Milling-based dynamic mechanical property prediction method for tough difficult-to-machine material

Abstract

The invention discloses a method for predicting dynamic mechanical properties of a tough difficult-to-machine material based on milling. The method comprises the following steps: firstly, optimizing and solving a normal shear angle of an oblique angle cutting shear plane through an iterative method: (a) setting an initial value of the normal shear angle; (b) calculating an undeformed chip thickness, a cutter instantaneous invasion angle, a cutting force component and a normal friction angle based on the normal shear angle initial value; (c) updating a normal shear angle calculation value; (d) calculating the error between the initial value and the calculated value of the normal shear angle, if the error is not within the allowable range, repeating the steps (a)-(d) until the error is within the allowable range, and outputting the final calculated value as the optimized normal shear angle; then, parameters such as the optimized normal shear angle are substituted into a related equation containing fracture toughness, yield strength and viscous toughness to solve the fracture toughness Gc of a workpiece material at a tool nose in the milling process, the yield stress sigma Y in a shear plane and the viscous toughness Ga of chip slippage at a tool-chip contact interface.

Description

Technical Field

[0001] The present invention relates to the technical field of material processing, and in particular to a method for predicting the fracture toughness, yield strength and viscous toughness of tough and difficult-to-machine materials during a dynamic cutting process through ordinary milling. Background Art

[0002] Tough, difficult-to-machine materials possess excellent mechanical properties due to their high strength and hardness, but their machining presents multiple challenges: high chemical activity makes them susceptible to reaction with cutting tools, poor thermal conductivity exacerbates cutting heat accumulation, and severe work hardening further deteriorates cutting conditions. In actual cutting, these materials are prone to producing jagged chips over a wide range of cutting speeds and feed rates, leading to cutting instability, accelerated tool wear, and decreased surface quality. Research has shown that the yield strength and fracture toughness of a material are key parameters influencing machining deformation and surface quality. Specifically, a higher ratio of fracture toughness to yield strength increases the controllability of the material removal process and improves surface quality. However, the material's viscous toughness (i.e., the material's ability to dissipate energy generated by internal friction during plastic deformation) increases the sliding resistance of the rake face, causing material tearing and the formation of a bond nub, which accelerates tool wear and shortens tool life. Therefore, fracture toughness, yield strength, and viscous toughness are key factors influencing high-speed cutting efficiency. Accurate prediction of these parameters can provide a theoretical basis for optimizing cutting conditions, designing cutting tools, and reducing energy consumption, and is of great significance for achieving efficient cutting of tough and difficult-to-machine materials.

[0003] It is worth noting that traditional testing methods have limitations when characterizing the mechanical properties of such materials. Since tough and difficult-to-process materials do not meet the basic assumptions of linear elastic fracture mechanics, crack blunting is prone to occur in standard fracture mechanics tests, resulting in distorted fracture toughness value measurements. In addition, the yield strength of materials is usually determined by static or quasi-static tensile tests, but during the actual cutting process, the material will undergo the coupling of dynamic strain rate hardening effects and thermal softening effects, making it impossible for static test results to accurately reflect the true yield strength under dynamic cutting conditions. Therefore, there is an urgent need to develop a simple and effective technology that can simultaneously predict the fracture toughness, yield strength and viscous toughness of tough and difficult-to-process materials under dynamic cutting conditions. This technology not only has important scientific value, but also can provide key support for the development of advanced manufacturing processes.

[0004] Existing technologies have achieved the prediction of fracture toughness, yield strength and viscous toughness of tough and difficult-to-process materials during dynamic cutting by replacing standard mechanical tests with cutting processing methods. This method effectively circumvents the problem of crack blunting in standard fracture mechanics tests due to the material not satisfying the linear elastic assumption, while avoiding the irrationality of directly applying the yield strength obtained from static or quasi-static tensile tests to dynamic cutting conditions. However, current cutting tests mainly rely on two-dimensional orthogonal cutting modes, and their implementation requires special equipment and precision tools to ensure the stability of the cutting plane, resulting in a lack of versatility in the material processing method. Specifically, two-dimensional orthogonal cutting has extremely high requirements on the stiffness of the experimental apparatus, the geometry of the tool and the matching degree of the cutting parameters, making it difficult to directly promote in conventional processing environments, limiting its application potential in actual production. Summary of the Invention

[0005] The present invention proposes a method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling. By analyzing the cutting force and serrated chip morphology, the fracture toughness, yield strength and viscous toughness of tough and difficult-to-machine materials during the dynamic cutting process are simultaneously predicted, thereby overcoming the limitations of traditional methods and achieving simplicity, versatility and accuracy of prediction.

[0006] First, a method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling is proposed, including:

[0007] Optimize the normal shear angle φ of the bevel cutting shear plane by iterative method n :

[0008] (a) Assume the initial value of the normal shear angle, which ranges from 0 to 45 degrees;

[0009] (b) Calculation of the undeformed chip thickness t1, tool instantaneous penetration angle φ, and cutting force component F based on the initial value of the normal shear angle c 、F t 、F l and the normal friction angle λ n ;

[0010] (c) Update the calculated value of the normal shear angle;

[0011] (d) Calculation of the initial value of the normal shear angle and the calculated value of the normal shear angle φ n If the error is not within the allowable range, reassign the initial value of the normal shear angle and repeat steps (b)-(d) until the error is within the allowable range. The final calculated value of the normal shear angle is used as the optimized normal shear angle φ. n Output;

[0012] (e) Calculate the lateral flow direction angle β of the chip on the rake face;

[0013] (f) Calculate the shear flow direction angle δ of the material in the first deformation zone (i.e., the shear plane);

[0014] (g) The optimized normal shear angle φ n , the main cutting force F of the cutting force component c and lateral force F t , the thickness of the undeformed chip t1, the lateral flow direction angle β of the chip on the rake face, and the shear flow direction angle δ of the shear plane material are substituted into the following equation (1) to solve the fracture toughness G of the workpiece material at the tool tip during milling. c , yield stress in the shear plane σ Y and the viscous toughness G of chip sliding at the tool-chip contact interface a :

[0015]

[0016] Where γ is the inclination angle of the cutting edge of the tool when cutting at an angle (i.e., the helix angle of the cutting edge of the end mill), w1 is the width of the undeformed chip, and D is the diameter of the end mill, φ ex is the cutting end position angle when the tool cuts out the workpiece material, and μ is the coefficient of friction, and α is the tool rake angle, Z is the friction correction coefficient, and

[0017] Secondly, a dynamic mechanical properties prediction system for tough and difficult-to-machine materials based on milling is proposed, which includes: a dynamometer for measuring the cutting force components F in the X, Y, and Z directions at the instantaneous intrusion angle φ of the tool. x 、F y 、F z ; Signal analysis software, which includes one or more computer program modules, which, when executed by a computer, can implement the method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling.

[0018] In the third aspect, a computer system is proposed, comprising: a processor; a memory, comprising one or more computer program modules, wherein the one or more computer program modules are stored in the memory and configured to be executed by the processor, and the one or more computer program modules include instructions for implementing the method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling.

[0019] In a fourth aspect, a computer-readable storage medium is proposed for storing non-temporary computer-readable instructions, which, when executed by a computer, can implement the method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling.

[0020] The innovations of this invention lie in: using conventional milling methods to construct a dynamic prediction model for sawtooth chip generation during angled cutting; addressing the problem of biased fracture toughness estimates for tough and difficult-to-cut materials caused by crack blunting in traditional fracture toughness testing; and avoiding the limitations of directly applying yield strength from static / quasi-static standard tensile tests to dynamic cutting conditions. This invention enables more reasonable prediction of key mechanical parameters (fracture toughness, yield strength, and viscous toughness) of tough and difficult-to-cut materials during dynamic cutting, providing technical support for process optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 FIG. 4 is a schematic diagram of cutting force analysis in milling according to an embodiment of the present invention.

[0022] Figure 2a Schematic diagram of a geometric model for bevel cutting according to an embodiment of the present invention.

[0023] Figure 2b FIG. 4 is a schematic diagram of a cutting force model analysis according to an embodiment of the present invention.

[0024] Figure 3 The figure shows a geometric and cutting force analysis model for regular sawtooth chip generation according to an embodiment of the present invention.

[0025] Figure 4a 1 is a top view of a geometric model for force analysis of side milling according to an embodiment of the present invention.

[0026] Figure 4b FIG. 4 is a front view of a geometric model of an end mill according to an embodiment of the present invention.

[0027] Figure 5 Schematic diagram of a system for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to an embodiment of the present invention.

[0028] Figure 6 Schematic diagram of sawtooth chip morphology under different milling speed conditions according to an embodiment of the present invention.

[0029] Figure 7 1 is a test result and a fitting straight line thereof under different milling speed conditions according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] Example 1

[0031] The present invention proposes a method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling. The idea of this method is as follows:

[0032] As attached Figure 1 As shown, the end mill cutting edge is first discretized into several micro-elements along the tool axis. Referring to Figures 4(a) and 4(b), the cutting process of each micro-element is simplified to an oblique cutting model, that is, it is assumed that the cutting behavior of each micro-element is equivalent to single-point oblique cutting.

[0033] As shown in Figure 2(b), for the oblique cutting process of a single blade element, a cutting force model is established during chip generation. The cutting force vector in oblique cutting is projected onto the normal plane perpendicular to the cutting edge in order to uniformly analyze the force state of different elements. Figure 3 As shown, the fracture toughness of the material is introduced at the tool tip to characterize its ability to resist crack propagation. The viscous toughness of the material is introduced at the tool-chip interface to quantify the energy dissipated by internal friction during plastic deformation. Finally, combining the cutting force decomposition and equilibrium equations from orthogonal cutting theory, a systematic analysis of the cutting forces is conducted, resulting in the derivation of a correlation equation involving fracture toughness, yield strength, and viscous toughness. This equation can directly predict the mechanical properties of the material in actual machining by inputting dynamic cutting conditions (such as cutting speed and feed rate).

[0034] Measured cutting force data (such as normal and tangential forces) and the average thickness of serrated chips are used as inputs and substituted into the above equations to solve them. Through numerical inversion, the fracture toughness, yield strength, and viscous toughness of tough and difficult-to-machine materials during dynamic cutting can be simultaneously predicted.

[0035] The following is a detailed introduction to the process of establishing the correlation equation including fracture toughness, yield strength and viscous toughness.

[0036] Step 1: Based on the oblique cutting geometry model and cutting force model shown in Figures 2(a) and 2(b), the following equations can be derived to calculate the shear flow direction angle δ of the material in the first deformation zone (i.e., the shear plane), the lateral flow direction angle β of the chip on the rake face, and the normal friction angle λ in the second deformation zone (i.e., the tool-chip contact interface): n :

[0037]

[0038] Among them, φ n is the normal shear angle of the first deformation zone; α is the tool rake angle; γ is the cutting edge inclination angle during bevel cutting; F c is the main cutting force; F t is the lateral force; F l is the lateral force.

[0039] Step 2: Based on Figure 2(b), project the various cutting forces during the oblique cutting process onto the normal plane perpendicular to the cutting edge, and calculate the projection components using the following formula:

[0040] F' c =F c cosγ

[0041] F' s =F s cosδ

[0042] F' f =F f cosβ

[0043] Among them, F' c 、F' s 、F' f The main cutting force F c , shear force F in the first deformation zone s , Friction force F between chip and rake face f The projected component in the normal plane perpendicular to the cutting edge.

[0044] Step 3: Based on Figure 3 The cutting force balance in the first deformation zone (shear plane) is shown, and the following equation is derived:

[0045]

[0046] Where t1 is the thickness of the undeformed chip; w1 is the width of the undeformed chip; σ Y is the yield strength of the workpiece material in the first deformation zone (shear plane); G c is the fracture toughness of the workpiece material at the tool tip.

[0047] Step 4: According to the cutting force balance equation on the first deformation zone (shear plane) obtained in step 3, calculate tanφ n Taking the derivative, we get the fracture toughness of the workpiece material at the tool tip and the yield strength of the workpiece material in the first deformation zone (shear plane). and The expression is as follows:

[0048]

[0049] Step 5: See Figure 3 According to the cutting force balance in the second deformation zone (tool-chip contact interface), the equation is obtained Combined with Coulomb's friction law, F f -G a w2=μF N ,in The following equation can be obtained:

[0050]

[0051] Among them, F N is the normal pressure on the chip when it slides on the rake face; w3 is the length of the cutting edge involved in the bevel cutting process, and w2 is the width of the chip after cutting, and ; G a is the viscous toughness of the workpiece material (i.e., chip), that is, the unit viscous resistance when sliding on the rake face; μ is the friction coefficient when the chip slides on the rake face; λ is the friction angle when the chip slides on the rake face; Z is the friction correction coefficient, and

[0052] Step 6: Using the two equations obtained in step 3 and step 5, we can get the equation that takes into account the fracture toughness of the workpiece material at the tool tip, the yield strength of the workpiece material in the first deformation zone (shear plane), and the viscosity toughness of the chip when sliding on the rake face. and The expression is as follows:

[0053]

[0054] Step 7: Use the information in step 6 or The expression for tanφ n Take the derivative and get the value of tanφ n The quadratic equation of And solve the equation, we get the equation with respect to tanφ n A solution to is as follows:

[0055]

[0056] in, is an intermediate variable, and

[0057] Step 8: Subtract tanφ obtained in step 7 n Substitute the expression into step 6 to get and In the expression of step 6, we can get and The expression is simplified as follows:

[0058]

[0059] Subsequently, the fracture toughness, yield strength, and viscous toughness of tough and difficult-to-machine materials during dynamic cutting can be simultaneously predicted by fitting the measured cutting force and the undeformed chip thickness separately.

[0060] Step 9: Compare the results obtained in step 4 and step 8. and The expression of The expression for is the same, but The difference in the expression of is caused by whether the viscosity toughness of chip sliding at the tool-chip contact interface is considered. However, the expressions of and The expressions of tanφ are all based on the principle of minimum cutting force. n The equation obtained by taking the derivative can be found through the equation obtained in step five. and There is a linear functional relationship between them. Therefore, comparing the results obtained in step 4 and step 8 The expression of That is, the normal shear angle φ of the first deformation zone is finally obtained n and the normal friction angle λ at the tool-chip contact interface n The relationship expression between them is as follows:

[0061]

[0062] The method of the present invention can be summarized as follows: first, a geometric model of continuous chip generation and a cutting force model are constructed during oblique cutting, and equations are established to calculate the following parameters: the normal friction angle λ at the tool-chip contact interface n , the shear flow direction angle δ of the material in the first deformation zone, the lateral flow direction angle β of the chip on the rake face, and the normal shear angle φ of the first deformation zone n Subsequently, the geometric analysis model of serrated chip generation is established by extending the normal plane projection, and the projection component equation of the cutting force in the normal plane perpendicular to the cutting edge is derived. The fracture toughness G is then introduced at the tool tip. c , combined with the cutting force balance analysis, the cutting force balance equations for step three (shear plane in the first deformation zone) and step five (tool-chip contact interface in the second deformation zone) were established respectively, and finally the correlation equation for step eight containing fracture toughness, yield strength and viscous toughness was obtained. Based on the above equations, combined with the measured milling cutting force data and the average thickness of the serrated chip, the following mechanical parameters of tough and difficult-to-machine materials can be dynamically predicted: the fracture toughness G of the workpiece material at the tool tip c , the yield stress σ in the shear plane of the first deformation zone Y and the viscous toughness G of chip sliding at the tool-chip contact interface a.

[0063] The following describes the method for determining the parameters of the correlation equations involving fracture toughness, yield strength, and viscous toughness. Assume that a multi-tooth, flat-bottomed carbide end mill is used. Its radius can be selected according to the processing requirements (for example, 8 mm), the helix angle is typically between 30° and 45°, the rake and relief angles are adjusted according to the material properties (for example, a 10° rake angle and a 6° relief angle), and the tool coating is AlCrN for enhanced wear resistance and high-temperature resistance. The milling method can be either down-cut or down-cut, depending on the rigidity of the workpiece fixture, the material properties (such as the presence of a hard crust), and the processing stability requirements.

[0064] Under typical machining parameters, the radial depth of cut is typically controlled at 0.1-0.3 mm, the axial depth of cut is set based on the tool overhang and machine power (e.g., 2 mm), and the feed per tooth is adjusted based on chip thickness control requirements (e.g., 0.01-0.03 mm / tooth). This example uses the nickel-based superalloy Inconel 718 as the machining object, combining specific parameters (e.g., milling method, tool geometry, and cutting parameters) to measure and analyze cutting forces and chip thickness.

[0065] Step 1: Reference Figure 3 and Figure 6 , measure the maximum chip thickness t of the regular serrated segment of the serrated chip under a microscope c_max , minimum chip thickness t c_min (It should be noted that Figure 6 At a cutting speed of 80 m / min, irregular sawtooth size appeared, and at a cutting speed of 110 m / min, cracks and burrs appeared on the free side of the sawtooth, resulting in irregular sawtooth morphology. Therefore, the maximum chip thickness t of this sawtooth segment was not selected. c_max and minimum chip thickness t c_min measurement).

[0066] Step 2: Calculate the average thickness of the sawtooth segment of the sawtooth chip according to the following formula: chip :

[0067]

[0068] Step 3: Set the initial value of the normal shear angle of the first deformation zone [φ n ] ini Calculate the average thickness of the chip serration segment t according to the following formula chip The corresponding undeformed chip thickness t1 (i.e. the thickness of the uncut workpiece material h):

[0069]

[0070] Among them, r c It is the ratio of the undeformed chip thickness to the deformed chip thickness before and after machining.

[0071] Step 4: Calculate the instantaneous tool penetration angle φ at the thickness h of the uncut workpiece material according to the following formula:

[0072] hf' z sin(φ ex -φ)=0

[0073] Among them, f' z is the actual feed rate per tooth (f' z Can be close to the nominal feed rate per tooth f z );φ ex It is the cutting end position angle when the tool cuts out the workpiece material.

[0074] Step 5. Calculate the cutting force F at the instantaneous intrusion angle φ of the tool according to the following formula: c 、F t and F l :

[0075]

[0076] Among them, F x 、F y 、F z They are the cutting force components in the X, Y, and Z directions at the instantaneous intrusion angle φ of the tool measured by the dynamometer.

[0077] Step 6: According to the above equation Calculate the normal friction angle λ at the tool-chip contact interface n .

[0078] Step 7: According to the above equation Calculate the normal shear angle φ of the first deformation zone n .

[0079] Then the calculated normal shear angle [φ n ] cal The initial value [φ n ] ini Compare and calculate relative error If ε is within the allowable error range, it is considered that the normal shear angle [φ n ] cal The calculation result is reasonable, that is, acceptable; if ε is not within the allowable error range, return to step 3 and reset the initial value of the normal shear angle [φ n ] ini , recalculate until the iteration gets a satisfactory result, where the initial value of the normal shear angle [φ n ] ini The value range is between 0 and 45 degrees. Some results obtained from the test data are shown in Table 1.

[0080] Table 1 t under different cutting speed conditions chip , t1, φ n , β and δ calculation results

[0081]

[0082] Step 8: Based on the milling test data, i.e., cutting force and average thickness of sawtooth chips, calculate the vertical coordinate according to the cutting force equation obtained from the cutting force balance. and the abscissa (cosδcotφ n )t1, and the vertical coordinate and the horizontal coordinate (Zcosδcotφ n )t1, and then perform linear fitting respectively. The fitting results are as follows Figure 7 Then, the slope and intercept of the fitted line are used to calculate the yield stress σ of the workpiece material during the generation of sawtooth chips in bevel cutting. Y , fracture toughness G c and viscous toughness G a The calculated results are shown in Table 2 and Table 3:

[0083] Table 2 Under different cutting speed conditions and (cosδcotφ n )t1 The yield stress σ of the workpiece material predicted by the fitting straight line between Y Value and fracture toughness G c value

[0084]

[0085] Table 3 Under different cutting speed conditions and (Zcosδcotφ n )t1 The yield stress σ of the workpiece material predicted by the fitting straight line between Y Value and viscosity toughness G a value

[0086]

[0087] Step 9: The yield stress σ of the workpiece material during the milling process of the tough and difficult-to-machine material Inconel718 obtained in Tables 2 and 3 is Y By comparing them respectively, it is found that the yield stress σ predicted under different cutting speed conditions in Table 2 and Table 3 is Y The corresponding values are similar, which shows the rationality of the milling prediction method of the present invention. Y The difference between the values, fracture toughness G c The difference between the values and the viscous toughness Ga The differences between the values can be explained by the combined effects of strain rate hardening encountered during the generation of serrated chips in the cutting process and the softening of the workpiece material caused by high temperature. Combined with the yield strength and fracture toughness values of Inconel718 in the literature "B. Wang, ZQ Liu, Acoustic emission signal analysis during chip formation process in high speed machining of 7050-T7451aluminum alloy and Inconel718superalloy, Journal of Manufacturing Processes 27 (2017) 114-125." and the literature "C. Liu, M. Wan, CJShen, Y. Yang, Determination of the yield strength and the energy distribution in the milling of Inconel718 considering fracture toughness, Journal of Manufacturing Processes 82 (3) (2022) 347-361.", the results show that they are consistent with the milling test results of the present invention. Therefore, it is proved that the yield stress σ of the workpiece material of the tough and difficult-to-machine material during the serrated chip generation process of milling is predicted by the present invention. Y , fracture toughness G c and viscous toughness G a The effectiveness of the modeling method.

[0088] Example 2

[0089] Figure 5 A dynamic mechanical property prediction system for tough and difficult-to-machine materials based on milling is presented. The system includes a dynamometer, a charge amplifier, a data acquisition system, and signal analysis software. The dynamometer is used to measure the cutting force components F in the X, Y, and Z directions at the instantaneous penetration angle φ of the tool. x 、F y 、F z The charge amplifier is used to amplify the signal from the dynamometer. The data acquisition system transmits the amplified signal to signal analysis software on a computer. The signal analysis software includes one or more computer program modules, wherein the one or more computer program modules, when executed by a computer, can implement the method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling.

[0090] Example 3

[0091] The present invention also provides an embodiment of a computer system. The computer system includes a processor and a memory. The memory is used to store non-transitory computer-readable instructions (e.g., one or more computer program modules). The processor is used to execute the non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by the processor, one or more steps of the method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling processing are performed. The memory and the processor can be interconnected via a bus system and / or other forms of connection mechanisms.

[0092] For example, a processor can be a central processing unit (CPU), a graphics processing unit (GPU), or other forms of processing units with data processing capabilities and / or program execution capabilities. The processor can be a general-purpose processor or a special-purpose processor that can control other components in the computer to perform desired functions.

[0093] For example, the memory may include any combination of one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), a hard disk, an erasable programmable read-only memory (EPROM), a compact disc read-only memory (CD-ROM), a USB memory, a flash memory, etc. One or more computer program modules may be stored on the computer-readable storage medium, and the processor may execute the one or more computer program modules to implement various functions of the computer.

[0094] Example 4

[0095] The present invention also provides a computer-readable storage medium for storing non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a computer, one or more steps of the above-mentioned method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling can be implemented. When the method for predicting the dynamic mechanical properties of tough and difficult-to-machine materials based on milling of the present invention is implemented in the form of software and sold or used as an independent product, it can be stored in a computer-readable storage medium. For relevant descriptions of the storage medium, please refer to the corresponding description of the memory in the computer system above and will not be repeated here.

Claims

1. A method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling, characterized in that: include: Optimize the normal shear angle φ of the bevel cutting shear plane by iterative method n : (a) Assume the initial value of the normal shear angle, which ranges from 0 to 45 degrees; (b) Calculation of the undeformed chip thickness t1, the instantaneous tool penetration angle φ, and the cutting force component F based on the initial value of the normal shear angle c 、F t 、F l and the normal friction angle λ n ; (c) Update the calculated value of the normal shear angle; (d) Calculation of the initial value of the normal shear angle and the calculated value of the normal shear angle φ n If the error is not within the allowable range, reassign the initial value of the normal shear angle and repeat steps (b)-(d) until the error is within the allowable range. The final calculated value of the normal shear angle is used as the optimized normal shear angle φ. n Output; (e) Calculate the lateral flow direction angle β of the chip on the rake face; (f) Calculate the shear flow direction angle δ of the material in the shear plane; (g) The optimized normal shear angle φ n , the main cutting force F of the cutting force component c and lateral force F t , the thickness of the undeformed chip t1, the lateral flow direction angle β of the chip on the rake face, and the shear flow direction angle δ of the shear plane material are substituted into the following equation (1) to solve the fracture toughness G of the workpiece material at the tool tip during milling. c , yield stress in the shear plane σ Y and the viscous toughness G of chip sliding at the tool-chip contact interface a : Where γ is the inclination angle of the tool cutting edge during bevel cutting, w1 is the width of the undeformed chip, and D is the diameter of the end mill, φ ex is the cutting end position angle when the tool cuts out the workpiece material, and μ is the coefficient of friction, and α is the tool rake angle, Z is the friction correction coefficient, and 2. The method according to claim 1, characterized in that The chip is serrated. The average thickness of the chip serrated section t is calculated according to the following formula (2): chip : Where, t c_max , t c_min is the maximum and minimum chip thickness of the serrated segment; According to the following formula (3), the average thickness of the chip serration segment t is calculated chip The corresponding undeformed chip thickness t1: Where r c It is the ratio of the undeformed chip thickness to the deformed chip thickness before and after machining.

3. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: The instantaneous tool penetration angle φ is calculated according to the following formula (4): hf' z sin(φ ex -φ)=0(4) Where h is the thickness of the uncut workpiece material, f' z is the actual feed rate per tooth.

4. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: Calculate the cutting force component F according to the following formula (5): c 、F t 、F l : Where, F x 、F y 、F z are the cutting force components in the X, Y, and Z directions at the instantaneous intrusion angle φ of the tool.

5. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: The normal friction angle λ at the tool-chip contact interface is calculated according to the following formula (6): n :

6. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: The normal friction angle λ at the tool-chip contact interface n Substitute the following formula (7) to obtain the calculated value of the normal shear angle:

7. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: The optimized normal shear angle φ n and the normal friction angle λ at the tool-chip contact interface n Substituting the following formula (8) into the lateral flow direction angle β of the chip on the rake face:

8. The method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling according to claim 1, characterized in that: The optimized normal shear angle φ n The lateral flow direction angle β of the chip on the rake face is substituted into the following formula (9) to obtain the shear flow direction angle δ of the shear plane material:

9. A dynamic mechanical properties prediction system for tough and difficult-to-machine materials based on milling, characterized in that: include: Dynamometer, used to measure the cutting force components F in the X, Y, and Z directions at the instantaneous penetration angle φ of the tool x 、F y 、F z ; Signal analysis software, comprising one or more computer program modules, which, when executed by a computer, can implement the method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling as described in any one of claims 1 to 8.

10. A computer-readable storage medium for storing non-transitory computer-readable instructions, characterized in that: When the non-transitory computer-readable instructions are executed by a computer, the method for predicting dynamic mechanical properties of tough and difficult-to-machine materials based on milling processing as described in any one of claims 1 to 8 can be implemented.

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