Machine tool guide rail cooling aperture and cooling liquid parameter collaborative optimization design method

Abstract

The invention discloses a machine tool guide rail cooling aperture and cooling liquid parameter collaborative optimization design method, and relates to the technical field of machine tool guide rail cooling, and the method comprises the following steps: building an overall model of a machine tool guide rail slide block in SolidWorks; the model is imported into ANSYS WorkBench finite element analysis software to be subjected to one-way flow thermosetting simulation analysis; parameterization setting is conducted on the cooling hole diameter, the cooling liquid inlet temperature and the flow speed; obtaining a data sample through Latin hypercube experiment design; constructing a response surface model of the cooling parameters about the average thermal deformation of the guide rail; the method comprises the following steps of: optimizing a cooling parameter by utilizing ANSYS WorkBench; and verifying and comparing the average thermal deformation of the guide rail of the initial model and the optimization model. According to the method, key design variables including the aperture and the cooling flow parameters can be optimized at the same time, the guide rail average thermal deformation serves as an optimization target, the globally optimal cooling parameter scheme is rapidly determined, and therefore the thermal state precision and design efficiency of the machine tool are remarkably improved.

Description

Technical Field

[0001] This invention relates to the technical field of machine tool guideway cooling, and specifically to a method for the collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters. Background Technology

[0002] The accuracy of the feed system of a precision CNC machine tool largely depends on the thermal stability of its key moving components (such as guideways) during long-term operation. When the guideway slider moves at high speed and under heavy load, frictional heat generation can lead to local temperature rise, which in turn causes uneven thermal deformation of the bed and guideways, reducing the machining accuracy of the machine tool. Active cooling is an effective technical means to suppress thermal deformation.

[0003] Existing technologies primarily focus on innovations in cooling structures and the placement of cooling pipes, including creating cooling holes in the guide rails, arranging curved copper tubes within the bed grooves, and surrounding the guide rails with cooling water pipes. These methods utilize circulating coolant to remove heat, aiming to achieve basic cooling or maintain a constant temperature. However, these approaches do not delve into how to scientifically determine the operating parameters of the cooling system to further minimize the design goal of minimizing guide rail thermal deformation. Therefore, minimizing guide rail thermal deformation while a cooling system is in operation, and scientifically and efficiently determining the optimal combination of cooling parameters, has become crucial for improving the machining accuracy and thermal stability of precision CNC machine tools. Summary of the Invention

[0004] The purpose of this invention is to provide a method for the coordinated optimization design of machine tool guideway cooling hole diameter and coolant parameters, so as to overcome the above-mentioned defects in the prior art.

[0005] A method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters includes the following steps: S1. Create an overall model of the machine tool guide rail slider in SolidWorks; S2. Import the model into ANSYS WorkBench finite element analysis software for unidirectional flow thermo-mechanical simulation analysis. S3. Parameterize the cooling hole diameter, coolant inlet temperature and flow rate; S4. Obtain data samples through Latin hypercube experimental design; S5. Construct a response surface model of the cooling parameters with respect to the average thermal deformation of the guide rail; S6. Optimize cooling parameters using ANSYS WorkBench; S7. Verify and compare the average thermal deformation of the guide rail between the initial model and the optimized model.

[0006] Preferably, in step S1, a three-dimensional model of the assembly of the machine tool bed, guide rail, cooling pipe and slider is created using SolidWorks three-dimensional modeling software, wherein the cooling pipe is arranged on the side of the guide rail on the machine tool bed for cooling the guide rail.

[0007] Preferably, the cooling pipe is a straight flow channel with a round hole, which is installed on the side of the machine tool bed by means of an independent metal round pipe, or the straight flow channel with a built-in round hole is directly machined on the machine tool bed.

[0008] Preferably, in step S2, the unidirectional flow thermo-solid simulation analysis is used, which first calculates the flow and convective heat transfer of the coolant fluid, then uses the heat transfer results as boundary conditions to calculate the solid temperature field, and finally uses the temperature field as a load to calculate the thermal deformation of the structure.

[0009] Preferably, the specific steps are as follows: S2.1 Define the convective heat transfer coefficient for different component surfaces. The formula for calculating the convective heat transfer coefficient is as follows:

[0010] Where h is the convective heat transfer coefficient. Let L be the Nusselt number and L be the feature size. S2.2. Set the running speed of the slider to V, the weight of the slide table it carries to G, and the coefficient of friction between the slider and the guide rail to μ. The total frictional heat generated by the guide rail-slider friction pair is calculated using the formula... The calculation shows that by applying this total power equivalently to the actual contact area A of the slider, the average heat flux density of the slider contact surface can be calculated. The contact area A is the inner surface of the slider that directly bears the gravity load of the slide table on one side in the contact pair between the slider and the guide rail. S2.3. Utilize the Fluent project to calculate the flow and convective heat transfer of the coolant, as well as the heat conduction inside the machine tool guide rail, outputting the steady-state temperature field of the machine tool guide rail. Use the steady-state temperature field as a thermal load and transfer it to the static structure project. In the static structure project, set a constant ambient temperature, add remote displacement constraints to the four anchor bolt mounting seats of the machine tool bed, apply pressure to the vertical outer surface of the slider, perform steady-state thermal analysis, and then obtain the average value of the thermal deformation of the guide rail.

[0011] Preferably, in step S3, the pipe radius of the cooling pipe is set to Rmm, the inlet temperature of the coolant is set to T℃, and the flow rate of the coolant is set to Vm / s.

[0012] Preferably, in step S5, a response surface model established by nonparametric regression is used to fit the response surface model and establish an approximate response surface model of the cooling parameters with respect to the average thermal deformation of the guide rail.

[0013] Preferably, in step S6, based on the generated response surface model, the genetic algorithm in ANSYS WorkBench is used to optimize and solve the response surface model, and finally obtain a set of optimal cooling parameter combinations and optimal solutions.

[0014] Preferably, in step S7, the optimized cooling parameter combination is substituted into the original model for calculation to verify the accuracy of the optimization results, and compared with the uncooled model and the model without cooling optimization to confirm the effectiveness of the method.

[0015] The beneficial effects achieved by this invention are as follows: This application integrates cooling orifice diameter and coolant parameters as key design variables, uses the average thermal deformation of the guide rail as the optimization objective, and employs a systematic process combining Latin hypercube experimental design, response surface modeling, and genetic algorithms to efficiently and globally find the optimal combination of cooling parameters within a given design space. This method not only achieves synergistic optimization of multiple variables but also significantly reduces guide rail thermal deformation, thereby effectively improving the thermal accuracy of the machine tool. Furthermore, its systematic and automated optimization process greatly shortens the time required for traditional trial and error, improving overall design efficiency. Attached Figure Description

[0016] Figure 1 This is a flowchart of the unidirectional flow thermo-mechanical simulation analysis and cooling parameter optimization of the machine tool guideway according to the present invention; Figure 2 This is a schematic diagram of the machine tool guideway structure of the present invention; Figure 3 This is a schematic diagram of the reference structure of the machine tool guideway cooling system of the present invention; Figure 4 This is the response surface distribution diagram of the optimal cooling parameter combination of the present invention; Figure 5 This is a diagram showing the average thermal deformation of the guide rail when no cooling system is added according to the present invention. Figure 6 Average thermal deformation diagram of the guide rail when a cooling system is added to this invention. Figure 7 This is the average thermal deformation diagram of the guide rail after the synergistic optimization of cooling hole diameter and coolant parameters according to the present invention. Figure 8 The average thermal deformation diagram of a guide rail is obtained by optimizing structural parameters based on optimal space filling, second-order polynomial response surface and multi-objective genetic algorithm. Figure 9 The average thermal deformation diagram of the guide rail obtained by the method of the present invention is shown below (the setting conditions are: cooling pipe radius is 5mm, the cooling medium is No. 5 spindle oil, the coolant temperature is 18℃, the flow rate is 1m / s, the heat flux density is 880.5w / m2, the ambient temperature is 22℃, and the vertical pressure applied to the slider is 100N).

[0017] In the diagram: 1. Machine tool bed; 2. Guide rail; 3. Cooling pipe; 4. Slider. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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.

[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; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims and drawings of this application are intended to cover non-exclusive inclusion.

[0020] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0021] The cooling pipe of the present invention has a straight flow channel with a circular hole. It can be installed on the side of the bed by an independent circular metal pipe, or the built-in straight flow channel with a circular hole can be directly machined on the bed. The optimized design method provided by the present invention is applicable to both of the above structural forms.

[0022] like Figure 1-9 As shown, this invention discloses a collaborative optimization design method for machine tool guideway cooling orifice diameter and coolant parameters based on Latin hypercube experiments and response surface methodology, comprising the following steps: 1) Create an overall model of the machine tool guide rail slider in SolidWorks: Using SolidWorks 3D modeling software, create a 3D assembly model of the machine tool bed 1, guide rail 2, cooling pipe 3, and slider 4. The cooling pipe 3 is arranged on the side of the guide rail 2 on the machine tool bed 1 to cool the guide rail 2. In this embodiment, the bolt holes on the mounting surface of the guide rail 2 and the bolt holes on the lead screw mounting seat of the machine tool bed 1 are deleted to simplify the model. 2): The model is imported into ANSYS Workbench finite element analysis software for unidirectional flow thermo-mechanical simulation analysis. Material properties are assigned to different components in the engineering data module, including density, coefficient of thermal expansion, isotropic elasticity, isotropic thermal conductivity, and constant-pressure specific heat capacity. Tetrahedral meshing is used to mesh the overall model. The unidirectional flow thermo-mechanical simulation analysis used in this invention first calculates the flow and convective heat transfer of the coolant, then uses the heat transfer results as boundary conditions to calculate the solid temperature field, and finally uses the temperature field as a load to calculate the structural thermal deformation. The specific steps are as follows: 2.1): The formula for calculating the convective heat transfer coefficient of the component surface is: Where h is the convective heat transfer coefficient, N u Let L be the Nusselt number and L be the feature size. In this embodiment, the convective heat transfer coefficients of the horizontal and vertical walls of the slider are 5.482 W / m². 3 9.49W / m 3 The convective heat transfer coefficients of the horizontal and vertical walls of the guide rail are 5.128 W / m. 3 9.754W / m 3 The convective heat transfer coefficients of the horizontal and vertical walls of the bed are 2.12 W / m². 3 6.319W / m 3 The convective heat transfer coefficients of the horizontal and vertical walls of the cooling pipe are 11.12 W / m. 3 9.323W / m 3 .

[0023] 2.2): The running speed of the slider is set to V, the weight of the slide table it bears is G, and the coefficient of friction between the slider and the guide rail is taken as μ. The total frictional heat generated by the guide rail-slider friction pair is calculated using the formula... The calculation shows that by applying this total power equivalently to the actual contact area A of the slider, the average heat flux density of the slider contact surface can be calculated. The contact area A is the inner surface of the slider that directly bears the load of the slide table's gravity (vertical direction) in the contact pair between the slider and the guide rail.

[0024] In this embodiment, the relative running speed V of the slider is set to 0.33 m / s, the weight G of the slide table is 100 N, the coefficient of friction μ between the slider and the guide rail is 0.1, and the contact area A between the slider and the guide rail is 3748 mm². 2 The calculated average heat flux density q at the contact surface of the guide rail and slider is 880.5 W / m². 2 ; 2.3): The Fluent project is used to calculate the flow and convective heat transfer of the coolant, as well as the heat conduction inside the machine tool guideway, and output the steady-state temperature field of the machine tool guideway. The steady-state temperature field is used as a thermal load and transferred to the static structure project. In the static structure project, a constant ambient temperature is set, remote displacement constraints are added to the four anchor bolt mounting seats of the bed, pressure is applied to the vertical outer surface of the slider, and steady-state thermal analysis is performed to obtain the average thermal deformation of the guideway. In this embodiment, the ambient temperature is 22°C and the vertical pressure borne by the slider is 47619 Pa. 3): Parameterize the cooling hole diameter, coolant inlet temperature and flow rate: Parameterize the pipe radius, coolant inlet temperature and coolant flow rate of the cooling pipe. The pipe radius is set to Rmm, the coolant inlet temperature is T℃, and the coolant flow rate is Vm / s. In this embodiment, the pipe radius Rmm ranges from 2 to 8 mm, the coolant inlet temperature T ranges from 17 to 23°C, and the coolant flow velocity V ranges from 0.1 to 1.3 m / s. 4) Data samples were obtained through Latin hypercube experimental design: This ensures spatial coverage of the samples and greatly reduces the number of sample points, significantly reducing the time and economic cost of finite element simulation calculations; In this embodiment, 40 sets of simulation data were calculated using the Latin hypercube experimental design method. 5): Constructing a response surface model of cooling parameters with respect to the average thermal deformation of the guide rail: Using a non-parametric regression method to establish a response surface model, an approximate response surface model of cooling parameters with respect to the average thermal deformation of the guide rail is established. 6): Optimize cooling parameters using the genetic algorithm in ANSYS Workbench: Based on the generated response surface model, use the genetic algorithm to optimize and solve the response surface model, and finally obtain a set of optimal cooling parameter combinations and optimal solutions; In this embodiment, a genetic algorithm is used to explore the response surface model globally, and finally outputs a set of non-dominated optimal solutions. The cooling combination is as follows: cooling pipe radius 3.2465mm, coolant flow rate 0.66397m / s, coolant inlet temperature 19.561℃, and average thermal deformation value of guide rail 0.47473µm.

[0025] 7): Verify and compare the average thermal deformation of the guide rail between the initial model and the optimized model: Substitute the optimized cooling parameters into the original model for calculation, verify the accuracy of the optimization results, and compare them with the uncooled model and the model without cooling optimization to confirm the effectiveness of the method. Under the premise of the same guide rail base structure model, the cooling effect of the present invention was compared with that of the method based on cooling structure parameters optimization. The guide rail optimized based on cooling structure parameters refers to optimizing the position and diameter of the built-in base cooling pipe, that is, parameterizing the distance of the cooling pipe from the bottom of the guide rail contact surface, the side of the guide rail contact surface, and the radius of the cooling pipe. The optimal parameters obtained are a pipe radius of 4.99 mm, a distance of 7.0148 mm from the bottom of the guide rail contact surface, a distance of 21.511 mm from the side of the guide rail contact surface, and an average thermal deformation of 1.2392 µm for the guide rail.

[0026] Based on the optimized structural parameters, this invention optimizes the cooling parameters to obtain the optimal combination of cooling parameters and the average thermal deformation of the guide rail. The results are then compared to verify the effectiveness of the invention. The optimized cooling parameter combination is as follows: coolant inlet temperature 20.11℃, flow rate 1.1234m / s, and average thermal deformation of the guide rail 0.49949µm.

[0027] In this embodiment, a circular correction is performed based on the optimal combination of pipe diameter, flow velocity, and temperature obtained from the optimization solution. Accordingly, the overall unidirectional flow thermo-mechanical simulation model of the machine tool is reconstructed and verified. The calculation shows that the average thermal deformation of the guide rail without cooling pipes is 17.248 μm, while the average thermal deformation of the guide rail directly cooled without cooling parameter optimization is 0.65841 μm. Compared with the former, the average thermal deformation of the guide rail using the method of the present invention is reduced by 0.23488 μm.

[0028] Furthermore, under the same conditions, the cooling effect of this invention was compared with that of a method based on optimization of cooling structure parameters. The results showed that the average thermal deformation of the guide rail obtained by optimizing the cooling parameter combination using this scheme was reduced by 0.73971 μm, and the average thermal deformation of the guide rail was reduced by 59.69%, demonstrating the applicability of this method to other circular cooling pipe systems.

[0029] The embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters, characterized in that: Includes the following steps: S1. Create an overall model of the machine tool guide rail slider in SolidWorks; S2. Import the model into ANSYS WorkBench finite element analysis software for unidirectional flow thermo-mechanical simulation analysis. S3. Parameterize the cooling hole diameter, coolant inlet temperature and flow rate; S4. Obtain data samples through Latin hypercube experimental design; S5. Construct a response surface model of the cooling parameters with respect to the average thermal deformation of the guide rail; S6. Optimize cooling parameters using ANSYS WorkBench; S7. Verify and compare the average thermal deformation of the guide rail between the initial model and the optimized model.

2. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S1, a three-dimensional model of the assembly of the machine tool bed (1), guide rail (2), cooling pipe (3) and slider (4) is established using SolidWorks three-dimensional modeling software. The cooling pipe (3) is arranged on the side of the guide rail (2) on the machine tool bed (1) to cool the guide rail (2).

3. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 2, characterized in that: The cooling pipe is a straight flow channel with a round hole. It is installed on the side of the machine tool bed by means of an independent metal round pipe, or the straight flow channel with a built-in round hole is directly machined on the machine tool bed.

4. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S2, the unidirectional flow thermo-solid simulation analysis is used, which first calculates the flow and convective heat transfer of the coolant fluid, then uses the heat transfer results as boundary conditions to calculate the solid temperature field, and finally uses the temperature field as a load to calculate the thermal deformation of the structure.

5. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 4, characterized in that: The specific steps are as follows: S2.1 Define the convective heat transfer coefficient for different component surfaces. The formula for calculating the convective heat transfer coefficient is as follows: Where h is the convective heat transfer coefficient. Let L be the Nusselt number and L be the feature size. S2.

2. Set the running speed of slider (4) to V, the weight of the slide table it carries to be G, and the friction coefficient between slider (4) and guide rail (2) to be μ. The total frictional heat generation power of the guide rail slider friction pair is calculated using the formula. The calculation shows that the total power is applied equivalently to the actual contact area A of the slider (4), and the average heat flux density of the contact surface of the slider (4) is calculated. The contact area A is the inner surface of the slider (4) that directly bears the gravity load of the slide table on one side in the contact pair between the slider (4) and the guide rail (2). S2.

3. Calculate the flow and convection heat transfer of coolant and the heat conduction inside the machine tool guide rail (2) using the Fluent project, output the steady-state temperature field of the machine tool guide rail (2), and transfer the steady-state temperature field as a heat load to the static structure project. In the static structure project, set a constant ambient temperature, add remote displacement constraints to the four anchor bolt mounting seats of the machine tool bed (1), apply pressure to the vertical outer surface of the slider (4), perform steady-state thermal analysis, and then obtain the average value of the thermal deformation of the guide rail (2).

6. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S3, the pipe radius of the cooling pipe is set to Rmm, the inlet temperature of the coolant is set to T℃, and the flow rate of the coolant is set to Vm / s.

7. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S5, the response surface model established by the nonparametric regression method is fitted to establish an approximate response surface model of the cooling parameters with respect to the average thermal deformation of the guide rail.

8. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S6, based on the generated response surface model, the genetic algorithm in ANSYS WorkBench is used to optimize and solve the response surface model, and finally obtain a set of optimal cooling parameter combinations and optimal solutions.

9. The method for collaborative optimization design of machine tool guideway cooling hole diameter and coolant parameters according to claim 1, characterized in that: In step S7, the optimized cooling parameter combination is substituted into the original model for calculation to verify the accuracy of the optimization results. The results are then compared with uncooled models and models without cooling optimization to confirm the effectiveness of the method.

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