Cutting process damage depth and process parameter prediction, system, device and medium

Abstract

The application discloses a cutting processing damage depth and process parameter prediction, system, device and medium, relates to the technical field of composite material processing, and at least solves the technical problem that the existing method has low prediction efficiency for the surface damage depth of particle reinforced metal matrix composite material processing. The application obtains a plurality of parameters, obtains the friction coefficient between the material and the tool, the contact characteristic angle and the distance from the initial contact point to the processed surface based on the parameters, further calculates the surface particle internal damage characteristic parameters of the processed material model and the damage depth value of the processed material model based on the parameters, judges whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold, and outputs the cutting parameters. The method can improve the prediction efficiency for the surface damage depth of particle reinforced metal matrix composite material processing.

Description

Technical Field

[0001] This application relates to the field of composite material processing technology, and in particular to cutting damage depth and process parameter prediction, systems, equipment and media. Background Technology

[0002] Particle-reinforced metal matrix composites possess advantages such as light weight, high strength, good wear and impact resistance, isotropy, excellent thermal and electrical conductivity, low coefficient of thermal expansion, good dimensional stability, and designable performance. Therefore, these materials have broad application prospects in aerospace, weaponry, optical instruments, transportation vehicles, and electronic packaging. While the presence of particles significantly enhances material properties, the high hardness and brittleness of these particles cause damage such as particle fracture, pull-out, and debonding on the machined surface after machining. The depth of particle damage on the machined surface is large and random, which is uncontrollable. This damage can significantly impact component fatigue and service life. Therefore, assessing the depth of damage on the machined surface and optimizing process parameters are crucial for ensuring the processing quality of particle-reinforced metal matrix composites.

[0003] Therefore, there is an urgent need to propose a method for predicting the damage depth and optimizing the process parameters of particle-reinforced metal matrix composites during machining. This method would provide a theoretical basis for optimizing the cutting parameters and tool parameters of particle-reinforced metal matrix composites and provide an important guarantee for achieving high-quality and efficient machining of particle-reinforced metal matrix composites. Summary of the Invention

[0004] This application provides a system, device, and medium for predicting machining damage depth and process parameters, which at least solves the technical problem of low prediction efficiency of existing methods for the surface damage depth of particle-reinforced metal matrix composites.

[0005] To address the aforementioned technical problems, this application provides a method for predicting machining damage depth and process parameters, comprising the following steps:

[0006] Obtain the parameters of the material to be processed, the tool parameters, the cutting parameters, and the standard threshold for damage depth;

[0007] The cutting temperature of the material to be processed during the cutting process is measured. Based on the parameters of the material to be processed, the tool parameters, the cutting parameters, and the cutting temperature of the material to be processed during the cutting process, the friction coefficient between the material to be processed and the tool, the contact characteristic angle between the tool and the particles in the material to be processed, and the distance from the tool to the initial contact point of the particles to the processed surface are obtained.

[0008] Based on the cutting temperature of the material to be processed during the cutting process, the friction coefficient between the material to be processed and the cutting tool, and the contact characteristic angle and characteristic distance between the cutting tool and the particles in the material to be processed, the surface particle internal damage characteristic parameters of the processed material model are obtained; wherein, the surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length;

[0009] Based on the damage angle of the internal cracks of the surface particles and the propagation length of the internal cracks of the surface particles, the damage depth value of the processed material model is obtained.

[0010] Determine whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold; if so, output the cutting parameters of the tool as the target cutting parameters.

[0011] As some optional embodiments of this application, the parameters of the material to be processed include particle volume fraction and average particle size; the tool parameters include tool rake angle, tool cutting edge radius and tool material hardness; the cutting parameters include cutting speed, undeformed chip thickness and cutting width.

[0012] As some optional embodiments of this application, the coefficient of friction between the material to be processed and the cutting tool satisfies the following relationship:

[0013] μ=F(V p ,T)

[0014] Where μ represents the friction coefficient at the tool-workpiece interface, T represents the interface temperature, and V represents the friction coefficient at the tool-workpiece interface. p This represents the volume fraction of particles in the composite material; if it is a metal, this value is 0. F represents a function related to temperature and particle volume fraction.

[0015] As some optional embodiments of this application, the contact characteristic angle between the cutting tool and the particles in the material to be processed includes the friction angle between the cutting tool and the particles, the angle between the line connecting the center of the cutting edge of the cutting tool and the center of the particles and the vertical direction, and the angle between the line connecting the center of the cutting edge of the cutting tool and the center of the particles and the horizontal direction.

[0016] As some optional embodiments of this application, the friction angle between the cutting tool and the particles satisfies the following relationship:

[0017] β=arctan(μ(V p ,T))+α

[0018] Wherein, β represents the friction angle between the cutting tool and the particles in the material to be processed;

[0019] μ(V p ,T)

[0020] The coefficient of friction between the material to be processed and the cutting tool is represented by α; the rake angle of the cutting tool is represented by α.

[0021] As some optional embodiments of this application, the angle between the line connecting the center of the cutting edge and the center of the particle and the vertical direction satisfies the following relationship:

[0022]

[0023] Where, α N1 The angle between the line connecting the center of the cutting edge and the center of the reinforcing phase particles and the vertical direction is represented by r; the cutting edge radius of the tool is represented by r; the average size of the reinforcing phase particles is represented by R. hi This indicates the height of the reinforcing phase particles above the tool cutting path.

[0024] As some optional embodiments of this application, the angle between the line connecting the center of the cutting edge and the center of the grain and the horizontal direction satisfies the following relationship:

[0025]

[0026] Where, α M1 The angle between the line connecting the center of the cutting edge of the tool and the center of the grain and the horizontal direction is represented by π; π is the value of pi; α N1 This indicates the angle between the line connecting the center of the cutting edge and the center of the particle and the vertical direction.

[0027] As some optional embodiments of this application, the distance from the initial contact point between the tool and the particle to the machined surface satisfies the following relationship:

[0028] h B =r-rcosα M1

[0029] Among them, h B The distance from the initial contact point between the tool and the particle to the machined surface is represented by r; the cutting edge radius of the tool is represented by α. M1 This indicates the angle between the line connecting the center of the cutting edge of the tool and the center of the particle and the horizontal direction.

[0030] As some optional embodiments of this application, the internal crack damage angle of the surface particles satisfies the following relationship:

[0031] cot 2 (ξ+β+α M1 -α)sin2ξ(1+cos2ξ)-

[0032] 2cot(ξ+β+α M1 -α)(sin 2 2ξ-coS 2 2ξ-cos2ξ)+sin2ξ(1-3cos2ξ)=0

[0033] Wherein, ξ represents the internal crack damage angle of the surface particles; β represents the friction angle between the cutting tool and the particles in the material to be processed; α M1 The angle between the line connecting the center of the cutting edge of the tool and the center of the particle and the horizontal direction is indicated; α represents the rake angle of the tool.

[0034] As some optional embodiments of this application, the crack propagation length inside the surface particles satisfies the following relationship:

[0035]

[0036] Among them, l cr R represents the length of crack propagation inside the surface particles; H represents the average particle size; tool Indicates the hardness of the tool material; δ p0 Indicates the depth to which the particle penetrates the back face of the cutting tool; v p E represents the Poisson's ratio of the reinforcing phase. p The modulus of elasticity of the reinforcing phase is represented by π, and K is the value of pi. c γ represents the fracture toughness of the reinforcing phase; w represents the initial width of the particle-matrix interface crack; λ represents the initial length of the particle-matrix interface crack; γ represents the integral variable.

[0037] As some optional embodiments of this application, the depth to which the particles penetrate the back face of the cutting tool satisfies the following relationship:

[0038]

[0039] Where, δ p0 Indicates the depth to which the particle penetrates the back face of the cutting tool; π is the value of pi; H tool Indicates the hardness of the tool material; R represents the average particle size; E * This represents the composite modulus of the cutting tool and the particles.

[0040] As some optional embodiments of this application, the composite modulus of the cutting tool and the particles satisfies the following relationship:

[0041]

[0042] Among them, E * Indicates the composite modulus of the cutting tool and the particles; υ tool E represents the Poisson's ratio of the tool material. tool Indicates the elastic modulus of the tool material; v p E represents the Poisson's ratio of the reinforcing phase. p This represents the elastic modulus of the reinforcing phase.

[0043] As some optional embodiments of this application, the damage depth of the processed material model satisfies the following relationship:

[0044]

[0045] Where SSD2 represents the damage depth of the processed material model; cr ξ represents the crack propagation length inside the surface particles; h represents the crack damage angle inside the surface particles; B This indicates the distance from the initial contact point between the cutting tool and the particle to the machined surface.

[0046] On the other hand, embodiments of this application also provide: a device for predicting cutting damage depth and process parameters, comprising:

[0047] The parameter acquisition module is used to acquire parameters of the material to be processed, tool parameters, cutting parameters, and standard threshold values ​​for damage depth.

[0048] The first calculation module is used to measure the cutting temperature of the material to be processed during the cutting process. Based on the parameters of the material to be processed, the tool parameters, the cutting parameters, and the cutting temperature of the material to be processed during the cutting process, it obtains the friction coefficient between the material to be processed and the tool, the contact characteristic angle between the tool and the particles in the material to be processed, and the distance from the tool to the initial contact point of the particles to the processed surface.

[0049] The second calculation module is used to obtain the surface particle internal damage characteristic parameters of the processed material model based on the cutting temperature of the material to be processed during the cutting process, the friction coefficient between the material to be processed and the tool, and the contact characteristic angle and characteristic distance between the tool and the particles in the material to be processed; wherein, the surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length;

[0050] The third calculation module is used to obtain the damage depth value of the processed material model based on the damage angle of the internal crack of the surface particles and the crack propagation length of the internal crack of the surface particles.

[0051] The target parameter output module is used to determine whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold; if so, the cutting parameters of the tool are output as the target cutting parameters.

[0052] On the other hand, embodiments of this application also provide: a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the cutting damage depth and process parameter prediction method as described above.

[0053] On the other hand, embodiments of this application also provide: a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the cutting damage depth and process parameter prediction method as described above.

[0054] Compared with existing technologies, this application provides a method for predicting machining damage depth and process parameters. First, it obtains the parameters of the material to be machined, tool parameters, cutting parameters, and a standard threshold for damage depth. Then, it measures the cutting temperature of the material during the cutting process. Based on the parameters of the material to be machined, the tool parameters, the cutting parameters, and the cutting temperature, it obtains the friction coefficient between the material to be machined and the tool, the contact characteristic angle between the tool and particles in the material to be machined, and the distance from the initial contact point between the tool and the particles to the machined surface. Finally, based on the cutting temperature of the material to be machined during the cutting process... The method obtains the surface particle internal damage characteristic parameters of the processed material model by calculating the friction coefficient between the material to be processed and the cutting tool, as well as the contact characteristic angle and characteristic distance between the cutting tool and the particles in the material to be processed. These surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length. Based on the surface particle internal crack damage angle and surface particle internal crack propagation length, the damage depth value of the processed material model is obtained. Finally, it is determined whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold. If so, the cutting parameters of the cutting tool are output as the target cutting parameters. It can be seen that the method described in this application establishes the mechanical relationship between material properties, cutting tool parameters, and the processed surface damage depth by calculating the contact characteristic angle and characteristic distance between the cutting tool and the particles, and the particle internal damage characteristic parameters. This enables accurate prediction of the cutting damage depth and allows for the rational selection of cutting parameters and cutting tool parameters based on the surface damage depth quality requirements, avoiding the problem of excessively large processed surface damage depth due to unreasonable cutting parameter selection. Furthermore, the method described in this application takes into account the microstructure of the material, can accurately determine the particle damage location under different process parameter conditions, and optimize the process parameters based on the calculation results to achieve low-damage machining of particle-reinforced metal matrix composites. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0056] Figure 1This is a schematic diagram of the computer device structure for the hardware operating environment involved in this application;

[0057] Figure 2 This is a flowchart illustrating the method for predicting cutting damage depth and process parameters in this application.

[0058] Figure 3 This is a flowchart of the method for predicting the damage depth and optimizing the process parameters of particle-reinforced metal matrix composites during machining, as described in this application.

[0059] Figure 4 This is a diagram showing the particle fracture damage morphology of a machined surface under the action of a cutting tool, as described in this application.

[0060] Figure 5 This is a schematic diagram showing the contact feature angle and feature distance between the cutting tool and the particles involved in this application;

[0061] Figure 6 This application presents the prediction and experimental results of damage depth on machined surfaces under conditions of unoptimized cutting and tool parameters.

[0062] Figure 7 This application presents the prediction and experimental results of damage depth on machined surfaces under the preferred cutting parameters and tool parameters involved in this application.

[0063] Figure 8 This is a schematic diagram of a cutting damage depth and process parameter prediction device involved in this application.

[0064] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0065] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0066] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationship and movement of each component in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0067] In this application, unless otherwise expressly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0068] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0069] Reference Figure 1 , Figure 1 This is a schematic diagram of the computer device structure of the hardware operating environment involved in this embodiment, such as... Figure 1 As shown, the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0070] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0071] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and electronic programs, and may also include a data storage module.

[0072] exist Figure 1 In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the computer device of this embodiment can be set in the computer device. The computer device calls the cutting damage depth and process parameter prediction device stored in the memory 1005 through the processor 1001 and executes the cutting damage depth and process parameter prediction method provided in this embodiment.

[0073] It should be noted that the aforementioned computer equipment can be an external, independently operating hardware device, or it can be a hardware device built into the Internet of Things system itself.

[0074] Reference Figure 2 Based on the aforementioned hardware environment, this embodiment also provides a method for predicting cutting damage depth and process parameters, including the following steps:

[0075] Step S10: Obtain the parameters of the material to be processed, the tool parameters, the cutting parameters, and the standard threshold for damage depth.

[0076] It should be noted that the parameters of the material to be processed include particle volume fraction V. p and average particle size R; the tool parameters include the tool rake angle α, the tool cutting edge radius r, and the tool material hardness H. tool The cutting parameters include the cutting speed V. s Undeformed chip thickness t c and cutting width a w The damage depth standard threshold can be represented by SSD1.

[0077] Step S20: Measure the cutting temperature T of the material to be processed during the cutting process. Based on the parameters of the material to be processed, the tool parameters, the cutting parameters, and the cutting temperature of the material to be processed during the cutting process, obtain the friction coefficient between the material to be processed and the tool, the contact characteristic angle between the tool and the particles in the material to be processed, and the distance from the tool to the initial contact point of the particles to the processed surface.

[0078] Specifically, the coefficient of friction between the material to be processed and the cutting tool satisfies the following formula 1:

[0079] μ=F(V p T)

[0080] Where μ represents the friction coefficient at the tool-workpiece interface, T represents the interface temperature, and V represents the friction coefficient at the tool-workpiece interface. p This represents the volume fraction of particles in the composite material; if it is a metal, this value is 0. F represents a function related to temperature and particle volume fraction.

[0081] It should be noted that the contact characteristic angle between the cutting tool and the particles in the material to be processed includes the friction angle between the cutting tool and the particles, the angle between the line connecting the center of the cutting edge of the cutting tool and the center of the particles and the vertical direction, and the angle between the line connecting the center of the cutting edge of the cutting tool and the center of the particles and the horizontal direction.

[0082] Specifically, the friction angle between the cutting tool and the particles satisfies the following formula 2:

[0083] β=arctan(μ(V p ,T))+α

[0084] Wherein, β represents the friction angle between the cutting tool and the particles in the material to be processed;

[0085] μ(V p T)

[0086] The coefficient of friction between the material to be processed and the cutting tool is represented by α; the rake angle of the cutting tool is represented by α.

[0087] Specifically, the angle between the line connecting the center of the cutting edge and the center of the particle and the vertical direction satisfies the following formula 3:

[0088]

[0089] Where, α N1 The angle between the line connecting the center of the cutting edge and the center of the reinforcing phase particles and the vertical direction is represented by r; the cutting edge radius of the tool is represented by r; the average size of the reinforcing phase particles is represented by R. hi This indicates the height of the reinforcing phase particles above the tool cutting path.

[0090] Specifically, the angle between the line connecting the center of the cutting edge of the tool and the center of the grain and the horizontal direction satisfies the following formula 4:

[0091]

[0092] Where, α M1 The angle between the line connecting the center of the cutting edge of the tool and the center of the grain and the horizontal direction is represented by π; π is the value of pi; α N1This indicates the angle between the line connecting the center of the cutting edge and the center of the particle and the vertical direction.

[0093] Specifically, the distance from the initial contact point between the cutting tool and the particle to the machined surface satisfies the following formula 5:

[0094] h B =r-rcosα M1

[0095] Among them, h B The distance from the initial contact point between the tool and the particle to the machined surface is represented by r; the cutting edge radius of the tool is represented by α. M1 This indicates the angle between the line connecting the center of the cutting edge of the tool and the center of the particle and the horizontal direction.

[0096] Step S30: Based on the cutting temperature of the material to be processed during the cutting process, the friction coefficient between the material to be processed and the tool, and the contact characteristic angle and characteristic distance between the tool and the particles in the material to be processed, obtain the surface particle internal damage characteristic parameters of the processed material model; wherein, the surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length.

[0097] Specifically, the internal crack damage angle of the surface particles satisfies the following formula 6:

[0098] cot 2 (ξ+β+α M1 -α)sin2ξ(1+cos2ξ)-

[0099] 2cot(ξ+β+α M1 -α)(sin 2 2ξ-cos 2 2ξ-cos2ξ)+sin2ξ(1-3cos2ξ)=0

[0100] Wherein, ξ represents the internal crack damage angle of the surface particles; β represents the friction angle between the cutting tool and the particles in the material to be processed; α M1 The angle between the line connecting the center of the cutting edge of the tool and the center of the particle and the horizontal direction is indicated; α represents the rake angle of the tool.

[0101] Specifically, the crack propagation length inside the surface particles satisfies the following formula 7:

[0102]

[0103] Among them, l cr R represents the length of crack propagation inside the surface particles; H represents the average particle size; tool Indicates the hardness of the tool material; δ p0Indicates the depth to which the particle penetrates the back face of the cutting tool; v p E represents the Poisson's ratio of the reinforcing phase. p The modulus of elasticity of the reinforcing phase is represented by π, and K is the value of pi. c γ represents the fracture toughness of the reinforcing phase; w represents the initial width of the particle-matrix interface crack; λ represents the initial length of the particle-matrix interface crack; γ represents the integral variable.

[0104] In the above formula, the depth to which the particle enters the back face of the tool satisfies the following formula 8:

[0105]

[0106] Where, δ p0 Indicates the depth to which the particle penetrates the back face of the cutting tool; π is the value of pi; H tool Indicates the hardness of the tool material; R represents the average particle size; E * This represents the composite modulus of the cutting tool and the particles.

[0107] In the above formula, the composite modulus of the cutting tool and the particles satisfies the following formula 9:

[0108]

[0109] Among them, E * Indicates the composite modulus of the cutting tool and the particles; υ tool E represents the Poisson's ratio of the tool material. tool Indicates the elastic modulus of the tool material; v p E represents the Poisson's ratio of the reinforcing phase. p This represents the elastic modulus of the reinforcing phase.

[0110] Step S40: Based on the damage angle of the internal cracks of the surface particles and the length of the internal crack propagation of the surface particles, obtain the damage depth value of the processed material model.

[0111] Specifically, the damage depth of the processed material model satisfies the following formula 10:

[0112]

[0113] Where SSD2 represents the damage depth of the processed material model; cr ξ represents the crack propagation length inside the surface particles; h represents the crack damage angle inside the surface particles; B This indicates the distance from the initial contact point between the cutting tool and the particle to the machined surface.

[0114] Step S50: Determine whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold; if so, output the cutting parameters of the tool as the target cutting parameters.

[0115] In other embodiments, if the damage depth of the processed material model is greater than the damage depth standard threshold, the cutting parameters are reset and obtained, and steps S20 to S50 are repeated to recalculate the damage depth of the processed material model and compare it with the damage depth standard threshold until the damage depth of the processed material model is less than or equal to the damage depth standard threshold. Then, the current cutting parameters of the tool are output as the target cutting parameters. It should be noted that when the damage depth of the processed material model is less than or equal to the damage depth standard threshold, it means that the current cutting parameters meet the quality requirements, and these cutting parameters can be used for machining particle-reinforced metal matrix composites.

[0116] As can be seen, the method for predicting the damage depth and optimizing process parameters of particle-reinforced metal matrix composites during machining proposed in this application establishes a mapping relationship between material parameters, cutting parameters, tool parameters, and the damage depth of the machined surface, enabling accurate prediction of the damage depth of the machined surface after machining. Furthermore, this application is applicable to all particle-reinforced metal matrix composites, where the reinforcing phase materials include SiC, Al2O3, TiB2, TiB, and TiC; and the metal matrix materials include aluminum-based, titanium-based, nickel-based, iron-based, copper-based, and magnesium-based materials. It can be seen that the method for predicting the damage depth and optimizing process parameters of particle-reinforced metal matrix composites during machining proposed in this application assumes that the particles are randomly distributed in the matrix, and the height of the particles above the tool cutting path is not a constant value but follows a uniform distribution. This is consistent with the microstructural characteristics of the material itself and can more accurately reflect the actual damage location of the particles after machining. Furthermore, the method for predicting the damage depth and optimizing the process parameters of particle-reinforced metal matrix composites during machining proposed in this application avoids the scrapping of expensive composite materials due to failure to meet quality requirements, reduces economic costs, provides a theoretical basis for optimizing the machining parameters and tool parameters of particle-reinforced metal matrix composite components, provides an important guarantee for achieving high-quality and efficient machining of particle-reinforced metal matrix composite components, and provides technical support for improving the machining technology level of particle-reinforced metal matrix composite components.

[0117] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings and specific examples.

[0118] like Figure 3 As shown, the method for predicting the damage depth and optimizing process parameters during machining of particle-reinforced metal matrix composites according to this embodiment includes the following steps:

[0119] Step 1: The test material in this example is a SiCp / Al composite material, and its material properties are shown in Table 1; the cutting tool is a diamond grooving tool, and its material properties are shown in Table 2. The specific cutting parameters are: cutting speed V... s =155m / min, undeformed chip thickness t c =0.15mm. The depth of damage on the machined surface, SSD1, is <55μm.

[0120] Table 1 Performance parameters of SiCp / Al composite materials

[0121]

[0122]

[0123] Table 2 Performance parameters of diamond tools

[0124]

[0125] Step 2: Conduct orthogonal cutting experiments on SiCp / Al composite materials on a CNC lathe. An infrared thermal imager with a macro lens (FLIR T630sc, frequency: 30Hz, pixel: 640*480, measurement range: -40℃-650℃) is used to acquire the temperature field of the machined surface on the side of the workpiece during the experiment. When installing the infrared thermal imager, the distance between the macro lens and the side of the workpiece to be cut should be 84mm ± 1mm ​​to ensure a clear and stable field of view. The thermal emissivity of the SiCp / Al composite material is set to 0.901. Orthogonal cutting experiments on the SiCp / Al composite material are conducted to obtain the temperature field of the machined surface, and the cutting temperature T = 137℃ is determined.

[0126] Step 3: Conduct friction coefficient measurement experiments on PCD material and SiCp / Al composite material at different temperatures, fit the experimental results, and establish a friction coefficient model that takes into account temperature and particle volume fraction, which can be expressed as:

[0127]

[0128] The particle volume fraction V of the SiCp / Al composite material p Substituting the cutting temperature T into the above formula, the friction coefficient between the tool and the workpiece is calculated to be μ = 0.304.

[0129] Step 4: Morphology of particle fracture damage on the machined surface under the action of the cutting tool, as shown in the figure. Figure 4 As shown in Equation 2-5, the characteristic contact angles β and α between the tool and particles during the cutting process of SiCp / Al composite materials are calculated. N1 and α M1 and the characteristic distance h between the tool and the particle B ,like Figure 5 as shown. In formula 3, R hi is the height of the particle above the cutting path of the tool. Since the particles are randomly distributed in the matrix, the height of the particle above the cutting path of the tool is not a fixed value but follows a uniform distribution, and R hi ∈[0, 2R].

[0130] Step 5: Calculate the characteristic parameters ξ and l of the internal damage of the particles on the machined surface during the cutting process of the SiCp / Al composite material through formulas 6 - 9 cr .

[0131] Step 6: According to the contact characteristic distance h B between the tool and the particle, the internal damage parameters ξ and l cr of the surface particles obtained in Step 4 and Step 5, calculate the machined surface damage depth SSD2 through formula 10, and the results are as Figure 6

[0132] shown in Figure 6. It can be seen that the predicted minimum value of the machined surface damage depth is 34.9 μm, the maximum value is 54.7 μm, and the average value is 45.7 μm. The error between the predicted result and the test detection result is less than 13.2%.

[0133] Step 7: The calculated maximum value of the surface damage depth SSD2 = 59.5 μm > SSD1, so the cutting parameters and tool parameters do not meet the machining quality requirements of the SiCp / Al composite material.

[0134] Step 8: Under the condition of meeting the quality requirement SSD1 = 55 μm, reduce the undeformed chip thickness by 0.01 mm and increase the tool rake angle by 5°, and then re - execute Step 2.

[0135] Step 9: When the undeformed chip thickness is reduced from t c = 0.15 mm to t c = 0.12 mm, and the tool rake angle is increased from 0° to 5°, while other parameters remain unchanged, the results of the machined surface damage depth of the SiCp / Al composite material are as Figure 7 shown. It can be seen that the calculated maximum value of the surface damage depth SSD2 = 51.9 μm < SSD1, so the cutting parameters and tool parameters meet the machining quality requirements of the SiCp / Al composite material. Finally, under the condition of meeting the quality requirement SSD1 = 55 μm, the optimized cutting parameters are V s = 155 m / min, the undeformed chip thickness t c = 0.12 mm; the optimized tool parameters: rake angle = 5°, clearance angle = 7°.

[0136] On the other hand, as Figure 8As shown, to solve the above-mentioned technical problems, a cutting damage depth and process parameter prediction device is provided, comprising:

[0137] The parameter acquisition module is used to acquire parameters of the material to be processed, tool parameters, cutting parameters, and standard threshold values ​​for damage depth.

[0138] The first calculation module is used to measure the cutting temperature of the material to be processed during the cutting process. Based on the parameters of the material to be processed, the tool parameters, the cutting parameters, and the cutting temperature of the material to be processed during the cutting process, it obtains the friction coefficient between the material to be processed and the tool, the contact characteristic angle between the tool and the particles in the material to be processed, and the distance from the tool to the initial contact point of the particles to the processed surface.

[0139] The second calculation module is used to obtain the surface particle internal damage characteristic parameters of the processed material model based on the cutting temperature of the material to be processed during the cutting process, the friction coefficient between the material to be processed and the tool, and the contact characteristic angle and characteristic distance between the tool and the particles in the material to be processed; wherein, the surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length;

[0140] The third calculation module is used to obtain the damage depth value of the processed material model based on the damage angle of the internal crack of the surface particles and the crack propagation length of the internal crack of the surface particles.

[0141] The target parameter output module is used to determine whether the damage depth of the processed material model is less than or equal to the damage depth standard threshold; if so, the cutting parameters of the tool are output as the target cutting parameters.

[0142] The device for predicting machining damage depth and process parameters can be used to execute the methods described in the above embodiments. Therefore, the functions that each functional module of the device for predicting machining damage depth and process parameters can achieve can be referred to the description in the above embodiments, and will not be repeated here.

[0143] In some possible implementations, various aspects of the methods provided in this application may also be implemented as a program component comprising program code that, when run on a computer device, causes the computer device to perform the steps of the methods according to the various exemplary embodiments of this application described above.

[0144] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. Alternatively, if the integrated unit of the present invention is implemented as a software functional module and sold or used as an independent part, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software part. This computer software part 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 methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0145] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0146] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A cutting damage depth and process parameter prediction method characterized by, The method comprises the following steps: Obtaining parameters of the material to be machined, tool parameters, cutting parameters and a standard threshold of damage depth; the parameters of the material to be machined include a particle volume fraction and a particle average size; the tool parameters include a tool rake angle, a tool cutting edge radius and a tool material hardness; the cutting parameters include a cutting speed, an undeformed chip thickness and a cutting width; Measuring a cutting temperature of the material to be machined in the cutting process, and obtaining a friction coefficient between the material to be machined and the tool, a contact characteristic angle of the tool and the particles in the material to be machined and a distance from an initial contact point of the tool to the particles to a machined surface based on the parameters of the material to be machined, the tool parameters, the cutting parameters and the cutting temperature of the material to be machined in the cutting process; the contact characteristic angle of the tool and the particles in the material to be machined includes a friction angle of the tool and the particles, an angle between a line connecting a tool cutting edge center and a particle center and a vertical direction and an angle between the line connecting the tool cutting edge center and the particle center and a horizontal direction; the distance from the initial contact point of the tool to the particles to the machined surface satisfies the following relationship: wherein, h B represents the distance from the initial contact point of the tool to the particle to the machined surface; r represents the tool cutting edge radius; represents the angle between the line connecting the center of the tool cutting edge and the center of the particle and the horizontal direction; Obtaining surface particle internal damage characteristic parameters of a machined material model based on the cutting temperature of the material to be machined in the cutting process, the friction coefficient between the material to be machined and the tool, the contact characteristic angle of the tool and the particles in the material to be machined and the characteristic distance; wherein the surface particle internal damage characteristic parameters include a surface particle internal crack damage angle and a surface particle internal crack propagation length; the surface particle internal crack damage angle satisfies the following relationship: wherein, represents the internal crack damage angle of the surface particle; β represents the friction angle between the tool and the particle in the material to be machined; represents the angle between the line connecting the center of the cutting edge of the tool and the center of the particle and the horizontal direction; represents the rake angle of the tool; The surface particle internal crack propagation length satisfies the following relationship: wherein, represents the internal crack length of the surface particle; represents the average size of the particle; represents the hardness of the tool material; represents the depth of the particle into the tool rake face; represents the Poisson's ratio of the reinforcement phase; represents the elastic modulus of the reinforcement phase; π is the value of the circle constant; represents the fracture toughness of the reinforcement phase; represents the initial width of the particle-matrix interface crack; is the initial length of the particle-matrix interface crack; represents the integration variable; Obtaining a damage depth value of the machined material model based on the surface particle internal crack damage angle and the surface particle internal crack propagation length; the damage depth of the machined material model satisfies the following relationship: where SSD2 represents the damage depth of the machined material model; represents the internal crack propagation length of the surface particle; represents the internal crack damage angle of the surface particle; h B represents the distance from the initial contact point of the tool to the particle to the machined surface; Judging whether the damage depth of the machined material model is less than or equal to the standard threshold of damage depth; if yes, outputting the cutting parameters of the tool as target cutting parameters.

2. The method of claim 1, wherein the method further comprises: The friction coefficient between the material to be machined and the tool satisfies the following relationship: wherein, represents the friction coefficient at the tool-workpiece interface, represents the target interface temperature, represents the volume fraction of composite particles, which value is 0 if the material is a metal; represents a function related to the temperature and the volume fraction of particles.

3. The method of claim 1, wherein the cutting damage depth and process parameter prediction method is characterized by, The friction angle of the tool and the particles satisfies the following relationship: wherein β represents the friction angle between the tool and the particles in the material to be machined; wherein β represents the friction angle between the tool and the particles in the material to be machined; 4. The method of claim 1, wherein the method further comprises: The angle between the line connecting the tool cutting edge center and the particle center and the vertical direction satisfies the following relationship: wherein, represents the angle between the line connecting the center of the cutting edge and the center of the reinforcing phase particle and the vertical direction; r represents the radius of the cutting edge of the tool; R represents the average size of the reinforcing phase particle; represents the height of the reinforcing phase particle above the cutting path of the tool.

5. The method of claim 1, wherein the method further comprises: determining a cutting depth of the cutting tool; and determining a cutting speed of the cutting tool. The angle between the line connecting the tool cutting edge center and the particle center and the horizontal direction satisfies the following relationship: wherein, represents the angle between the line connecting the center of the tool cutting edge and the center of the particle and the horizontal direction; and π is the value of the circular constant; represents the angle between the line connecting the center of the tool cutting edge and the center of the particle and the vertical direction.

6. The method of claim 1, wherein the method further comprises: The depth of the particles into a tool relief surface satisfies the following relationship: wherein, represents the depth of the particle into the tool's flank face; π is the value of pi; represents the hardness of the tool material; represents the average size of the particle; represents the complex modulus of the tool and particle.

7. The cutting damage depth and process parameter prediction method of claim 6, wherein, A composite modulus of the tool and the particles satisfies the following relationship: wherein, represents the complex modulus of the tool and the particles; represents the Poisson's ratio of the tool material; represents the elastic modulus of the tool material; represents the Poisson's ratio of the reinforcing phase; represents the elastic modulus of the reinforcing phase.

8. A device for predicting cutting damage depth and process parameters, characterized in that, The device is used for realizing the cutting machining damage depth and process parameter prediction method according to any one of claims 1-7, and the device comprises: A parameter acquisition module is configured to obtain parameters of the material to be machined, tool parameters, cutting parameters and a standard threshold of damage depth; The first calculation module is configured to measure the cutting temperature of the material to be processed in the cutting process, and obtain the friction coefficient between the material to be processed and the tool, the particle contact characteristic angle of the tool and the material to be processed, and the distance from the initial contact point of the tool to the particle to the machined surface based on the parameters of the material to be processed, the tool parameters, the cutting parameters and the cutting temperature of the material to be processed in the cutting process. The second calculation module is configured to obtain the surface particle internal damage characteristic parameters of the machined material model based on the cutting temperature of the material to be processed in the cutting process, the friction coefficient between the material to be processed and the tool, and the particle contact characteristic angle and the characteristic distance of the tool and the material to be processed; wherein the surface particle internal damage characteristic parameters include the surface particle internal crack damage angle and the surface particle internal crack propagation length. The third calculation module is configured to obtain the damage depth value of the machined material model based on the surface particle internal crack damage angle and the surface particle internal crack propagation length. The target parameter output module is configured to judge whether the damage depth of the machined material model is less than or equal to the damage depth standard threshold value; if yes, the cutting parameters of the tool are output as the target cutting parameters.

9. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the cutting processing damage depth and process parameter prediction method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the processor executes the computer program to realize the cutting processing damage depth and process parameter prediction method according to any one of claims 1-7.

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