A simulation method and apparatus for heat-cold source composite assisted milling

Abstract

This invention provides a simulation method and apparatus for heat-cold source combined assisted milling. The simulation method includes: determining an induction heating model in the heat-cold source combined assisted milling process based on the acquired geometric parameters, material properties, and heating conditions of the workpiece; determining a preheating temperature field in the heat-cold source combined assisted milling process based on the induction heating model; and inputting preset milling parameters into a preset heat-cold source combined assisted milling simulation model based on the preheating temperature field to simulate the milling process of the workpiece and obtain the target simulation result. The heat-cold source combined assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions, and tool contact model. This invention provides a scientific basis for determining the optimal combination of milling process parameters by simulating the milling process under heat-cold source combined assistance, thereby improving milling efficiency and quality.

Description

Technical Field

[0001] This invention relates to the field of steel milling technology, and in particular to a simulation method and apparatus for heat-cold source composite assisted milling. Background Technology

[0002] H13 hardened cast steel is widely used in the abrasive manufacturing industry. Its high hardness (approximately 60 HRC) and high thermal strength lead to problems such as large cutting forces, severe tool wear, and difficulty in ensuring workpiece surface quality during conventional cutting processes. Studies have shown that the mechanical stress of high-strength steel during shear deformation can be reduced through heat-assisted machining. However, more heat is concentrated in the tool-chip (workpiece) contact area and the workpiece's plastic deformation area, causing localized overheating in the machining zone. This can lead to workpiece damage or premature tool wear, compromising machining efficiency and quality. Current technologies typically use a combination of cold and heat to assist milling. However, in this combined-assisted milling process, the cutting deformation zone involves complex electromagnetic and thermal effects, the effects of low-temperature coolant, and the thermo-mechanical coupling load at the tool-workpiece (chip) contact interface. Existing simulation software struggles to accurately reproduce the actual machining scenario, resulting in significant simulation discrepancies and an inability to obtain accurate and effective milling parameters. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a simulation method and device for heat-cold source combined assisted milling. By simulating the milling process under heat-cold source combined assistance, a scientific basis is provided for determining the optimal combination of milling process parameters, thereby improving the efficiency and quality of milling.

[0004] To address the aforementioned technical problems, embodiments of the present invention provide a simulation method for heat-cold source composite assisted milling, comprising:

[0005] Obtain the geometric parameters, material properties, and heating conditions of the workpiece to be processed;

[0006] Based on the geometric parameters, material properties, and heating conditions, an induction heating model is determined for the heat-cold source composite assisted milling process.

[0007] Based on the induction heating model, the preheating temperature field in the heat-cold source composite assisted milling process is determined;

[0008] Based on the preheating temperature field, preset milling parameters are input into the preset heat-cold source composite assisted milling simulation model to simulate the milling process of the workpiece by heat-cold source composite assisted milling, and the target simulation result is obtained; the heat-cold source composite assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions and tool contact model.

[0009] In one embodiment, the geometric parameters of the workpiece to be processed include the geometric shape of the workpiece to be processed and its corresponding length, width and height; the material properties include the material, thermal properties and mechanical properties of the workpiece to be processed; and the heating conditions include the alternating frequency of the heating current, the heating power and the moving speed of the heating induction coil.

[0010] Based on the geometric parameters, material properties, and heating conditions, an induction heating model is determined for the heat-cold source composite assisted milling process, including:

[0011] The heating induction coil and the workpiece to be processed are geometrically modeled using a preset 3D modeling software, and the positioned geometric model is saved in a preset format to ensure data compatibility.

[0012] The geometric model in the preset format is imported into the preset DEFORM-3D simulation software. At the same time, the material, thermal properties, mechanical properties, alternating frequency of heating current, heating power, and moving speed of heating induction coil of the workpiece to be processed are set to determine the induction heating model.

[0013] In one embodiment, the simulation method for heat-cold source composite assisted milling further includes:

[0014] The tool is geometrically modeled using the preset 3D modeling software to obtain the tool model;

[0015] Based on a preset mesh refinement depth, the contact surface region of the tool model and the workpiece geometry model corresponding to the workpiece to be processed is locally meshed to obtain multiple unit meshes of the contact surface region.

[0016] In one embodiment, the preset mesh refinement depth is represented by the following formula:

[0017] ;

[0018] in, Indicates the preset mesh refinement depth; Represents angular frequency. f represents frequency; Indicates the resistivity of the material; Indicates the permeability of free space; This indicates the relative magnetic permeability of the material.

[0019] In one embodiment, the preset heat exchange window parameters include the temperature of the cooling medium, the convective heat transfer coefficient, and the range of the cooling area during the heat-cold source composite assisted milling process.

[0020] In one embodiment, the tool contact model includes a friction model of the tool-workpiece contact interface and a tool wear model during tool cutting.

[0021] In one embodiment, the friction model is expressed by the following equation:

[0022] ;

[0023] in, Let m represent the shear stress, m represent the shear factor, and k represent the shear strength and yield strength of the material. related.

[0024] In one embodiment, the tool wear model is represented by the following formula:

[0025] ;

[0026] in, The value represents the tool wear amount, where a and b are wear coefficients, p represents the tool contact pressure, V represents the relative speed of tool movement, T represents the absolute temperature, and dt represents the time increment.

[0027] In one embodiment, the simulation method for heat-cold source composite assisted milling further includes:

[0028] Based on the target simulation results, the parameters of the hot-cold source composite assisted milling simulation model are updated and adjusted.

[0029] Embodiments of the present invention also provide a simulation device for heat-cold source composite assisted milling, comprising:

[0030] The acquisition module is used to acquire the geometric parameters, material properties, and heating conditions of the workpiece to be processed; the construction module is used to determine the induction heating model in the heat-cold source composite assisted milling process based on the geometric parameters, material properties, and heating conditions; and to determine the preheating temperature field in the heat-cold source composite assisted milling process based on the induction heating model.

[0031] The simulation module is used to input preset milling parameters into a preset heat-cold source composite assisted milling simulation model based on the preheating temperature field to simulate the milling process of the workpiece by heat-cold source composite assisted milling and obtain the target simulation result; the heat-cold source composite assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions and tool contact model.

[0032] The above-described solution of the present invention has at least the following beneficial effects:

[0033] The simulation method and apparatus for heat-cold source combined assisted milling provided by the above-described solution of the present invention, wherein the method acquires the geometric parameters, material properties, and heating conditions of the workpiece to be processed; determines the induction heating model in the heat-cold source combined assisted milling process based on the geometric parameters, material properties, and heating conditions; determines the preheating temperature field in the heat-cold source combined assisted milling process based on the induction heating model; and, based on the preheating temperature field, inputs preset milling parameters into the preset heat-cold source combined assisted milling simulation model to simulate the milling process of the workpiece and obtains the target simulation result. The heat-cold source combined assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions, and tool contact model. By simulating the milling process under heat-cold source combined assistance, a scientific basis is provided for determining the optimal combination of milling process parameters, thereby improving milling efficiency and quality. Attached Figure Description

[0034] Figure 1 This is a flowchart of a simulation method for heat-cold source composite assisted milling provided in an embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of a preset milling parameter input preset heat-cold source composite assisted milling simulation model provided in an optional embodiment of the present invention;

[0036] Figure 3 This is a cutting force range analysis diagram provided in an optional embodiment of the present invention;

[0037] Figure 4 This is a cutting temperature range analysis diagram provided in an optional embodiment of the present invention;

[0038] Figure 5 This is a tool wear range analysis diagram provided in an optional embodiment of the present invention;

[0039] Figure 6 This is a schematic diagram of the module block of the simulation device for heat-cold source composite assisted milling provided in an embodiment of the present invention;

[0040] Figure 7 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention;

[0041] Figure 8 This is a schematic block diagram of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0042] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0043] In the following description, certain specific details are set forth for the purpose of illustrating various disclosed embodiments in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the art will recognize that embodiments may be practiced without one or more of these specific details. In other instances, well-known apparatuses, structures, and techniques associated with this application may not have been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0044] Throughout this specification, references to "an embodiment" or "an embodiment" indicate that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Therefore, the appearance of "in an embodiment" or "an embodiment" in various places throughout the specification does not necessarily refer to the same embodiment. Furthermore, a particular feature, structure, or characteristic may be combined in any manner in one or more embodiments.

[0045] It should be understood that the terms "comprising / including," "consisting of," or any other variations are intended to cover non-exclusive inclusion, such that a product, apparatus, process, or method that comprises a list of elements includes not only those elements but may also include, where necessary, other elements not expressly listed, or elements inherent to such a product, apparatus, process, or method. Without further limitation, an element defined by the phrases "comprising / including," "consisting of," does not exclude the presence of additional identical elements in the product, apparatus, process, or method that includes said element.

[0046] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0047] like Figure 1 As shown, an embodiment of the present invention provides a simulation method for heat-cold source composite assisted milling, comprising the following steps:

[0048] Step 11: Obtain the geometric parameters, material properties, and heating conditions of the workpiece to be processed;

[0049] Step 12: Determine the induction heating model in the hot-cold source composite assisted milling process based on the geometric parameters, material properties, and heating conditions;

[0050] Step 13: Determine the preheating temperature field in the heat-cold source composite assisted milling process based on the induction heating model;

[0051] Step 14: Based on the preheating temperature field, input the preset milling parameters into the preset heat-cold source composite assisted milling simulation model to simulate the milling process of the workpiece by heat-cold source composite assisted milling, and obtain the target simulation result; the heat-cold source composite assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions and tool contact model.

[0052] In this embodiment, modeling based on the geometric parameters, material properties, and heating conditions of the workpiece to be processed can ensure the accuracy of the induction heating model, thereby ensuring the accuracy of the subsequent milling simulation. Here, the induction heating model is a three-dimensional geometric model that includes the heating conditions, specifically including the three-dimensional geometric model corresponding to the heating induction coil and the three-dimensional geometric model of the workpiece to be processed. Furthermore, under the heating conditions, induction heating is simulated through the induction heating model to obtain the preheating temperature field during hot-cold composite assisted milling, providing heat conduction conditions for the subsequent milling simulation.

[0053] Here, when constructing the thermal-cold source composite assisted milling simulation model, the following assumptions and simplifications need to be made to ensure that the constructed thermal-cold source composite assisted milling simulation model can accurately reproduce the milling process: (a) Assume that the workpiece material is homogeneous and isotropic, and ignore the differences in the microstructure of the workpiece material grains during the milling simulation process; (b) When the heating induction coil heats the workpiece surface, ignore the heating effect of the coil on the tool surface; (c) Ignore the changes in contact pressure distribution and chip flow path caused by tool wear during the actual machining process.

[0054] Here, the preset heat exchange window parameters are parameters such as the cooling medium in a low-temperature micro-lubricant environment (low-temperature cold source) during milling, so as to control the temperature of the cutting area when the tool and the workpiece are in contact during milling simulation, thereby realizing the simulation of the milling process assisted by heat and cold source, so as to realistically restore the heat-cold composite assisted milling process and obtain the target simulation results; here, the target simulation results can include cutting force, cutting temperature, chip morphology, tool wear morphology, workpiece surface roughness, workpiece surface morphology integrity, workpiece subsurface microstructure, and workpiece subsurface microstructure hardness for evaluating milling quality.

[0055] By simulating the milling process assisted by a combined heat and cold source, and combining the simulation results with the analysis of the target, the optimal milling process parameters (the moving speed of the heating induction coil or the tool feed rate V) are determined. f Tool spindle speed n, milling width a e Milling depth a p The combination provides a scientific basis, thereby improving the efficiency and quality of milling.

[0056] In an optional embodiment of the present invention, the preset heat exchange window parameters include the cooling medium temperature, convective heat transfer coefficient, and cooling zone range during the heat-cold source composite assisted milling process; preferably, the cooling medium temperature T can be -10℃, and the convective heat transfer coefficient h can be 2000 W / (m²). 2 The cooling zone, primarily encompassing the areas affected by the induction heat source and the cryogenic cold source, is the surface area of ​​the cutting tool and the workpiece. Preferably, to ensure accurate heat transfer, a convective heat transfer coefficient of 1400 W / (m²) is set between the interfaces of the cutting tool and the workpiece, and between the cutting tool and the chips. 2 ·K). In an optional embodiment of the present invention, the geometric parameters of the workpiece to be processed include the geometric shape of the workpiece and its corresponding length, width and height; the material properties include the material, thermal properties and mechanical properties of the workpiece; and the heating conditions include the alternating frequency of the heating current, the heating power and the moving speed of the heating induction coil. Here, the length, width, height of the workpiece to be processed and the geometric features of the induction coil can be simplified, retaining only the main working area of ​​the induction coil and the main action areas of the induced heat source and the low-temperature cold source, so as to ensure the accuracy of the modeling and avoid the problem of increased computational complexity caused by the sharp increase in subsequent model mesh data after modeling with the overall size.

[0057] Step 12 above may include:

[0058] Step 121: Perform geometric modeling of the heating induction coil and the workpiece to be processed using preset 3D modeling software, and save the positioned geometric model in a preset format to ensure data compatibility.

[0059] Step 122: Import the geometric model in the preset format into the preset DEFORM-3D simulation software, and at the same time set the material, thermal properties, mechanical properties, heating current alternating frequency, heating power and heating induction coil moving speed of the workpiece to be processed in the geometric model, so as to determine the induction heating model.

[0060] In this embodiment, SolidWorks 3D modeling software can be used to perform geometric modeling on the simplified workpiece to be processed and the induction coil, and the positioned geometric model can be saved as .STL format and imported into the preset DEFORM-3D simulation software to further set relevant initial conditions, including the material, thermal properties, mechanical properties, alternating frequency of heating current, heating power, and moving speed of heating induction coil of the workpiece to be processed.

[0061] Here, the material of the workpiece to be processed is hardened mold steel with a Rockwell hardness of 45HRC, such as H13 steel. This material has high hardness and strength, good thermal stability and thermal fatigue performance, and is suitable for mold processing applications. Preferably, the constitutive equation of H13 steel can be described by the DEF model. The material of the heating induction coil can be pure copper to ensure good electromagnetic induction effect.

[0062] In an optional embodiment of the present invention, the above-mentioned simulation method for heat-cold source composite assisted milling may further include:

[0063] Step 123: Perform geometric modeling of the cutting tool based on the preset 3D modeling software to obtain the cutting tool model;

[0064] Step 124: Based on a preset mesh refinement depth, perform local meshing on the contact surface region of the tool model and the workpiece geometry model corresponding to the workpiece to be processed, so as to obtain multiple unit meshes of the contact surface region.

[0065] In this embodiment, SolidWorks 3D modeling software can be used to perform geometric modeling on the simplified tool, and the positioned tool geometry model can be saved as .STL format and imported into the preset DEFORM-3D simulation software; here, the milling cutter and tool holder in the tool are made of cemented carbide WC, whose high hardness and wear resistance can effectively ensure machining accuracy;

[0066] During ultra-high frequency induction heating, the skin effect causes eddy current density to be concentrated mainly in the surface area of ​​the tool and the workpiece, resulting in approximately 86% of the heat being distributed within the skin depth range. Therefore, in the main area of ​​action of the induction heat source and the low-temperature cold source, namely the contact surface area between the tool and the workpiece, the contact surface area between the tool and the workpiece can be meshed by setting a preset mesh refinement depth and combining it with parameters such as the number of meshes and the mesh size ratio, and the mesh density distribution can be controlled to achieve precise allocation of computing resources in different areas. Preferably, the mesh parameters of the tool and the workpiece are set as shown in Table 1 below.

[0067] Table 1. Mesh Parameter Settings for Tool and Workpiece

[0068]

[0069] By meshing the local area (the contact surface area between the tool and the workpiece), the temperature gradient distribution of the tool and workpiece surface area can be accurately simulated. Furthermore, the sparsification of non-critical areas achieves a balance between computational efficiency and accuracy, thus ensuring the high efficiency and accuracy of numerical simulation.

[0070] In an optional embodiment of the present invention, the preset mesh refinement depth is expressed by the following formula:

[0071] ;

[0072] in, Indicates the preset mesh refinement depth; Represents angular frequency. f represents frequency; Indicates the resistivity of the material; Indicates the permeability of free space; This indicates the relative magnetic permeability of the material.

[0073] In this embodiment,

[0074] It should be understood that the contact surface area between the tool model and the workpiece geometry model corresponding to the workpiece to be machined includes both the tool surface area and the workpiece surface area; therefore, the aforementioned preset mesh refinement depth can include:

[0075] ;

[0076] ;

[0077] in, Indicates the preset mesh refinement depth of the cutting tool; Indicates the resistivity of the cutting tool; Indicates the preset mesh refinement depth of the workpiece; This indicates the resistivity of the workpiece.

[0078] In an optional embodiment of the present invention, the tool contact model includes a friction model of the interface between the tool and the workpiece and a tool wear model during tool cutting.

[0079] In this embodiment, the frictional behavior of the tool-chip contact interface is one of the key factors affecting machining performance. During heat-cold source assisted milling, the tool-chip contact interface is subjected to extreme high temperature and high pressure environments due to the preheating treatment by the induction heat source and the complex thermo-mechanical coupling effect in the cutting deformation zone. Compared to the traditional Coulomb friction model, the friction model considering the change in material yield strength can more reasonably describe the plastic flow behavior of metallic materials under high temperature and high pressure (thermal softening effect) conditions.

[0080] Meanwhile, during the removal of H13 hardened die steel, the coupling effect of induced heat and cutting heat causes the tool to be in a high-temperature working state for a long time. The tool wear model can dynamically reflect the key damage mechanisms such as tool material softening and oxidation wear caused by high temperature by introducing the temperature variable T.

[0081] Preferably, in an optional embodiment of the present invention, the friction model is expressed by the following formula:

[0082] ;

[0083] in, Let m represent the shear stress, m represent the shear factor, and k represent the shear strength and yield strength of the material. related.

[0084] Preferably, in an optional embodiment of the present invention, the tool wear model is represented by the following formula:

[0085] ;

[0086] in, The value represents the tool wear amount, where a and b are wear coefficients, p represents the tool contact pressure, V represents the relative speed of tool movement, T represents the absolute temperature, and dt represents the time increment.

[0087] In an optional embodiment of the present invention, the above-described simulation method based on hot-cold source composite assisted milling may further include:

[0088] Step 15: Based on the target simulation results, update and adjust the parameters of the heat-cold source composite assisted milling simulation model.

[0089] In this embodiment, to comprehensively evaluate the applicability of the simulation model, it can be run with several different sets of milling process parameters, and the simulation results corresponding to different parameters can be analyzed to ensure that the simulation process includes various levels of milling parameters. Here, the parameters of the simulation model may include the alternating frequency of the heating current, heating power, the moving speed of the heating induction coil, the cooling medium temperature in the preset heat exchange window parameters, and the convective heat transfer coefficient. By analyzing the target simulation results under different milling process parameter conditions, the parameters of the simulation model can be adjusted in a timely manner, thereby ensuring the accuracy of the simulation. Preferably, the analysis of the target simulation results can be performed by designing orthogonal experiments and using range analysis to ensure the accuracy and reliability of the analysis results.

[0090] The following simulation experiment of heat-cold source combined assisted milling will be conducted using H13 hardened die steel and the corresponding limited cutting process parameters: feed rate 200~400 mm / min, tool spindle speed 500~1500 r / min, milling width 4~12 mm, and milling depth 0.2~0.8 mm as an example. Five key cutting process parameters, namely heating power, feed rate, tool spindle speed, milling width, and milling depth, are selected as control variables. An L18 orthogonal experiment is designed to conduct multi-factor optimization analysis, as shown in Table 2.

[0091] Table 2. Orthogonal experimental design (T = -10℃, h = 2000 W / (m2·K))

[0092]

[0093] Simulation calculations and analyses were performed based on the experimental scheme shown in Table 2, and the experimental results are summarized in Table 3. Cutting force, cutting temperature, and total wear on the tool rake face were selected as key output variables for range analysis. The total cutting force Fr, calculated from the average cutting force components Fx, Fy, and Fz obtained during the simulation's stable phase, was used as the cutting force evaluation value.

[0094] Table 3. Results of the orthogonal experimental design

[0095]

[0096] Table 4 shows the results of range analysis on the influence of cutting force in the simulated hot-cold source combined assisted milling of H13 hardened die steel. The results indicate that the order of cutting force is: depth of cut > spindle speed > width of cut > feed rate > heating power. In actual machining, the lower the cutting force, the lower the mechanical load on the tool. Simultaneously, reducing the cutting temperature indirectly reduces tool thermal damage, effectively delaying tool wear and increasing tool life. Therefore, when cutting force is the optimization target, its value should be as low as possible. The optimal combination of milling process parameters is: heating power 80 kW, feed rate 200 mm / min, spindle speed 1500 r / min, width of cut 4 mm, and depth of cut 0.2 mm.

[0097] Table 4. Cutting Force Range Analysis Table

[0098]

[0099] analyze Figure 3 It can be seen that the cutting force F increases with the feed rate V f Milling width a e and milling depth a pThe cutting force increases with increasing preheating power; however, when the heating power P increases from 50 kW to 80 kW, the decrease in cutting force is more significant. This is mainly because the material enters a stage of rapid decrease in yield strength and tensile strength at higher preheating temperatures, thereby reducing cutting resistance. When the spindle speed n increases from 1000 r / min to 1500 r / min, the decreasing trend in cutting force slows down to some extent.

[0100] Table 5 shows the results of the range analysis on the influence of cutting temperature. The results indicate that the order is: heating power > milling width > milling depth > spindle speed > feed rate. In actual machining, excessively high cutting temperatures will exacerbate tool wear and cause thermal damage to the workpiece surface. Therefore, when cutting temperature is the optimization target, its value should be as small as possible. The optimal combination of milling process parameters is: heating power 20 kW, feed rate 200 mm / min, spindle speed 500 r / min, milling width 4 mm, and milling depth 0.2 mm.

[0101] Table 5. Analysis of Cutting Temperature Range

[0102]

[0103] according to Figure 4 The analysis results show that the cutting temperature T increases with the feed rate V. f Tool spindle speed n, milling width a e and milling depth a p The temperature rises with the increase of process parameters, but once these process parameters reach a certain level, the temperature rise trend tends to level off. In contrast, when the heating power P increases from 50kW to 80kW, the cutting temperature shows a more significant upward trend. The combined effect of induction heat and cutting heat causes a sharp increase in cutting temperature.

[0104] Table 6 shows the range analysis results when the cumulative wear of the tool rake face is the optimization objective. The results indicate that the influence of each factor on tool wear is in the following order: milling width > milling depth > heating power > feed rate > spindle speed. Reducing tool wear is crucial for extending tool life and improving workpiece surface quality, while also helping to reduce production costs and increase machining efficiency. Therefore, when tool wear is the optimization objective, the lower the value, the better. The optimal combination of milling process parameters is: heating power 50 kW, feed rate 300 mm / min, spindle speed 500 r / min, milling width 4 mm, and milling depth 0.2 mm.

[0105] Table 6. Range Analysis of Total Wear on Tool Rake Face

[0106]

[0107] analyze Figure 5It can be seen that the tool wear first decreases and then increases with the change of heating power P. The main reason for this phenomenon is that when the preheating temperature increases, the workpiece material undergoes a thermal softening effect, leading to a reduction in cutting force and thus delaying tool wear; however, as the preheating temperature further increases, the cutting temperature rises sharply, which in turn exacerbates tool wear. Meanwhile, with the increase of feed rate V... f As the cutting temperature increases, tool wear initially decreases and then increases. This may be because high temperatures enhance chip flow and reduce contact pressure p, thus reducing wear on the tool rake face. However, with further increases in cutting temperature, tool wear intensifies. Furthermore, with increasing spindle speed n and milling width a... e and milling depth a p As the wear rate increases, tool wear shows an upward trend, but once it reaches a certain level, the upward trend in wear rate tends to level off.

[0108] The simulation method for heat-cold source composite assisted milling provided in the above embodiments of the present invention obtains the geometric parameters, material properties, and heating conditions of the workpiece to be processed; determines the induction heating model in the heat-cold source composite assisted milling process based on the geometric parameters, material properties, and heating conditions; determines the preheating temperature field in the heat-cold source composite assisted milling process based on the induction heating model; and, based on the preheating temperature field, inputs the preset milling parameters into the preset heat-cold source composite assisted milling simulation model to simulate the milling process of the workpiece and obtains the target simulation results. This provides a scientific basis for determining the optimal combination of milling process parameters, thereby improving the efficiency and quality of milling.

[0109] like Figure 6 As shown, embodiments of the present invention also provide a simulation device 30 based on heat-cold source composite assisted milling, comprising:

[0110] The acquisition module 31 is used to acquire the geometric parameters, material properties and heating conditions of the workpiece to be processed;

[0111] The construction module 32 determines the induction heating model in the heat-cold source composite assisted milling process based on the geometric parameters, material properties, and heating conditions; and determines the preheating temperature field in the heat-cold source composite assisted milling process based on the induction heating model.

[0112] Simulation module 33 is used to simulate the milling process of a workpiece by inputting preset milling parameters into a preset heat-cold source composite assisted milling simulation model based on the preheating temperature field, and to obtain the target simulation result; the heat-cold source composite assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions, and tool contact model.

[0113] It should be noted that this device is the same as the simulation method based on the hot-cold source composite assisted milling described above. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0114] like Figure 7 As shown, embodiments of the present invention also provide an electronic device 50, comprising: a memory 51 for storing one or more computer programs; and one or more processors 52 for executing the one or more computer programs. When the computer programs are run by the processors, they perform the simulation method for hot-cold source composite assisted milling as described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects. The electronic device 50 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown in this invention, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0115] like Figure 8 As shown, electronic device 50 is a computing device or computer system, which may include CPU 501 (computing unit), which can perform various appropriate actions and processes according to a computer program stored in ROM 502 (read-only memory) or a computer program loaded from storage unit 508 into random access RAM 503 (memory). RAM 503 may also store various programs and data required for the operation of device 500. CPU 501, ROM 502, and RAM 503 are interconnected via bus 504. I / O interface 505 (input / output interface) is also connected to bus 504.

[0116] Multiple components in electronic device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0117] CPU 501 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of CPU 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. CPU 501 performs the various methods and processes described above. For example, in some embodiments, the simulation method based on hot-cold source composite assisted milling can be implemented as a computer software program tangibly contained in a computer-readable storage medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by CPU 501, one or more steps of the simulation method based on hot-cold source composite assisted milling described above can be performed. Alternatively, in other embodiments, CPU 501 may be configured by any other suitable means (e.g., by means of firmware) to perform a simulation method based on hot-cold source combined assisted milling.

[0118] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the simulation method for heat-cold source composite assisted milling as described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0120] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0121] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0122] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0123] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0124] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0125] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0126] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps for performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0127] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A simulation method of hot-cold source composite assisted milling, characterized by, The method comprises the following steps: obtaining the geometric parameters of the workpiece to be processed, the material properties and the heating conditions; determining the induction heating model in the hot-cold source composite assisted milling process according to the geometric parameters, the material properties and the heating conditions, specifically comprising: carrying out geometric modeling on the heating induction coil and the workpiece to be processed according to a preset three-dimensional modeling software, and saving the positioned geometric model in a preset format to ensure the compatibility of the data; importing the geometric model in the preset format into a preset DEFORM-3D simulation software, and setting the material, thermal performance, mechanical performance, heating current alternating frequency, heating power and heating induction coil moving speed of the workpiece to be processed of the geometric model to determine the induction heating model; determining the preheating temperature field in the hot-cold source composite assisted milling process according to the induction heating model; inputting preset milling parameters into a preset hot-cold source composite assisted milling simulation model based on the preheating temperature field to simulate the milling process of the workpiece in the hot-cold source composite assisted milling, and obtaining a target simulation result; the hot-cold source composite assisted milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions and a tool contact model; the preset heat exchange window parameters include the cooling medium temperature, the convective heat transfer coefficient and the cooling area range in the hot-cold source composite assisted milling process; the tool contact model includes a friction model of the tool and workpiece contact interface and a tool wear model when the tool is cutting.

2. The simulation method of hot-cold source composite assisted milling according to claim 1, characterized in that, The geometric parameters of the workpiece to be processed include the geometric shape, length, width and height of the workpiece to be processed; the material properties include the material, thermal performance and mechanical performance of the workpiece to be processed; and the heating conditions include the heating current alternating frequency, heating power and heating induction coil moving speed.

3. The simulation method of hot-cold source composite assisted milling according to claim 2, characterized in that, The method further comprises the following steps: carrying out geometric modeling on the tool based on the preset three-dimensional modeling software, and obtaining a tool model; performing local grid division on the contact surface layer area of the tool model and the workpiece geometric model corresponding to the workpiece to be processed based on a preset grid refinement depth, to obtain a plurality of unit grids of the contact surface layer area.

4. The simulation method of hot-cold source composite assisted milling according to claim 3, characterized in that, The preset grid refinement depth is represented by the following formula: ； wherein, represents a preset grid refinement depth; ω represents an angular frequency, , f represents a frequency; represents the resistivity of a material; represents the vacuum permeability; represents the relative permeability of a material.

5. The simulation method of hot-cold source composite assisted milling according to claim 1, characterized in that, The friction model is represented by the following formula: ； wherein, represents the shear stress, m represents the shear factor, k represents the shear strength of the material, and σyrepresents the yield strength of the material .

6. The simulation method of hot-cold source composite assisted milling according to claim 5, characterized in that, The tool wear model is represented by the following formula: ； wherein, wherein, a, b, p, V, T and dt represent the tool wear amount, the wear coefficients, the tool contact pressure, the relative speed of tool movement, the absolute temperature and the time increment, respectively.

7. The simulation method of hot-cold source composite assisted milling according to claim 1, characterized in that, The method further comprises the following steps: updating and adjusting the parameters of the hot-cold source composite assisted milling simulation model according to the target simulation result.

8. A simulation device based on hot-cold source composite assisted milling, characterized by, The device is applied to implement the simulation method of the hot-cold source composite assisted milling according to any one of claims 1-7, and specifically comprises: an acquisition module configured to obtain the geometric parameters of the workpiece to be processed, the material properties and the heating conditions; a construction module configured to determine the induction heating model in the hot-cold source composite assisted milling process according to the geometric parameters, the material properties and the heating conditions, and determine the preheating temperature field in the hot-cold source composite assisted milling process according to the induction heating model; The simulation module is configured to input preset milling parameters into a preset thermal-cold source composite auxiliary milling simulation model to simulate a milling process of the workpiece assisted by the thermal-cold source composite auxiliary milling based on the preheating temperature field, and obtain a target simulation result. The thermal-cold source composite auxiliary milling simulation model is constructed based on the induction heating model, preset heat exchange window parameters, initial boundary conditions, and a tool contact model.

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