and guide rail bracket are assembled, the system detects a spatial interference area. After extraction, it is found that the reinforcing rib structure at the bottom of the slide collides with the bolt boss on the guide rail bracket. At this time, the software extracts the three-dimensional contour data of the slide reinforcing rib and bolt boss in the interference area, and measures the overlapping volume as 12500mm³. The overlapping position coordinates are concentrated around X=420mm, Y=180mm, Z=95mm. This information is recorded in the interference parameter table, with the entry "Slide-Guide Rail Bracket, CG-01, Overlap Volume 12500mm³, Overlap Position (420,180,95)". The interference type is determined based on the interference parameter table, and an adjustment plan list is formulated according to the interference type. In specific implementation, the interference is classified according to the overlapping volume size, overlapping position coordinate distribution, and structural and functional attributes of the interfering sub-components in the interference parameter table. If the overlapping volume is small and located in a non-load-bearing area, it is determined to be a local dimensional deviation type interference; if the overlapping volume is large and involves critical mating surfaces, it is determined to be a design conflict type interference; if the interference occurs on the travel path of the moving part, it is determined to be a motion interference type. Corresponding adjustment strategies are formulated for different interference types, forming an adjustment plan list. For example, the interference between the slide and the guide rail bracket is determined to be a design conflict type interference because it occurs in the fixed connection area and the overlapping volume is large. The adjustment plan is to design a cut-out avoidance for the bottom reinforcing rib of the slide, with the cut-out size extended outward by 2mm according to the overlapping position coordinates to ensure a safe clearance, or alternatively, to adjust the height of the bolt boss on the guide rail bracket to reduce its Z-direction extension. This adjustment plan is recorded in the adjustment plan list, clearly indicating the modification object, modification method, and parameter range.Based on the adjustment scheme list, the dimensions or spatial orientation of the interfering sub-components in the assembly simulation model are modified to obtain the adjusted pre-assembly. The spatial interference is then re-inspected on the adjusted pre-assembly to obtain the interference re-inspection results. When the interference re-inspection results show no spatial interference area, the adjusted assembly simulation model is obtained. In this step, the 3D model of the interfering sub-component is opened in the 3D modeling environment, and geometric modification operations are performed according to the instructions in the adjustment scheme list. For example, slotting is performed on the slide reinforcing rib, with the slotted area centered at the overlapping position coordinates, and dimensions of 60mm in length and 30mm in width. After modifying the sub-component 3D model to a depth of 15mm, the updated model is re-imported into the assembly simulation environment, replacing the original model while maintaining the original assembly constraints. This forms the adjusted pre-assembly. The interference check function is then run again for a comprehensive re-inspection. The system recalculates the spatial relationships between all sub-components. If the interference re-inspection results do not report any overlapping areas, the adjustment is confirmed to be effective. The adjusted pre-assembly is then confirmed as the adjusted assembly simulation model. If new spatial interference areas still exist, the above extraction, judgment, and adjustment process is repeated until the interference is completely eliminated, ensuring that the final model is feasible for assembly.

[0038] In a specific embodiment, the step of performing material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculating the load-bearing capacity based on the material combination scheme, includes: The force points and directions of each sub-component in the adjusted assembly simulation model are marked to obtain a force marking diagram, and the load type of each sub-component is determined based on the force marking diagram; Based on the load type, suitable candidate materials are selected, and the candidate materials are subjected to pairing compatibility testing to obtain a material matching degree table. Based on the material matching degree table, the combination with the highest matching degree is selected to obtain the material combination scheme, and stress and strain calculations are performed on each sub-component in the material combination scheme to obtain the load-bearing capacity value.

[0039] Specifically, the force points and directions of each sub-component in the adjusted assembly simulation model are labeled to obtain a force labeling diagram. Based on the force labeling diagram, the load type of each sub-component is determined. This process, based on the adjusted assembly simulation model and combined with the actual operating conditions of the CNC machine tool, involves preprocessing the 3D model of each sub-component before force analysis. First, based on the machine tool dynamics characteristics and the force transmission path during machining, force points are labeled at key locations of each sub-component in the 3D simulation software. These force points are usually located in the force input, output, or concentrated transmission area. For example, on the slide sub-component of a CNC milling machine, the cutting force is mainly transmitted from the tool through the spindle to the slide guide contact surface. Therefore, multiple discrete points are selected as force points on the mating surface between the slide and the guide support, and their force directions are set according to typical machining conditions. Vertically downward (-Z direction) and horizontally in the feed direction (±X direction), while inertial force acts on the center of mass of the slide, so another force point is marked at the geometric center. The direction changes with acceleration and deceleration. All force points and their corresponding direction vectors are uniformly marked in the model to form a force annotation diagram. Then, based on the distribution characteristics, direction rules and dynamic changes of each force point in the force annotation diagram, the type of load borne by each sub-component is determined. If the force direction is fixed and the magnitude is constant, it is classified as a static load; if it changes periodically with time, it is classified as a dynamic load; if it involves impact or vibration, it is classified as an impact load. For the slide, since it bears periodically changing cutting force and acceleration and deceleration inertial force during the feed process, its load type is determined to be a dynamic load. The guide rail bracket mainly undertakes the support function, and the force is relatively stable, so it is determined to be a static load. Candidate materials are selected based on load type, and pairing compatibility tests are performed on these materials to obtain a material matching table. In practice, metals or composite materials that meet the requirements of each load type are retrieved from the material database as candidate materials. For example, for slides subjected to dynamic loads, candidate materials include high-strength cast iron HT300, alloy steel 40Cr, and ductile iron QT600; for guide rail supports subjected to static loads and requiring weight reduction, candidate materials include aluminum alloy 7075-T6 and cast aluminum ZL101A, etc. Subsequently, pairing compatibility tests are performed on the selected candidate materials for each pair of paired sub-components (such as slides and guide rail supports). The content covers differences in thermal expansion coefficients, electrochemical corrosion tendency, hardness matching, and adaptability of connection processes. For example, when the slide is made of cast iron and the guide rail bracket is made of aluminum alloy, there is a large potential difference between the two, which can easily lead to electrochemical corrosion. Moreover, the difference in thermal expansion coefficients is significant, affecting long-term operational accuracy. Therefore, the compatibility score of this combination is low. However, if both the slide and the guide rail bracket are made of cast iron, the compatibility is high. The compatibility evaluation results of all candidate material combinations are recorded in the form of quantitative scores to form a material matching degree table. Each row corresponds to a material pairing scheme, and the columns include the sub-component name, candidate material, compatibility score, and overall matching degree.Based on the material matching degree table, the combination with the highest matching degree is selected to obtain the material combination scheme. Stress and strain calculations are then performed on each sub-component in the material combination scheme to obtain the load-bearing capacity value. This step selects the material combination with the highest overall matching degree from the material matching degree table. For example, in the pairing of slide block and guide rail bracket, the slide block is made of HT300 cast iron (matching degree 92 points), and the guide rail bracket is made of ZG230-450 cast steel (matching degree 88 points). This combination is selected as the optimal scheme because of its close thermal expansion coefficient, good hardness matching, and no risk of electrochemical corrosion. The material properties of the material combination scheme were then assigned to the corresponding three-dimensional models of the sub-components in the finite element analysis software. Parameters such as elastic modulus, Poisson's ratio, density, and yield strength were set, meshes were generated, and boundary conditions and loads were applied. Static and modal joint simulations were performed to calculate the stress distribution, strain degree, and maximum deformation of each sub-component under rated working conditions. The final output showed that the maximum equivalent stress of the slide was 185 MPa, the safety factor was 2.8, and the maximum displacement of the guide rail bracket was 0.012 mm. The overall load-bearing capacity was thus determined, providing a quantitative basis for subsequent optimization.

[0040] In a specific embodiment, optimizing the entire machine tool component entity based on the load-bearing capacity and material combination scheme to obtain the optimized machine tool component entity includes: Based on the load-bearing capacity values, key stress areas are marked for each sub-component in the adjusted assembly simulation model to obtain a key stress area diagram. Stress concentration factors are then calculated for each sub-component in the key stress area diagram to obtain a stress concentration factor table. Structural reinforcement design is performed on the key stress areas of each sub-component using the stress concentration factor table to obtain a structural reinforcement scheme. The assembly simulation model is then updated based on the structural reinforcement scheme to obtain an updated assembly simulation model. The weight distribution of each sub-component in the updated assembly simulation model is calculated based on the material combination scheme to obtain a sub-component weight distribution table. The center of gravity position of the updated assembly simulation model is then calculated using the sub-component weight distribution table to obtain the center of gravity coordinates. The overall balance of the updated assembly simulation model is adjusted based on the center of gravity coordinates to obtain a balance adjustment scheme. Finally, the entire machine tool component entity is optimized based on the balance adjustment scheme to obtain an optimized machine tool component entity.

[0041] Specifically, based on the load-bearing capacity values, key stress areas are marked for each sub-component in the adjusted assembly simulation model, resulting in a key stress area map. Stress concentration factors are then calculated for each sub-component in the key stress area map, yielding a stress concentration factor table. This process, building upon material matching analysis and load-bearing capacity calculations, combines the stress distribution cloud map from the finite element simulation results with visualization processing of the adjusted assembly simulation model in a 3D modeling environment. By combining areas with high stress levels with locations of structural geometric abrupt changes, the parts of each sub-component most prone to fatigue failure or deformation under actual working conditions are identified. These parts are the key stress areas and are highlighted on the model with different colors or... Boundary lines are marked to form a critical stress area map. For example, in the slide sub-component of a CNC milling machine, the area around the threaded hole connecting to the lead screw nut seat becomes a key marked area due to load concentration and hole edge effect. At the same time, the corners where the guide rail mounting surface and the main structure meet are also included in the critical stress area due to the discontinuous shape transition. Subsequently, for each marked critical stress area, the local stress extraction function of the simulation software is used to evaluate its stress concentration degree in combination with the nominal load level borne by the area, and quantitative values ​​are generated and recorded in the stress concentration factor table. This table includes the name of each sub-component, the location of the critical stress area and its corresponding stress concentration factor value, which is used for subsequent structural optimization decisions. By using a stress concentration factor table, structural reinforcement designs are performed on the key stress areas of each sub-component to obtain a structural reinforcement scheme. Based on the structural reinforcement scheme, the assembly simulation model is updated to obtain an updated assembly simulation model. In specific execution, the value in the stress concentration factor table is used to determine whether structural improvements are needed. For areas with higher coefficients, optimization measures are prioritized. For example, for the high stress state around the threaded hole of the slide block, methods such as increasing the local wall thickness, expanding the countersunk hole structure, or setting a reinforcing ring are adopted to improve its load-bearing capacity. For the corner area at the connection between the guide rail bracket and the base, the force flow transmission path is improved by increasing the fillet transition radius or adding auxiliary support ribs. All these improvement measures are summarized to form a structural reinforcement scheme. In the 3D modeling environment, the corresponding 3D models of the sub-components in the original assembly simulation model are geometrically modified to ensure that the modified model still meets the assembly constraints and connection interface matching requirements. After all structural adjustments are completed, the updated assembly simulation model is generated.Based on the material combination scheme, the weight distribution of each sub-component in the updated assembly simulation model is calculated to obtain a sub-component weight distribution table. Then, the center of gravity position of the updated assembly simulation model is calculated using this table to obtain the coordinates of the center of gravity. This step, based on the material types of each sub-component determined in the material combination scheme (e.g., high-strength cast iron for the slide and cast steel for the guide rail bracket), combined with the actual geometric volume of each sub-component in the updated assembly simulation model, calculates the mass data of each sub-component and records its center of gravity position information in the overall coordinate system. All data is summarized into a sub-component weight distribution table, covering the sub-component name, material type, mass value, and local center of gravity coordinates. On this basis, considering the mass and spatial distribution of all sub-components, the overall center of gravity position coordinates of the entire assembly are determined through system-level center of gravity calculation logic. For example, the calculation shows that the center of gravity of the CNC milling machine bed component is located at a specific three-dimensional coordinate point above the equipment base. Based on the center of gravity coordinates, the updated assembly simulation model is balanced to obtain a balance adjustment scheme. Based on the balance adjustment scheme, the entire machine tool component entity is optimized to obtain an optimized machine tool component entity. In specific operation, the calculated center of gravity coordinates are compared with the reference center of gravity position expected in the machine tool design. If there is a significant offset, a balance compensation mechanism is activated. For example, a local reinforcement structure is added in the symmetrical direction of the offset side of the center of gravity or a weight reduction and slotting treatment is implemented in the non-load-bearing area to achieve a rebalancing of the mass distribution. This adjustment strategy forms a balance adjustment scheme and is applied to the updated assembly simulation model. After completing the structural adjustment and mass redistribution, the center of gravity position is rechecked until the overall machine stability requirements are met. The final confirmed structural form and material configuration together constitute the optimized machine tool component entity.

[0042] The above describes the machine tool component structure optimization design method in the embodiments of the present invention. The following describes the machine tool component structure optimization design device in the embodiments of the present invention. Please refer to [link / reference]. Figure 2 One embodiment of the machine tool component structure optimization design system of the present invention includes: The scanning module 21 is used to scan the machine tool component entity to obtain a 3D model of the component, and to disassemble the 3D model of the component to obtain multiple sub-component 3D models; the calculation module 22 is used to calculate the dimensions of each sub-component in the sub-component 3D model to obtain a sub-component dimension parameter table; the simulation module 23 is used to simulate the assembly relationship of each sub-component based on the sub-component dimension parameter table to obtain an assembly simulation model. When the assembly simulation model has a spatial interference region, the assembly simulation model is adjusted according to the spatial interference region to obtain an adjusted assembly simulation model; the analysis module 24 is used to perform material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and to calculate the load-bearing capacity based on the material combination scheme; the optimization module 25 is used to optimize the entire machine tool component entity based on the load-bearing capacity and the material combination scheme to obtain an optimized machine tool component entity.

[0043] In this embodiment, the specific implementation of each unit in the above device embodiment is described in the above method embodiment, and will not be repeated here.

[0044] Reference Figure 3 This invention also provides a computer device whose internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0045] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present invention and do not constitute a limitation on the computer devices on which the present invention is applied.

[0046] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0047] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0048] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0049] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for optimizing the structural design of machine tool components, characterized in that, Includes the following steps: Scan the machine tool component entity to obtain a 3D model of the component, and then disassemble the 3D model of the component to obtain multiple 3D models of sub-components; Calculate the dimensions of each sub-component in the 3D model of the sub-component to obtain a sub-component dimension parameter table; Based on the sub-component size parameter table, the assembly relationship of each sub-component is simulated to obtain an assembly simulation model. When the assembly simulation model has a spatial interference region, the assembly simulation model is adjusted according to the spatial interference region to obtain an adjusted assembly simulation model. Based on the adjusted assembly simulation model, material matching analysis is performed on each sub-component to obtain a material combination scheme, and the load-bearing capacity is calculated based on the material combination scheme. Based on the aforementioned load-bearing capacity and material combination scheme, the entire machine tool component entity is optimized to obtain the optimized machine tool component entity.

2. The machine tool component structure optimization design method according to claim 1, characterized in that, The scanning machine tool component entity is used to obtain a 3D model of the component, and the 3D model of the component is structurally disassembled to obtain multiple sub-component 3D models, including: The machine tool component is scanned from all angles using a 3D laser scanner to obtain the original point cloud of the component. Redundant points in the original point cloud are then filtered to obtain a simplified point cloud image. Based on the simplified point cloud map, the connection features of the machine tool component entity are identified and labeled, and the simplified point cloud map is reconstructed into a surface according to the connection features to obtain a three-dimensional model of the component. Based on the connection features, the sub-component splitting boundary lines are determined, and the 3D model of the component is cut and separated according to the sub-component splitting boundary lines to obtain multiple sub-component 3D models.

3. The machine tool component structure optimization design method according to claim 1, characterized in that, The calculation of the dimensions of each sub-component in the 3D model of the sub-component, resulting in a sub-component dimension parameter table, includes: The three-dimensional models of the multiple sub-components are grouped according to their assembly relationships to obtain sub-component association groups. The dimensions of each sub-component within the sub-component association group are calculated to obtain a sub-component dimension parameter table that includes the sub-component name, association group number, and mating dimensions.

4. The machine tool component structure optimization design method according to claim 1, characterized in that, The assembly simulation model is obtained by simulating the assembly relationship of each sub-component based on the sub-component size parameter table, including: Based on the sub-component size parameter table, the connection interface size of each sub-component is extracted, and the matching of the connection interface size is verified to obtain an interface matching table; Based on the interface matching table, a list of connection methods between sub-components is determined, and the corresponding assembly direction is marked on the list of connection methods; Based on the assembly direction, each sub-component is sequentially positioned and simulated in three-dimensional space according to the interface matching relationship to obtain an assembly simulation model.

5. The machine tool component structure optimization design method according to claim 1, characterized in that, The step of adjusting the assembly simulation model according to the spatial interference region to obtain the adjusted assembly simulation model includes: Extract the three-dimensional contour data of the interferometric sub-components in the spatial interferometric region, and measure the overlap volume and overlap position coordinates of the three-dimensional contour data to obtain the interferometric parameter table; Based on the interference parameter table, the interference type is determined, and an adjustment scheme list is formulated according to the interference type; Based on the adjustment scheme list, the dimensions or spatial orientation of the interfering sub-components in the assembly simulation model are modified to obtain the adjusted pre-assembly. The spatial interference of the adjusted pre-assembly is then re-inspected to obtain the interference re-inspection result. When the interference re-inspection result shows no spatial interference area, the adjusted assembly simulation model is obtained.

6. The machine tool component structure optimization design method according to claim 1, characterized in that, The process of performing material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculating the load-bearing capacity based on the material combination scheme, includes: The force points and directions of each sub-component in the adjusted assembly simulation model are marked to obtain a force marking diagram, and the load type of each sub-component is determined based on the force marking diagram; Based on the load type, suitable candidate materials are selected, and the candidate materials are subjected to pairing compatibility testing to obtain a material matching degree table. Based on the material matching degree table, the combination with the highest matching degree is selected to obtain the material combination scheme, and stress and strain calculations are performed on each sub-component in the material combination scheme to obtain the load-bearing capacity value.

7. The machine tool component structure optimization design method according to claim 1, characterized in that, The optimization of the entire machine tool component entity based on the load-bearing capacity and material combination scheme yields the optimized machine tool component entity, including: Based on the load-bearing capacity values, key stress areas are marked for each sub-component in the adjusted assembly simulation model to obtain a key stress area diagram. Stress concentration factors are then calculated for each sub-component in the key stress area diagram to obtain a stress concentration factor table. Structural reinforcement design is performed on the key stress areas of each sub-component using the stress concentration factor table to obtain a structural reinforcement scheme. The assembly simulation model is then updated based on the structural reinforcement scheme to obtain an updated assembly simulation model. The weight distribution of each sub-component in the updated assembly simulation model is calculated based on the material combination scheme to obtain a sub-component weight distribution table. The center of gravity position of the updated assembly simulation model is then calculated using the sub-component weight distribution table to obtain the center of gravity coordinates. The overall balance of the updated assembly simulation model is adjusted based on the center of gravity coordinates to obtain a balance adjustment scheme. Finally, the entire machine tool component entity is optimized based on the balance adjustment scheme to obtain an optimized machine tool component entity.

8. A machine tool component structure optimization design device, characterized in that, include: The scanning module is used to scan the machine tool component entity to obtain a three-dimensional model of the component, and to disassemble the three-dimensional model of the component to obtain multiple three-dimensional models of sub-components; The calculation module is used to calculate the dimensions of each sub-component in the 3D model of the sub-component and obtain a sub-component dimension parameter table; The simulation module is used to simulate the assembly relationship of each sub-component based on the sub-component size parameter table to obtain an assembly simulation model. When the assembly simulation model has a spatial interference region, the assembly simulation model is adjusted according to the spatial interference region to obtain an adjusted assembly simulation model. The analysis module is used to perform material matching analysis on each sub-component based on the adjusted assembly simulation model to obtain a material combination scheme, and calculate the load-bearing capacity based on the material combination scheme. The optimization module is used to optimize the entire machine tool component entity based on the load-bearing capacity and material combination scheme, so as to obtain the optimized machine tool component entity.

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 method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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