Interactive mechanical model three-dimensional modeling method

Abstract

The invention relates to the technical field of three-dimensional modeling, in particular to a mechanical model three-dimensional modeling method based on interaction. The method comprises the following steps: performing initial mechanical three-dimensional model modeling on target mechanical equipment to obtain an initial three-dimensional mechanical model; performing model thermal stress state feature coupling on the initial three-dimensional mechanical model to obtain mechanical thermal stress state feature data; performing model embedding thermal compensation reconstruction on the initial three-dimensional mechanical model by utilizing the mechanical thermal stress state characteristic data to generate a mechanical thermal compensation three-dimensional model; carrying out mechanical working condition interaction event monitoring on the mechanical thermal compensation three-dimensional model, and carrying out multi-physical field thermal coupling simulation to obtain actual deformation simulation data of the model; and performing mechanical deformation deviation analysis according to the actual deformation simulation data of the model to generate thermal compensation evaluation data of the mechanical model. According to the method, deformation of the machine under the thermal-mechanical coupling effect is simulated through interactive simulation, and the model of the machine in the actual working condition is accurately constructed.

Description

Technical Field

[0001] The invention relates to the technical field of three-dimensional modeling, and in particular to a three-dimensional modeling method of a mechanical model based on interaction. Background Art

[0002] In the field of modern industrial design and manufacturing, the three-dimensional modeling of mechanical models is not only the basis of product design, but also the basis for subsequent engineering analysis, simulation verification and manufacturing. Three-dimensional modeling technology is one of the core technologies of CAD / CAE. It can present mechanical parts and assemblies in the form of three-dimensional digital models, providing basic data for subsequent simulation analysis, processing and manufacturing. At present, there are many mature three-dimensional modeling software on the market, such as SolidWorks, Creo, Inventor, etc. These software provide rich modeling tools and functions, which can easily create various complex geometric models. However, most of the existing three-dimensional modeling methods focus on the construction of geometric shapes, and do not consider the deformation of mechanical parts under actual working conditions. Especially in complex mechanical systems involving thermal-mechanical coupling, temperature changes will cause thermal expansion or contraction of parts, resulting in changes in the shape and size of parts. If the influence of these thermal deformations is ignored during the modeling process, the model will deviate from the actual situation, resulting in product design failure. Summary of the invention

[0003] Based on this, the present invention provides an interactive three-dimensional modeling method for mechanical models to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a three-dimensional modeling method of a mechanical model based on interaction includes the following steps:

[0005] Step S1: acquiring geometric information of the parts to be modeled of the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled; performing mechanical model preprocessing according to the geometric data of the mechanical parts to be modeled, and modeling an initial mechanical three-dimensional model, thereby obtaining an initial three-dimensional mechanical model;

[0006] Step S2: obtaining material thermal physical property parameters of the initial three-dimensional mechanical model to generate temperature-dependent nonlinear material parameters; optimizing the model finite element mesh according to the temperature-dependent nonlinear material parameters to obtain optimized finite element mesh data; coupling the model thermal stress state characteristics of the initial three-dimensional mechanical model based on the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data; visualizing the thermal stress deformation state of the initial three-dimensional mechanical model using the mechanical thermal stress state characteristic data to obtain thermal stress deformation cloud data of the mechanical model;

[0007] Step S3: performing displacement difference calculation according to the mechanical model thermal stress deformation cloud data to generate characteristic point displacement difference data; performing mechanical compensation parameter processing on the optimized finite element mesh data through the characteristic point displacement difference data to generate mechanical shape compensation parameters;

[0008] Step S4: using the mechanical shape compensation parameters to perform model embedding thermal compensation reconstruction on the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model;

[0009] Step S5: Initialize the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data; monitor the mechanical working condition interactive events of the mechanical thermal compensation three-dimensional model based on the interactive interface data, and perform multi-physical field thermal coupling simulation to obtain the actual deformation simulation data of the model; perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

[0010] The present invention acquires the geometric information of the parts and performs pre-processing to establish an initial three-dimensional model, takes into account the thermophysical parameters of the materials, can more accurately reflect the mechanical properties of the materials at different temperatures, and avoids the error caused by the simplification of material properties. The finite element mesh optimization is performed on the temperature-related nonlinear material parameters, the influence of temperature changes on the shape and size of the parts is quantified, and intuitively displayed, effectively avoiding the deviation between the model and the actual situation. Through the visualized deformation cloud data, the designer can intuitively understand the deformation of the parts at different temperatures, so as to better perform structural optimization design. By calculating the displacement difference of the characteristic points and processing the mechanical compensation parameters of the finite element mesh, the embedded thermal compensation reconstruction of the model is finally realized. According to the dynamic adjustment of temperature changes, the model can more accurately reflect the deformation of the parts under actual working conditions. An interactive interface is introduced, and multi-physical field thermal-mechanical coupling simulation is realized, which can interact with the model in real time and observe the deformation of the model under different working conditions. Through interactive simulation analysis, designers can have a deeper understanding of the performance of the model and discover potential problems in time. By performing deviation analysis on the simulation results, the thermal compensation effect of the model can be evaluated, and further guidance can be provided for the design of mechanical three-dimensional models. Therefore, the interactive three-dimensional modeling method of the mechanical model of the present invention allows designers to dynamically adjust model parameters and observe thermal deformation effects in real time by obtaining detailed geometric information and material properties of mechanical parts and combining the operation of a real-time interactive interface. By optimizing the finite element mesh and introducing nonlinear material parameters, the performance and reliability of mechanical design under complex working conditions are ensured, and a real-time feedback mechanism is provided, so that designers can quickly identify and solve potential problems in the design stage, providing further guidance for the design of mechanical three-dimensional models.

[0011] Preferably, step S1 comprises the following steps:

[0012] Step S11: acquiring geometric information of the parts to be modeled from the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled;

[0013] Step S12: performing 3D CAD solid modeling according to the geometric data of the mechanical part to be modeled, to obtain 3D mechanical part model data;

[0014] Step S13: performing assembly relationship analysis on the target mechanical equipment through the three-dimensional mechanical parts model data to generate mechanical parts assembly relationship data;

[0015] Step S14: extracting part working condition parameters from the three-dimensional mechanical part model data to obtain the mechanical part working condition parameters;

[0016] Step S15: An initial three-dimensional mechanical model is constructed by using the three-dimensional mechanical part model data according to the mechanical part assembly relationship data, and the model is pre-processed using the mechanical part working condition parameters, so as to obtain an initial three-dimensional mechanical model.

[0017] The present invention obtains geometric information of the parts to be modeled and uses three-dimensional CAD software for entity modeling, thereby ensuring the geometric accuracy and integrity of the model. This is more accurate than the traditional modeling method based on simplified geometric bodies and can more truly reflect the shape characteristics of the parts. By analyzing the assembly relationship of the target mechanical equipment and integrating it into the model building process, the structural integrity and assembly accuracy of the model can be ensured. This avoids the result deviation caused by assembly relationship errors in subsequent simulation analysis and improves the reliability of the simulation. It is applied to the model in the model pre-processing stage, which enables the model to more accurately reflect the stress state and deformation of the parts under actual working conditions.

[0018] Preferably, step S2 comprises the following steps:

[0019] Step S21: performing initial finite element mesh division of mechanical parts on the initial three-dimensional mechanical model to obtain initial finite element mesh data of the model;

[0020] Step S22: acquiring material thermal physical property parameters from the initial finite element mesh data of the model to generate temperature-dependent nonlinear material parameters;

[0021] Step S23: performing anisotropic thermal coefficient processing on the initial three-dimensional mechanical model through temperature-dependent nonlinear material parameters to generate anisotropic thermal conductivity matrix data;

[0022] Step S24: optimizing the initial finite element mesh data of the model by mechanical mesh unit through the anisotropic thermal conductivity matrix data to obtain optimized finite element mesh data; performing iterative temperature field processing according to the optimized finite element mesh data to obtain steady-state temperature field distribution data;

[0023] Step S25: performing model thermal stress state characteristic coupling on the initial three-dimensional mechanical model according to the steady-state temperature field distribution data and the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data;

[0024] Step S26: using the mechanical thermal stress state characteristic data to visualize the thermal stress deformation state of the initial three-dimensional mechanical model, thereby obtaining the mechanical model thermal stress deformation cloud data.

[0025] The present invention performs finite element meshing on the initial three-dimensional model and introduces temperature-related nonlinear material parameters into the model, so that the model can more accurately reflect the mechanical properties of the material at different temperatures, which effectively avoids the errors caused by the simplification of material properties. The finite element mesh is optimized by the anisotropic thermal conductivity matrix, which enables the model to more accurately simulate heat conduction in different directions, thereby more accurately capturing the temperature distribution and thermal stress gradient inside the part, especially for materials with significant anisotropy such as composite materials. The thermal stress state of the part under the action of a steady-state temperature field can be more accurately calculated through iterative temperature field processing. By observing the deformation cloud map, engineers can quickly identify the stress concentration areas and potential failure risks of the parts, thereby providing guidance for structural optimization design.

[0026] Preferably, step S24 includes the following steps:

[0027] Step S241: setting the thermal boundary conditions of the mechanical model for the initial three-dimensional mechanical model by using the initial finite element mesh data of the model to generate the thermal boundary condition data of the model;

[0028] Step S242: performing mechanical heat conduction control processing according to the anisotropic thermal conductivity matrix data, and performing grid node temperature calculation according to the model thermal boundary condition data to generate grid node temperature data;

[0029] Step S243: performing preliminary temperature field distribution processing on the initial three-dimensional mechanical model through the grid node temperature data to obtain preliminary temperature field data;

[0030] Step S244: Calculate the temperature gradient of the preliminary temperature field data to generate model grid node temperature gradient data;

[0031] Step S245: traversing the grid cells according to the temperature gradient data of the model grid nodes, and marking the grid cells with high temperature gradient using a preset temperature gradient threshold, to obtain the number data of the grid cells to be refined;

[0032] Step S246: performing mechanical mesh unit segmentation according to the mesh unit number data to be refined, and generating new mesh unit node data;

[0033] Step S247: mapping the new mesh unit node data to the old mesh unit relationship to obtain optimized finite element mesh data;

[0034] Step S248: Perform new node temperature interpolation calculation on the preliminary temperature field data, and perform iterative temperature field processing on the optimized finite element mesh data through the anisotropic thermal conductivity matrix data, so as to obtain steady-state temperature field distribution data.

[0035] The present invention realizes accurate simulation of temperature field distribution by iteratively refining grids and calculating temperature fields, especially in areas with large temperature gradients, the accuracy of the model is significantly improved. The thermal boundary conditions of the model are set, and the heat conduction control processing is carried out in combination with the anisotropic thermal conductivity matrix, which provides a basis for temperature field calculation. By calculating the grid node temperature, a preliminary temperature field distribution is obtained. By calculating the temperature gradient and marking the high temperature gradient grid unit, the area where the temperature field changes drastically can be identified. Then, the grid is refined in these areas, and the temperature interpolation calculation is performed on the new node. This adaptive grid refinement strategy based on temperature gradient can concentrate computing resources on areas with drastic temperature changes, thereby improving the accuracy of the model while ensuring computing efficiency. Through iterative temperature field processing, this iterative calculation process combines grid refinement and temperature field update, can more accurately capture the details of the temperature field, especially in areas with large temperature gradients, such as near heat sources or at material interfaces, can more effectively simulate complex temperature field distribution, more accurately reflect the actual temperature distribution of parts, thereby improving the accuracy and reliability of subsequent analysis.

[0036] Preferably, step S25 comprises the following steps:

[0037] Step S251: Calculate the thermal expansion coefficient according to the anisotropic thermal conductivity matrix data to generate a temperature-dependent thermal expansion coefficient;

[0038] Step S252: performing finite element temperature load processing on the steady-state temperature field distribution data to obtain finite element model temperature load data;

[0039] Step S253: Calculate the grid unit temperature difference according to the finite element model temperature load data to generate grid unit temperature change data;

[0040] Step S254: Calculate the thermal strain of the grid unit according to the temperature-related thermal expansion coefficient and the grid unit temperature change data to generate the grid unit thermal strain data;

[0041] Step S255: performing thermal expansion deformation analysis on the initial three-dimensional mechanical model through the thermal strain data of the grid unit to generate thermal expansion deformation data of the mechanical model;

[0042] Step S256: extracting the material elastic modulus according to the temperature-related nonlinear material parameters to obtain the mechanical equipment material elastic modulus data;

[0043] Step S257: performing inter-unit stress transfer analysis on the mechanical model thermal expansion deformation data through the mechanical equipment material elastic modulus data, and performing grid unit thermal stress calculation to generate mechanical model thermal stress distribution data;

[0044] Step S258: performing nonlinear finite element thermal characteristic coupling on the initial three-dimensional mechanical model through the mechanical model thermal expansion deformation data and the mechanical model thermal stress distribution data, and updating the unit thermal stress state, thereby obtaining mechanical thermal stress state characteristic data.

[0045] The present invention calculates the temperature-related thermal expansion coefficient based on the anisotropic thermal conductivity matrix, and performs finite element temperature load processing in combination with the steady-state temperature field distribution data. By calculating the temperature difference and thermal strain of the grid unit, the thermal expansion deformation data of the model is obtained. The thermal expansion deformation data is subjected to inter-unit stress transfer analysis, and the thermal stress distribution of the grid unit is calculated, which enables the model to more accurately reflect the stress state inside the part, especially in areas with drastic temperature changes. Through the nonlinear finite element thermal characteristic coupling, the interaction between the temperature field and the stress field can be more comprehensively considered, thereby more accurately simulating the deformation and stress state of the part under the action of thermal coupling. Finally, the obtained mechanical thermal stress state characteristic data can more comprehensively and accurately reflect the stress and deformation of the part under actual working conditions.

[0046] Preferably, step S255 includes the following steps:

[0047] Calculate the three-dimensional linear expansion of the mesh unit thermal strain data to generate mesh unit linear expansion data;

[0048] Perform node displacement component analysis based on grid unit linear expansion data to obtain grid node displacement component data;

[0049] Calculate the displacement of points in the unit according to the grid node displacement component data to generate grid unit point displacement data;

[0050] The thermal expansion deformation of the surface nodes of the initial three-dimensional mechanical model is processed based on the point displacement data in the mesh unit and the optimized finite element mesh data to generate the thermal expansion deformation data of the mechanical model.

[0051] The present invention calculates the linear expansion data of each unit by performing unit three-dimensional linear expansion calculation on the thermal strain data of the grid unit. By analyzing the node displacement component, the displacement component data of each grid node is obtained, which reflects the displacement of each node under the action of thermal expansion, calculates the displacement of the points within the unit, and thus obtains more detailed unit deformation information. This is more accurate than the method that only considers the node displacement, and can more accurately reflect the deformation inside the unit. The initial three-dimensional mechanical model is processed with the thermal expansion deformation of the surface nodes, and an accurate description of the overall deformation of the model is achieved, which can more accurately reflect the shape change of the model under the action of thermal expansion and the deformation of the parts under temperature changes.

[0052] Preferably, step S3 comprises the following steps:

[0053] Step S31: extracting characteristic point displacements according to the mechanical model thermal stress deformation cloud data to generate model characteristic point displacement data;

[0054] Step S32: calculating the displacement difference of the initial three-dimensional mechanical model through the displacement data of the model feature points to generate feature point displacement difference data;

[0055] Step S33: Processing mechanical process constraint conditions according to temperature-related nonlinear material parameters to generate mechanical process constraint condition data;

[0056] Step S34: setting a compensation target according to the feature point displacement difference data, and solving the feature point compensation amount for the mechanical process constraint condition data using a sequential quadratic programming algorithm to generate feature point compensation amount data;

[0057] Step S35: Processing the optimized finite element mesh data with mechanical compensation parameters using the feature point compensation data to generate mechanical shape compensation parameters.

[0058] The present invention obtains the characteristic point displacement difference data by extracting the characteristic point displacement in the thermal stress deformation cloud data of the mechanical model and comparing it with the initial model. This reflects the influence of thermal stress deformation on the shape of the model. Considering the mechanical process constraints, such as material properties, processing accuracy, etc., and using the sequential quadratic programming algorithm to solve the characteristic point compensation, the characteristic point compensation data obtained by solving can correct the shape deviation caused by thermal stress deformation to the greatest extent under the premise of meeting the process constraints. The characteristic point compensation data is applied to the optimized finite element mesh. These parameters contain the information of model shape correction, which can more effectively predict the final shape of the part and provide precise guidance for the thermal compensation reconstruction of the model, thereby ensuring the accuracy and reliability of the final model.

[0059] Preferably, step S35 includes the following steps:

[0060] Step S351: performing displacement interpolation and inversion according to the feature point compensation amount data, and performing preliminary compensation size calculation to generate preliminary compensation size data;

[0061] Step S352: updating the mesh node coordinates of the optimized finite element mesh data through the preliminary compensation size data, and performing initial compensation surface fitting to generate initial compensation surface data;

[0062] Step S353: performing smoothing processing on the initial compensation surface data to generate smooth compensation surface data;

[0063] Step S354: performing compensation surface point cloud distance calculation according to the smooth compensation surface data, and adjusting the surface deviation to obtain optimized mechanical compensation adjustment surface data;

[0064] Step S355: extracting mechanical compensation shape parameters according to the optimized mechanical compensation adjustment surface data to generate mechanical shape compensation parameters.

[0065] The present invention performs displacement interpolation inversion and preliminary compensation size calculation based on feature point compensation data to obtain preliminary compensation size data, which provides basic data for subsequent grid node coordinate update and surface fitting. By updating the grid node coordinates and performing initial compensation surface fitting, in order to ensure the smoothness and continuity of the compensation surface, the initial surface is smoothed. This avoids sharp corners or mutations on the surface and improves the surface quality. The point cloud distance calculation and surface deviation adjustment are performed on the smoothed compensation surface, which enables the compensation surface to fit the target shape more accurately, thereby more effectively correcting the shape deviation caused by thermal stress deformation. Mechanical shape compensation parameters are extracted from the optimized compensation surface. These parameters contain precise geometric information, which can guide the thermal compensation reconstruction of the model, so that the final model is closer to the actual shape of the part after processing, thereby achieving accurate correction of the model shape.

[0066] Preferably, step S4 comprises the following steps:

[0067] Step S41: performing CAD parameter processing on the mechanical shape compensation parameters to generate CAD model compensation parameters;

[0068] Step S42: performing compensation feature association constraint processing on the initial three-dimensional mechanical model through CAD model compensation parameters to obtain feature association constraint data;

[0069] Step S43: embedding the feature association constraint data into a thermal compensation logic process, and reconstructing the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model.

[0070] The present invention converts mechanical shape compensation parameters into CAD model compensation parameters so that these parameters can be recognized and used by CAD software. The initial three-dimensional mechanical model is subjected to compensation feature association constraint processing through the CAD model compensation parameters, and the compensation parameters are associated with the features of the model, thereby ensuring the accuracy and effectiveness of the compensation. By establishing feature association constraints, it can be ensured that the compensation amount is correctly applied to the corresponding position of the model, thereby avoiding compensation errors. The compensation information is integrated into the geometric structure of the model to achieve thermal compensation of the model. The new model not only contains the original geometric information, but also contains thermal deformation compensation information, thereby more accurately reflecting the shape of the parts under actual working conditions, and can effectively improve the accuracy and reliability of the model. The mechanical thermal compensation three-dimensional model finally generated more accurately reflects the true shape of the parts under the action of thermal-mechanical coupling.

[0071] Preferably, step S5 comprises the following steps:

[0072] Step S51: Initializing the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data;

[0073] Step S52: setting an interactive monitoring point for the interactive interface data to obtain interactive monitoring point data;

[0074] Step S53: using the interactive monitoring point data to monitor the mechanical working condition interactive events, and generating mechanical working condition interactive event data;

[0075] Step S54: responding to the mechanical working condition interaction event data, and mapping the working condition physical field simulation parameters through a preset physical field simulation parameter library to generate interactive mechanical working condition physical parameters;

[0076] Step S55: using the physical parameters of the interactive mechanical working condition to perform multi-physical field thermal-mechanical coupling simulation on the mechanical thermal compensation three-dimensional model, and extracting the model simulation deformation characteristics to obtain the actual deformation simulation data of the model;

[0077] Step S56: Perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

[0078] The present invention provides users with a convenient model operation and data input method by initializing the model interactive operation interface and setting interactive monitoring points. By monitoring the mechanical working condition interaction events, the working condition parameters input by the user, such as temperature, pressure, load, etc., can be obtained in real time. The working condition state response is performed according to the interactive event data, and the corresponding simulation parameters are mapped from the preset physical field simulation parameter library. This realizes the automatic matching of working condition parameters and simulation parameters, and uses the interactive mechanical working condition physical parameters to perform multi-physical field thermal coupling simulation on the mechanical thermal compensation three-dimensional model, and extracts the simulation deformation characteristics of the model to obtain the actual deformation simulation data of the model. By performing mechanical deformation deviation analysis on the actual deformation simulation data of the model, it can be used to evaluate the effect of thermal compensation, which can help designers better understand the performance of the model and quickly discover potential problems, and can more effectively support design iteration and optimization, thereby improving the efficiency and quality of mechanical product design. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A schematic diagram of the steps of the interactive three-dimensional mechanical modeling method of the present invention;

[0080] Figure 2 for Figure 1 Detailed implementation steps of step S1 in FIG.

[0081] Figure 3 for Figure 1 Detailed implementation steps of step S5;

[0082] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0083] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0084] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0085] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0086] To achieve this, please refer to Figures 1 to 3 The present invention provides an interactive three-dimensional modeling method for a mechanical model, comprising the following steps:

[0087] Step S1: acquiring geometric information of the parts to be modeled of the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled; performing mechanical model preprocessing according to the geometric data of the mechanical parts to be modeled, and modeling an initial mechanical three-dimensional model, thereby obtaining an initial three-dimensional mechanical model;

[0088] Step S2: obtaining material thermal physical property parameters of the initial three-dimensional mechanical model to generate temperature-dependent nonlinear material parameters; optimizing the model finite element mesh according to the temperature-dependent nonlinear material parameters to obtain optimized finite element mesh data; coupling the model thermal stress state characteristics of the initial three-dimensional mechanical model based on the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data; visualizing the thermal stress deformation state of the initial three-dimensional mechanical model using the mechanical thermal stress state characteristic data to obtain thermal stress deformation cloud data of the mechanical model;

[0089] Step S3: performing displacement difference calculation according to the mechanical model thermal stress deformation cloud data to generate characteristic point displacement difference data; performing mechanical compensation parameter processing on the optimized finite element mesh data through the characteristic point displacement difference data to generate mechanical shape compensation parameters;

[0090] Step S4: using the mechanical shape compensation parameters to perform model embedding thermal compensation reconstruction on the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model;

[0091] Step S5: Initialize the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data; monitor the mechanical working condition interactive events of the mechanical thermal compensation three-dimensional model based on the interactive interface data, and perform multi-physical field thermal coupling simulation to obtain the actual deformation simulation data of the model; perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

[0092] In the embodiment of the present invention, reference Figure 1FIG. 1 is a schematic diagram of the steps of the interactive three-dimensional modeling method of a mechanical model according to the present invention. In this embodiment, the interactive three-dimensional modeling method of a mechanical model comprises the following steps:

[0093] Step S1: acquiring geometric information of the parts to be modeled of the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled; performing mechanical model preprocessing according to the geometric data of the mechanical parts to be modeled, and modeling an initial mechanical three-dimensional model, thereby obtaining an initial three-dimensional mechanical model;

[0094] In the embodiment of the present invention, taking the centrifugal pump as an example, firstly, a three-coordinate measuring machine is used to collect geometric information of the parts to be modeled of the centrifugal pump, such as the pump casing, the impeller, etc., to obtain point cloud data. A laser scanner can also be used for scanning, or the CAD model of the parts can be directly exported from the design software. The acquired point cloud data is imported into reverse engineering software such as Geomagic Design X, and point cloud processing is performed, including denoising, streamlining, splicing and other operations to obtain a clear and complete point cloud model. Then, the surface reconstruction function in the software is used to convert the point cloud data into a NURBS surface, and surface fitting, smoothing and stitching and other operations are performed to construct an accurate three-dimensional model of each part. For the model exported from the CAD software, it is necessary to check the integrity and accuracy of the model, and perform necessary repair and simplification operations. Finally, the three-dimensional models of all parts are imported into three-dimensional modeling software such as SolidWorks for assembly to establish a complete initial three-dimensional model of the centrifugal pump.

[0095] Step S2: obtaining material thermal physical property parameters of the initial three-dimensional mechanical model to generate temperature-dependent nonlinear material parameters; optimizing the model finite element mesh according to the temperature-dependent nonlinear material parameters to obtain optimized finite element mesh data; coupling the model thermal stress state characteristics of the initial three-dimensional mechanical model based on the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data; visualizing the thermal stress deformation state of the initial three-dimensional mechanical model using the mechanical thermal stress state characteristic data to obtain thermal stress deformation cloud data of the mechanical model;

[0096] In the embodiment of the present invention, according to the materials of various parts of the centrifugal pump, such as cast iron of the pump casing, stainless steel of the impeller, etc., the corresponding material thermophysical parameters are found, including density, specific heat capacity, thermal conductivity, elastic modulus, Poisson's ratio, etc. Since these parameters will change with the change of temperature, it is necessary to obtain the parameter values ​​at different temperatures, and establish a temperature-dependent nonlinear material parameter model in the form of a fitting function or a table. These material parameters are assigned to the initial three-dimensional mechanical model. Next, the model is meshed using finite element analysis software such as ANSYS Workbench. According to the geometric shape and stress conditions of the model, a suitable mesh type and size are selected, and a mesh quality check is performed to ensure the rationality and accuracy of the mesh. In order to improve the calculation efficiency, a coarser mesh can be used for some areas with less stress or less deformation, while a denser mesh can be used for some key parts, such as the gap between the impeller and the pump casing. The temperature-dependent nonlinear material parameters and the optimized finite element mesh data are input into the finite element analysis software, and the corresponding boundary conditions and load conditions, such as the inlet pressure, outlet pressure, working temperature, etc. of the pump are set to perform thermal stress coupling analysis. After the solution is completed, the stress, strain and displacement data of the centrifugal pump at different working temperatures can be obtained.

[0097] Step S3: performing displacement difference calculation according to the mechanical model thermal stress deformation cloud data to generate characteristic point displacement difference data; performing mechanical compensation parameter processing on the optimized finite element mesh data through the characteristic point displacement difference data to generate mechanical shape compensation parameters;

[0098] In an embodiment of the present invention, the key feature points of the centrifugal pump, such as the tip of the impeller, the inlet and outlet of the pump casing, etc., are selected according to the thermal stress deformation cloud data of the mechanical model obtained in step S2. The displacement difference of these feature points at different operating temperatures is calculated, that is, the displacement at high temperature minus the displacement at normal temperature. These displacement difference data reflect the deformation of the centrifugal pump under thermal stress. These feature point displacement difference data are used as input, combined with the optimized finite element mesh data generated in step S2, and mathematical methods such as the least squares method are used to calculate the compensation parameters of each mesh node. These compensation parameters can be expressed as a displacement vector or a deformation gradient tensor, which is used to describe the shape compensation amount that each mesh node needs to perform under thermal stress.

[0099] Step S4: using the mechanical shape compensation parameters to perform model embedding thermal compensation reconstruction on the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model;

[0100] In an embodiment of the present invention, the converted compensation parameters are applied to the initial three-dimensional mechanical model to deform it. If the compensation parameter is a node displacement, the coordinates of the corresponding node are directly modified; if the compensation parameter is a surface deformation, the control points or other parameters of the surface need to be adjusted according to the deformation information. For the impeller of a centrifugal pump, for example, the blade thickness, curvature, etc. can be adjusted according to the compensation parameters to compensate for the deformation of the impeller at high temperatures. The deformed model needs to be verified to ensure that it meets the design requirements and geometric constraints. For example, check whether the deformed impeller interferes with the pump casing, whether the blade thickness meets the minimum wall thickness requirements, etc. If a problem is found, the compensation parameters need to be adjusted, and steps 2 and 3 are repeated until the requirements are met.

[0101] Step S5: Initialize the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data; monitor the mechanical working condition interactive events of the mechanical thermal compensation three-dimensional model based on the interactive interface data, and perform multi-physical field thermal coupling simulation to obtain the actual deformation simulation data of the model; perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

[0102] In an embodiment of the present invention, an interactive operation interface is initialized for the mechanical thermal compensation three-dimensional model. For example, a visual interface is created using software such as VTK or Unity3D to display the three-dimensional model of the centrifugal pump, and some interactive controls are set, such as a temperature input box, a working condition selection button, etc. Based on the initialized interactive interface, the user's operation events, such as changes in temperature values, selection of working conditions, etc., are monitored. When the user changes the input parameters, these parameters are passed to the finite element analysis software to perform multi-physics field thermal coupling simulation. For example, when the user enters a new operating temperature, the software automatically updates the material parameters and boundary conditions of the model, and re-performs the thermal stress coupling analysis to obtain new model actual deformation simulation data. The deformation data obtained by simulation is compared with the characteristic point displacement difference data calculated in step S3 to calculate the deformation deviation. For example, the difference between the simulated displacement and the compensation displacement of each characteristic point can be calculated, and the average deviation and the maximum deviation can be calculated. These deviation data can be used to evaluate the effect of thermal compensation of the mechanical model and provide a basis for further model optimization. These evaluation data are displayed on the interactive interface in the form of charts or reports to facilitate user analysis and decision-making.

[0103] As an example of the present invention, refer to Figure 2 As shown, Figure 1 Detailed implementation steps of step S1 in the flowchart, in this example, step S1 includes:

[0104] Step S11: acquiring geometric information of the parts to be modeled from the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled;

[0105] In the embodiment of the present invention, it is assumed that the target mechanical equipment is a centrifugal pump, and the geometric information of each part of the centrifugal pump is obtained. A variety of methods can be used to obtain geometric data, for example: 1. Use a three-dimensional measuring machine to scan existing physical parts, obtain point cloud data, and then convert the point cloud data into a geometric model that can be used for CAD modeling. This method is suitable for situations where physical parts already exist, and can accurately capture the actual shape of the parts. 2. If there is a two-dimensional engineering drawing of the part, you can use CAD software to manually draw a three-dimensional model of the part according to the drawing size. This method requires a certain amount of CAD operation experience, and the drawing needs to contain complete dimensional information. 3. If the target device already has a CAD model, you can directly read the CAD model file to obtain the geometric data of the part.

[0106] Step S12: performing 3D CAD solid modeling according to the geometric data of the mechanical part to be modeled, to obtain 3D mechanical part model data;

[0107] In an embodiment of the present invention, after obtaining the geometric data of each part of the centrifugal pump, solid modeling is performed using three-dimensional CAD software (such as SolidWorks, Creo, Inventor, etc.). According to the geometric data obtained in step S11, such as point cloud data, two-dimensional drawings or existing CAD models, a three-dimensional model of each part is created in the software. For example, when creating an impeller model, the three-dimensional solid model of the impeller can be constructed according to the geometric parameters of the impeller, such as the number of blades, blade shape, hub diameter, etc., using the modeling tools provided by the software, such as stretching, rotating, sweeping, etc. Similarly, according to the geometric data of parts such as pump casings, shafts, bearings, etc., their three-dimensional models are created respectively. During the modeling process, attention should be paid to the accuracy and details of the parts, such as chamfers, fillets, holes, etc., which need to be accurately modeled. The models of all parts are saved as CAD files, such as .sldprt, .prt, .ipt and other formats, which contain three-dimensional mechanical parts model data.

[0108] Step S13: performing assembly relationship analysis on the target mechanical equipment through the three-dimensional mechanical parts model data to generate mechanical parts assembly relationship data;

[0109] In an embodiment of the present invention, after completing the three-dimensional modeling of each part of the centrifugal pump, it is necessary to analyze the assembly relationship between them. The assembly relationship describes how the parts are connected and interact with each other. The assembly module in the CAD software can be used to perform assembly relationship analysis. The models of each part are imported into the assembly module, and the connection method between the parts is defined according to the actual assembly relationship, such as fit, connection, constraint, etc. For example, the impeller and the shaft are connected by a key, and the pump casing and the base are connected by bolts. When defining the assembly relationship, factors such as the fit tolerance and assembly order between the parts need to be considered. Through assembly relationship analysis, the relative position, motion relationship and assembly constraints between the parts can be determined, and this information can be saved as mechanical parts assembly relationship data.

[0110] Step S14: extracting part working condition parameters from the three-dimensional mechanical part model data to obtain the mechanical part working condition parameters;

[0111] In an embodiment of the present invention, for each part of the centrifugal pump, it is necessary to extract its parameters under specific working conditions. These parameters include material properties, loads, boundary conditions, etc. For example, the operating parameters of the impeller include the speed of the impeller, the inlet pressure, the outlet pressure, etc.; the operating parameters of the pump casing include the elastic modulus, Poisson's ratio, operating temperature, etc. of the material. These parameters can be obtained by consulting design documents, engineering manuals, or performing experimental measurements. For example, the speed of the impeller can be obtained from the design specifications of the centrifugal pump, and the elastic modulus of the material can be found in the material manual.

[0112] Step S15: An initial three-dimensional mechanical model is constructed by using the three-dimensional mechanical part model data according to the mechanical part assembly relationship data, and the model is pre-processed using the mechanical part working condition parameters, so as to obtain an initial three-dimensional mechanical model.

[0113] In an embodiment of the present invention, the various parts are assembled together according to the connection mode and constraint conditions defined in the assembly relationship data. For example, the impeller model and the shaft model are assembled in a key connection manner, and the pump casing model and the base model are assembled in a bolt connection manner, and finally a complete centrifugal pump assembly model is formed. After the assembly is completed, the operating parameters of the mechanical parts extracted in step S14 are used to pre-process the model. The pre-processing process includes defining material properties, applying loads and boundary conditions, etc. For example, according to the operating parameters of the impeller, the speed, inlet pressure and outlet pressure of the impeller are set; according to the operating parameters of the pump casing, the elastic modulus, Poisson's ratio and operating temperature of the pump casing material are set. The purpose of model pre-processing is to prepare for subsequent simulation analysis. After assembly and pre-processing, the final initial three-dimensional mechanical model is obtained, which contains complete geometric information, assembly relationship and operating parameters.

[0114] Preferably, step S2 comprises the following steps:

[0115] Step S21: performing initial finite element mesh division of mechanical parts on the initial three-dimensional mechanical model to obtain initial finite element mesh data of the model;

[0116] Step S22: acquiring material thermal physical property parameters from the initial finite element mesh data of the model to generate temperature-dependent nonlinear material parameters;

[0117] Step S23: performing anisotropic thermal coefficient processing on the initial three-dimensional mechanical model through temperature-dependent nonlinear material parameters to generate anisotropic thermal conductivity matrix data;

[0118] Step S24: optimizing the initial finite element mesh data of the model by mechanical mesh unit through the anisotropic thermal conductivity matrix data to obtain optimized finite element mesh data; performing iterative temperature field processing according to the optimized finite element mesh data to obtain steady-state temperature field distribution data;

[0119] Step S25: performing model thermal stress state characteristic coupling on the initial three-dimensional mechanical model according to the steady-state temperature field distribution data and the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data;

[0120] Step S26: using the mechanical thermal stress state characteristic data to visualize the thermal stress deformation state of the initial three-dimensional mechanical model, thereby obtaining the mechanical model thermal stress deformation cloud data.

[0121] In the embodiment of the present invention, taking the centrifugal pump as an example, the initial three-dimensional mechanical model includes parts such as the impeller, pump casing, and shaft. Use finite element analysis software (such as ANSYS, ABAQUS, COMSOL, etc.) to perform initial mesh division on each part. You can choose a suitable mesh type, such as a tetrahedral mesh, a hexahedral mesh, etc. The initial mesh division does not need to be too fine, but the mesh quality needs to be guaranteed to avoid deformed meshes. For example, for parts with complex shapes such as impellers, adaptive mesh division technology can be used to automatically encrypt the mesh in areas with large curvature. After the division is completed, the software will generate the initial finite element mesh data of the model, including information such as node coordinates and unit connection relationships. According to the materials of each part of the centrifugal pump, query the material database or perform experimental measurements to obtain its thermophysical parameters, such as thermal conductivity, specific heat capacity, thermal expansion coefficient, etc. Since these parameters are usually temperature-related, especially for high temperature conditions, it is necessary to obtain temperature-related nonlinear material parameters. Some materials, such as composite materials, have anisotropic thermal conductivity characteristics, that is, different directions have different thermal conductivities. For such parts in centrifugal pumps, it is necessary to calculate the anisotropic thermal conductivity matrix based on the temperature-dependent nonlinear material parameters. This matrix describes the thermal conductivity of the material in different directions. For example, for orthotropic materials, the thermal conductivity matrix is ​​a 3x3 diagonal matrix, and the elements on the diagonal represent the thermal conductivity in the three main directions. Based on the anisotropic thermal conductivity matrix data, the initial finite element mesh is optimized. For example, the mesh is encrypted in areas with large heat flux density to improve the calculation accuracy. The mesh optimization tool provided by the finite element software can be used to automatically adjust the mesh density according to the calculation results. The optimized mesh data will be used for temperature field calculation. Set the boundary conditions of the centrifugal pump, such as inlet temperature, outlet temperature, heat flux density, etc., and then perform iterative temperature field calculation. The iterative calculation process is to continuously solve the heat conduction equation until the temperature field reaches a stable state. Finally, the steady-state temperature field distribution data, that is, the temperature values ​​at each position of the centrifugal pump, are obtained. The steady-state temperature field distribution data is applied to the optimized finite element model as a thermal load. Then a thermal stress coupling analysis is performed to calculate the stress and strain distribution of the centrifugal pump under the action of the temperature field. Thermal stress coupling analysis takes into account the influence of temperature field on the mechanical properties of materials, such as thermal expansion effect. The analysis results include information such as displacement, stress, strain, etc. of each node, that is, the characteristic data of mechanical thermal stress state. Use the post-processing function of finite element software to visualize the characteristic data of mechanical thermal stress state, such as generating temperature cloud map, displacement cloud map, stress cloud map, etc. These cloud maps can intuitively show the deformation and stress distribution of centrifugal pumps under the action of temperature field. For example, the temperature cloud map can show the temperature of each part of the centrifugal pump, the displacement cloud map can show the deformation size and direction of the centrifugal pump, and the stress cloud map can show the stress concentration area of ​​the centrifugal pump.

[0122] Preferably, step S24 includes the following steps:

[0123] Step S241: setting the thermal boundary conditions of the mechanical model for the initial three-dimensional mechanical model by using the initial finite element mesh data of the model to generate the thermal boundary condition data of the model;

[0124] Step S242: performing mechanical heat conduction control processing according to the anisotropic thermal conductivity matrix data, and performing grid node temperature calculation according to the model thermal boundary condition data to generate grid node temperature data;

[0125] Step S243: performing preliminary temperature field distribution processing on the initial three-dimensional mechanical model through the grid node temperature data to obtain preliminary temperature field data;

[0126] Step S244: Calculate the temperature gradient of the preliminary temperature field data to generate model grid node temperature gradient data;

[0127] Step S245: traversing the grid cells according to the temperature gradient data of the model grid nodes, and marking the grid cells with high temperature gradient using a preset temperature gradient threshold, to obtain the number data of the grid cells to be refined;

[0128] Step S246: performing mechanical mesh unit segmentation according to the mesh unit number data to be refined, and generating new mesh unit node data;

[0129] Step S247: mapping the new mesh unit node data to the old mesh unit relationship to obtain optimized finite element mesh data;

[0130] Step S248: Perform new node temperature interpolation calculation on the preliminary temperature field data, and perform iterative temperature field processing on the optimized finite element mesh data through the anisotropic thermal conductivity matrix data, so as to obtain steady-state temperature field distribution data.

[0131] In the embodiment of the present invention, taking a centrifugal pump as an example, its thermal boundary conditions include: fluid temperature and convection heat transfer coefficient at the inlet, pressure and convection heat transfer coefficient at the outlet, radiation heat transfer with the external environment, and heat flux density on certain components. According to the actual working conditions and design parameters of the centrifugal pump, these thermal boundary conditions are set in the finite element software. For example, the inlet boundary can be set to a constant temperature or convection heat transfer boundary, the outlet boundary can be set to a pressure outlet boundary, and the outer surface of the pump casing can be set to a radiation heat transfer boundary. After the setting is completed, the software will generate model thermal boundary condition data, which contains information such as temperature, convection heat transfer coefficient, pressure, and emissivity on each boundary. Using the finite element method, a heat conduction control equation is established based on the anisotropic thermal conductivity matrix data and the model thermal boundary condition data. The equation describes the heat transfer process in various parts of the centrifugal pump. Then, a numerical method, such as a finite difference method or a finite element method, is used to solve the heat conduction control equation and calculate the temperature value of each node in the initial finite element mesh of the model. During the calculation process, it is necessary to consider the thermal conductivity of different materials, the influence of boundary conditions, and the heat transfer between grid units. The temperature field distribution is displayed in the form of a cloud map using the visualization function of the finite element software. The preliminary temperature field data reflects the temperature distribution of the centrifugal pump under the initial meshing and boundary conditions. The temperature gradient of each node can be calculated using numerical differentiation methods, such as the central difference method. After the calculation is completed, the model mesh node temperature gradient data is generated, which contains the temperature gradient vector of each node. Traverse all mesh units and calculate the average temperature gradient or maximum temperature gradient of the unit according to the temperature gradient data of the nodes in each unit. Compare the calculated temperature gradient with the preset temperature gradient threshold. If the temperature gradient of the unit exceeds the threshold, it is considered that the temperature change of the unit is drastic and the mesh needs to be refined, and the number of the unit is added to the list of mesh unit number data to be refined. According to the mesh unit number data to be refined, the marked mesh units are split. For example, a tetrahedral unit can be split into four smaller tetrahedral units, or a hexahedral unit can be split into eight smaller hexahedral units. After the split, new mesh nodes and units are generated, and the coordinate information of these new nodes is added to the list of new mesh unit node data. Associate the newly generated grid units and nodes with the original grid units and nodes to establish a mapping relationship between the new and old grid units. For example, record which original unit each new unit is divided from, and the position of the new node in the original unit. For the newly generated grid nodes, it is necessary to perform temperature interpolation calculations based on the preliminary temperature field data to obtain the temperature value of the new node. Various interpolation methods can be used, such as linear interpolation, spline interpolation, etc. Then, based on the optimized finite element grid data and the new node temperature value, perform the temperature field calculation again. This calculation uses the same heat conduction control equations and boundary conditions as step S242, but uses a finer grid.Repeat the iterative calculation until the temperature field reaches a stable state, and finally obtain the steady-state temperature field distribution data.

[0132] Preferably, step S25 comprises the following steps:

[0133] Step S251: Calculate the thermal expansion coefficient according to the anisotropic thermal conductivity matrix data to generate a temperature-dependent thermal expansion coefficient;

[0134] Step S252: performing finite element temperature load processing on the steady-state temperature field distribution data to obtain finite element model temperature load data;

[0135] Step S253: Calculate the grid unit temperature difference according to the finite element model temperature load data to generate grid unit temperature change data;

[0136] Step S254: Calculate the thermal strain of the grid unit according to the temperature-related thermal expansion coefficient and the grid unit temperature change data to generate the grid unit thermal strain data;

[0137] Step S255: performing thermal expansion deformation analysis on the initial three-dimensional mechanical model through the thermal strain data of the grid unit to generate thermal expansion deformation data of the mechanical model;

[0138] Step S256: extracting the material elastic modulus according to the temperature-related nonlinear material parameters to obtain the mechanical equipment material elastic modulus data;

[0139] Step S257: performing inter-unit stress transfer analysis on the mechanical model thermal expansion deformation data through the mechanical equipment material elastic modulus data, and performing grid unit thermal stress calculation to generate mechanical model thermal stress distribution data;

[0140] Step S258: performing nonlinear finite element thermal characteristic coupling on the initial three-dimensional mechanical model through the mechanical model thermal expansion deformation data and the mechanical model thermal stress distribution data, and updating the unit thermal stress state, thereby obtaining mechanical thermal stress state characteristic data.

[0141] In an embodiment of the present invention, the thermal expansion coefficient of a material is usually temperature-dependent, and in anisotropic materials, the thermal expansion coefficients in different directions are different. Therefore, it is necessary to calculate the temperature-dependent thermal expansion coefficient based on the anisotropic thermal conductivity matrix data and the material properties. The thermal expansion coefficients at different temperatures can be obtained by consulting a material property database or performing experimental measurements. For anisotropic materials, it is necessary to obtain the thermal expansion coefficients in each main direction. If the thermal expansion coefficient of a material is linearly related to temperature, a linear interpolation method can be used to calculate the thermal expansion coefficient at any temperature; if the relationship is nonlinear, a polynomial fitting or other nonlinear fitting methods can be used. For example, for the impeller of a centrifugal pump, if the material is anisotropic, it is necessary to calculate the temperature-dependent thermal expansion coefficients of the impeller in radial, axial and tangential directions. Map the temperature values ​​to the nodes of the finite element model. Different finite element software has different data format requirements, which need to be processed accordingly according to the software used. For example, in ANSYS, a temperature load can be applied using the BF command or the LDREAD command. The finite element model temperature load data includes the temperature value of each node and the way the load is applied, such as directly applying the temperature or applying the heat flux density. The reference temperature can be set to the ambient temperature or the initial temperature. For example, for a tetrahedral unit, the average value of the temperatures of its four nodes is calculated, and then the reference temperature is subtracted to obtain the temperature change of the unit. The temperature change of all units is stored as grid unit temperature change data. Based on the temperature-dependent thermal expansion coefficient obtained in step S251 and the grid unit temperature change data obtained in step S253, the thermal strain of each grid unit is calculated. Thermal strain refers to the strain caused by temperature change, and its calculation formula is: thermal strain = thermal expansion coefficient × temperature change. For anisotropic materials, it is necessary to calculate the thermal strain in different directions according to the thermal expansion coefficient in different directions. The displacement of each node can be calculated using finite element analysis software. For example, for a centrifugal pump model, the deformation of various components such as impellers and pump casings at different temperatures can be calculated. These deformation data contain the displacement values ​​of each node in the three directions of x, y, and z, which constitute the thermal expansion deformation data of the mechanical model. According to the temperature-dependent nonlinear material parameters obtained in step S22, the material elastic modulus values ​​at different temperatures are extracted. These data can be obtained by consulting the material database or by experimental measurement. Due to thermal expansion and deformation, interaction forces will be generated between adjacent units, resulting in the generation of stress. The finite element software will calculate the stress state of each unit based on the material properties of the unit, the deformation amount, and the connection relationship between the units. The calculation results contain the stress tensor of each unit, including normal stress and shear stress, forming the thermal stress distribution data of the mechanical model. In each iteration, the finite element software will update the material properties and boundary conditions according to the current temperature field, deformation field, and stress field, and then recalculate the temperature field, deformation field, and stress field until the calculation results meet the predetermined accuracy requirements.The final unit thermal stress state data contains the temperature, displacement, stress, strain and other information of each unit, that is, the mechanical thermal stress state characteristic data.

[0142] Preferably, step S255 includes the following steps:

[0143] Calculate the three-dimensional linear expansion of the mesh unit thermal strain data to generate mesh unit linear expansion data;

[0144] Perform node displacement component analysis based on grid unit linear expansion data to obtain grid node displacement component data;

[0145] Calculate the displacement of points in the unit according to the grid node displacement component data to generate grid unit point displacement data;

[0146] The thermal expansion deformation of the surface nodes of the initial three-dimensional mechanical model is processed based on the point displacement data in the mesh unit and the optimized finite element mesh data to generate the thermal expansion deformation data of the mechanical model.

[0147] In an embodiment of the present invention, for each unit, it is necessary to calculate its linear expansion in three dimensions. Linear expansion refers to the change in the length of the unit side due to temperature change. The linear expansion can be calculated based on the original length of the unit, thermal strain and temperature change. For example, for a tetrahedral unit, it is necessary to calculate the linear expansion of its six sides. If the thermal strain of the unit is uniform, the linear expansion can be obtained by directly multiplying the thermal strain by the original side length. If the thermal strain is not uniform, it is necessary to perform an integral calculation on the unit, such as Gaussian integral, to obtain a more accurate linear expansion. After the calculation is completed, the linear expansion data of each unit is stored to form grid unit linear expansion data, which contains the linear expansion of each unit in the x, y, and z directions. Based on the calculated grid unit linear expansion data, the displacement components of each node in three dimensions are analyzed. A node is usually shared by multiple units, so it is necessary to weighted average the linear expansion of all units connected to the node to obtain the displacement component of the node. The weight can be determined based on the volume, area or other factors of the unit. For example, for a node on the impeller of a centrifugal pump, if it is connected to four tetrahedral elements, it is necessary to weighted average the linear expansion of these four elements in the three directions of x, y, and z to obtain the displacement components of the node in the three directions. For each element, it is necessary to calculate the displacement of any point inside it. The shape function interpolation method can be used to calculate the displacement of any point in the element based on the displacement components of the element nodes. The shape function is a function that describes the displacement distribution within the element, and its form depends on the type of element, such as linear element, quadratic element, etc. For example, for a tetrahedral element, a linear shape function can be used to calculate the displacement of any point in the element based on the displacement components of the four nodes. According to the optimized finite element mesh, the surface nodes of the model are determined. Then, for each surface node, find the element containing the node, and use the point displacement data in the mesh element to calculate the displacement of the node. If a surface node belongs to multiple elements, the displacements of these elements need to be weighted averaged. For example, for the surface nodes of a centrifugal pump impeller, it is necessary to calculate the displacement of the node in the x, y, and z directions based on the displacement data of the unit containing the node to form the thermal expansion deformation data of the mechanical model.

[0148] Preferably, step S3 comprises the following steps:

[0149] Step S31: extracting characteristic point displacements according to the mechanical model thermal stress deformation cloud data to generate model characteristic point displacement data;

[0150] Step S32: calculating the displacement difference of the initial three-dimensional mechanical model through the displacement data of the model feature points to generate feature point displacement difference data;

[0151] Step S33: Processing mechanical process constraint conditions according to temperature-related nonlinear material parameters to generate mechanical process constraint condition data;

[0152] Step S34: setting a compensation target according to the feature point displacement difference data, and solving the feature point compensation amount for the mechanical process constraint condition data using a sequential quadratic programming algorithm to generate feature point compensation amount data;

[0153] Step S35: Processing the optimized finite element mesh data with mechanical compensation parameters using the feature point compensation data to generate mechanical shape compensation parameters.

[0154] In an embodiment of the present invention, the displacement of the feature point is extracted from the deformation cloud data. The feature point refers to a key point that has an important influence on the function and performance of the model, such as the blade tip, blade root, hub center, etc. of the impeller. The feature point can be selected manually or automatically according to a predefined rule. For example, a displacement threshold can be set, and the point with a displacement greater than the threshold is used as a feature point. The extracted displacement data of the model feature point is compared with the initial position of the corresponding feature point in the initial three-dimensional mechanical model to calculate the displacement difference. The displacement difference represents the displacement change of the feature point under the action of the thermal load. For example, for the blade tip of the centrifugal pump impeller, the displacement change in the radial, axial and tangential directions under the action of the thermal load can be calculated. The displacement difference data of all feature points are stored to generate feature point displacement difference data, which contains the displacement difference of each feature point in the three directions of x, y, and z. Considering the manufacturing process of the centrifugal pump impeller, such as casting, forging or machining, certain constraints will be imposed on the shape and size of the model. According to the temperature-related nonlinear material parameters and the specific manufacturing process, the process constraints of the model are determined. For example, the casting process will limit the minimum wall thickness of the impeller, and the machining process will limit the surface roughness of the impeller. These constraints are converted into mathematical expressions, such as inequalities or equations, to generate mechanical process constraint data. According to the feature point displacement difference data, the compensation target is set. The goal is to minimize the displacement difference of the feature point or meet certain tolerance requirements by adjusting the shape of the model. For example, the goal can be set to control the radial displacement difference of the impeller blade tip within 0.1mm. Then, the sequential quadratic programming algorithm (SQP) is used to solve the compensation of the feature point in combination with the mechanical process constraint data. The SQP algorithm is a commonly used nonlinear optimization algorithm that can solve nonlinear optimization problems with constraints. The solution result is the feature point compensation data, which contains the compensation of each feature point in the three directions of x, y, and z. The feature point compensation data obtained by the solution is applied to the optimized finite element mesh to generate the mechanical shape compensation parameters. The compensation of the feature point can be converted into the shape parameters of the model according to different compensation strategies. For example, the compensation of the feature point can be directly applied to the corresponding mesh node, or the compensation can be applied to the surrounding nodes using the interpolation method. The generated mechanical shape compensation parameters can be used to modify the initial 3D mechanical model to compensate for the effects of thermal deformation and improve the accuracy of the model.

[0155] Preferably, step S35 includes the following steps:

[0156] Step S351: performing displacement interpolation and inversion according to the feature point compensation amount data, and performing preliminary compensation size calculation to generate preliminary compensation size data;

[0157] Step S352: updating the mesh node coordinates of the optimized finite element mesh data through the preliminary compensation size data, and performing initial compensation surface fitting to generate initial compensation surface data;

[0158] Step S353: performing smoothing processing on the initial compensation surface data to generate smooth compensation surface data;

[0159] Step S354: performing compensation surface point cloud distance calculation according to the smooth compensation surface data, and adjusting the surface deviation to obtain optimized mechanical compensation adjustment surface data;

[0160] Step S355: extracting mechanical compensation shape parameters according to the optimized mechanical compensation adjustment surface data to generate mechanical shape compensation parameters.

[0161] In an embodiment of the present invention, these compensation amounts are interpolated so as to be applied to all mesh nodes. The compensation amounts of feature points can be interpolated to the entire model surface using methods such as radial basis function (RBF) interpolation and thin plate spline interpolation. Then, the displacement value obtained by interpolation is negated. This is because the goal of compensation is to offset the influence of thermal deformation, so it is necessary to apply a displacement in the opposite direction of thermal deformation. Finally, the preliminary compensation size is calculated based on the negated displacement value. For example, for a mesh node on an impeller blade, the compensation displacement amount required for the node in the three directions of x, y, and z can be calculated based on the displacement value obtained by interpolation to generate preliminary compensation size data. The original coordinates of each node are added with the corresponding compensation displacement amount to obtain new node coordinates. The updated mesh node coordinates reflect the shape of the model after compensation. Then, surface fitting techniques such as NURBS surface fitting, triangular mesh surface fitting, etc. are used to fit the updated mesh nodes to generate an initial compensation surface. For example, for a centrifugal pump impeller, the compensated blade surface can be fitted according to the updated blade grid node coordinates to generate the initial compensation surface data. The initial compensation surface has some small fluctuations or non-smooth areas. In order to obtain a more ideal compensation effect, the initial compensation surface needs to be smoothed. The surface can be smoothed using algorithms such as Laplace smoothing and curvature smoothing. The goal of smoothing is to eliminate local fluctuations on the surface and make it smoother while keeping the overall shape unchanged. The smooth compensation surface is converted into point cloud data, and then the distance from the point cloud to the original model surface is calculated. If the distance exceeds the preset tolerance, the compensation surface needs to be adjusted. The adjustment method can be to re-fit the surface or to fine-tune the compensation size. For example, for a centrifugal pump impeller, the distance between the smooth compensation surface and the original blade surface can be calculated. If the distance in some areas is too large, the compensation surface needs to be adjusted until the preset tolerance requirements are met to obtain the optimized mechanical compensation adjustment surface data. According to the optimized mechanical compensation adjustment surface data, the mechanical compensation shape parameters are extracted. These parameters can be the coordinates of the control points of the surface, the weight of the NURBS surface, or other parameters that can describe the shape of the surface. For example, for a centrifugal pump impeller, the coordinates of the control points of the blade surface after compensation can be extracted as mechanical shape compensation parameters. These parameters can be used to modify the initial 3D mechanical model to compensate for the shape error caused by thermal deformation.

[0162] Preferably, step S4 comprises the following steps:

[0163] Step S41: performing CAD parameter processing on the mechanical shape compensation parameters to generate CAD model compensation parameters;

[0164] Step S42: performing compensation feature association constraint processing on the initial three-dimensional mechanical model through CAD model compensation parameters to obtain feature association constraint data;

[0165] Step S43: embedding the feature association constraint data into a thermal compensation logic process, and reconstructing the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model.

[0166] In the embodiment of the present invention, the parameter formats of different CAD software are different, and corresponding conversion needs to be performed according to the software used. For example, if parametric CAD software is used, the compensation parameters can be converted into feature parameters, such as blade thickness, blade angle, etc. If direct modeling software is used, the compensation parameters can be converted into the coordinates of the grid nodes. The converted parameters are the CAD model compensation parameters. For the blades of the impeller, the coordinates of the control points of the compensated surface can be converted into the coordinates of the control points of the blade section line, and then the blade surface can be reconstructed in the CAD software. The compensation parameters can also be converted into parameters such as blade thickness and blade angle, and the blade shape can be adjusted by modifying these parameters. The CAD model compensation parameters are applied to the initial three-dimensional mechanical model, and an associated constraint relationship between the compensation feature and other features of the model is established. For example, for the centrifugal pump impeller, the compensated blade shape needs to be associated with features such as the hub, the leading edge of the blade, and the trailing edge of the blade. The associated constraints can ensure that the compensated model maintains the original topological structure and functional characteristics. For example, the connection relationship between the blade and the hub can be constrained to ensure that the blade is still connected to the hub after compensation. The shapes of the leading and trailing edges of the blades can also be constrained to ensure that the blades still maintain the original fluid dynamic characteristics after compensation. The reconstruction process needs to consider the thermal compensation logic, that is, adjust the shape of the model according to the temperature change. For example, for a centrifugal pump impeller, the shape parameters of the blades, such as blade thickness, blade angle, etc., can be adjusted according to the operating temperature. The reconstruction process needs to follow the constraint relationship defined in the feature-associated constraint data to ensure that the model still meets the design requirements after compensation. The modeling function of the CAD software can be used to rebuild the geometry of the model according to the compensation parameters and constraint relationships. For example, the blade surface can be regenerated according to the compensated blade section line and feature-associated constraints, and assembled with the hub to form a compensated impeller model. It is also possible to directly modify the mesh node coordinates of the initial three-dimensional model, adjust the position of the mesh nodes according to the compensation parameters and constraint relationships, and thus change the shape of the model.

[0167] As an example of the present invention, refer to Figure 3 As shown, Figure 1 Detailed implementation steps of step S5 in the flowchart, in this example, step S5 includes:

[0168] Step S51: Initializing the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data;

[0169] In an embodiment of the present invention, an interactive operation interface is developed to enable users to interact with the model. The interactive interface can be developed using a graphics library (e.g., Qt, OpenGL, etc.) or commercial software (e.g., Unity, UnrealEngine, etc.). A three-dimensional model can be displayed on the interface, and some interactive controls, such as sliders, buttons, text boxes, etc., can be provided to adjust the parameters and working conditions of the model. For example, a slider can be set to adjust the speed, inlet pressure, outlet pressure and other parameters of a centrifugal pump, a button can be set to start and stop the simulation, and a text box can be set to display the simulation results. After the interactive operation interface is initialized, the controls, model data and other information on the interface are stored as interactive interface data.

[0170] Step S52: setting an interactive monitoring point for the interactive interface data to obtain interactive monitoring point data;

[0171] In an embodiment of the present invention, an interactive monitoring point is set on the interactive interface to monitor the user's operation. For example, controls such as sliders, buttons, and text boxes can be set as interactive monitoring points. When the user operates these controls, the program will capture the corresponding events, such as the slider value changes, the button is clicked, etc. These interactive monitoring points and their corresponding event types are stored as interactive monitoring point data. For example, the slider that controls the speed of a centrifugal pump can be set as an interactive monitoring point, and its event type can be set to "value change". When the user drags the slider to change the speed, the program will capture the event and obtain the new speed value.

[0172] Step S53: using the interactive monitoring point data to monitor the mechanical working condition interactive events, and generating mechanical working condition interactive event data;

[0173] In an embodiment of the present invention, the interactive monitoring point data set in step S52 is used to monitor the user's operation and generate mechanical working condition interactive event data. When the user operates the controls on the interactive interface, the program determines whether the corresponding event is triggered based on the interactive monitoring point data. If the event is triggered, the type of event and related parameters are recorded to generate mechanical working condition interactive event data. For example, when the user changes the slider of the centrifugal pump speed, the program captures the "value change" event and records the new speed value to generate mechanical working condition interactive event data, such as {"event type": "speed change", "speed value": 1500rpm}.

[0174] Step S54: responding to the mechanical working condition interaction event data, and mapping the working condition physical field simulation parameters through a preset physical field simulation parameter library to generate interactive mechanical working condition physical parameters;

[0175] In an embodiment of the present invention, the operating state of the model is updated according to the mechanical operating condition interaction event data. For example, if the user changes the speed of the centrifugal pump, the speed parameters of the model need to be updated. Then, according to the updated operating state, the corresponding simulation parameters are searched from the preset physical field simulation parameter library. The physical field simulation parameter library contains simulation parameters under different operating conditions, such as fluid dynamics parameters at different speeds, thermodynamic parameters at different temperatures, etc. The mechanical operating condition interaction event data is mapped to the physical field simulation parameter library, the corresponding simulation parameters are obtained, and the interactive mechanical operating condition physical parameters are generated. For example, according to the new speed value, the corresponding fluid dynamics parameters, such as Reynolds number, flow rate, etc., are searched from the parameter library.

[0176] Step S55: using the physical parameters of the interactive mechanical working condition to perform multi-physical field thermal-mechanical coupling simulation on the mechanical thermal compensation three-dimensional model, and extracting the model simulation deformation characteristics to obtain the actual deformation simulation data of the model;

[0177] In an embodiment of the present invention, the physical parameters of the interactive mechanical working conditions are used to perform multi-physical field thermal coupling simulation on the mechanical thermal compensation three-dimensional model. Finite element analysis software or other simulation tools can be used for simulation. During the simulation process, it is necessary to consider the coupling effects of multiple physical fields such as fluid dynamics and thermodynamics. For example, for a centrifugal pump, it is necessary to consider the force and heat generated by the fluid flow on the impeller, as well as the effect of temperature changes on the shape of the impeller. After the simulation is completed, the deformation characteristics of the model, such as displacement, strain, etc., are extracted to generate the actual deformation simulation data of the model.

[0178] Step S56: Perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

[0179] In an embodiment of the present invention, the actual deformation simulation data of the model is compared with the expected deformation to analyze the mechanical deformation deviation. The expected deformation can be determined according to the design requirements or empirical formula. For example, the deformation of the centrifugal pump impeller at the rated speed and rated temperature can be used as the expected deformation. The actual deformation and the expected deformation are compared, the deformation deviation is calculated, and the effect of thermal compensation is evaluated. The information such as the deformation deviation and the compensation effect is stored as the mechanical model thermal compensation evaluation data.

[0180] The present application is to significantly improve the accuracy and reliability of the model by comprehensively considering the influence of thermal deformation of mechanical parts under actual working conditions. In the traditional three-dimensional modeling process, the influence of temperature change on the shape and size of mechanical parts is often ignored, especially in the complex environment of thermal-mechanical coupling. This neglect will cause the model to deviate from the actual situation, affect the accuracy of simulation analysis, and may even cause product design failure. The present invention introduces material thermal physical property parameters, couples the thermal stress state characteristics of the initial three-dimensional model, realizes the visualization of the thermal stress deformation state, and enables designers to intuitively understand the deformation of parts at different temperatures, so as to carry out more accurate structural optimization design. By calculating the displacement difference and processing the mechanical compensation parameters of the model, the mechanical shape compensation parameters are generated, and then the initial three-dimensional mechanical model is reconstructed by model embedding thermal compensation, which not only considers the geometric shape of the parts, but also considers the temperature influence under actual working conditions, so that the reconstructed model can more accurately reflect the real state of the parts. In addition, an interactive operation interface is provided, allowing users to perform real-time interaction and simulation analysis according to different working condition parameters, which greatly improves the interactivity and adaptability of the model. Through multi-physics field thermal-mechanical coupling simulation and mechanical deformation deviation analysis, mechanical model thermal compensation evaluation data can be generated to provide quantitative evaluation of the thermal compensation effect of the model, helping designers to promptly discover and solve potential design problems. This method not only improves design efficiency, but also reduces production costs because it reduces rework and material waste caused by inaccurate design.

[0181] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0182] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. An interactive three-dimensional modeling method for a mechanical model, characterized in that: The following steps are involved: Step S1: acquiring geometric information of the parts to be modeled from the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled; Pre-processing the mechanical model according to the geometric data of the mechanical parts to be modeled, and modeling the initial mechanical three-dimensional model, thereby obtaining an initial three-dimensional mechanical model; Step S2: obtaining material thermophysical property parameters of the initial three-dimensional mechanical model to generate temperature-dependent nonlinear material parameters; optimizing the model finite element mesh according to the temperature-dependent nonlinear material parameters to obtain optimized finite element mesh data; Based on the optimized finite element mesh data, the initial three-dimensional mechanical model is coupled with the model thermal stress state characteristics to obtain the mechanical thermal stress state characteristic data; The thermal stress deformation state of the initial three-dimensional mechanical model is visualized using the mechanical thermal stress state characteristic data to obtain the thermal stress deformation cloud data of the mechanical model; Step S3: performing displacement difference calculation according to the mechanical model thermal stress deformation cloud data to generate characteristic point displacement difference data; performing mechanical compensation parameter processing on the optimized finite element mesh data through the characteristic point displacement difference data to generate mechanical shape compensation parameters; Step S4: using the mechanical shape compensation parameters to perform model embedding thermal compensation reconstruction on the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model; Step S5: Initializing the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data; Based on the interactive interface data, the mechanical thermal compensation three-dimensional model is monitored for mechanical working condition interaction events, and multi-physics field thermal-mechanical coupling simulation is performed to obtain the actual deformation simulation data of the model; The mechanical deformation deviation analysis is performed based on the actual deformation simulation data of the model to generate the mechanical model thermal compensation evaluation data.

2. The interactive three-dimensional modeling method of mechanical model according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: acquiring geometric information of the parts to be modeled from the target mechanical equipment to obtain geometric data of the mechanical parts to be modeled; Step S12: performing 3D CAD solid modeling according to the geometric data of the mechanical part to be modeled, to obtain 3D mechanical part model data; Step S13: performing assembly relationship analysis on the target mechanical equipment through the three-dimensional mechanical parts model data to generate mechanical parts assembly relationship data; Step S14: extracting part working condition parameters from the three-dimensional mechanical part model data to obtain the mechanical part working condition parameters; Step S15: An initial three-dimensional mechanical model is constructed by using the three-dimensional mechanical part model data according to the mechanical part assembly relationship data, and the model is pre-processed using the mechanical part working condition parameters, so as to obtain an initial three-dimensional mechanical model.

3. The interactive three-dimensional modeling method of a mechanical model according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing initial finite element mesh division of mechanical parts on the initial three-dimensional mechanical model to obtain initial finite element mesh data of the model; Step S22: acquiring material thermal physical property parameters from the initial finite element mesh data of the model to generate temperature-dependent nonlinear material parameters; Step S23: performing anisotropic thermal coefficient processing on the initial three-dimensional mechanical model through temperature-dependent nonlinear material parameters to generate anisotropic thermal conductivity matrix data; Step S24: optimizing the initial finite element mesh data of the model by mechanical mesh unit through the anisotropic thermal conductivity matrix data to obtain optimized finite element mesh data; performing iterative temperature field processing according to the optimized finite element mesh data to obtain steady-state temperature field distribution data; Step S25: performing model thermal stress state characteristic coupling on the initial three-dimensional mechanical model according to the steady-state temperature field distribution data and the optimized finite element mesh data to obtain mechanical thermal stress state characteristic data; Step S26: using the mechanical thermal stress state characteristic data to visualize the thermal stress deformation state of the initial three-dimensional mechanical model, thereby obtaining the mechanical model thermal stress deformation cloud data.

4. The interactive three-dimensional modeling method of a mechanical model according to claim 3, characterized in that: Step S24 includes the following steps: Step S241: setting the thermal boundary conditions of the mechanical model for the initial three-dimensional mechanical model by using the initial finite element mesh data of the model to generate the thermal boundary condition data of the model; Step S242: performing mechanical heat conduction control processing according to the anisotropic thermal conductivity matrix data, and performing grid node temperature calculation according to the model thermal boundary condition data to generate grid node temperature data; Step S243: performing preliminary temperature field distribution processing on the initial three-dimensional mechanical model through the grid node temperature data to obtain preliminary temperature field data; Step S244: Calculate the temperature gradient of the preliminary temperature field data to generate model grid node temperature gradient data; Step S245: traversing the grid cells according to the temperature gradient data of the model grid nodes, and marking the grid cells with high temperature gradient using a preset temperature gradient threshold, to obtain the number data of the grid cells to be refined; Step S246: performing mechanical mesh unit segmentation according to the mesh unit number data to be refined, and generating new mesh unit node data; Step S247: mapping the new mesh unit node data to the old mesh unit relationship to obtain optimized finite element mesh data; Step S248: Perform new node temperature interpolation calculation on the preliminary temperature field data, and perform iterative temperature field processing on the optimized finite element mesh data through the anisotropic thermal conductivity matrix data, so as to obtain steady-state temperature field distribution data.

5. The interactive three-dimensional modeling method of mechanical model according to claim 3, characterized in that: Step S25 includes the following steps: Step S251: Calculate the thermal expansion coefficient according to the anisotropic thermal conductivity matrix data to generate a temperature-dependent thermal expansion coefficient; Step S252: performing finite element temperature load processing on the steady-state temperature field distribution data to obtain finite element model temperature load data; Step S253: Calculate the grid unit temperature difference according to the finite element model temperature load data to generate grid unit temperature change data; Step S254: Calculate the thermal strain of the grid unit according to the temperature-related thermal expansion coefficient and the grid unit temperature change data to generate the grid unit thermal strain data; Step S255: performing thermal expansion deformation analysis on the initial three-dimensional mechanical model through the thermal strain data of the grid unit to generate thermal expansion deformation data of the mechanical model; Step S256: extracting the material elastic modulus according to the temperature-related nonlinear material parameters to obtain the elastic modulus data of the mechanical equipment material; Step S257: performing inter-unit stress transfer analysis on the mechanical model thermal expansion deformation data through the mechanical equipment material elastic modulus data, and performing grid unit thermal stress calculation to generate mechanical model thermal stress distribution data; Step S258: performing nonlinear finite element thermal characteristic coupling on the initial three-dimensional mechanical model through the mechanical model thermal expansion deformation data and the mechanical model thermal stress distribution data, and updating the unit thermal stress state, thereby obtaining mechanical thermal stress state characteristic data.

6. The interactive three-dimensional modeling method of mechanical model according to claim 5, characterized in that: Step S255 includes the following steps: Calculate the three-dimensional linear expansion of the mesh unit thermal strain data to generate mesh unit linear expansion data; Perform node displacement component analysis based on grid unit linear expansion data to obtain grid node displacement component data; Calculate the displacement of points in the unit according to the grid node displacement component data to generate grid unit point displacement data; The thermal expansion deformation of the surface nodes of the initial three-dimensional mechanical model is processed based on the point displacement data in the mesh unit and the optimized finite element mesh data to generate the thermal expansion deformation data of the mechanical model.

7. The interactive three-dimensional modeling method of a mechanical model according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: extracting characteristic point displacements according to the mechanical model thermal stress deformation cloud data to generate model characteristic point displacement data; Step S32: calculating the displacement difference of the initial three-dimensional mechanical model through the displacement data of the model feature points to generate feature point displacement difference data; Step S33: Processing mechanical process constraint conditions according to temperature-related nonlinear material parameters to generate mechanical process constraint condition data; Step S34: setting a compensation target according to the feature point displacement difference data, and solving the feature point compensation amount for the mechanical process constraint condition data using a sequential quadratic programming algorithm to generate feature point compensation amount data; Step S35: Processing the optimized finite element mesh data with mechanical compensation parameters using the feature point compensation data to generate mechanical shape compensation parameters.

8. The interactive three-dimensional modeling method of a mechanical model according to claim 7, characterized in that: Step S35 includes the following steps: Step S351: performing displacement interpolation and inversion according to the feature point compensation amount data, and performing preliminary compensation size calculation to generate preliminary compensation size data; Step S352: updating the mesh node coordinates of the optimized finite element mesh data through the preliminary compensation size data, and performing initial compensation surface fitting to generate initial compensation surface data; Step S353: performing smoothing processing on the initial compensation surface data to generate smooth compensation surface data; Step S354: performing compensation surface point cloud distance calculation according to the smooth compensation surface data, and adjusting the surface deviation to obtain optimized mechanical compensation adjustment surface data; Step S355: extracting mechanical compensation shape parameters according to the optimized mechanical compensation adjustment surface data to generate mechanical shape compensation parameters.

9. The interactive three-dimensional modeling method of a mechanical model according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing CAD parameter processing on the mechanical shape compensation parameters to generate CAD model compensation parameters; Step S42: performing compensation feature association constraint processing on the initial three-dimensional mechanical model through CAD model compensation parameters to obtain feature association constraint data; Step S43: embedding the feature association constraint data into a thermal compensation logic process, and reconstructing the initial three-dimensional mechanical model to generate a mechanical thermal compensation three-dimensional model.

10. The interactive three-dimensional modeling method of a mechanical model according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: Initializing the model interactive operation interface of the mechanical thermal compensation three-dimensional model to obtain interactive interface data; Step S52: setting an interactive monitoring point for the interactive interface data to obtain interactive monitoring point data; Step S53: using the interactive monitoring point data to monitor the mechanical working condition interactive events, and generating mechanical working condition interactive event data; Step S54: responding to the mechanical working condition interaction event data, and mapping the working condition physical field simulation parameters through a preset physical field simulation parameter library to generate interactive mechanical working condition physical parameters; Step S55: using the physical parameters of the interactive mechanical working condition to perform multi-physical field thermal-mechanical coupling simulation on the mechanical thermal compensation three-dimensional model, and extracting the model simulation deformation characteristics to obtain the actual deformation simulation data of the model; Step S56: Perform mechanical deformation deviation analysis based on the actual deformation simulation data of the model to generate mechanical model thermal compensation evaluation data.

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