Finite element analysis model construction method for intelligent in-place equipment prototype
By applying wind loads in stages and using adaptive iterative optimization of the mesh, the problem of low positioning accuracy of traditional positioning equipment is solved, achieving efficient and accurate finite element analysis and supporting high-precision design of intelligent positioning equipment.
Patent Information
- Application Number
- CN202511845806.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-09
- Publication Date
- 2026-03-13
AI Technical Summary
Traditional positioning equipment relies on human experience and mechanical adjustments, resulting in low positioning accuracy and poor adaptability. Furthermore, existing finite element analysis fails to fully consider the multi-stage continuous evolution characteristics and equipment swaying effects during the positioning process, leading to discrepancies between simulation results and actual conditions, making it difficult to accurately predict the positioning error of intelligent positioning equipment.
A finite element analysis model of the intelligent positioning equipment prototype was constructed. Wind loads were applied in stages, and the mesh size was adjusted through an adaptive iteration process. The influence of equipment sway was considered, and the mesh accuracy was gradually optimized to ensure that the positioning error at each stage met the accuracy requirements. Finally, the overall positioning performance was evaluated.
Through phased mesh optimization, the mechanical properties and sway effects during the positioning process are accurately captured, significantly improving the accuracy and computational efficiency of the simulation results, providing a highly reliable positioning accuracy assessment, and supporting equipment optimization design.
Smart Images
Figure CN121659655A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of finite element analysis technology, specifically to a method for constructing a finite element analysis model of an intelligent positioning equipment prototype. Background Technology
[0002] In large-scale projects such as power and petrochemical industries, the installation accuracy of high-voltage gas-insulated switchgear (HGIS) directly affects the safe and stable operation of the entire system. Traditional positioning equipment relies on manual experience and mechanical adjustments, resulting in low positioning accuracy and poor adaptability. Therefore, the development of intelligent positioning equipment prototypes has become crucial. During the development process, finite element analysis is required to meet design accuracy requirements, especially in the study of positioning mechanisms and functions, which necessitates continuous analysis and adjustment.
[0003] When performing finite element analysis on the positioning process of the intelligent positioning equipment prototype, the finite element model generally uses a static mesh, which fails to fully consider the continuous evolution characteristics of multiple stages such as "initial alignment - contact bonding - clamping loading" during the positioning process. This leads to an imbalance between mesh accuracy and computational efficiency at different stages. Secondly, during the model analysis, the continuous shaking effect caused by external excitation during the positioning process is ignored, which fails to truly reflect the dynamic influence of the inertial force generated by the shaking on the contact state and the final positioning accuracy. This results in a deviation between the simulation results and the actual situation, making it difficult to accurately predict the positioning error of the intelligent positioning equipment and restricting the optimized design of high-precision intelligent positioning equipment. Summary of the Invention
[0004] To address the aforementioned technical issues, a finite element analysis model construction method for an intelligent positioning equipment prototype is provided to resolve existing problems.
[0005] The solution to the technical problem presented in this application is a method for constructing a finite element analysis model of an intelligent positioning equipment prototype, comprising the following steps: A finite element model containing the intelligent positioning equipment prototype, equipment and positioning mechanism was constructed, wind load was applied, and the entire positioning simulation process was divided into multiple stages. For any given stage, a mesh adaptive iterative process is executed, which includes: Based on the spatial gradient and grid size of the grid force distribution under the physical force field at any stage, and the acceleration change of the equipment sway caused by wind load in different directions, the positioning error component of the grid at any stage is calculated. The result is compared with the preset target error. The grid size of the stage is adjusted to re-divide the grid. The process is iterated until the positioning error components of all grids at this stage meet the accuracy requirements. Based on the re-divided grid at this stage, the simulation of the next stage begins. By utilizing the positioning error components of all grids at different stages, the final positioning error of the entire positioning simulation process is obtained, and the overall positioning performance of the intelligent positioning equipment prototype is evaluated.
[0006] Preferably, the plurality of stages includes an initial alignment stage, a contact and bonding stage, and a clamping and loading stage.
[0007] Preferably, the calculation process for the positioning error components of the grid during the initial alignment stage is as follows: For the stress field in the initial alignment stage, the ratio of the norm of the stress gradient of each grid to the preset material yield strength is calculated, and the product of this ratio and the size of each grid is used as the linearization error of each grid. Based on the magnitude of the equipment's acceleration in different directions during the initial alignment stage, calculate the influence factors of the equipment in each direction during the initial alignment stage. The maximum influence factor of the device in all directions is selected, and its product with the linearization error is used as the positioning error component of each grid in the initial alignment stage.
[0008] Preferably, the calculation process of the influence factor of the device in each direction during the initial alignment stage is as follows: In the initial alignment stage, a sensitivity coefficient is assigned to the device in each direction; the acceleration is normalized, and the product of the normalized acceleration of the device in each direction and the sensitivity coefficient in the corresponding direction is calculated as the correction factor in each direction; the sum of the value 1 and the correction factor is used as the influence factor in each direction.
[0009] Preferably, the calculation process for the positioning error components of the mesh during the contact bonding stage is as follows: For the contact force field during the contact bonding stage, the ratio of the norm of the contact pressure gradient of each grid to the maximum contact pressure of all grids on the contact surface is calculated, and the product of this ratio and the size of the grid is used as the pressure estimation error of each grid. Calculate the ratio of the norm of the contact stress gradient of each grid to the preset reference contact stress, and multiply it by the size of the grid as the stress estimation error of each grid. Based on the proportion of acceleration of the device in each direction during the contact bonding stage, the weighting factor for each direction is calculated. Using the weighting factors of the equipment in each direction as weights, the pressure estimation error and stress estimation error are weighted and summed to form the positioning error component of each grid during the contact bonding stage.
[0010] Preferably, the weighting factor is the ratio between the absolute value of the device's acceleration in each direction and the sum of the absolute values of the acceleration in all directions.
[0011] Preferably, the calculation process for the positioning error components of the mesh during the clamping loading stage is as follows: For the clamping force field during the clamping loading stage, the ratio of the norm of the clamping force gradient of each grid to the preset material yield strength is calculated, and the product of this ratio with the grid size and the preset compliance influence coefficient is used as the deformation error of each grid. Based on the magnitude and proportion of the device's acceleration in different directions during the clamping loading stage, the influencing factors during the clamping loading stage are calculated. The product of the deformation error of each grid and the influence factor of the clamping loading stage is used as the positioning error component of each grid during the clamping loading stage.
[0012] Preferably, the calculation of the influence factors during the clamping loading stage includes: for the clamping loading stage, calculating the ratio between the absolute value of the acceleration of the device in each direction and the sum of the absolute values of the acceleration in all directions, as the sensitivity coefficient for each direction; normalizing the acceleration, calculating the product of the normalized acceleration of the device in each direction and the sensitivity coefficient in the corresponding direction, as the correction factor for each direction; and summing the value 1 and the correction factors in all directions as the influence factor for the clamping loading stage.
[0013] Preferably, the adjusted size corresponds to the r-th grid in the q-th stage. The calculation formula is: ,in, Let r be the size of the r-th grid before adjustment in the q-th stage. The preset target error, Let be the positioning error component of the r-th grid in the q-th stage. This is a function that takes the minimum value.
[0014] Preferably, the process of obtaining the final positioning error is as follows: the maximum value of the positioning error components of all grids in the initial alignment stage is taken as the initial alignment error; the maximum values of the positioning error components of all grids on the contact surface in the contact bonding stage and the clamping loading stage are taken as the contact deformation error and clamping deformation error, respectively; the sum of the initial alignment error, contact deformation error and clamping deformation error is taken as the final positioning error.
[0015] This application has at least the following beneficial effects: This application simulates the positioning process by constructing a finite element model and applying wind loads consistent with the actual site conditions. The entire positioning simulation process is divided into multiple stages to match the simulation conditions with the actual installation environment, facilitating subsequent analysis of the mechanical properties at different stages. The positioning error components of the mesh in the initial alignment stage are calculated. This calculation considers the stress change rate of the mesh in this stage, reflecting the accuracy of the mesh size in capturing stress changes. It also incorporates the impact of equipment sway caused by wind loads on positioning accuracy to comprehensively evaluate the positioning error of the mesh in the initial alignment stage. The mesh size in the initial alignment stage is adjusted to re-mesh, iterating until all meshes in this stage are re-meshed. All positioning error components meet the accuracy requirements. The beneficial effect lies in refining the mesh for areas with drastic stress changes and large positioning errors, while leaving the mesh for areas with gentle stress changes and small positioning errors unrefined. This ensures the accuracy of the dynamic response to wind-induced equipment sway and the overall structural stress distribution, while effectively avoiding the waste of computational resources caused by excessive mesh refinement in low-gradient regions. After iterative convergence, the positioning error meets the preset accuracy standard, thus providing a highly reliable geometric configuration for the subsequent contact bonding stage, preventing the error from the initial alignment stage from being amplified and propagated to subsequent stages. Calculating the positioning error components of the mesh during the contact bonding stage has the beneficial effect of ensuring accurate mesh formation when the equipment comes into contact with the positioning mechanism. This method can accurately capture and quantify the rate of change of shear stress caused by contact pressure and friction during potential micro-slippage. Combined with the impact of equipment swaying caused by wind loads on positioning accuracy, mesh optimization can respond to the transient evolution of the contact state during swaying, accurately capturing the pressure distribution and slippage state at the contact interface, thereby assessing the impact of contact bonding on positioning accuracy. The mesh size is adjusted during the contact bonding stage to re-mesh, iterating until all mesh positioning error components at this stage meet accuracy requirements. Its beneficial effect lies in accurately capturing the stress singularity and frictional behavior at the contact edges by refining the mesh in areas with high contact pressure gradients and high potential slippage risk, while ensuring... While ensuring the accuracy of the mechanical state calculation at the contact interface, it effectively avoids the waste of computational resources caused by excessive mesh refinement in low gradient regions. After iterative convergence, the positioning error reaches the preset accuracy, thus providing a reliable and accurate initial contact state for the force analysis during the clamping loading stage. Calculating the positioning error components of the mesh during the clamping loading stage has the beneficial effect of quantitatively evaluating the overall deformation of the component introduced by the clamping force, reflecting the accuracy of the mesh size in capturing changes in the clamping force gradient. Combined with the influence of equipment sway caused by wind load on the positioning accuracy, it ensures that the simulation can accurately predict the local clamping deformation and dynamic disturbance effects that have a decisive influence on the overall mechanical state of the structure after clamping, especially on the positioning accuracy.The mesh size is adjusted and re-divided during the clamping loading stage. This process is iterated until the positioning error components of all meshes at this stage meet the accuracy requirements. The beneficial effect is that by optimizing and re-dividing the mesh size, a sufficiently fine mesh is ensured to capture accurate stress and displacement fields in areas of stress concentration and large deformation gradient caused by clamping force. This avoids problems such as inaccurate stress calculations and distorted deformation predictions caused by coarse meshes. Through iterative optimization, computational efficiency and result reliability can be balanced while meeting preset accuracy standards, providing a high-confidence numerical solution for evaluating the shape and stress state of the clamped component. Using the positioning error components of all meshes at different stages, the final positioning error of the entire positioning simulation process is obtained, evaluating the overall positioning performance of the intelligent positioning equipment prototype. The beneficial effect is that by integrating the positioning errors of each stage—"initial alignment - contact bonding - clamping loading"—the comprehensive positioning accuracy of the intelligent positioning equipment under wind load conditions is quantified. This provides a comprehensive data-driven basis for optimizing the equipment's positioning strategy, control logic, and structural design, significantly improving the R&D efficiency and design reliability of the intelligent positioning equipment. Attached Figure Description
[0016] The following section, in conjunction with the accompanying drawings, provides a more detailed explanation of the finite element analysis model construction method for a prototype of an intelligent positioning equipment according to this application.
[0017] Figure 1 A flowchart illustrating the steps of a method for constructing a finite element analysis model of an intelligent positioning equipment prototype, as provided in this application embodiment; Figure 2 A flowchart illustrating the steps of a method for obtaining the positioning error components of a mesh during the clamping and loading stage, as provided in an embodiment of this application. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description, in conjunction with the accompanying drawings and implementation examples, provides a method for constructing a finite element analysis model of an intelligent positioning equipment prototype proposed in this application. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit the scope of this application.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.
[0020] Please see Figure 1 The diagram illustrates a flowchart of the steps involved in constructing a finite element analysis model of an intelligent positioning equipment prototype according to an embodiment of this application. The method includes the following steps: Step 1: Construct a finite element model that includes the intelligent positioning equipment prototype, equipment, and positioning mechanism; apply wind loads; and divide the entire positioning simulation process into multiple stages.
[0021] High-voltage gas-insulated switchgear (HGIS) equipment is a core hub device in substations, undertaking critical functions such as power distribution, system protection, and control. HGIS equipment comprises multiple electrical components, such as circuit breakers and disconnectors. HGIS equipment needs to be installed in specific locations within the substation and works in conjunction with transformers and other electrical equipment via electrical connections.
[0022] Within substations, space is typically limited, and the prototype intelligent positioning equipment needs to complete complex installation tasks within confined spaces. High-precision positioning and handling technologies are crucial for successful installation. The core function of the prototype is to achieve precise handling, positioning, and placement of HGIS equipment within limited spaces, based on positioning and visual recognition technologies. To achieve high-precision positioning and installation of HGIS equipment in complex and hazardous confined spaces, and to ensure the reliability, safety, and accuracy of the prototype under harsh conditions such as wind loads and heavy loads, simulations are needed to verify and optimize the positioning performance of the prototype.
[0023] The intelligent equipment prototype for HGIS equipment placement mainly consists of a truss, a walking mechanism, a lifting mechanism, and a positioning mechanism. Through the coordinated work of these mechanisms, the HGIS equipment can be accurately transported, positioned, and placed within a limited space, effectively addressing the shortcomings of traditional construction methods in terms of efficiency, accuracy, and safety, and providing strong support for the efficient construction and safe operation of substations.
[0024] Among them, the truss is the main frame structure of the intelligent equipment prototype, which mainly bears the weight of the HGIS equipment and various loads generated during the placement process, providing stability and support for the entire equipment prototype. The traveling mechanism is responsible for driving the equipment prototype to move within the substation, enabling the equipment prototype to smoothly reach the installation position of the HGIS equipment, and adjusting its position as needed during the placement process; The lifting mechanism enables the vertical lifting and horizontal movement of HGIS equipment, accurately placing it in the predetermined installation position. The lifting mechanism employs a hydraulic lifting system, characterized by high load-bearing capacity, high lifting accuracy, and good stability. The hydraulic system drives the lifting device through hydraulic cylinders or hydraulic motors, achieving smooth lifting and precise positioning of the equipment. The positioning mechanism utilizes wireless positioning and computer vision technologies, along with intelligent sensor data, to develop a prototype of intelligent positioning equipment for HGIS equipment based on a movable truss structure. This prototype enables highly stable movement and intelligent positioning during the hoisting process of HGIS equipment, addressing challenges such as large working areas and high risks in the confined spaces of substations.
[0025] It should be noted that, compared with existing equipment and methods, the prototype equipment can accurately adapt to the complex environment of the limited space in a substation, reducing the risk of collisions in narrow passages and complex layouts, providing a safer operating space for construction personnel, reducing safety risks during construction, and ensuring the safety of construction personnel and equipment. Therefore, its positioning function is the core function, and the current simulation focuses on the positioning function.
[0026] Based on the above analysis, the entire process of the intelligent positioning equipment prototype moving the HGIS device to the positioning mechanism and aligning and contacting it is simulated in the finite element software. The clamping device on the positioning mechanism begins to apply clamping force to fix the HGIS device. Therefore, in the finite element software, a finite element model including the intelligent positioning equipment prototype, the HGIS device and the positioning mechanism is constructed, and wind load is applied to simulate the shaking of the HGIS device in order to record the acceleration of the HGIS device in different directions. In this embodiment, ANSYS Workbench 2023 R1 finite element software is used. The simulation process is a well-known technology and will not be described in detail here. The positioning mechanism of the HGIS equipment is a V-block + double positioning pin, with a rated load of 3 tons and a positioning accuracy requirement of ±0.1mm.
[0027] It should be noted that acceleration is used to assess the shaking of the equipment. Different directions refer to the parallel and perpendicular directions of the contact surface when the HGIS equipment and the positioning mechanism come into contact, that is, the tangential and normal directions of the contact surface.
[0028] The entire positioning simulation process is divided into three stages, as follows: During the initial alignment phase, the HGIS equipment gradually moves towards the positioning reference along the guiding mechanism, such as a guide rail or other guiding device. At this time, the equipment is close to the positioning reference, but has not yet made contact with it. During the contact and bonding stage, the positioning surface of the positioning mechanism makes initial contact with the surface of the HGIS equipment, transitioning from point contact to surface contact and generating elastic deformation. During the clamping and loading phase, the grippers of the positioning mechanism gradually apply clamping force, and the device posture is eventually fixed in the corresponding position.
[0029] The finite element model is meshed, and the physical force field at each stage is recorded during the simulation process. It should be noted that the finite element model is coarsely meshed. The meshing process is a well-known technique and will not be described in detail here. The mesh size is 1m. As for other implementation methods, implementers can set it according to their actual situation.
[0030] Thus, the physical force field at each stage of the entire positioning simulation process, as well as the acceleration of the equipment in different directions at each stage, are obtained.
[0031] Step 2: Based on the spatial gradient of the force distribution of the grid under the physical force field in the initial alignment stage and the grid size, as well as the acceleration changes of the equipment swaying caused by wind load in different directions, calculate the positioning error components of the grid in the initial alignment stage, compare them with the preset target error, adjust the grid size of this stage to re-divide the grid, and iterate continuously until the positioning error components of all grids in this stage meet the accuracy requirements.
[0032] The positioning mechanism is the core execution unit for the precise positioning of HGIS equipment. Positioning accuracy is a key issue in simulation, and it is generally analyzed based on positioning error, meaning the positioning accuracy is reflected through the positioning error. However, during the operation of the equipment prototype, vibrations may occur due to environmental influences. Therefore, the impact of equipment vibration on positioning error needs to be considered when performing positioning error analysis.
[0033] In simulation analysis, the mesh size directly affects the simulation results. An excessively large mesh can lead to inaccurate simulation results, while an excessively small mesh results in a surge in computational load, impacting simulation efficiency. Furthermore, under the influence of shaking, the distribution of positioning errors is uneven, with significant differences in positioning errors at different stages. Therefore, a fixed mesh size cannot meet simulation requirements. It is necessary to continuously adjust the mesh size during the simulation process to ensure optimal simulation results.
[0034] During the initial alignment stage, the shaking of the equipment will cause positioning errors. The shaking can occur in two directions: parallel to the contact surface and perpendicular to the contact surface. Let the direction parallel to the contact surface be denoted as the X direction and the direction perpendicular to the contact surface as the Y direction. However, since no contact occurs at this stage, the impact of shaking on the error should be the same in both directions.
[0035] Based on the above analysis, by analyzing the stress gradient changes in the mesh, a finer mesh is used in areas with large stress gradients to capture local deformation. Specifically: In the initial alignment stage, finite element analysis is performed using finite element software to output the stress gradient of each mesh. It should be noted that finite element software outputs a stress field, and the process of obtaining the stress gradient based on the stress field is a well-known technique, which will not be elaborated here.
[0036] The ratio of the norm of the stress gradient of each grid to the preset material yield strength is multiplied by the size of each grid and used as the linearization error of each grid. In this embodiment, the L2 norm is used for calculation. The calculation of the L2 norm is a well-known technique and will not be elaborated here. Secondly, the material yield strength refers to the yield limit of the material when it yields, that is, the stress that resists a small amount of plastic deformation. It can be obtained by looking up the data manual of the HGIS equipment. For example, the yield strength of 5052-H112 aluminum alloy is about 70MPa, and the yield strength of SS400 steel is about 215MPa~245MPa. The implementer can set it according to the specific situation. Secondly, the size of the mesh is the initial mesh size during meshing, which is 1m.
[0037] It should be noted that in regions with large stress gradients, finer meshes can capture stress changes more accurately, thus reducing errors. In regions with large stress gradients, coarser meshes may not be able to accurately capture stress changes, leading to larger errors. Therefore, the norm of the stress gradient reflects the stress changes of the mesh. The larger the value, the more drastic the local stress changes. The larger the stress gradient, the larger the error, and the greater the linearization error.
[0038] The swaying of the equipment in different directions has different effects on the error during this stage. The influence factors are calculated based on the acceleration of the equipment in different directions during this stage. Specifically: During the initial alignment phase, a sensitivity coefficient is assigned to the device in each direction; The acceleration is normalized, and the product of the normalized acceleration in each direction and the sensitivity coefficient in the corresponding direction is used as the correction factor in each direction. In this embodiment, the normalization process is as follows: the ratio of acceleration to gravitational acceleration is used as the normalized acceleration; secondly, since no contact occurs during the initial alignment stage, the sensitivity of the swaying in both directions to the error can be determined to be consistent. Therefore, the preset sensitivity coefficients for both directions are set to 0.5.
[0039] The sum of the value 1 and the correction factor is used as the influence factor in each direction; In this embodiment, the formula for calculating the influence factor in each direction is as follows: in, This represents the influence factor of the device in the X direction during the initial alignment stage. This refers to the preset sensitivity coefficient of the device in the X direction during the initial alignment stage. This represents the acceleration of the device in the X direction during the initial alignment phase. Represents gravitational acceleration; This represents the influence factor of the device in the Y direction during the initial alignment stage. This is the preset sensitivity coefficient of the device in the Y direction during the initial alignment stage. This represents the acceleration of the device in the Y direction during the initial alignment phase. It should be noted that by adding the value 1 to the correction factor, the influence factor is equal to 1 when the equipment is not shaking, and when shaking occurs, the influence factor can reflect the additional impact of acceleration on the error during shaking.
[0040] Furthermore, since the impact of swaying in different directions on the error is consistent during this stage, the linearization error is corrected using the larger value of the influence factor, specifically as follows: The maximum influence factor of the equipment in all directions is selected, and its product with the linearization error is used as the positioning error component of each grid in the initial alignment stage. It should be noted that the larger the maximum influence factor, the greater the impact of the sway in this direction on the error; the larger the obtained positioning error component, the more drastic the stress gradient change of the grid in this stage, reflecting the uneven stress distribution. In larger grids, the stress change is averaged out, resulting in a larger error.
[0041] Therefore, the mesh is refined based on the positioning error components, with meshes having larger errors using smaller sizes, while meshes with smaller errors are not adjusted in size. Specifically: in, This represents the adjusted size of the r-th grid during the initial alignment stage. This represents the size of the r-th grid before adjustment during the initial alignment stage. The preset target error, Let be the positioning error component of the r-th grid during the initial alignment stage. This represents a function that takes the minimum value. It should be noted that the target error range is 0.05~0.1. In this embodiment, the preset target error is 0.07. As for other implementation methods, the implementer can set it according to the actual situation. Secondly, when the positioning error component is greater than the preset target error, the grid is refined. At this time, the grid size is reduced, and the larger the positioning error component is relative to the target error, the greater the grid reduction.
[0042] Based on the adjusted size of the mesh in the initial alignment stage, the mesh in the finite element model is refined, a new mesh is generated, and the size of the mesh is continuously adjusted by iteratively calculating the positioning error components on the new mesh until the positioning error components of all meshes in the initial alignment stage are less than or equal to the preset target error. The iteration stops then, and the refined finite element model in the initial alignment stage is obtained.
[0043] This completes the simulation process for the initial alignment stage.
[0044] Step 3: Calculate the positioning error components of the grid under the physical force field during the contact bonding stage, considering the spatial gradient and grid size of the grid force distribution, as well as the acceleration changes of the equipment swaying caused by wind load in different directions. Compare these components with the preset target error and adjust the grid size for this stage to re-divide the grid. Iterate continuously until the positioning error components of all grids in this stage meet the accuracy requirements.
[0045] After completing the initial alignment stage, the device enters the contact bonding stage, where it comes into contact with the positioning mechanism. At this time, the contact pressure will cause local deformation errors, which are mainly reflected in the contact pressure of the contact surface. Furthermore, the shaking also affects the error in two directions. The shaking in the direction parallel to the contact surface, i.e., the tangential direction of the contact surface, will trigger shear deformation and slippage behavior of the contact surface, generating shear stress on the contact surface. The shaking in the direction perpendicular to the contact surface, i.e., the normal direction of the contact surface, will directly change the contact pressure of the contact surface, thus affecting the error.
[0046] Based on the refined finite element model in the initial alignment stage, finite element analysis is performed using finite element software in the contact bonding stage to output the contact pressure gradient and contact stress gradient of each mesh on the contact surface. It should be noted that finite element software will obtain the contact force field, and the process of obtaining the contact pressure gradient and contact stress gradient based on the contact force field is a well-known technique. Among them, the contact pressure gradient refers to the rate of change of contact pressure in space.
[0047] Calculate the ratio of the norm of the contact pressure gradient of each grid during the contact bonding stage to the maximum contact pressure of all grids on the contact surface, and multiply it by the size of the grid as the pressure estimation error of each grid. In this embodiment, the L2 norm is used for calculation. The calculation of the L2 norm is a well-known technique and will not be described in detail here.
[0048] It should be noted that the mesh size is the mesh size on the finite element model after refinement during the initial alignment stage.
[0049] Simultaneously, when there is shaking in different directions, not only is a contact pressure gradient generated at the contact surface, but shear deformation and potential slippage behavior are also induced. From the perspective of contact mechanics, when the equipment shakes along the direction parallel to the contact surface, the inertial force will generate additional shear stress, i.e., contact stress, at the contact surface. This stress, superimposed on the static friction force, may change the contact state from adhesion to slippage. At this time, the contact stress gradient reflects the severity of this state transition. Therefore, the error is assessed through the contact stress gradient, specifically as follows: The ratio of the norm of the contact stress gradient of each grid during the contact bonding stage to the preset reference contact stress is calculated, and the product of this ratio and the size of the grid is used as the stress estimation error of each grid. In this embodiment, the L2 norm is used for calculation. The calculation of the L2 norm is a well-known technique and will not be described in detail here.
[0050] It should be noted that the reference contact stress was selected by consulting the data manual and choosing the allowable compressive stress value of the positioning mechanism and the housing material of the HGIS equipment as the reference contact stress; secondly, the size of the grid is also the size of the grid after refinement in the initial alignment stage.
[0051] It should be noted that the pressure estimation error reflects the error caused by uneven distribution of contact pressure. The larger the norm of the contact pressure gradient, the more drastic the pressure changes on the contact surface. The grid cannot accurately depict how the contact force is specifically transmitted at the interface, which will lead to a decrease in positioning accuracy. The larger the stress estimation error, the more high the stress gradient exists inside the material. The grid cannot capture the sudden changes in local material stress caused by contact, which will cause a large error.
[0052] Secondly, during the contact bonding stage, the contact interface simultaneously bears significant tangential shear force and normal pressure. When the equipment shakes, the contact area may experience a coupling effect of slippage and contact separation tendencies, making the contact mechanical behavior more complex. Therefore, it is necessary to consider the influence of equipment shaking in different directions and calculate the weighting factors for each direction, specifically: During the contact bonding phase, the ratio between the absolute value of the acceleration of the calculation device in each direction and the sum of the absolute values of the acceleration in all directions is used as the weighting factor for each direction. Using the weighting factors of the equipment in each direction as weights, the pressure estimation error and stress estimation error are weighted and summed to serve as the positioning error components of each grid during the contact bonding stage. In this embodiment, since the directions of the device include directions parallel to the contact surface and directions perpendicular to the contact surface, namely tangential and normal directions, and the stress estimation error refers to the error in the tangential direction of the contact surface, the weighted summation process is as follows: the product of the weight factor in the tangential direction and the stress estimation error is recorded as the first product; the product of the weight factor in the normal direction and the stress estimation error is recorded as the second product; and the sum of the first product and the second product is used as the positioning error component of each grid.
[0053] It should be noted that the weighting factor reflects the degree of equipment sway in different directions. The larger the value, the more significant the equipment sway in that direction. The larger the resulting positioning error component, the more drastic the stress and pressure gradient changes on the grid on the contact surface, and the larger the total error.
[0054] Furthermore, based on the positioning error components, the grid size at this stage is adjusted so that grids with large errors require smaller sizes, while grids with small errors do not require size adjustments. Specifically: in, Let r be the adjusted size of the r-th grid during the contact bonding stage. Let r be the size of the r-th grid before adjustment during the contact bonding stage. The preset target error, Let be the positioning error component of the r-th grid during the contact bonding stage. This represents a function that takes the minimum value. It should be noted that the r-th grid in the contact bonding stage corresponds to the size before adjustment. That is, it is equal to the adjusted size of the r-th grid during the initial alignment stage. .
[0055] It should be noted that when the positioning error component is greater than the preset target error, the grid is refined, and the grid size is reduced. The larger the positioning error component is relative to the target error, the greater the reduction in grid size. Conversely, when the positioning error component is less than the preset target error, the grid size is not adjusted.
[0056] Based on the adjusted dimensions of each mesh during the contact bonding stage, the mesh in the finite element model is refined again, and a new mesh is generated. On the new mesh, the size of the mesh is continuously adjusted by iteratively calculating the positioning error components until the positioning error components of all meshes during the contact bonding stage are less than or equal to the preset target error. This process is then stopped to obtain the refined finite element model during the contact bonding stage.
[0057] This completes the simulation process for the contact bonding stage.
[0058] Step 4: Calculate the positioning error components of the grid under the clamping loading stage, taking into account the spatial gradient and grid size of the grid force distribution under the physical force field during the clamping loading stage, as well as the acceleration changes of the equipment swaying caused by wind load in different directions. Compare these with the preset target error and adjust the grid size for this stage to re-divide the grid. Iterate continuously until the positioning error components of all grids under this stage meet the accuracy requirements.
[0059] Furthermore, the flowchart of the method for obtaining the positioning error components of the mesh during the clamping and loading stage provided in this application embodiment is as follows: Figure 2 As shown.
[0060] After the contact and bonding stage is completed, the clamping and loading stage begins. At this time, the clamping device on the positioning mechanism begins to apply clamping force. Uneven clamping force will cause deformation, reflecting the instantaneous response when transitioning from a contact stable state to a clamping constraint state. During this stage, no matter which direction the equipment shakes, it will not cause rigid displacement of the equipment, but will be converted into a dynamic inertial force acting on the entire clamping device. At this time, the error mainly comes from the deformation of the clamping contact surface. At the same time, the deformation effect of the clamping force on the contact surface is also affected by the flexibility of the contact surface. The contact surface with greater material flexibility will produce greater deformation under the same clamping force.
[0061] Based on the refined finite element model in the contact bonding stage, finite element analysis is performed using finite element software in the clamping loading stage to output the clamping force gradient of each mesh on the contact surface. It should be noted that finite element software will obtain a clamping force field, and the process of obtaining the clamping force gradient based on the clamping force field is a well-known technique. Here, the clamping force gradient refers to the rate of change of the clamping force in space.
[0062] Calculate the ratio of the norm of the clamping force gradient of each grid to the preset material yield strength, and multiply it by the grid size and the preset compliance influence coefficient to obtain the deformation error of each grid. In this embodiment, the L2 norm is used for calculation. The calculation of the L2 norm is a well-known technique and will not be described in detail here. Secondly, by consulting the manual, the preset flexibility influence coefficient is set to 0.6. As another implementation method, the implementer can set it according to the actual situation.
[0063] It should be noted that the mesh size refers to the mesh size on the refined finite element model during the touch bonding stage.
[0064] It should be noted that a large clamping force gradient indicates that the clamping force varies drastically in space. This means that the clamping force may be very high in some areas and low in others, resulting in an uneven force field distribution. This uneven force field leads to uneven stress distribution on the contact surface, thereby increasing deformation. A larger compliance influence coefficient indicates that the material of the contact surface may have higher compliance, meaning that the contact surface is more prone to deformation under clamping force. Consequently, the degree of mesh deformation is greater. In larger meshes, the variation of clamping force may be averaged out, leading to increased error.
[0065] Secondly, the swaying affects the error from two directions, and the error at this point originates from clamping deformation. Regardless of the direction of the swaying, the final error is reflected in the deformation. Therefore, the swaying from both directions can be directly combined and processed, specifically as follows: During the clamping and loading phase, the ratio between the absolute value of the acceleration of the calculation device in each direction and the sum of the absolute values of the acceleration in all directions is used as the sensitivity coefficient for each direction. The acceleration is normalized, and the product of the normalized acceleration in each direction and the sensitivity coefficient in the corresponding direction is used as the correction factor in each direction. The sum of the value 1 and the correction factors in all directions is used as the influence factor in the clamping loading stage. In this embodiment, the formula for calculating the influence factor during the clamping loading stage is: in, This indicates the influencing factors during the clamping and loading phase. The sensitivity coefficient of the device in the X direction during the clamping and loading phase. The sensitivity coefficient of the device in the Y direction during the clamping and loading phase. This refers to the acceleration of the device in the X direction during the clamping and loading phase. This refers to the acceleration of the device in the Y direction during the clamping and loading phase; where, as well as This represents the normalized acceleration; The calculation process for the sensitivity coefficient is as follows: The product of the deformation error of each grid and the influence factor of the clamping loading stage is used as the positioning error component of each grid under the clamping loading stage. It should be noted that the larger the sensitivity coefficient, the larger the resulting correction factor, indicating that the acceleration in that direction has a greater impact on the clamping force distribution and contact surface deformation. The larger the influence factor, the more severe the comprehensive dynamic load experienced by the equipment during the clamping loading stage, which will significantly exacerbate the error risk caused by the uneven clamping force itself. This means that the clamping force distribution and contact surface deformation are more significantly affected by acceleration. The larger the resulting positioning error component, the more significantly the clamping force distribution and contact surface deformation of the mesh are affected by acceleration during the clamping loading stage. The greater the degree of deformation, the higher the resulting error.
[0066] Furthermore, based on the positioning error components of the mesh during the clamping loading stage, the mesh size for this stage is adjusted so that meshes with large errors require smaller sizes, while meshes with small errors do not require mesh size adjustment. Specifically: in, The adjusted size corresponds to the r-th mesh during the clamping and loading phase. This represents the original size of the r-th mesh during the clamping loading phase. The preset target error, This represents the positioning error component of the r-th grid during the clamping loading stage. This represents a function that takes the minimum value. It should be noted that the size of the r-th grid during the clamping loading phase corresponds to the size before adjustment. That is, equal to the adjusted size of the r-th grid during the contact bonding stage. .
[0067] It should be noted that during the clamping and loading stage, when the positioning error component is greater than the preset target error, the grid is refined, and the grid size is reduced. The larger the positioning error component is relative to the target error, the greater the reduction in grid size. Conversely, when the positioning error component is less than the preset target error, the grid size is not adjusted.
[0068] Based on the adjusted size of each mesh during the clamping loading stage, the mesh in the finite element model is refined, a new mesh is generated, and the size of the mesh is continuously adjusted by iteratively calculating the positioning error components on the new mesh until the positioning error components of all meshes during the clamping loading stage are less than or equal to the preset target error. This concludes the simulation process for the complete clamping and loading phase.
[0069] Step 5: Using the positioning error components of all grids at different stages, obtain the final positioning error of the entire positioning simulation process and evaluate the overall positioning performance of the intelligent positioning equipment prototype.
[0070] Furthermore, based on the mesh errors at different stages of the entire positioning simulation process, the final positioning error is calculated, specifically as follows: Calculate the maximum value of the positioning error components of all grids in the initial alignment stage, and use it as the initial alignment error; Calculate the maximum value of the positioning error components of all grids on the contact surface during the contact bonding stage, and use it as the contact deformation error; Calculate the maximum value of the positioning error components of all grids on the contact surface during the clamping loading stage, and use it as the clamping deformation error; The sum of the initial alignment error, contact deformation error, and clamping deformation error is taken as the final positioning error. Therefore, the finite element software outputs the error matrix for the entire positioning simulation process, specifically: ,in, This indicates the final positioning error. This indicates the initial alignment error. Indicates contact deformation error. This indicates clamping deformation error.
[0071] Then, it was verified through physical experiments, the specific process of which is as follows: Strain gauges and laser displacement sensors were attached to the positioning surface of the positioning mechanism prototype and the positioning reference point of the HGIS equipment. The intelligent equipment prototype was operated to perform the entire positioning process in a real or simulated wind field, and the deformation at each stage and the final positioning error were measured.
[0072] It should be noted that after the equipment is in place, the deviation of the theoretical position in the X, Y and Z directions is measured using a laser sensor to obtain the final positioning error.
[0073] Finally, the simulation results and experimental results are used for calibration to output the optimal structural design, clamping strategy and positioning accuracy requirements of the positioning mechanism, ensuring the millimeter-level positioning accuracy of the HGIS equipment.
[0074] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
[0075] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0076] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application, without departing from the content of the technical solution of this application, shall fall within the protection scope of the technical solution of this application.
Claims
1. A method for constructing a finite element analysis model of an intelligent positioning equipment prototype, characterized in that, The method includes the following steps: A finite element model containing the intelligent positioning equipment prototype, equipment and positioning mechanism was constructed, wind load was applied, and the entire positioning simulation process was divided into multiple stages. For any given stage, a mesh adaptive iterative process is executed, which includes: Based on the spatial gradient and grid size of the grid force distribution under the physical force field at each stage, and the acceleration change of the equipment sway caused by wind load in different directions, the positioning error components of the grid at each stage are calculated. The results are compared with the preset target error. The grid size of the stage is adjusted to re-divide the grid. The process is iterated until the positioning error components of all grids at this stage meet the accuracy requirements. Based on the re-divided grid at this stage, the simulation of the next stage begins. By utilizing the positioning error components of all grids at different stages, the final positioning error of the entire positioning simulation process is obtained, and the overall positioning performance of the intelligent positioning equipment prototype is evaluated.
2. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 1, characterized in that, The multiple stages include the initial alignment stage, the contact and bonding stage, and the clamping and loading stage.
3. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 2, characterized in that, The calculation process for the positioning error components of the grid during the initial alignment stage is as follows: For the stress field in the initial alignment stage, the ratio of the norm of the stress gradient of each grid to the preset material yield strength is calculated, and the product of this ratio and the size of each grid is used as the linearization error of each grid. Based on the magnitude of the equipment's acceleration in different directions during the initial alignment stage, calculate the influence factors of the equipment in each direction during the initial alignment stage. The maximum influence factor of the device in all directions is selected, and its product with the linearization error is used as the positioning error component of each grid in the initial alignment stage.
4. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 3, characterized in that, The calculation process of the influence factor of the device in each direction during the initial alignment stage is as follows: In the initial alignment stage, a sensitivity coefficient is assigned to the device in each direction; the acceleration is normalized, and the product of the normalized acceleration of the device in each direction and the sensitivity coefficient in the corresponding direction is calculated as the correction factor in each direction. The sum of the value 1 and the correction factor is used as the influence factor in each direction.
5. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 2, characterized in that, The calculation process for the positioning error components of the mesh during the contact bonding stage is as follows: For the contact force field during the contact bonding stage, the ratio of the norm of the contact pressure gradient of each grid to the maximum contact pressure of all grids on the contact surface is calculated, and the product of this ratio and the size of the grid is used as the pressure estimation error of each grid. Calculate the ratio of the norm of the contact stress gradient of each grid to the preset reference contact stress, and multiply it by the size of the grid as the stress estimation error of each grid. Based on the proportion of acceleration of the device in each direction during the contact bonding stage, the weighting factor for each direction is calculated. Using the weighting factors of the equipment in each direction as weights, the pressure estimation error and stress estimation error are weighted and summed to form the positioning error component of each grid during the contact bonding stage.
6. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 5, characterized in that, The weighting factor is the ratio between the absolute value of the device's acceleration in each direction and the sum of the absolute values of the acceleration in all directions.
7. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 2, characterized in that, The calculation process for the positioning error components of the mesh during the clamping loading stage is as follows: For the clamping force field during the clamping loading stage, the ratio of the norm of the clamping force gradient of each grid to the preset material yield strength is calculated, and the product of this ratio with the grid size and the preset compliance influence coefficient is used as the deformation error of each grid. Based on the magnitude and proportion of the device's acceleration in different directions during the clamping loading stage, the influencing factors during the clamping loading stage are calculated. The product of the deformation error of each grid and the influence factor of the clamping loading stage is used as the positioning error component of each grid during the clamping loading stage.
8. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 7, characterized in that, The calculation of the influencing factors during the clamping loading stage includes: for the clamping loading stage, calculating the ratio between the absolute value of the acceleration of the device in each direction and the sum of the absolute values of the acceleration in all directions, as the sensitivity coefficient for each direction; normalizing the acceleration, calculating the product of the normalized acceleration of the device in each direction and the sensitivity coefficient in the corresponding direction, as the correction factor for each direction; and summing the value 1 and the correction factors in all directions as the influencing factors for the clamping loading stage.
9. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 1, characterized in that, The adjusted size corresponds to the r-th grid in the q-th stage. The calculation formula is: ,in, Let r be the size of the r-th grid before adjustment in the q-th stage. The preset target error, Let be the positioning error component of the r-th grid in the q-th stage. This is a function that takes the minimum value.
10. The method for constructing a finite element analysis model of an intelligent positioning equipment prototype as described in claim 2, characterized in that, The process of obtaining the final positioning error is as follows: the maximum value of the positioning error components of all grids in the initial alignment stage is taken as the initial alignment error; the maximum value of the positioning error components of all grids on the contact surface in the contact bonding stage and the clamping loading stage are taken as the contact deformation error and clamping deformation error, respectively; the sum of the initial alignment error, contact deformation error and clamping deformation error is taken as the final positioning error.