Numerical simulation method for dust motion distribution in machine tool by considering cutting process characteristics

Abstract

The invention discloses a numerical simulation method for motion distribution of dust in a machine tool by considering cutting process characteristics. The method comprises the following steps: establishing a digital model of a cutting machine tool; constructing a computational domain model of computational fluid dynamics; carrying out finite element grid division and grid optimization on each computational domain; importing the grids into a solver, and configuring a CFD model, materials, boundary conditions and the like; setting dynamic grid simulation according to motion characteristics of a cutter and a main shaft in a cutting process; particle source modeling and DEM model parameter setting are carried out according to dust characteristics in the cutting process; performing dynamic monitoring setting and demonstration animation configuration in a numerical simulation process; initializing a calculation domain and setting a calculation process; starting to calculate fluid dynamics-discrete element method coupling simulation calculation; and post-processing a numerical simulation result. According to the method, cutting process characteristics are fully considered in the modeling process, and accurate simulation of cutting dust motion distribution in the machine tool can be realized.

Description

Technical Field

[0001] The invention belongs to the field of dust numerical simulation, and relates to a method for numerical simulation of dust movement distribution in a machine tool taking into account cutting process characteristics. Background Art

[0002] In the processing of high-end equipment in the aerospace field, a large amount of cutting dust is easily generated during the high-speed cutting of metals and the cutting of certain special materials such as carbon fiber composite materials. These cutting dusts are mostly in the micron scale. Affected by high-speed rotating tools and spindles, they are easily diffused inside the machine tool and suspended in the air, and are difficult to settle in a short time. Long-term exposure to this dust can easily cause irritation to the skin and eyes of workers. After inhaling a large amount, it is very easy to harm the health of the respiratory system. In severe cases, it may cause pneumoconiosis, renal failure, etc. Therefore, it is particularly important to prevent and control dust in the working area of ​​the machine tool. However, many machine tools are equipped with large-scale wall suction or floor suction systems for dust removal, and most of them use a uniform distribution method to extract the dust generated during the processing. This dust removal method lacks scientific theoretical guidance and is often inefficient. It takes a lot of time to completely remove the dust, which affects the processing efficiency.

[0003] Numerical simulation has the advantages of accuracy, high efficiency, low consumption, environmental protection, and full visualization. It is known as the third scientific research method besides physical experiments and theoretical analysis. In order to obtain the movement and distribution law of cutting dust in machine tools, to guide the layout of negative pressure air sources in machine tools and improve dust removal efficiency, numerical simulation can be used for simulation analysis. By simulating the air flow and dust distribution in machine tools, theoretical guidance is provided for the optimal design of dust removal systems.

[0004] In order to solve the problem of simulating the movement and distribution of dust in working environments, scholars from many fields such as construction and mining have conducted research on relevant numerical simulation methods. The patent publication number of Zhou Gang et al. is CN113177370, and the invention name is "Numerical simulation method of airflow-dust gas-solid two-phase flow considering environmental humidity factors". The method regards airflow and water vapor as continuous phases for modeling, and uses the component transport model to simulate the dust movement process in the comprehensive mining working face; the patent publication number of Jiang Pinglin et al. is CN116992795, and the invention name is "Tunnel ventilation-spray dust removal simulation method and system based on DEM-CFD coupling". The method uses the DEM method to characterize the distribution of dust particles and droplet particles, and uses the CFD method to accurately simulate the flow field in the tunnel, and then obtains the optimal ventilation-spray dust removal working condition based on the actual engineering environment; the patent publication number of Gong Xiaoyan et al. is CN111027252, and the invention name is "Parameterized simulation method of dust, gas and airflow in comprehensive mining face of coal mine". The method is based on the commercial software Ansys for simulation analysis, and uses Python language to encapsulate the simulation calculation process to realize the programmability of parameters. The overall ideas of the above three methods are worth referring to, but in comparison, due to the high-speed rotation of the tool and spindle during the cutting process in the machine tool, the air flow state is more complicated, and the movement and distribution of dust are more difficult to predict. In addition, the generation and movement of dust will also be affected by the tool structure and process parameters, so the existing numerical simulation methods are difficult to apply directly. Therefore, a numerical simulation method that takes into account the characteristics of the cutting process is needed to realize the simulation of the movement and distribution of cutting dust in the machine tool. Summary of the invention

[0005] Based on the above technical problems, the present invention provides a numerical simulation method for dust movement distribution in machine tools that takes into account the characteristics of the cutting process. The method takes into account the impact of the cutting process on dust generation and movement: the influence of the high-speed rotating tool spindle on air and dust is simulated by the rotating domain and dynamic grid method; the scale distribution of dust is predicted by empirical formulas to achieve discrete phase modeling; the process of cutting to generate dust is simplified according to the characteristics of the material cutting process to achieve dust source modeling. On this basis, the air flow field changes, dust movement and distribution area in the machine tool during the cutting process are predicted by means of bidirectional coupling simulation of computational fluid dynamics and discrete element method, so as to guide the optimal design of the dust removal system in the machine tool.

[0006] The technical solution of the present invention:

[0007] A numerical simulation method for dust movement distribution in a machine tool taking into account the characteristics of a cutting process, the numerical simulation method is a bidirectional coupling simulation of computational fluid dynamics and discrete element method (CFD-DEM): by using a computational fluid dynamics method, a turbulence model adapted to the cutting process is called and model parameters are configured to simulate the air flow in the machine tool during the cutting process; the motion state of a single cutting dust particle is tracked and simulated by the discrete element method, and the interaction between air and dust particles is considered by bidirectional coupling of computational fluid dynamics and discrete element method, and a discrete phase force model adapted to the cutting process is called to accurately simulate the movement and distribution of cutting dust, comprising the following steps:

[0008] S1: Establish a digital model of the cutting machine tool;

[0009] S2: Construct computational fluid dynamics domain model;

[0010] S3: Finite element meshing and mesh optimization of each computational domain;

[0011] S4: Import the mesh into the solver and configure the CFD model, materials and boundary conditions;

[0012] S5: Set dynamic mesh simulation according to the tool and spindle motion characteristics during cutting process;

[0013] S6: Particle source modeling and DEM model parameter setting based on dust characteristics of the cutting process;

[0014] S7: Dynamic monitoring settings and demonstration animation configuration of numerical simulation process;

[0015] S8: initialization of computing domain and setting of computing process;

[0016] S9: Start the computational fluid dynamics-discrete element method bidirectional coupling simulation calculation;

[0017] S10: Post-processing of numerical simulation results.

[0018] Furthermore, in step S1, establishing a digital model of the cutting machine tool refers to: establishing a digital model of the processing area of ​​the cutting machine tool, which must include the processed parts, tools, spindles, and air sources, among which the moving bodies (such as tools and spindles) need to be modeled independently for further processing in step S2.

[0019] Further, in step S2, the construction of the computational fluid dynamics calculation domain model refers to: importing the digital model constructed in step S1 into the computational fluid dynamics pre-processing software, and preliminarily establishing the computational fluid dynamics fluid domain model by using the volume extraction method; then, by plane stretching modeling on the periphery of the rotating body (such as a tool, a spindle), a cylindrical rotating domain with a diameter 5% to 20% greater than the diameter of the rotating body is constructed to simulate its motion; finally, by volume extraction and Boolean operations, the part of the computational fluid dynamics fluid domain model that overlaps with the rotating domain is removed to obtain an outer flow domain. The outer flow domain and the rotating domain are independent of each other and together constitute the computational fluid dynamics calculation domain model.

[0020] Further, in step S3, the finite element meshing and mesh optimization of each computational domain refers to: importing the computational domain model into the finite element meshing tool, selecting the mesh size range according to the size of the computational domain model to draw an unstructured mesh, and encrypting it at key structures such as the tool and the part being cut. The mesh is iteratively optimized for the entire mesh and adjusted for individual meshes to ensure that the mesh distortion is below 0.8 and there is no distorted surface mesh, and the distorted surface mesh includes free, multi-sided, self-intersecting, and self-adjacent. Subsequently, the properties of each surface are defined, the negative pressure gas source is defined as the pressure outlet, the machine tool vent is defined as the pressure inlet, and the machine tool wall and the outer surface of the tool spindle are defined as the wall surface. The regional properties of each computational domain are defined, the outer flow domain and the rotation domain are defined as the fluid region, and the tool spindle region is defined as the physical inhibition region. Finally, a volume mesh is further generated based on the surface mesh and at least 3 boundary layers are added. Through iterative optimization of the entire mesh, the quality of the volume mesh is improved to above 0.25 and there is no negative volume mesh, and the mesh information can be output for subsequent configuration.

[0021] Furthermore, in step S4, the importing of the mesh into the solver and the configuration of the CFD model, materials and boundary conditions refer to: importing the volume mesh obtained in step S3 into the computational fluid dynamics solver, setting general parameters including temperature, pressure, gravity and selecting the solution mode; calling an appropriate turbulence model according to the cutting conditions, and configuring the model parameters; defining the material properties of the air and the tool in the calculation domain; setting the boundary conditions of the flow field inlet, outlet, wall and interfaces of different calculation domains, and the boundary conditions include pressure, air flow rate, backflow, and interface data interaction.

[0022] Furthermore, in step S5, setting the dynamic mesh simulation according to the tool and spindle motion characteristics during the cutting process means: for the rotation domain constructed in step S2, it is necessary to use a rotating coordinate system, a motion mesh or a mesh reconstruction method, set physical parameters such as the rotation center coordinates, the axis coordinates, the rotation speed, and the translation speed, and give the tool spindle rotation and feed motion in the calculation domain, so as to achieve accurate simulation of the air flow and dust movement distribution under the rotation disturbance during the cutting process.

[0023] Furthermore, in step S6, the particle source modeling and DEM model parameter setting based on the dust characteristics of the cutting process refer to: based on the characteristics of the material cutting process, the process of cutting to generate dust is abstracted as a process of incident particles from a particle source of a specific morphology (e.g., for the drilling process, the dust generation process can be abstracted as the incident of several conical particle sources with different vertex angles, and for the milling process, the dust generation process can be abstracted as the incident of a translated point particle source); based on the empirical formula for the dust scale distribution of composite material cutting, the dust scale distribution law under specific cutting parameters is clarified, and the parameters are set according to the dust particle diameter grouping to establish a multi-scale particle source model, and the appropriate force model is called according to the particle scale, and the force model includes lift model, drag model, rotational lift model, pressure gradient force model, Brownian force model, turbulent diffusion force model, and collision model; the physical parameters of the dust particles are set according to the cutting material and cutting process, and the physical parameters include density, specific heat, exit velocity, and flow rate.

[0024] Furthermore, the empirical formula for the size distribution of composite material cutting dust is a multivariate nonlinear regression analysis empirical formula constructed based on composite material cutting experiments. The empirical formula assumes that the size distribution of composite material cutting dust conforms to the logarithmic normal distribution law, as shown in the following formula:

[0025]

[0026] Among them, y 0 is the offset, which affects the overall offset of the curve along the y-axis direction; c is the mean of the lognormal distribution, which affects the position of the curve peak along the x-axis; ω is the standard deviation of the lognormal distribution, which affects the overall width of the curve peak; A is the area of ​​the lognormal distribution. When ω is constant, A affects the height of the curve peak.

[0027] The distribution formula contains four parameters: 0 、x c , ω, A. When describing the dust size distribution problem, the offset y 0 The default value should be 0, x c The values ​​of the three parameters ω, A should be obtained by composite cutting calibration experiment calculation and obey the following formula:

[0028] x c =a 0 +a 1 F+a 2 F 2 +a 3 F 3 +a 4 F 4 +a 5 F 5 +b1 S+b 2 S 2 +b 3 S 3 +b 4 S 4

[0029] ω=c 0 +c 1 F+c 2 F 2 +c 3 F 3 +c 4 F 4 +c 5 F 5 +d 1 S+d 2 S 2 +d 3 S 3 +d 4 S 4

[0030] A=e 0 +e 1 F+e 2 F 2 +e 3 F 3 +e 4 F 4 +e 5 F 5 +f 1 S+f 2 S 2 +f 3 S 3 +f 4 S 4

[0031] Among them, F is the tool feed speed; S is the tool speed; a i , b i 、c i ,d i 、e i 、f i It is a regression parameter and needs to be determined by calibration experiment. After the regression parameters are determined by calibration experiment, the cutting parameters rotation speed (S) and feed speed (F) can be used as input to calculate the distribution formula of composite cutting dust size under the cutting parameters and clarify the specific distribution law of dust size.

[0032] Furthermore, in step S7, the dynamic monitoring setting and demonstration animation configuration of the numerical simulation process refer to: in order to monitor the operating status of the model constructed in steps S1-S6 in real time during the calculation process, it is necessary to perform dynamic monitoring settings of key calculation parameters (such as monitoring various residual values, air flow rate near the main axis, and the mass of released particles) to ensure the normal progress of the simulation calculation process; in addition, it is necessary to configure the demonstration animation during the simulation process, set the animation scene, add key grid drawings, cloud maps, particle trajectories, and adjust the output frame rate, so as to visualize the dynamic simulation process of changes in air flow fields and changes in dust movement distribution.

[0033] Furthermore, in step S8, the calculation domain initialization and calculation process setting means that before the simulation calculation is performed, the entire calculation domain needs to be initialized, the fluid therein is given an initial state, and the initial motion state of the moving bodies such as the tool and the spindle is also given. It is also necessary to set the iterative calculation process parameters including the number of iteration steps, the iteration step length, and the convergence condition to prepare for the start of the simulation calculation.

[0034] Furthermore, in step S9, the starting of the computational fluid dynamics-discrete element method bidirectional coupling simulation calculation refers to simultaneously calling two solution models, the computational fluid dynamics model and the discrete element method model, and using the two configured models to perform bidirectional coupling simulation, performing data interaction in each iterative calculation process, considering the interaction between the fluid phase and the discrete phase, and realizing accurate simulation of air flow and dust movement distribution.

[0035] Furthermore, in step S10, the post-processing of the numerical simulation results refers to: after the simulation is completed, the key information of the simulation process can be extracted in the finite element analysis post-processing module to visualize the simulation results. The air flow field information in the simulation area is obtained through computational fluid dynamics post-processing, and the air flow trajectory, velocity distribution cloud map, and velocity vector map are drawn; the dust movement trajectory, movement state and distribution are obtained through discrete element method post-processing, and the dust concentration information in different areas is statistically analyzed, and curves and distribution cloud maps are drawn; the demonstration animation of the simulation process can also be exported according to step S7, including the movement demonstration of the tool spindle, the change of air flow field distribution, the particle movement trajectory and the change of the diffusion area. Through the post-processing step of the numerical simulation results, the air flow law in the machine tool and the movement distribution law of the cutting dust are accurately characterized, so as to provide theoretical guidance for the subsequent optimization design of the dust removal system.

[0036] The beneficial effects of the present invention are as follows: in view of the lack of scientific theoretical guidance for the removal of cutting dust in machine tools, the low dust removal efficiency, the impact on processing efficiency, and the harm to workers' health, a numerical simulation method for the movement and distribution of dust in machine tools that takes into account the characteristics of the cutting process is proposed. The air flow and dust movement distribution laws in the machine tool are obtained through numerical simulation, providing theoretical guidance for the optimal design of the dust removal system. A numerical simulation model for the movement and distribution of cutting dust in machine tools is constructed based on the bidirectional coupling of computational fluid dynamics and discrete element method. The air flow in the machine tool is simulated by computational fluid dynamics method, and the simulation of cutting dust movement and distribution is achieved by coupling simulation with the former using discrete element method. In the modeling process, the characteristics of the cutting process are fully considered, and the characteristic factors such as the scale distribution, emission form, and the influence of high-speed rotating tools and spindles on air and dust of cutting dust are introduced into the simulation model, ensuring the accuracy of the simulation of cutting dust. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a numerical simulation method of dust movement distribution in a machine tool taking into account the characteristics of the cutting process;

[0038] Figure 2 A computational domain model of computational fluid dynamics in one embodiment of the present invention;

[0039] Figure 3 In one embodiment of the present invention, a rotating coordinate system motion grid is constructed taking into account the rotation of the tool and the spindle;

[0040] Figure 4 In one embodiment of the present invention, a solid conical incident source is formed by highly abstracting the dust outflow characteristics during the drilling process;

[0041] Figure 5 The air flow trajectory in a machine tool simulated by CFD-DEM coupling simulation in one embodiment of the present invention;

[0042] Figure 6 This is a cloud diagram of air velocity distribution near a high-speed rotating tool and a spindle in a machine tool simulated by CFD-DEM coupling simulation in one embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the distribution of cutting dust in a machine tool at the first second, simulated by CFD-DEM coupling simulation in one embodiment of the present invention;

[0044] Figure 8 This is a schematic diagram of the distribution of cutting dust in a machine tool at the second second, simulated by CFD-DEM coupling simulation in one embodiment of the present invention;

[0045] Fig. 9This is a schematic diagram of the distribution of cutting dust in a machine tool at the 3rd second, simulated by CFD-DEM coupling simulation in one embodiment of the present invention;

[0046] Fig.10 This is a schematic diagram of the cutting dust distribution in the machine tool at the 8th second simulated by CFD-DEM coupling simulation in one embodiment of the present invention; DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer and enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. It should be noted that the technical solutions claimed to be protected by the present invention include but are not limited to the following embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative work should fall within the scope of protection of the present invention.

[0048] like Figure 1 As shown, an embodiment of the present invention provides a numerical simulation method for dust movement distribution in a machine tool taking into account the characteristics of a cutting process, specifically a numerical simulation method for movement distribution of dust during drilling in a carbon fiber composite material machining center, the method comprising the following steps:

[0049] S1: Establish a digital model of the cutting machine tool;

[0050] S2: Construct computational fluid dynamics domain model;

[0051] S3: Finite element meshing and mesh optimization of each computational domain;

[0052] S4: Import the mesh into the solver and configure the CFD model, materials, boundary conditions, etc.;

[0053] S5: Set dynamic mesh simulation according to the tool and spindle motion characteristics during cutting process;

[0054] S6: Particle source modeling and DEM parameter setting based on dust characteristics of the cutting process;

[0055] S7: Dynamic monitoring settings and demonstration animation configuration of numerical simulation process;

[0056] S8: initialization of computing domain and setting of computing process;

[0057] S9: Start the computational fluid dynamics-discrete element method bidirectional coupling simulation calculation;

[0058] S10: Post-processing of numerical simulation results.

[0059] Furthermore, in step S1, establishing a digital model of the cutting machine tool refers to: establishing a digital model of the processing area of ​​the cutting machine tool in the digital modeling software Autodesk Inventor, including the processed composite plate, drilling tool, spindle, and air source, wherein the moving body tool and spindle need to be modeled independently for further processing in step S2.

[0060] Further, in step S2, the construction of the computational fluid dynamics calculation domain model refers to: importing the digital model built in step S1 into the computational fluid dynamics pre-processing software SpaceClaim, and using the volume extraction method to preliminarily establish the computational fluid dynamics fluid domain model; then, the tool and the spindle are modeled by plane stretching to construct a cylindrical rotation domain with a diameter greater than the diameter of the rotating body, so as to simulate its movement, and the specific setting is: the tool is a twist drill, the handle diameter is 8mm, and its rotation domain diameter is set to 9.6mm, the spindle diameter is 100mm, and its rotation domain diameter is set to 108mm; finally, through volume extraction and Boolean operation, the outer flow domain is removed from the part of the computational fluid dynamics fluid domain model that overlaps with the rotation domain to obtain the outer flow domain. The outer flow domain and the rotation domain are independent of each other and together constitute the computational fluid dynamics calculation domain model.

[0061] Further, in step S3, the finite element meshing and mesh optimization of each computational domain refers to importing the computational domain model into the finite element meshing tool Fluentmeshing, selecting the mesh size range according to the size of the computational domain model to draw an unstructured mesh, and encrypting it at key structures such as the tool and the part being cut. The mesh is iteratively optimized as a whole and adjusted as individual meshes to ensure that the mesh distortion is below 0.8 and there is no distorted surface mesh, and the distorted surface mesh includes free, multi-sided, self-intersecting, and self-adjacent. Subsequently, the properties of each surface are defined, the negative pressure gas source is defined as the pressure outlet, the machine tool vent is defined as the pressure inlet, and the machine tool wall and the outer surface of the tool spindle are defined as the wall surface. The regional properties of each computational domain are defined, the outer flow domain and the rotation domain are defined as the fluid region, and the tool spindle region is defined as the physical inhibition region. Finally, a volume mesh is further generated on the basis of the surface mesh and 4 layers of boundary layers are added. Through iterative optimization of the overall mesh, the quality of the volume mesh is improved to above 0.25 and there is no negative volume mesh, and the mesh information can be output for subsequent configuration.

[0062] Further, in step S4, the step of importing the mesh into the solver Ansys Fluent and configuring the CFD model, materials and boundary conditions refers to: importing the volume mesh obtained in step S3 into the computational fluid dynamics solver, setting general parameters, and setting the gravity to -9.81 m / s in the Y-axis direction. 2, the temperature is set to 273.15K, the solver selects the pressure basis type, absolute velocity format, and transient solution mode; calls the standard k-ε turbulence model according to the cutting conditions, and configures the model parameters; defines the material properties of the air and tool in the calculation domain; sets the boundary conditions of the flow field inlet, outlet, wall, and interfaces of different calculation domains, sets the outlet pressure according to the negative pressure value of the negative pressure gas source, does not need to set the outlet flow rate, suppresses the outlet backflow, and selects the interface between the rotating domain and the external flow domain for data interaction.

[0063] Furthermore, in step S5, the dynamic mesh simulation is set according to the motion characteristics of the cutting tool and the spindle during the cutting process, which means: for the rotating domain constructed in step S2, the rotating coordinate system method is used to set the physical parameters such as the rotation center coordinates, the rotation axis coordinates, and the rotation speed, and the tool and the spindle in the calculation domain are given rotational motion, so as to realize the accurate simulation of the air flow and dust movement distribution under the rotation disturbance during the cutting process. Figure 3 As shown, in the embodiment, a rotation speed of 3000 r / min is used for composite material hole making, and the rotation speed of the moving grid body needs to be set to 3000 r / min by the rotating coordinate system method.

[0064] Furthermore, in step S6, the particle source modeling and DEM model parameter setting based on the dust characteristics of the cutting process refers to: according to the characteristics of the twist drill hole making process, the dust generation process is abstracted into a conical particle source incident process with two different vertex angles of 120° and 60°, such as Figure 4 As shown in the figure; according to the empirical formula of dust size distribution in composite material cutting, the dust size distribution law under specific cutting parameters is clarified, and the parameters are set according to the dust particle diameter grouping to establish a multi-scale particle source model, and the appropriate force model is called according to the particle size, calling the Saffman lift model, Stokes-Cunningham drag criterion, Dennis-et-al rotation drag criterion, setting the collision pair and collision model, calling the Brownian force model and turbulent diffusion force model for small-scale dust particles; the particle physical characteristics are assigned according to the material properties of carbon fiber composite materials, and the density is set to 1550kg / m 3 , the specific heat is set to 800 J / (g·K), the particle exit velocity is estimated to be 0.94 m / s based on the cutting parameters, and the flow rate is set to 8e-11 kg / s to shorten the calculation time.

[0065] Furthermore, the empirical formula for the size distribution of composite material cutting dust is a multivariate nonlinear regression analysis empirical formula constructed based on composite material cutting experiments. The empirical formula assumes that the size distribution of composite material cutting dust conforms to the logarithmic normal distribution law, as shown in the following formula:

[0066]

[0067] Among them, y0 is the offset, which affects the overall offset of the curve along the y-axis direction; c is the mean of the lognormal distribution, which affects the position of the curve peak along the x-axis; ω is the standard deviation of the lognormal distribution, which affects the overall width of the curve peak; A is the area of ​​the lognormal distribution, and when ω is constant, A affects the height of the curve peak.

[0068] The distribution formula contains four parameters: 0 、x c , ω, A. When describing the dust size distribution problem, the offset y 0 The default value should be 0, x c The values ​​of the three parameters ω, A should be obtained by composite cutting calibration experiment calculation and obey the following formula:

[0069] x c =a 0 +a 1 F+a 2 F 2 +a 3 F 3 +a 4 F 4 +a 5 F 5 +b 1 S+b 2 S 2 +b 3 S 3 +b 4 S 4

[0070] ω=c 0 +c 1 F+c 2 F 2 +c 3 F 3 +c 4 F 4 +c 5 F 5 +d 1 S+d 2 S 2 +d 3 S 3 +d 4 S 4

[0071] A=e 0 +e 1 F+e 2 F 2 +e 3 F 3 +e 4 F 4 +e5 F 5 +f 1 S+f 2 S 2 +f 3 S 3 +f 4 S 4

[0072] Among them, F is the tool feed speed; S is the tool speed; a i , b i 、c i ,d i 、e i 、f i It is a regression parameter and needs to be determined by calibration experiment. After the regression parameters are determined by calibration experiment, the cutting parameters rotation speed (S) and feed speed (F) can be used as input to calculate the distribution formula of composite cutting dust size under the cutting parameters and clarify the specific distribution law of dust size.

[0073] Furthermore, in step S7, the dynamic monitoring setting and demonstration animation configuration of the numerical simulation process refer to: in order to monitor the operating status of the model constructed in steps S1-S6 in real time during the calculation process, it is necessary to perform dynamic monitoring settings of key calculation parameters (such as monitoring various residual values, air flow rate near the main axis, and the mass of released particles) to ensure the normal progress of the simulation calculation process; in addition, it is necessary to configure the demonstration animation during the simulation process, set the animation scene, add key grid drawings, cloud maps, particle trajectories, and adjust the output frame rate, so as to visualize the dynamic simulation process of changes in air flow fields and changes in dust movement distribution.

[0074] Furthermore, in step S8, the calculation domain initialization and calculation process setting means that before the simulation calculation is performed, the entire calculation domain needs to be initialized, the fluid therein is given an initial state, and the initial motion state is also given to the moving bodies such as the tool and the spindle. It is also necessary to set the iterative calculation process parameters, set the number of iterations to 10,000 steps, set the iteration step length to 0.001 seconds, set the calculation residual convergence conditions, and prepare for the start of the simulation calculation.

[0075] Furthermore, in step S9, the starting of the computational fluid dynamics-discrete element method bidirectional coupling simulation calculation refers to simultaneously calling two solution models, the computational fluid dynamics model and the discrete element method model, and using the two configured models to perform bidirectional coupling simulation, performing data interaction in each iterative calculation process, considering the interaction between the fluid phase and the discrete phase, and realizing accurate simulation of air flow and dust movement distribution.

[0076] Furthermore, in step S10, the post-processing of the numerical simulation results means that after the simulation is completed, the key information of the simulation process can be extracted in the finite element post-processing module CFD-Post, and the simulation results can be visualized. The air flow field information in the simulation area is obtained through computational fluid dynamics post-processing, and the air flow trajectory and flow velocity distribution cloud map are drawn, such as Figure 5 , Figure 6 As shown; the dust movement trajectory, movement state and distribution are obtained through discrete element method post-processing, the dust concentration information in different areas is counted, and the curve graph and distribution cloud graph are drawn; the demonstration animation in the simulation process can also be exported according to the S7 step, including the movement demonstration of the tool spindle, the change of air flow field distribution, the particle movement trajectory and the change of the diffusion area, such as Figures 7 to 10 As shown, the distribution of drilling dust in the machine tool at the 1st, 2nd, 3rd and 8th seconds are simulated respectively. After the post-processing steps of the numerical simulation results, the air flow law in the machine tool and the movement distribution law of the cutting dust are accurately characterized, so as to provide theoretical guidance for the optimization design of the subsequent dust removal system.

Claims

1. A numerical simulation method for dust movement distribution in machine tools taking into account the characteristics of the cutting process, It is characterized in that The following steps are involved: S1: Establish a digital model of the cutting machine tool; S2: Construct computational fluid dynamics domain model; S3: Finite element meshing and mesh optimization of each computational domain; S4: Import the mesh into the solver and configure the CFD model, materials and boundary conditions; S5: Set dynamic mesh simulation according to the tool and spindle motion characteristics during cutting process; S6: Particle source modeling and DEM model parameter setting based on dust characteristics of the cutting process; S7: Dynamic monitoring settings and demonstration animation configuration of numerical simulation process; S8: initialization of computing domain and setting of computing process; S9: Start the computational fluid dynamics-discrete element method bidirectional coupling simulation calculation; S10: Post-processing of numerical simulation results.

2. A numerical simulation method for dust movement distribution in a machine tool taking into account the characteristics of the cutting process according to claim 1, It is characterized in that In step S1, establishing a digital model of the cutting machine tool refers to establishing a digital model of the machining area of ​​the cutting machine tool, which must include the machined parts, tools, spindles, and air sources, wherein the moving body must be independently modeled for further processing in step S2.

3. A numerical simulation method for dust movement distribution in a machine tool taking into account the characteristics of the cutting process according to claim 1, It is characterized in that In step S2, constructing a computational fluid dynamics calculation domain model refers to: importing the digital model constructed in step S1 into the computational fluid dynamics pre-processing software, and preliminarily establishing a computational fluid dynamics fluid domain model by using the volume extraction method; then constructing a cylindrical rotating domain with a diameter 5% to 20% larger than the diameter of the rotating body by plane stretching modeling on the periphery of the rotating body, so as to simulate its movement; finally, by volume extraction and Boolean operations, removing the part of the computational fluid dynamics fluid domain model that overlaps with the rotating domain to obtain an outer flow domain; the outer flow domain and the rotating domain are independent of each other and together constitute the computational fluid dynamics calculation domain model.

4. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S3, the finite element meshing and mesh optimization of each computational domain refer to: importing the computational domain model into the finite element meshing tool, selecting the mesh size range according to the size of the computational domain model to draw an unstructured mesh, and encrypting it at key structures such as the tool and the part being cut; iteratively optimizing the overall mesh and adjusting individual meshes to ensure that the mesh distortion is below 0.8 and there is no distorted surface mesh, and the distorted surface mesh includes free, polygonal, self-intersecting, and self-adjacent; then defining the properties of each surface, defining the negative pressure gas source as a pressure outlet, the machine tool vent as a pressure inlet, and the machine tool wall and the outer surface of the tool spindle as a wall; defining the regional properties of each computational domain, defining the outer flow domain and the rotation domain as a fluid region, and defining the tool spindle region as a physical inhibition region; finally, further generating a volume mesh based on the surface mesh and adding at least 3 boundary layers, and through iterative optimization of the overall mesh, improving the quality of the volume mesh to above 0.25 and ensuring that there is no negative volume mesh, and then outputting the mesh information for subsequent configuration.

5. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S4, the importing of the mesh into the solver and the configuration of the CFD model, materials and boundary conditions refer to: importing the volume mesh obtained in step S3 into the computational fluid dynamics solver, setting general parameters including temperature, pressure, gravity and selecting the solution mode; calling the appropriate turbulence model according to the cutting conditions, and configuring the model parameters; defining the material properties of the air and tool in the calculation domain; setting the boundary conditions of the flow field inlet, outlet, wall and the interface of different calculation domains, and the boundary conditions include pressure, air flow rate, backflow, and interface data interaction.

6. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S5, setting the dynamic mesh simulation according to the tool and spindle motion characteristics in the cutting process means: for the rotation domain constructed in step S2, it is necessary to use a rotating coordinate system, a motion mesh or a mesh reconstruction method, set physical parameters such as the rotation center coordinates, the axis coordinates, the rotation speed, and the translation speed, and give the tool spindle rotation and feed motion in the calculation domain, so as to achieve accurate simulation of the air flow and dust movement distribution under the rotation disturbance in the cutting process.

7. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S6, the particle source modeling and DEM model parameter setting based on the dust characteristics of the cutting process refer to: based on the characteristics of the material cutting process, the process of cutting to generate dust is abstracted as the process of incident particles of a particle source with a specific morphology; based on the empirical formula for the dust scale distribution of composite material cutting, the dust scale distribution law under specific cutting parameters is clarified, and the parameters are set according to the dust particle diameter grouping to establish a multi-scale particle source model, and the appropriate force model is called according to the particle scale, and the force model includes a lift model, a drag model, a rotational lift model, a pressure gradient force model, a Brownian force model, a turbulent diffusion force model, and a collision model; the physical parameters of the dust particles are set according to the cutting material and the cutting process, and the physical parameters include density, specific heat, exit velocity, and flow rate; The empirical formula for the size distribution of composite material cutting dust is a multivariate nonlinear regression analysis empirical formula constructed based on composite material cutting experiments; the empirical formula assumes that the size distribution of composite material cutting dust conforms to the logarithmic normal distribution law, as shown in the following formula: Among them, y 0 is the offset, which affects the overall offset of the curve along the y-axis direction; c is the mean of the lognormal distribution, which affects the position of the curve peak along the x-axis; ω is the standard deviation of the lognormal distribution, which affects the overall width of the curve peak; A is the area of ​​the lognormal distribution. When ω is constant, A affects the height of the curve peak; The distribution formula contains four parameters: 0 、x c , ω, A; offset y when describing the dust size distribution problem 0 The default value should be 0, x c The values ​​of the three parameters ω, A should be obtained by composite cutting calibration experiment calculation and obey the following formula: x c =a 0 +a 1 F+a 2 F 2 +a 3 F 3 +a 4 F 4 +a 5 F 5 +b 1 S+b 2 S 2 +b 3 S 3 +b 4 S 4 ω=c 0 +c 1 F+c 2 F 2 +c 3 F 3 +c 4 F 4 +c 5 F 5 +d 1 S+d 2 S 2 +d 3 S 3 +d 4 S 4 A=e 0 +e 1 F+e 2 F 2 +e 3 F 3 +e 4 F 4 +e 5 F 5 +f 1 S+f 2 S 2 +f 3 S 3 +f 4 S 4 Among them, F is the tool feed speed; S is the tool speed; a i , b i 、c i ,d i 、e i 、f i It is a regression parameter and needs to be determined by a calibration experiment. After the regression parameters are determined by the calibration experiment, the cutting parameter rotation speed S and feed speed F can be used as input to calculate the distribution formula of composite material cutting dust size under the cutting parameters and clarify the specific distribution law of dust size.

8. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S7, the dynamic monitoring setting and demonstration animation configuration of the numerical simulation process refer to: in order to monitor the operating status of the model built in steps S1-S6 in real time during the calculation process, dynamic monitoring settings of key calculation parameters are required to ensure the normal progress of the simulation calculation process; in addition, it is necessary to configure the demonstration animation during the simulation process, set the animation scene, add key grid drawings, cloud maps, particle trajectories, and adjust the output frame rate, so as to visualize the dynamic simulation process of changes in air flow fields and changes in dust movement distribution.

9. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S8, the calculation domain initialization and calculation process setting refer to: before performing the simulation calculation, the entire calculation domain needs to be initialized, and the fluid therein is given an initial state, and the initial motion state is also given to moving bodies such as tools and spindles; it is also necessary to set the iterative calculation process parameters including the number of iterations, iteration step size, and convergence conditions to prepare for the start of the simulation calculation; in step S9, the start of the computational fluid dynamics-discrete element method two-way coupling simulation calculation refers to calling two solution models, the computational fluid dynamics model and the discrete element method model, at the same time, using the two configured models to perform two-way coupling simulation, data interaction is performed in each iterative calculation process, considering the interaction between the fluid phase and the discrete phase, to achieve accurate simulation of air flow and dust movement distribution.

10. A numerical simulation method for dust movement distribution in a machine tool taking into account cutting process characteristics according to claim 1, It is characterized in that In step S10, the post-processing of the numerical simulation results refers to: after the simulation is completed, the key information of the simulation process can be extracted in the finite element analysis post-processing module to visualize the simulation results; the air flow field information in the simulation area is obtained through computational fluid dynamics post-processing, and the air flow trajectory, flow velocity distribution cloud map, and flow velocity vector map are drawn; the dust movement trajectory, movement state and distribution are obtained through discrete element method post-processing, the dust concentration information in different areas is counted, and the curve graph and distribution cloud map are drawn; The demonstration animation of the simulation process can also be exported according to step S7, including the movement demonstration of the tool spindle, the change of the air flow field distribution, the particle movement trajectory and the change of the diffusion area; through the post-processing step of the numerical simulation results, the air flow law in the machine tool and the movement distribution law of the cutting dust can be accurately characterized, so as to provide theoretical guidance for the subsequent optimization design of the dust removal system.

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