Method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling machining

Abstract

The application discloses a method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling processing, which comprises the following steps: firstly, a normal shear angle of a shear plane in an oblique angle cutting is solved by an iterative optimization method; (a) setting an initial value of the normal shear angle; (b) calculating an undeformed chip thickness, a tool instantaneous invasion angle, a cutting force component and a normal friction angle based on the initial value of the normal shear angle; (c) updating a calculated value of the normal shear angle; (d) calculating an error between the initial value and the calculated value of the normal shear angle, if the error is not within an allowable range, repeating steps (a)-(d) until the error is within the allowable range, and outputting a final calculated value as an optimized normal shear angle; and then, the optimized normal shear angle and other parameters are substituted into a correlation equation containing a fracture toughness, a yield strength and a viscous toughness to solve the fracture toughness G c of a workpiece material at a tool tip in the milling processing, a yield stress σ Y in a shear plane and a viscous toughness G a of chip sliding at a tool-chip contact interface.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of material processing technology, and particularly relates to a method for predicting the fracture toughness, yield strength and viscous toughness of a tough difficult-to-machine material in a dynamic cutting process through ordinary milling. BACKGROUND

[0002] Tough difficult-to-machine materials have excellent mechanical properties due to their high strength and high hardness characteristics, but their processing faces multiple challenges: high chemical activity leads to easy reaction between the material and the tool, poor thermal conductivity exacerbates the accumulation of cutting heat, and severe work hardening further worsens the cutting conditions. In actual cutting process, this kind of material is prone to produce jagged chips in a wide range of cutting speed and feed rate, which leads to unstable cutting process, accelerated tool wear and deteriorated machined surface quality. Research shows that the yield strength and fracture toughness of the material are the core parameters affecting the processing deformation and surface quality. Specifically, the higher the ratio of fracture toughness to yield strength, the stronger the controllability of the material removal process, and it helps to improve the machined surface quality. However, the viscous toughness of the material (i.e. the energy dissipation capacity of the material due to internal friction during plastic deformation) will increase the slip resistance of the rake face, causing the material to tear and form a bond nodule, thereby accelerating tool wear and shortening its service life. Therefore, fracture toughness, yield strength and viscous toughness are key factors affecting high-speed cutting efficiency. Precise prediction of these parameters can provide a theoretical basis for cutting condition optimization, tool design and energy consumption reduction, and is of great significance to realize efficient cutting of tough difficult-to-machine materials.

[0003] It is worth noting that the traditional testing method has limitations in characterizing the mechanical properties of this kind of material. Since the tough difficult-to-machine material does not meet the basic assumptions of linear elastic fracture mechanics, crack blunting phenomenon often occurs in standard fracture mechanics tests, resulting in distorted fracture toughness value measurement results. In addition, the yield strength of the material is usually determined by static or quasi-static tensile test, but the material will experience the coupling effect of dynamic strain rate hardening and thermal softening effect in the actual cutting process, so the static test results cannot accurately reflect the true yield strength under dynamic cutting conditions. Therefore, it is urgent to develop a simple and effective technology that can simultaneously predict the fracture toughness, yield strength and viscous toughness of tough difficult-to-machine 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] The prior art realizes the prediction of the fracture toughness, yield strength and viscous toughness of the tough difficult-to-machine material in the dynamic cutting process by replacing the standard mechanical test with a cutting process method. This method effectively avoids the problem of crack blunting caused by the fact that the material does not meet the linear elastic assumption in the standard fracture mechanics test, and also avoids the unreasonable direct application of the yield strength obtained from the static or quasi-static tensile test to the dynamic cutting condition. However, the current cutting test mainly relies on the two-dimensional orthogonal cutting mode, which requires special equipment and precise tools to ensure the stability of the cutting plane, resulting in the lack of universality of the method in material processing. Specifically, the two-dimensional orthogonal cutting has very high requirements for the rigidity of the experimental device, the matching degree of the tool geometry and the cutting parameters, and it is difficult to be directly popularized in the conventional machining environment, which limits its application potential in actual production. SUMMARY

[0005] The present application proposes a dynamic mechanical property prediction method for tough difficult-to-machine materials based on milling processing, which synchronously predicts the fracture toughness, yield strength and viscous toughness of tough difficult-to-machine materials in the dynamic cutting process by analyzing the cutting force and sawtooth chip shape, solves the limitations of traditional methods, and realizes the simplicity, universality and accuracy of prediction.

[0006] In the first aspect, a dynamic mechanical property prediction method for tough difficult-to-machine materials based on milling processing is proposed, comprising:

[0007] The normal shear angle φ of the oblique angle cutting shear plane is optimized and solved by an iterative method n :

[0008] (a) assuming an initial value of the normal shear angle, which is in the range of 0 degrees to 45 degrees;

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

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

[0011] (d) calculating the error between 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, reassigning the initial value of the normal shear angle and repeating steps (b)-(d) until the error is within the allowable range, and outputting the final calculated value of the normal shear angle as the optimized normal shear angle φ n ;

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

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

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

[0015]

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

[0017] In a second aspect, a system for predicting the dynamic mechanical properties of tough difficult-to-machine materials based on milling is provided, comprising: a dynamometer for measuring the cutting force components F x , F y , F z in the X, Y, Z directions at the instantaneous tool engagement angle φ; and signal analysis software comprising one or more computer program modules that, when executed by a computer, implement the method for predicting the dynamic mechanical properties of tough difficult-to-machine materials based on milling.

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

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

[0020] The innovation of the present application is that a dynamic prediction model of the formation process of the sawtooth chip of the oblique angle cutting is constructed by using the ordinary milling machining method, the problem of the deviation of the fracture toughness evaluation of the tough difficult-to-machine material caused by the crack blunting in the traditional fracture toughness test is solved, and the limitation of directly using the yield strength of the static / quasi-static standard tensile test for the dynamic cutting condition is avoided. The present application can more reasonably predict the key mechanical parameters (fracture toughness, yield strength, and viscous toughness) of the tough difficult-to-machine material in the dynamic cutting process, and provides technical support for process optimization. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 Fig. 1 is a schematic diagram of the milling machining cutting force analysis according to an embodiment of the present application.

[0022] Figure 2a Fig. 2 is a schematic diagram of the oblique angle cutting geometric model according to an embodiment of the present application.

[0023] Figure 2b Fig. 3 is a schematic diagram of the cutting force model analysis according to an embodiment of the present application.

[0024] Figure 3 Fig. 4 is a geometric and cutting force analysis model of the regular sawtooth chip formation according to an embodiment of the present application.

[0025] Figure 4a Fig. 5 is a top view of the side milling machining stress analysis geometric model according to an embodiment of the present application.

[0026] Figure 4b Fig. 6 is a front view of the end milling cutter geometric model according to an embodiment of the present application.

[0027] Figure 5 Fig. 7 is a schematic diagram of the system for predicting the dynamic mechanical properties of the tough difficult-to-machine material based on the milling machining according to an embodiment of the present application.

[0028] Figure 6 Fig. 8 is a schematic diagram of the sawtooth chip morphology under different milling speeds according to an embodiment of the present application.

[0029] Figure 7 Fig. 9 is a test result and a fitted straight line under different milling speeds according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] Embodiment 1

[0031] The application provides a method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling machining.

[0032] As shown in the accompanying drawings, Figure 1 firstly, the cutting edge of the end mill is discretized into a plurality of microelements along the tool axis direction. Referring to Figure 4a and 4b , the cutting process of each microelement is simplified as an oblique angle cutting model, that is, the cutting behavior of each microelement is equivalent to single-point oblique angle cutting.

[0033] As shown in the accompanying drawings, Figure 2b for the oblique angle cutting process of a single cutting edge microelement, a cutting force model during chip formation is established. The cutting force vector in oblique angle cutting is projected onto the normal plane perpendicular to the cutting edge, so as to uniformly analyze the stress state of different microelements. Meanwhile, as shown in the accompanying drawings, Figure 3 the fracture toughness of the material is introduced at the tool tip to represent the ability to resist crack propagation; the viscous toughness of the material is introduced at the tool-chip contact interface to quantify the energy dissipation caused by internal friction in the plastic deformation process. Finally, combined with the cutting force decomposition and balance equation in the orthogonal cutting theory, the cutting force is systematically analyzed, so as to deduce and establish a correlation equation containing fracture toughness, yield strength and viscous toughness. The equation can directly predict the mechanical property parameters of the material in actual machining by inputting dynamic cutting conditions (such as cutting speed, feed rate, etc.).

[0034] The measured cutting force data (such as normal force, tangential force) and the average thickness of the sawtooth chip are taken as input conditions and substituted into the above equation for solving. Through the numerical inversion method, the fracture toughness, yield strength and viscous toughness of the tough difficult-to-machine material in the dynamic cutting process can be finally predicted synchronously.

[0035] The establishment process of the correlation equation containing fracture toughness, yield strength and viscous toughness is described in detail below.

[0036] Step one: based on the oblique angle cutting geometric model and the cutting force model shown in Figure 2a and 2b , the following equation can be derived for calculating 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 of the second deformation zone (i.e. the tool-chip contact interface) n .

[0037]

[0038] Wherein, φ n is the normal shear angle of the first deformation zone; α is the tool rake angle; γ is the blade inclination angle when the cutting edge is obliquely cut; F c is the main cutting force; F tIt is a lateral force; F l It is a lateral force.

[0039] Step Two: Combining Figure 2b The various cutting forces during the bevel cutting process are projected onto a normal plane perpendicular to the cutting edge, and each projection component is calculated 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 Frictional force F between the chip and the rake face f The projection 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) shown in the figure is derived from the following equation:

[0045]

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

[0047] Step 4: Based on the cutting force balance equation on the first deformation zone (shear plane) obtained in Step 3, calculate tanφ. n By taking the derivative, we obtain the equation regarding 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 Based on the cutting force balance in the second deformation zone (tool-chip contact interface), the equation is obtained. And combined with Coulomb's law of friction, i.e. F fG a w2=μF N where The following equation can be obtained:

[0050]

[0051] where F N is the normal pressure on the rake face when the chip slides on the rake face; w3 is the length of the cutting edge involved in the cutting process in the oblique angle cutting process, and w2 is the width of the chip after cutting, and G a is the viscous toughness of the removed workpiece material (i.e. chip), i.e. the unit viscous resistance when the chip slides 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 a friction correction coefficient, and

[0052] Step six: using the two equations obtained in steps three and five, an expression about and that simultaneously considers 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 viscous toughness of the chip when it slides on the rake face can be obtained, as shown below:

[0053]

[0054] Step seven: using the expression about or in step six, the derivative of tanφ n is taken to obtain a quadratic equation about tanφ n and the equation is solved to obtain a solution of the equation about tanφ n , as shown below:

[0055]

[0056] where is an intermediate variable, and

[0057] Step eight: substituting the tanφ n expression obtained in step seven into the expression about and obtained in step six, the expression about and obtained in step six can be simplified, as shown below:

[0058] ​

[0059] Subsequently, the fracture toughness, yield strength and stickiness toughness of the tough-to-machine material in the dynamic cutting process can be predicted simultaneously by linear fitting of the measured cutting force and undeformed chip thickness, respectively.

[0060] Step nine: comparing the expressions of φ and obtained in step four and step eight, it can be found that the expression of φ is the same, while the difference of the expression of φ is caused by whether the stickiness toughness of chip sliding at the tool-chip contact interface is considered. However, the expressions of φ and obtained in step four and step eight are both derived by the minimum cutting force principle of tanφ n , and it can be found from the equation obtained in step five that there is a certain linear function relationship between φ and . Therefore, comparing the expressions of φ obtained in step four and step eight, it can be obtained that φ , that is, the relationship expression between the first deformation zone normal shear angle φ n and the normal friction angle λ n at the tool-chip contact interface is as follows:

[0061]

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

[0063] The parameter determination method of the correlation equation including fracture toughness, yield strength and viscous toughness is introduced below. It is assumed that a multi-tooth flat-bottomed hard alloy end mill is used, the radius can be selected according to the processing requirements (for example 8mm), the helix angle is usually between 30°-45°, the rake angle and the relief angle are adjusted according to the material properties (such as rake angle 10°, relief angle 6°), and the tool coating is AlCrN to enhance wear resistance and high temperature performance. The milling method can be forward milling or reverse milling, depending on the rigidity of the workpiece clamp, the material properties (such as whether there is a hard skin) and the processing stability requirements.

[0064] Under typical processing parameters, the radial depth of cut is usually controlled at 0.1-0.3mm, the axial depth of cut is set according to the tool overhang length and machine power (for example 2mm), and the feed per tooth is adjusted according to the chip thickness control requirements (such as 0.01-0.03mm / tooth). In this embodiment, nickel-based superalloy Inconel718 is used as the processing object, and the cutting force and chip thickness are measured and analyzed in combination with specific parameters (such as milling method, tool geometry parameters, cutting parameters).

[0065] Step one, refer to Figure 3 and Figure 6 , measure the maximum chip thickness t c_max and the minimum chip thickness t c_min of the regular sawtooth segment of the sawtooth chip under the microscope Figure 6 (need to note that c_max in the cutting speed of 80m / min, the sawtooth size is irregular, and at 110m / min, the crack burr on the free side of the sawtooth causes the sawtooth morphology to be irregular, so the measurement of the maximum chip thickness t c_min and the minimum chip thickness t of this kind of sawtooth segment is not carried out).

[0066] Step two, calculate the average thickness t chip of the sawtooth segment of the sawtooth chip according to the following formula:

[0067]

[0068] Step three, set the initial value of the normal shear angle of the first deformation zone [φ n ] ini , and calculate the undeformed chip thickness t1 (i.e. the thickness h of the uncut workpiece material) corresponding to the average thickness t chip of the sawtooth segment of the chip according to the following formula:

[0069]

[0070] Where r c is the ratio of the undeformed chip thickness before and after processing and the deformed chip thickness.

[0071] Step four, the instantaneous angle of tool invasion φ at the material thickness h of the uncut workpiece is solved by programming according to the following formula:

[0072] h-f' z sin(φ ex -φ)=0

[0073] Wherein, f' z is the actual feed rate per tooth (f' z may approach the nominal feed rate per tooth f z ); φ ex is the angle of the cutting end position when the tool cuts the material of the workpiece,

[0074] Step five, the cutting forces F c , F t and F l at the instantaneous angle of tool invasion φ are calculated according to the following formula:

[0075]

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

[0077] Step six, the normal friction angle λ n at the tool-chip contact interface is calculated according to the above equation .

[0078] Step seven, the normal shear angle φ n of the first deformation zone is calculated according to the above equation .

[0079] Then, the calculated normal shear angle [φ n ] cal is compared with the initial value [φ n ] ini set for it, and the relative error ε is calculated. If ε is within the allowable error range, it is considered that the calculation result of the normal shear angle [φ n ] cal is reasonable, i.e. acceptable; if ε is not within the allowable error range, return to step three, reset the initial value [φ n ] ini of the normal shear angle, and recalculate until a satisfactory result is obtained, wherein the initial value [φ n ] iniThe value range is between 0 degree and 45 degree. Some results obtained from the test data are shown in Table 1.

[0080] Table 1 t chip , t1, φ n , β and δ calculation results

[0081]

[0082] Step eight, according to the milling test data, i.e. the cutting force and the average thickness of the sawtooth chip, the cutting force equation obtained according to the cutting force balance is used to calculate the longitudinal coordinate and the transverse coordinate (cosδcotφ n )t1, and the longitudinal coordinate and the transverse coordinate (Zcosδcotφ n )t1, are respectively linearly fitted, and the fitting results are shown in Table 2 and Table 3. Figure 7 Then, the slope and intercept of the fitting line are used to calculate the yield stress σ Y , the fracture toughness G c and the viscous toughness G a of the workpiece material in the sawtooth chip generation process of the oblique angle cutting saw, and the calculated results are shown in Table 2 and Table 3.

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

[0084]

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

[0086]

[0087] Step nine, the yield stress σ Y of the workpiece material of the toughness difficult-to-machine material Inconel718 in the sawtooth chip generation process of the milling machining is compared respectively according to the results in Table 2 and Table 3, and it is found that the yield stress σ Y values predicted in Table 2 and Table 3 under different cutting speed conditions are corresponding to each other, which shows the rationality of the milling prediction method. Since the yield stress σ Ythe difference between the values, the fracture toughness G c the difference between the values and the viscous toughness G a The difference between the values can be explained by the combined effect of strain rate hardening encountered during the formation of a saw-tooth chip and the softening of the workpiece material caused by high temperatures during the cutting process. By comparing the yield strength and fracture toughness values of Inconel718 in the literature "B. Wang, Z. Q. Liu, Acoustic emission signal analysis during chip formation process in high speed machining of 7050-T7451 aluminum alloy and Inconel718 superalloy, Journal of Manufacturing Processes 27 (2017) 114-125." and "C. Liu, M. Wan, C. J. Shen, 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.", it is found that they can better match the milling test results of the present application, thus proving the effectiveness of the modeling method of the present application for predicting the yield stress σ Y , the fracture toughness G c and the viscous toughness G a of the workpiece material of the tough-to-machine material during the formation of a saw-tooth chip by milling.

[0088] Example 2

[0089] Figure 5 A system for predicting the dynamic mechanical properties of a tough-to-machine material based on milling is shown. 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 x , F y , F z in the X, Y, Z directions at the instantaneous tool engagement angle φ. The charge amplifier is used to amplify the signal of the dynamometer. The data acquisition system transmits the amplified signal to the signal analysis software on the computer. The signal analysis software includes one or more computer program modules, wherein one or more computer program modules are executed by the computer to implement the method for predicting the dynamic mechanical properties of a tough-to-machine material based on milling.

[0090] Embodiment 3

[0091] The present application also provides an embodiment of a computer system. The computer system comprises a processor and a memory. The memory is configured to store non-transitory computer-readable instructions (e.g., one or more computer program modules). The processor is configured to execute the non-transitory computer-readable instructions, which, when executed by the processor, can perform one or more steps of the method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling machining described above. The memory and the processor can be interconnected by a bus system and / or other forms of connection mechanism.

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

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

[0094] Embodiment 4

[0095] The present application also provides a computer-readable storage medium for storing non-transitory computer-readable instructions, which, when executed by a computer, can implement one or more steps of the method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling machining described above. When the method for predicting dynamic mechanical properties of tough difficult-to-machine materials based on milling machining of the present application 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. The relevant description of the storage medium can be referred to the corresponding description of the memory in the computer system above, which will not be repeated here.

Claims

1. A method for predicting the dynamic mechanical properties of tough, difficult-to-machine materials based on milling, characterized in that, include: The normal shear angle φ of the oblique cutting shear plane is optimized by an iterative method. n : (a) Assume an initial value for the normal shear angle, which ranges from 0 degrees to 45 degrees; (b) Calculate the undeformed chip thickness t1, tool instantaneous intrusion angle φ, and cutting force component F based on the initial value of the normal shear angle. c F t F l and normal friction angle λ n ; (c) Update the calculated normal shear angle value; (d) Calculate the initial value and the calculated value φ of the normal shear angle. n If the error is outside 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. Then, use the final calculated value of the normal shear angle 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 Substituting the thickness t1 of the undeformed chip, the lateral flow direction angle β of the chip on the rake face, and the shear flow direction angle δ of the material in the shear plane into the following equation (1), the fracture toughness G of the workpiece material at the tool tip during milling is solved. c Yield stress σ in the shear plane Y Viscous toughness G of chip slippage at the tool-chip contact interface a : In the formula, γ is the inclination angle of the cutting edge when the tool is cutting at an angle, w1 is the width of the undeformed chip, and D is the diameter of the end mill, φ ex It is the angle at which the cutting ends when the tool cuts through 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 chips are serrated. The average thickness t of the serrated segments of the chips is calculated according to the following formula (2). chip : In the formula, t c_max t c_min These are the maximum and minimum chip thicknesses of the sawtooth segment; The average thickness t of the saw tooth segment is calculated according to the following formula (3). chip The corresponding undeformed chip thickness t1: In the formula, r c This represents the ratio of the thickness of the undeformed chip to the thickness of the deformed chip before and after processing.

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

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

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

7. The method for predicting the dynamic mechanical properties of tough, difficult-to-machine materials based on milling as described in 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 into the following formula (8), we obtain the lateral flow direction angle β of the chip on the rake face:

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

9. A dynamic mechanical property prediction system for tough, difficult-to-machine materials based on milling, characterized in that, include: A force gauge is used to measure the cutting force components F in the X, Y, and Z directions at the instantaneous entry angle φ of the cutting tool. x F y F z ; Signal analysis software, comprising 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 as described in any one of claims 1-8.

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 the dynamic mechanical properties of tough and difficult-to-machine materials based on milling, as described in any one of claims 1-8, can be implemented.

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