A machine tool structure optimization method, apparatus and medium

Abstract

This application relates to the field of machine tool structure optimization technology, specifically to a machine tool structure optimization method, device, and medium, comprising: establishing a parametric simulation model of the machine tool, which has structural variable parameters, including bed dimension variable parameters; determining the first variable range of the structural variable parameters, ensuring that each structural variable parameter meets preset constraints; performing parametric simulation analysis with preset weight and preset stiffness indices as optimization objectives; outputting the first value of the structural variable parameters under the optimal optimization result, with the first value of the bed dimension variable parameters being the final optimized value. This application employs parametric modeling technology, parameterizing the bed dimension variables and setting reasonable variable ranges and constraints, using preset weight and preset stiffness indices as optimization objectives, and using parametric simulation analysis to design the bed dimensions, achieving a balance between weight and structural stiffness optimization, and solving the resonance problem.

Description

Technical Field

[0001] This application relates to the field of machine tool structure optimization technology, specifically to a machine tool structure optimization method, device, and medium. Background Technology

[0002] The bed of the related ultra-precision machine tool uses natural marble. Natural marble has good thermal stability, but its elastic modulus is low and it is brittle. Due to these material properties, the processed shape of natural marble is generally square or rectangular, making it impossible to arbitrarily remove material according to design requirements. Furthermore, to reduce deformation caused by bed load and improve static stiffness, the overall structural dimensions of the bed are usually designed to be large, resulting in excessive bed weight. Under the influence of its own weight and load, the flatness of the bed table is poor, wasting material and increasing processing costs. When the bed weight is large, the overall machine weight is also excessive, which can lead to a decrease in the machine's dynamic vibration resistance, especially since the first-order natural frequency of the machine is too low. Vibrations from the external environment and during processing can easily cause resonance in the entire machine tool system. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, and medium for optimizing machine tool structure to solve the problem of resonance that easily occurs in machine tools.

[0004] To solve the above-mentioned technical problems, this application provides a machine tool structure optimization method, including:

[0005] A parametric simulation model of a machine tool is established, wherein the parametric simulation model of the machine tool has structural variable parameters, including bed dimension variable parameters;

[0006] The first variable range of each of the structural variable parameters is determined, and the structural variable parameters satisfy preset constraints. With preset weight index and preset stiffness index as optimization targets, the parametric simulation model of the machine tool is used to perform parametric simulation analysis on the structural variable parameters, and the first value of the structural variable parameter under the optimal optimization result is output. The first value of the bed dimension variable parameter is the final optimized value.

[0007] Optionally, the machine tool parametric simulation model has motion variable parameters, the structural variable parameters further include layout variable parameters, the first value of the structural variable parameters includes the first value of the layout variable parameters, and the machine tool structure optimization method further includes:

[0008] The range of motion variable parameters is determined, and the second range of layout variable parameters is determined based on the first value of the layout variable parameters. The layout variable parameters satisfy the preset constraint conditions. The preset stiffness index is used as the optimization target. The layout variable parameters and motion variable parameters are parametrically simulated and analyzed using the machine tool parametric simulation model. The second value of the layout variable parameters is output when the preset stiffness index is optimal.

[0009] Based on the first and second values ​​of the layout variable parameters, a third variable range for the layout variable parameters is determined, and the preset constraints are satisfied among the various layout variable parameters. Taking the preset stiffness index as the optimization target, the layout variable parameters and the motion variable parameters are subjected to parametric simulation analysis using the machine tool parametric simulation model. The third value of the layout variable parameters is output when the preset stiffness index is optimal, and the third value of the layout variable parameters is the final optimized value.

[0010] Optionally, the preset weight index includes the weight of the machine tool bed.

[0011] Optionally, the preset stiffness index includes at least one of the following: the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, the strain value of the bed, and the first natural frequency of the bed, wherein the Y direction is the gravity direction.

[0012] Optionally, the preset stiffness index is the maximum deformation of the machine tool bed in the Y direction, and the preset stiffness index is optimal when the maximum deformation of the machine tool bed in the Y direction is the minimum.

[0013] Alternatively, the preset stiffness index is the stress value of the bed, and the preset stiffness index is optimal when the stress value of the bed is at its minimum.

[0014] Alternatively, the preset stiffness index is the strain value of the bed, and the preset stiffness index is optimal when the strain value of the bed is the minimum.

[0015] Alternatively, the preset stiffness index is the first-order natural frequency of the bed, and the preset stiffness index is optimal when the first-order natural frequency of the bed is the highest.

[0016] Optionally, the preset stiffness index includes at least one of the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, and the strain value of the bed, and the optimal optimization result includes:

[0017] The preset weight index and the preset stiffness index are both minimized;

[0018] Alternatively, the weighted sum of the preset weight index and the preset stiffness index is minimized.

[0019] Optionally, the preset stiffness index includes the first-order natural frequency of the bed, and the optimal optimization result includes:

[0020] The preset weight index is the minimum and the preset stiffness index is the maximum.

[0021] Optionally, determining the second variable range of the layout variable parameter based on the first value of the layout variable parameter includes:

[0022] Using the first value of the layout variable parameter as the center point, the second variable range of the layout variable parameter is determined based on experience.

[0023] Optionally, determining the third variable range of the layout variable parameter based on the first value and the second value of the layout variable parameter includes:

[0024] The upper limit of the third variable range is determined by using the larger of the first and second values ​​of the layout variable parameter as the upper limit of the third variable range, and the lower limit of the third variable range is determined by using the smaller of the first and second values ​​of the layout variable parameter as the lower limit of the third variable range.

[0025] Optionally, the machine tool parametric simulation model includes a bed, and a first guide rail component, a second guide rail component, and four support components mounted on the bed. The bed includes an upper bed and a lower bed.

[0026] The distance between the outer edge of the support component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P1. The distance between the outer edge of the first guide rail component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P2. The distance between the adjacent edges of the first guide rail component and the second guide rail component along the Z direction is P3. The distance between the outer edge of the second guide rail component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P4. The layout variable parameters include P1, P2, P3, and P4. The Z direction is a direction perpendicular to the Y direction.

[0027] Optionally, the dimension of the upper bed body along the X direction is P5, the dimension of the lower bed body along the X direction is P6, the dimension of the upper bed body along the Y direction is P7, the dimension of the lower bed body along the Y direction is P8, and the dimensions of the upper bed body and the lower bed body along the Z direction are P9. The bed body dimension variable parameters include P5, P6, P7, P8, and P9, and the X direction, the Y direction, and the Z direction are perpendicular to each other.

[0028] Optionally, both the first guide rail component and the second guide rail component include a guide portion and a sliding portion slidably mounted on the guide portion. The distances between the edges of the sliding portion and the guide portion of the first guide rail component that are close to each other along the X direction are P10 and P13, respectively. The distances between the edges of the sliding portion and the guide portion of the second guide rail component that are close to each other along the Z direction are P11 and P12, respectively. The motion variable parameters include P10, P11, P12, and P13.

[0029] Optionally, the dimensions of the guide portion in the first guide rail component along the X direction and the dimensions of the guide portion in the second guide rail component along the Z direction are L1, the dimensions of the guide portion in the first guide rail component along the Z direction and the dimensions of the guide portion in the second guide rail component along the X direction are W1, the dimensions of the support assembly along the Z direction are L2, the dimensions of the support assembly along the X direction are W2, the dimensions of the sliding portion in the first guide rail component along the X direction and the dimensions of the sliding portion in the second guide rail component along the Z direction are L3, and the dimensions of the center of the spindle component and the upper surface of the upper bed component along the Y direction are H;

[0030] The preset restrictions include:

[0031] (H+P7) / (P9-2×P1-L2)≤1:2

[0032] (H+P7) / (P5+W2)≤1:2

[0033] P2 + P4 + W1 + P3 + L1 ≤ P9

[0034] L1≤P5.

[0035] Optionally, the preset limiting condition also includes: P9-2×P1-2×L2≥500mm.

[0036] Optionally, the range of the motion variable parameters is 0 to (L1-L3).

[0037] Optionally, the machine tool parametric simulation model further includes a spindle component and a tool post component, wherein the sliding part of the first guide rail component is slidably connected to the spindle component, and the sliding part of the second guide rail component is slidably connected to the tool post component;

[0038] In the process of performing parametric simulation analysis on the structural variable parameters using the machine tool parametric simulation model with preset weight and stiffness indicators as optimization targets, the first guide rail component, the second guide rail component, the spindle component, and the tool post component in the machine tool parametric simulation model are suppressed. The weight of the first guide rail component and the spindle component is loaded into the area S1 of the upper bed for mounting the first guide rail component, and the weight of the second guide rail component and the tool post component is loaded into the area S2 of the upper bed for mounting the second guide rail component.

[0039] Optionally, the machine tool parametric simulation model further includes a spindle component and a tool post component, wherein the sliding part of the first guide rail component is slidably connected to the spindle component, and the sliding part of the second guide rail component is slidably connected to the tool post component;

[0040] In the process of using the machine tool parametric simulation model to perform parametric simulation analysis on the layout variable parameters and the motion variable parameters with the preset stiffness index as the optimization target, the spindle component and the tool post component in the machine tool parametric simulation model are suppressed, and the weight of the spindle component is loaded into the sliding part of the first guide rail component in the area for mounting the spindle component, and the weight of the tool post component is loaded into the sliding part of the second guide rail component in the area for mounting the tool post component.

[0041] Optionally, the parametric simulation model of the machine tool is established based on the parametric geometric model of the machine tool, and the machine tool structure optimization method further includes:

[0042] The parametric geometric model of the machine tool is modified based on the first value of the bed dimension variable parameter and the third value of the layout variable parameter.

[0043] This application also provides a machine tool structure optimization device, comprising:

[0044] processor;

[0045] Memory for storing the executable instructions of the processor;

[0046] The processor is configured to execute the aforementioned machine tool structure optimization method by executing the executable instructions.

[0047] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned machine tool structure optimization method.

[0048] The technical effects of this application are as follows:

[0049] The machine tool structure optimization method of this application adopts parametric modeling technology, parameterizes the bed size variables and sets reasonable variable ranges and constraints, and uses preset weight and stiffness indicators as optimization targets. Parametric simulation analysis is used to design the bed size to achieve a balance between weight and structural stiffness. Under the premise of ensuring static stiffness, the weight of the bed is significantly reduced, which not only reduces the amount of table deformation, material consumption and processing costs, but also improves the overall dynamic vibration resistance of the machine through lightweight design. The first-order natural frequency of the bed is raised to a reasonable range, effectively avoiding the problem of decreased machining accuracy caused by whole-machine resonance, and meeting the stringent requirements of ultra-precision machining for structural stability. Attached Figure Description

[0050] Figure 1 A flowchart of a specific embodiment of the machine tool structure optimization method provided in this application;

[0051] Figure 2 for Figure 1 A schematic diagram of the three-dimensional model of the machine tool established in the machine tool structure optimization method;

[0052] Figure 3 for Figure 2 Top view;

[0053] Figure 4 for Figure 2 Schematic diagram of the middle bed structure;

[0054] Figure 5 for Figure 4 Top view;

[0055] in, Figures 2-5 The accompanying figure labels are as follows:

[0056] 1-Bed; 11-Upper bed; 12-Lower bed; 2-First guide rail assembly; 3-Second guide rail assembly; A-Guide part; B-Sliding part; 4-Spindle assembly; 5-Tool post assembly; 6-Support assembly; 7-Bed support assembly. Detailed Implementation

[0057] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0058] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0059] It should be understood that the phrase "some embodiments" throughout the specification means that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, "some embodiments" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0060] In this description, unless otherwise expressly specified and limited, the terms "connected," "linked," and "fixed" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art will understand the specific meaning of these terms in this document based on the specific circumstances.

[0061] The bed of the related ultra-precision machine tool uses natural marble. Natural marble has good thermal stability, but its elastic modulus is low and it is brittle. Due to these material properties, the processed shape of natural marble is generally square or rectangular, making it impossible to arbitrarily remove material according to design requirements. Furthermore, to reduce deformation caused by bed load and improve static stiffness, the overall structural dimensions of the bed are usually designed to be large, resulting in excessive bed weight. Under the influence of its own weight and load, the flatness of the bed table is poor, wasting material and increasing processing costs. When the bed weight is large, the overall machine weight is also excessive, which can lead to a decrease in the machine's dynamic vibration resistance, especially since the first-order natural frequency of the machine is too low. Vibrations from the external environment and during processing can easily cause resonance in the entire machine tool system.

[0062] To address the aforementioned technical problems, embodiments of this application provide a machine tool structure optimization method. Figure 1 This is a flowchart of a specific embodiment of the machine tool structure optimization method provided in this application.

[0063] The machine tool structure optimization method in this application includes:

[0064] Establish a parametric simulation model for the machine tool. The parametric simulation model for the machine tool has structural variable parameters, including bed dimension parameters.

[0065] The first variable range of each structural variable parameter is determined, and the parameters of each structural variable parameter meet the preset constraints. With preset weight index and preset stiffness index as optimization targets, the parametric simulation model of the machine tool is used to perform parametric simulation analysis on the structural variable parameters. The first value of the structural variable parameter under the optimal optimization result is output, and the first value of the bed dimension variable parameter is the final optimized value.

[0066] The machine tool structure optimization method proposed in this application adopts parametric modeling technology, parameterizes the bed size variables and sets reasonable variable ranges and constraints, and uses preset weight and stiffness indicators as optimization targets. Parametric simulation analysis is used to design the bed size to achieve a balance between weight and structural stiffness. While ensuring static stiffness, the weight of the bed is significantly reduced, which not only reduces table deformation and material consumption and processing costs, but also improves the overall dynamic vibration resistance of the machine through lightweight design. The first-order natural frequency of the bed is raised to a reasonable range, effectively avoiding the problem of decreased machining accuracy caused by whole-machine resonance, and meeting the stringent requirements of ultra-precision machining for structural stability.

[0067] In this embodiment of the application, establishing a parametric simulation model of the machine tool includes:

[0068] It is recommended to use a parametric geometric model for the machine tool. The initial values ​​of the structural dimensions in the parametric geometric model can be determined based on experience.

[0069] Import the parametric geometric model of the machine tool into the finite element software, and simultaneously input the mechanical parameters of the materials into the finite element software. Assign different material properties to each component in the parametric geometric model of the machine tool, set fixed constraints at the fixed connection of the machine tool, add global gravitational acceleration in the Y direction, and adopt a tetrahedral mesh generation method globally. Ensure that the mesh element nodes of the joint surfaces between all components are consistent, and complete the establishment of the parametric simulation model of the machine tool.

[0070] The range of the first variable for each structural variable parameter can be determined empirically.

[0071] Parametric simulation analysis can be achieved through the analysis module in finite element software. The specific analysis steps are well known to those skilled in the art and will not be elaborated here.

[0072] Research has shown that machine tools are subjected to dynamic loads during actual processing, and their dynamic stiffness is directly affected by the layout and motion state of the bed bearing components. Therefore, in order to further improve the overall dynamic vibration resistance performance of the machine, it is also necessary to make reasonable arrangements for the bed bearing components.

[0073] Based on this, the machine tool parametric simulation model has motion variable parameters, and the structural variable parameters also include layout variable parameters. The first value of the structural variable parameters includes the first value of the layout variable parameters. The machine tool structure optimization method of this application embodiment further includes:

[0074] The range of motion variable parameters is determined, and the second range of layout variable parameters is determined based on the first value of layout variable parameters. The layout variable parameters meet the preset constraints. The preset stiffness index is used as the optimization target. The layout variable parameters and motion variable parameters are parametrically simulated and analyzed using the machine tool parametric simulation model. The second value of layout variable parameters is output under the condition that the preset stiffness index is optimal.

[0075] The range of the third variable of the layout variable is determined based on the first and second values ​​of the layout variable parameters, and the layout variable parameters meet the preset constraints. With the preset stiffness index as the optimization target, the layout variable parameters and motion variable parameters are parametrically simulated and analyzed using the machine tool parametric simulation model. The third value of the layout variable parameters is output under the condition of optimal preset stiffness index. The third value of the layout variable parameters is the final optimized value.

[0076] As set above, the machine tool structure optimization method of this application further optimizes the layout of the bed bearing components based on the original bed structure optimization. Specifically: First, this application innovatively introduces layout variable parameters and motion variable parameters into the machine tool parametric simulation model. By adjusting the layout variable parameters (such as the assembly position of the bearing components) and motion variable parameters (such as the spatial position of the moving components), the overall mass distribution and stiffness transmission path of the machine tool are adjusted, thereby improving the vibration resistance of the whole machine. Second, this application adopts a progressive optimization strategy to determine the final optimized value of the layout variable parameters. Specifically: First, based on the initial optimization result (the first value of the layout variable parameters), the second variable range of the layout variable parameters is determined. Under the premise of meeting the preset constraints, the preset stiffness index is used as the optimization target. The second value of the layout variable parameters is screened out through parametric simulation analysis under dynamic load, thereby improving the dynamic stiffness of the machine tool. In the second stage, the second variable range of the secondary constraint variable range (the third variable range) is used for refined optimization, and finally the third value of the layout variable parameters that takes into account both static and dynamic stiffness is obtained. The third value of the layout variable parameters is the final optimized value.

[0077] Therefore, the machine tool structure optimization method of this application first determines the bed size under static load, significantly reduces the bed weight and improves the bed static stiffness while ensuring static stiffness; on this basis, layout variables and motion variables are introduced to more comprehensively consider the machine tool structure under dynamic load, optimize the dynamic performance of the machine tool, achieve a balance between static stiffness and dynamic stiffness, and ensure the stability of the machine tool in ultra-precision machining.

[0078] In some embodiments of this application, the preset weight index includes the weight of the machine tool bed.

[0079] By taking the weight of the machine tool bed as one of the optimization targets, the weight of the bed can be significantly reduced while ensuring static stiffness, thereby reducing the amount of table deformation, reducing material consumption and processing costs, and improving the overall dynamic vibration resistance of the machine through lightweight design.

[0080] In some embodiments of this application, the preset stiffness index includes at least one of the following: the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, the strain value of the bed, and the first natural frequency of the bed, where the Y direction is the direction of gravity.

[0081] As set up above, the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, and the strain value of the bed can all characterize the deformation of the bed. Using the maximum deformation, stress, or strain value of the machine tool bed in the Y direction as one of the optimization targets can reduce the deformation of the bed and improve its vibration resistance. The first-order natural frequency of the bed is related to the dynamic performance of the machine tool. Using the first-order natural frequency of the bed as one of the optimization targets, and constraining the frequency threshold, can avoid the excitation frequencies of the moving parts of the machine tool, thereby reducing the risk of resonance.

[0082] Among them, the preset stiffness index is the maximum deformation of the machine tool bed in the Y direction. The preset stiffness index is optimal when the maximum deformation of the machine tool bed in the Y direction is the minimum.

[0083] Alternatively, the preset stiffness index can be the stress value of the bed. When the stress value of the bed is the minimum, the preset stiffness index is optimal.

[0084] Alternatively, the preset stiffness index is the strain value of the bed. When the strain value of the bed is the minimum, the preset stiffness index is optimal.

[0085] Alternatively, the preset stiffness index can be the first natural frequency of the bed. The preset stiffness index is optimal when the first natural frequency of the bed is the highest.

[0086] In some embodiments of this application, the preset stiffness index includes at least one of the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, and the strain value of the bed. The optimal optimization result includes:

[0087] The preset weight index is the minimum and the preset stiffness index is the optimal;

[0088] Alternatively, the weighted sum of the preset weight index and the preset stiffness index is minimized.

[0089] The above settings enable a balanced optimization of weight and structural stiffness, significantly reducing bed weight, table deformation, material consumption and processing costs, and improving the overall machine's dynamic vibration resistance while ensuring static stiffness.

[0090] In other embodiments of this application, the preset stiffness index includes the first-order natural frequency of the bed, and the optimal optimization result includes:

[0091] The preset weight index is the minimum and the preset stiffness index is the maximum.

[0092] The above settings can achieve a balance between weight and structural stiffness, reduce the weight of the bed and the whole machine, and avoid the excitation frequency of the moving parts of the machine tool, thereby reducing the risk of resonance and improving the overall dynamic vibration resistance performance of the machine.

[0093] Furthermore, the aforementioned determination of the second variable range of the layout variable parameters based on the first value of the layout variable parameters includes:

[0094] Using the first value of the layout variable parameter as the center point, determine the second variable range of the layout variable parameter based on experience.

[0095] With the above settings, when further optimizing the layout of the bed-bearing components, the variable range is set around the initial optimization result (the first value of the layout variable parameters). On the premise of ensuring that the static stiffness is not reduced due to subsequent optimization, small-scale fine adjustments are made to the layout parameters and motion parameters to improve the dynamic stiffness of the machine tool, reduce the amount of calculation, and improve optimization efficiency.

[0096] Furthermore, the aforementioned third variable range for determining the layout variable parameters based on the first and second values ​​of the layout variable parameters includes:

[0097] The upper limit of the third variable range is determined by using the larger of the first and second values ​​of the layout variable parameter as the upper limit, and the lower limit is determined by using the smaller of the first and second values ​​of the layout variable parameter as the lower limit.

[0098] As set above, the larger of the first and second values ​​of the layout variable parameters is used as the upper limit of the third variable range, and the smaller of the first and second values ​​of the layout variable parameters is used as the lower limit of the third variable range. Fine optimization is performed within this range so that the optimized values ​​of the layout variable parameters can take into account both the static and dynamic stiffness of the machine tool and improve the dynamic performance of the machine tool.

[0099] Please refer to Figures 2-5 , Figure 2 for Figure 1 A schematic diagram of the three-dimensional model of the machine tool established in the machine tool structure optimization method; Figure 3 for Figure 2 Top view; Figure 4 for Figure 2 Schematic diagram of the middle bed structure; Figure 5 for Figure 4 Top view.

[0100] The parametric simulation model of the machine tool established in this embodiment includes a bed 1, a first guide rail component 2, a second guide rail component 3, a spindle component 4, a tool post component 5, and four support components 6, wherein:

[0101] The bed frame 1 includes an upper bed frame 11 and a lower bed frame 12. The upper bed frame 11 is connected to the upper end of the lower bed frame 12 along the Y direction. The dimension of the upper bed frame 11 along the X direction is larger than the dimension of the lower bed frame 12 along the X direction. A step is formed between the upper bed frame 11 and the lower bed frame 12.

[0102] The first guide rail component 2 and the second guide rail component 3 both include a guide part A and a sliding part B. The guide part A of the first guide rail component 2 is connected to the upper surface of the upper bed 11 and extends along the X direction. The sliding part B of the first guide rail component 2 is slidably connected to the spindle component 4. The guide part A of the second guide rail component 3 is connected to the upper surface of the upper bed 11 and extends along the Z direction. The sliding part B of the second guide rail component 3 is slidably connected to the tool holder component 5.

[0103] Two of the support components 6 are located on one side of the lower bed 12 in the X direction and distributed along the Z direction. The other two support components 6 are located on the other side of the lower bed 12 in the X direction and distributed along the Z direction. The upper end of the support component 6 in the Y direction is connected to the bed 1. The X, Y and Z directions are perpendicular to each other.

[0104] Specifically, the distance between the outer edge of the support component 6 along the Z direction and the corresponding outer edge of the upper bed 11 along the Z direction is defined as P1; the distance between the outer edge of the first guide rail component 2 along the Z direction and the corresponding outer edge of the upper bed 11 along the Z direction is defined as P2; the distance between the adjacent edges of the first guide rail component 2 and the second guide rail component 3 along the Z direction is defined as P3; the distance between the outer edge of the second guide rail component 3 along the Z direction and the corresponding outer edge of the upper bed 11 along the Z direction is defined as P4; and the distance between the upper bed 11 along the X direction is defined as P5. The dimension along the X direction is P5, the dimension along the X direction of the lower bed 12 is P6, the dimension along the Y direction of the upper bed 11 is P7, the dimension along the Y direction of the lower bed 12 is P8, the dimensions along the Z direction of the upper bed 11 and the lower bed 12 are P9, the distances between the edges of the sliding part B and the guide part A of the first guide rail component 2 that are close to each other along the X direction are P10 and P13 respectively, and the distances between the edges of the sliding part B and the guide part A of the second guide rail component 3 that are close to each other along the Z direction are P11 and P12 respectively.

[0105] The layout variables include P1, P2, P3, and P4; the bed dimensions variables include P5, P6, P7, P8, and P9; and the motion variables include P10, P11, P12, and P13.

[0106] As can be seen from the above description, the structure of bed 1 can be clarified by performing parametric simulation analysis on the bed size variable parameters. By performing parametric simulation analysis on the layout variable parameters and motion variable parameters, the precise positions of the first guide rail component 2, the second guide rail component 3, and the support component 6 when installed on bed 1 can be determined, thereby reducing the weight of bed 1 and the whole machine, realizing a reasonable layout of the load-bearing components, reducing the deformation of bed 1, and improving the vibration resistance of the whole machine.

[0107] It should be noted that, here, in the two support components 6 located on the same side of the lower bed 12 in the X direction, the edges that are close to each other in the Z direction are defined as inner edges, and the edges that are far apart in the Z direction are defined as outer edges. Similarly, in the first guide rail component 2 and the second guide rail component 3, the edges that are close to each other in the Z direction are defined as inner edges, and the edges that are far apart in the Z direction are defined as outer edges.

[0108] Depend on Figure 2 As can be seen, four bed support components 7 are connected to the stepped portion of the bed 1. Support assemblies 6 and bed support components 7 are connected accordingly to support the bed 1. When establishing the parametric simulation model of the machine tool, fixed constraints are set at the connection points between support assemblies 6 and bed support components 7. Support assembly 6 includes a vibration isolation component, an adjusting seat component, and a bracket component connected sequentially from top to bottom along the Y direction. Support assembly 6 also serves as a vibration isolation and height adjustment component. The connection surface between the vibration isolation component and the bed support component 7 is defined as the vibration isolation surface.

[0109] Please continue to refer to this. Figure 2 and Figure 3 The dimensions of the guide portion A in the first guide rail component 2 along the X direction and the guide portion A in the second guide rail component 3 along the Z direction are L1 and W1, respectively. The dimensions of the support assembly 6 along the Z direction are L2 and W2, respectively. The dimensions of the sliding portion B in the first guide rail component 2 along the X direction and the sliding portion B in the second guide rail component 3 along the Z direction are L3. The dimensions of the rotation center of the spindle component 4 and the upper surface of the upper bed 11 along the Y direction are H. The aforementioned preset limiting conditions include:

[0110] (H+P7) / (P9-2×P1-L2)≤1:2

[0111] (H+P7) / (P5+W2)≤1:2

[0112] P2 + P4 + W1 + P3 + L1 ≤ P9

[0113] L1≤P5.

[0114] Wherein, (H+P7) / (P9-2×P1-L2)≤1:2 indicates that the ratio of the distance from the rotation center of the spindle component 4 to the vibration isolation surface along the Y direction to the center distance of the two support components 6 on the same side of the lower bed 12 in the X direction is not greater than 1:2. (H+P7) / (P5+W2)≤1:2 indicates that the ratio of the distance from the rotation center of the spindle component 4 to the vibration isolation surface along the Y direction to the center distance of the two support components 6 on the same side of the lower bed 12 in the Z direction is not greater than 1:2.

[0115] Thus, the above two conditions limit the spindle height and the support spacing (X and Z directions) of the support assembly 6, which helps to maintain a reasonable ratio between the spindle height and the support spacing, reduce the overall center of gravity height of the machine tool, improve the support stability of the machine tool, optimize the load transmission path, improve static and dynamic stiffness, reduce deformation during processing, reduce resonance, and enhance the vibration resistance of the machine tool.

[0116] Wherein, P2+P4+W1+P3+L1≤P9, ensuring that the bed 1 has sufficient space in the Z direction to arrange the first guide rail component 2 and the second guide rail component 3, and avoiding the problem of the first guide rail component 2 and the second guide rail component 3 being suspended.

[0117] Where L1≤P5, it ensures that the bed 1 has sufficient space in the X direction to arrange the first guide rail component 2, and avoids the first guide rail component 2 from being suspended.

[0118] Furthermore, in some embodiments of this application, the preset limiting conditions also include:

[0119] P9-2×P1-2×L2≥500mm.

[0120] In other words, it is also necessary to ensure that the distance between the adjacent edges of the two support components 6 on the same side of the lower bed 12 in the X direction is not less than 500mm, so as to ensure the operator's operating space.

[0121] In this embodiment of the application, the range of motion variable parameters is 0 to (L1-L3).

[0122] Taking the second guide rail component 3 as an example, when the sliding part B is at the leftmost end, P11=0, P12= L1-L3; when the sliding part B is at the rightmost end, P11= L1-L3, P12=0. It can be seen that the range of motion variable parameters is: 0~(L1-L3).

[0123] Further, please refer to Figures 3-5 In some embodiments of this application, when using a machine tool parametric simulation model to perform parametric simulation analysis on structural variable parameters with preset weight and preset stiffness as optimization targets, the first guide rail component 2, the second guide rail component 3, the spindle component 4, and the tool post component 5 in the machine tool parametric simulation model are suppressed, and the weight of the first guide rail component 2 and the spindle component 4 is loaded into the area S1 of the upper bed 11 used for installing the first guide rail component 2, and the weight of the second guide rail component 3 and the tool post component 5 is loaded into the area S2 of the upper bed 11 used for installing the second guide rail component 3.

[0124] Since the movement of the first guide rail component 2, the second guide rail component 3, the spindle component 4, and the tool post component 5 does not need to be considered when performing parametric simulation analysis of structural variable parameters, the first guide rail component 2, the second guide rail component 3, the spindle component 4, and the tool post component 5 in the parametric simulation model of the machine tool can be suppressed. This helps to reduce the complexity of the model, thereby improving the simulation speed and efficiency, and avoiding the problem of excessively long simulation time or insufficient computing resources caused by complex models. The first guide rail component 2, the second guide rail component 3, the spindle component 4, and the tool post component 5 can be restored at any time after suppression. Loading the weight of the first guide rail component 2 and the spindle component 4 into the area S1 of the upper bed 11 used for mounting the first guide rail component 2, and loading the weight of the second guide rail component 3 and the tool post component 5 into the area S2 of the upper bed 11 used for mounting the second guide rail component 3, can more accurately simulate the load distribution under the actual working conditions of the machine tool, which helps to more accurately analyze the deformation of the bed 1, thereby optimizing the design of the bed 1.

[0125] Furthermore, in some embodiments of this application, in the parametric simulation analysis of layout variable parameters and motion variable parameters using a machine tool parametric simulation model with a preset stiffness index as the optimization target, the spindle component 4 and tool holder component 5 in the machine tool parametric simulation model are suppressed, and the weight of the spindle component 4 is loaded into the sliding part B of the first guide rail component 2 in the area for mounting the spindle component 4, and the weight of the tool holder component 5 is loaded into the sliding part B of the second guide rail component 3 in the area for mounting the tool holder component 5.

[0126] Since parametric simulation analysis of layout and motion variables requires consideration of the motion of the first guide rail component 2 and the second guide rail component 3, both components need to be active. However, the sliding parts B of the spindle component 4 and the first guide rail component 2 are relatively fixed, as are the sliding parts B of the tool holder component 5 and the second guide rail component 3. Therefore, the spindle component 4 and the tool holder component 5 can be suppressed, reducing model complexity and improving simulation speed and efficiency. This avoids the problem of excessively long simulation times or insufficient computational resources caused by complex models. The suppressed spindle component 4 and tool holder component 5 can be restored at any time. Loading the weight of the spindle component 4 onto the area in the sliding part B of the first guide rail component 2 used for mounting the spindle component 4, and loading the weight of the tool holder component 5 onto the area in the sliding part B of the second guide rail component 3 used for mounting the tool holder component 5, allows for a more accurate simulation of the load distribution under actual machine tool operating conditions. This helps to more accurately analyze the deformation of the bed 1, thereby optimizing the design of the bed 1.

[0127] Furthermore, as mentioned above, the parametric simulation model of the machine tool is established based on the parametric geometric model of the machine tool. The machine tool structure optimization method of this application embodiment also includes:

[0128] The parametric geometric model of the machine tool is corrected based on the first value of the bed dimension variable parameter and the third value of the layout variable parameter.

[0129] In this way, the revised parametric geometric model of the machine tool can be used in actual machining and production, improving the overall vibration resistance of the machine.

[0130] This application embodiment also provides a machine tool structure optimization device, including:

[0131] processor;

[0132] Memory is used to store the processor's executable instructions;

[0133] The processor is configured to execute the aforementioned machine tool structure optimization method by executing executable instructions.

[0134] The machine tool structure optimization device of this application embodiment is used to perform the aforementioned machine tool structure optimization method, and therefore has the same technical effect as the aforementioned machine tool structure optimization method, which will not be repeated here.

[0135] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the machine tool structure optimization method described above.

[0136] The computer-readable storage medium of this application embodiment is used to implement the machine tool structure optimization method as described above, and therefore has the same technical effect as the aforementioned machine tool structure optimization method, which will not be repeated here.

[0137] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for optimizing machine tool structure, characterized in that, include: A parametric simulation model of a machine tool is established, wherein the parametric simulation model of the machine tool has structural variable parameters, including bed dimension variable parameters; The first variable range of each of the structural variable parameters is determined, and the structural variable parameters satisfy preset constraints. With preset weight index and preset stiffness index as optimization targets, the parametric simulation model of the machine tool is used to perform parametric simulation analysis on the structural variable parameters, and the first value of the structural variable parameter under the optimal optimization result is output. The first value of the bed size variable parameter is the final optimized value. The machine tool parametric simulation model has motion variable parameters, and the structural variable parameters also include layout variable parameters. The first value of the structural variable parameters includes the first value of the layout variable parameters. The machine tool structure optimization method further includes: The range of motion variable parameters is determined, and the second range of layout variable parameters is determined based on the first value of the layout variable parameters. The layout variable parameters satisfy the preset constraint conditions. The preset stiffness index is used as the optimization target. The layout variable parameters and motion variable parameters are parametrically simulated and analyzed using the machine tool parametric simulation model. The second value of the layout variable parameters is output when the preset stiffness index is optimal. Based on the first and second values ​​of the layout variable parameters, a third variable range for the layout variable parameters is determined, and the preset constraints are satisfied among the various layout variable parameters. Taking the preset stiffness index as the optimization target, the layout variable parameters and the motion variable parameters are subjected to parametric simulation analysis using the machine tool parametric simulation model. The third value of the layout variable parameters is output when the preset stiffness index is optimal, and the third value of the layout variable parameters is the final optimized value.

2. The machine tool structure optimization method according to claim 1, characterized in that, The preset weight index includes the weight of the machine tool bed.

3. The machine tool structure optimization method according to claim 1, characterized in that, The preset stiffness index includes at least one of the following: the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, the strain value of the bed, and the first natural frequency of the bed, wherein the Y direction is the gravity direction.

4. The machine tool structure optimization method according to claim 3, characterized in that, The preset stiffness index is the maximum deformation of the machine tool bed in the Y direction. The preset stiffness index is optimal when the maximum deformation of the machine tool bed in the Y direction is minimized. Alternatively, the preset stiffness index is the stress value of the bed, and the preset stiffness index is optimal when the stress value of the bed is at its minimum. Alternatively, the preset stiffness index is the strain value of the bed, and the preset stiffness index is optimal when the strain value of the bed is the minimum. Alternatively, the preset stiffness index is the first-order natural frequency of the bed, and the preset stiffness index is optimal when the first-order natural frequency of the bed is the highest.

5. The machine tool structure optimization method according to claim 3, characterized in that, The preset stiffness index includes at least one of the maximum deformation of the machine tool bed in the Y direction, the stress value of the bed, and the strain value of the bed. The optimal optimization result includes: The preset weight index and the preset stiffness index are both minimized; Alternatively, the weighted sum of the preset weight index and the preset stiffness index is minimized.

6. The machine tool structure optimization method according to claim 3, characterized in that, The preset stiffness index includes the first-order natural frequency of the bed, and the optimal optimization result includes: The preset weight index is the minimum and the preset stiffness index is the maximum.

7. The machine tool structure optimization method according to claim 1, characterized in that, Determining the second variable range of the layout variable parameters based on the first value of the layout variable parameters includes: Using the first value of the layout variable parameter as the center point, the second variable range of the layout variable parameter is determined based on experience.

8. The machine tool structure optimization method according to claim 1, characterized in that, Determining the third variable range of the layout variable parameters based on the first value and the second value of the layout variable parameters includes: The upper limit of the third variable range is determined by using the larger of the first and second values ​​of the layout variable parameter as the upper limit of the third variable range, and the lower limit of the third variable range is determined by using the smaller of the first and second values ​​of the layout variable parameter as the lower limit of the third variable range.

9. The machine tool structure optimization method according to claim 1, characterized in that, The machine tool parametric simulation model includes a bed, a first guide rail component, a second guide rail component, and four support components mounted on the bed. The bed includes an upper bed and a lower bed. The distance between the outer edge of the support component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P1. The distance between the outer edge of the first guide rail component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P2. The distance between the adjacent edges of the first guide rail component and the second guide rail component along the Z direction is P3. The distance between the outer edge of the second guide rail component along the Z direction and the corresponding outer edge of the upper bed along the Z direction is P4. The layout variable parameters include P1, P2, P3, and P4. The Z direction is a direction perpendicular to the Y direction.

10. The machine tool structure optimization method according to claim 9, characterized in that, The upper bed body has a dimension of P5 along the X direction, the lower bed body has a dimension of P6 along the X direction, the upper bed body has a dimension of P7 along the Y direction, the lower bed body has a dimension of P8 along the Y direction, and the upper and lower bed bodies have a dimension of P9 along the Z direction. The bed body dimension variable parameters include P5, P6, P7, P8, and P9. The X, Y, and Z directions are perpendicular to each other.

11. The machine tool structure optimization method according to claim 10, characterized in that, Both the first guide rail component and the second guide rail component include a guide portion and a sliding portion slidably mounted on the guide portion. The distances between the edges of the sliding portion and the guide portion of the first guide rail component that are close to each other along the X direction are P10 and P13, respectively. The distances between the edges of the sliding portion and the guide portion of the second guide rail component that are close to each other along the Z direction are P11 and P12, respectively. The motion variable parameters include P10, P11, P12, and P13.

12. The machine tool structure optimization method according to claim 11, characterized in that, The dimensions of the guide portion in the first guide rail component along the X direction and the dimensions of the guide portion in the second guide rail component along the Z direction are L1; the dimensions of the guide portion in the first guide rail component along the Z direction and the dimensions of the guide portion in the second guide rail component along the X direction are W1; the dimensions of the support assembly along the Z direction are L2; the dimensions of the support assembly along the X direction are W2; the dimensions of the sliding portion in the first guide rail component along the X direction and the dimensions of the sliding portion in the second guide rail component along the Z direction are L3; and the dimensions of the center of the spindle component and the upper surface of the upper bed component along the Y direction are H. The preset restrictions include: (H+P7) / (P9-2×P1-L2)≤1:2 (H+P7) / (P5+W2)≤1:2 P2 + P4 + W1 + P3 + L1 ≤ P9 L1≤P5.

13. The machine tool structure optimization method according to claim 12, characterized in that, The preset limiting conditions also include: P9-2×P1-2×L2≥500mm.

14. The machine tool structure optimization method according to claim 12, characterized in that, The range of the motion variable parameters is 0 to (L1-L3).

15. The machine tool structure optimization method according to claim 11, characterized in that, The machine tool parametric simulation model also includes a spindle component and a tool post component. The sliding part of the first guide rail component is slidably connected to the spindle component, and the sliding part of the second guide rail component is slidably connected to the tool post component. In the process of performing parametric simulation analysis on the structural variable parameters using the machine tool parametric simulation model with preset weight and stiffness indicators as optimization targets, the first guide rail component, the second guide rail component, the spindle component, and the tool post component in the machine tool parametric simulation model are suppressed. The weight of the first guide rail component and the spindle component is loaded into the area S1 of the upper bed for mounting the first guide rail component, and the weight of the second guide rail component and the tool post component is loaded into the area S2 of the upper bed for mounting the second guide rail component.

16. The machine tool structure optimization method according to claim 11, characterized in that, The machine tool parametric simulation model also includes a spindle component and a tool post component. The sliding part of the first guide rail component is slidably connected to the spindle component, and the sliding part of the second guide rail component is slidably connected to the tool post component. In the process of using the machine tool parametric simulation model to perform parametric simulation analysis on the layout variable parameters and the motion variable parameters with the preset stiffness index as the optimization target, the spindle component and the tool post component in the machine tool parametric simulation model are suppressed, and the weight of the spindle component is loaded into the sliding part of the first guide rail component in the area for mounting the spindle component, and the weight of the tool post component is loaded into the sliding part of the second guide rail component in the area for mounting the tool post component.

17. The machine tool structure optimization method according to claim 1, characterized in that, The parametric simulation model of the machine tool is established based on the parametric geometric model of the machine tool, and the machine tool structure optimization method further includes: The parametric geometric model of the machine tool is modified based on the first value of the bed dimension variable parameter and the third value of the layout variable parameter.

18. A machine tool structure optimization device, characterized in that, include: processor; Memory for storing the executable instructions of the processor; The processor is configured to execute the machine tool structure optimization method according to any one of claims 1-17 by executing the executable instructions.

19. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the machine tool structure optimization method as described in any one of claims 1-17.

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