A method for identifying the machining performance parameters of nanocrystalline cubic boron nitride cutters

Abstract

The present application relates to the field of mechanical processing manufacturing, and particularly relates to a preparation and wear reconstruction method of a nanocrystalline whole end mill cutter. The relative motion relationship between a grinding wheel and a cutter rod is constructed, and a nanocrystalline binderless cubic boron nitride cutter is processed. A cutting experiment is conducted, and a cutter wear surface area and volume model is constructed. The present application constructs a relative motion trajectory model of the grinding wheel and the cutter rod, and the motion trajectory of the grinding wheel is reflected onto the nanocrystalline cutter through conversion between coordinates, which effectively guarantees the precision of the geometric size in the cutter processing process. The present application divides the cutter surface, quickly identifies the cutting edge boundary of the original cutter, and can quickly reconstruct the wear amount of the cutter. The wear amount can accurately determine the wear surface area and the wear volume of the cutter through integration. The model completely gets rid of the traditional one-dimensional wear measurement method of the cutter, and provides strong support for accurate and reliable monitoring of the processing process.

Description

TECHNICAL FIELD

[0001] The application relates to the field of mechanical processing manufacturing, and in particular to a nanocrystalline cubic boron nitride cutter preparation method and a processing performance parameter identification method thereof. BACKGROUND

[0002] Hardened steel is widely used in industrial fields such as bearing and die manufacturing due to its high mechanical strength and wear resistance. Hardened steel is a typical difficult-to-machine material, and in the cutting process, the cutting force is large, the cutting temperature is high, and the tool wear is serious. Using higher hardness cutters and high-speed machining technology to process hardened steel is a common technical means at present. As the main consumable material for hard cutting, the cutter plays an important role in the machining process, and therefore its manufacturing method and cutting performance parameters have always been the focus of hard machining. Polycrystalline cubic boron nitride (PcBN) is widely used in high-speed cutting of difficult-to-machine materials due to its excellent performance, such as high hardness and high chemical stability. According to the Hall-Petch effect, the strength of the material will be significantly improved within a certain range when the grain size of the material decreases. However, the preparation of superhard cutters with lower grain size requires complex chemical process and grinding parameters, so cubic boron nitride cutters with lower grain size are extremely rare. In addition, the prepared superhard cutters still face the problem of unknown cutting performance parameters, especially when the cutter is slightly worn, the average friction coefficient of the rake face of the cutter and the cutting force coefficient cannot be known. The above problems bring great obstacles to the preparation and performance evaluation of difficult-to-machine material cutters. SUMMARY

[0003] The technical problem to be solved by the application is to provide a cubic boron nitride cutter with a nanometer grain size and a cutting machining parameter identification method based on the nanocrystalline cubic boron nitride cutter.

[0004] To solve the above technical problems, the application adopts the following technical solutions:

[0005] ①Put the cubic boron nitride powder into a cavity press, set the pressure value of the cavity press to 10 GPa, and set the temperature to 1600 DEG C, and perform high-temperature and high-pressure conversion on the cubic boron nitride powder;

[0006] ②Maintain the temperature and pressure conditions of the cavity press for 6 minutes, the content of the cubic boron nitride component in the sample is greater than 97%, and the content of the hexagonal boron nitride component is less than 3%; restore the cavity press to normal temperature and pressure, obtain a nanocrystalline binderless cubic boron nitride blank sample, the diameter size is 5 mm, and the height is 2.6 mm;

[0007] ③Using tungsten carbide as the tool bar substrate, the nanocrystalline binderless cubic boron nitride blank sample is connected to the tool bar by high vacuum process using active solder AgCuTi at a brazing temperature of 850℃, an average heating rate of 30K / min and a cooling rate of 25K / min;

[0008] ④The relative motion relationship between the grinding wheel and the tool bar is constructed, and the nanocrystalline binderless cubic boron nitride tool is processed;

[0009] ⑤Cutting experiments are carried out, and a tool cutting force coefficient identification model based on tool wear is constructed;

[0010] 501The cutting tool is measured on a three-dimensional profile instrument, the scanning interval is set to 24°, the tool is scanned 15 times, the three-dimensional profile of the tool is extracted, the new tool cutting edge profile is fitted, and the effective cutting radius function r(t) of the tool is determined according to the wear amount;

[0011] 502Considering the tool runout factor, the motion trajectory equation of the tool center point (x o (t), y o (t)) is as follows:

[0012]

[0013] Where v is the feed speed, w is the angular velocity, Ω is the spindle speed, N is the number of teeth, f z is the feed per tooth, e is the runout eccentricity, and λ is the runout angle;

[0014] The motion trajectory of the tool cutting point P(x p (t), y p (t)) is:

[0015]

[0016] 503Combining formulas (one) and (two), the instantaneous undeformed chip thickness expression is obtained using the kth tooth cutting time t k and the k-1th tooth cutting time t k-1

[0017]

[0018] Where

[0019] 504The objective function is constructed, which is composed of the cutting force measurement and the cutting force model, and the cutting force coefficient is taken as the optimization target, and the objective function is as follows:

[0020]

[0021] Where​ is the cutting force measurement value, is the cutting force model, the cutting force coefficient matrix K = [K tc , K te ; K rc , K re ], K tc and K rc are tangential and normal cutting force coefficients, respectively, K te and K re are tangential and normal edge force coefficients, respectively; the cutting force model expression is:

[0022]

[0023] where F t , F r are tangential and normal forces, respectively, is the instantaneous position angle function of the milling cutter, a is the axial cutting depth; in the formula (five), Δt is the phase difference between the cutting force measurement value in the objective function and the cutting force model;

[0024] 505 identify the cutting coefficient matrix by using the genetic algorithm in the global optimization algorithm;

[0025] ⑥ construct a tool rake face average friction coefficient identification model based on tool wear; determine the tool rake face average friction coefficient expression by using the cutting force model in steps 504 and 505:

[0026]

[0027] where δ is the tool rake angle.

[0028] The step ④ includes: 401 constructing a grinding wheel kinematics equation, in the grinding wheel coordinate system OXYZ, the coordinates R A of any point A on the grinding wheel circumferential surface are:

[0029]

[0030] where R0 is the outer circumferential radius of the grinding wheel, α is the instantaneous azimuth angle, which is formed by the line connecting the point A and the center of the grinding wheel and the normal vector of the grinding wheel perpendicular to the tool bar axis, and u is the height along the vector perpendicular to the outer circumferential vector of the grinding wheel;

[0031] 402 convert the coordinates R AF of any point A on the grinding wheel circumferential surface into the tool bar fixed coordinate system, and the converted coordinates R are:

[0032]

[0033] where γ is the included angle between the tool bar axis and the vector perpendicular to the outer circumferential vector of the grinding wheel, lx , l y and l z is the distance between the grinding wheel coordinate system and the fixed coordinate system of the tool bar;

[0034] 403 with the grinding process, the fixed coordinate system of the tool bar is converted into the coordinate system of the milling cutter to be processed, and the converted coordinates R AFT are:

[0035]

[0036] wherein r is the tool radius of the milling cutter to be processed, beta is the helix angle of the tool, is the instantaneous position angle of the milling cutter in the coordinate system of the milling cutter to be processed;

[0037] 404 steps 401-403 are performed to obtain a binderless nanocrystalline cubic boron nitride tool.

[0038] The prepared series of whole solid end mills are two-blade milling cutters, the diameter is 3mm, the rake angle is 8°, the helix angle is 0, 15° and 30°, and the cutting edge length is 10mm.

[0039] The grain size of the nanocrystalline binderless cubic boron nitride sample is 45-50nm.

[0040] The positive effects of the present application are as follows: the present application proposes a synthesis method of nanocrystalline cubic boron nitride tool, discloses the process parameters of the brazing process, which greatly facilitates the preparation process of the nanocrystalline tool and ensures the quality of the tool preparation; the present application constructs the relative motion trajectory model of the grinding wheel and the tool bar, and the motion trajectory of the grinding wheel is reflected on the nanocrystalline tool through the conversion between the coordinates, which effectively ensures the precision of the geometric size in the tool processing process; the present application fits the tool wear and incorporates the tool radius function into the instantaneous undeformed chip analysis, and determines the instantaneous undeformed chip thickness under the consideration of tool runout by combining the motion trajectories between adjacent tool teeth; the present application fully considers the signal lag in the experimental value acquisition process, compensates the phase difference of the cutting force model, and then identifies the cutting force coefficient by using the global optimization algorithm, which effectively ensures the convergence of the objective function and the accuracy of the cutting force coefficient identification; the present application identifies and analyzes the average friction coefficient of the tool rake face based on the obtained cutting force coefficient, and the cutting performance of the newly prepared tool can be more specifically displayed through the cutting force coefficient and the average friction coefficient, which breaks the bondage of the traditional tool based on the cutting force mechanical model or semi-empirical model, greatly ensures the identification accuracy of the parameters, and provides strong support for accurate and reliable monitoring of the processing process. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 is the tool preparation and performance parameter identification flowchart of the present application;

[0042] Figure 2 Schematic diagram for phase difference compensation of objective function of the present application;

[0043] Figure 3 Schematic diagram for iteration of genetic algorithm of the present application;

[0044] Figure 4 Schematic diagram for fitting of cutting force coefficient of the present application. DETAILED DESCRIPTION

[0045] The present application will be described in detail below in conjunction with the accompanying drawings and specific examples. The pure polycrystalline cubic boron nitride (PcBN) raw material to be used has the following properties: high hardness (3000-3500 HK), high chemical oxidation resistance, good thermal conductivity (> 110 W / m-K), low friction coefficient, high thermal stability when used in the atmosphere, at least up to 1200℃, and low tendency to react with steel (carbon).

[0046] As shown in Figure 1 The preparation steps of the nanocrystalline cubic boron nitride tool (BNNC tool) are as follows: ① Place the cubic boron nitride powder in a cavity press, set the pressure value of the cavity press to 10 GPa, and set the temperature to between 1400℃ and 2200℃, preferably 1400℃, 1600℃, 1800℃, 2000℃ and 2200℃, and perform high-temperature and high-pressure conversion on the cubic boron nitride powder;

[0047] ② Maintain the temperature and pressure conditions of the cavity press for 6 minutes, the content of the cubic boron nitride component in the sample is greater than 97%, and the content of the hexagonal boron nitride component is less than 3%; restore the cavity press to normal temperature and pressure, obtain a nanocrystalline binderless cubic boron nitride blank sample with a diameter size of 5 mm and a height of 2.6 mm;

[0048] ③Using tungsten carbide as the tool bar base, the nanocrystalline binderless cubic boron nitride sample blank is connected to the tool bar by high vacuum process using active solder AgCuTi at a brazing temperature of 850℃, an average heating rate of 30K / min and a cooling rate of 25K / min. Before the brazing process, the nanocrystalline binderless cubic boron nitride sample blank must be polished flat at the connection point, because under the action of high pressure and high temperature, the surface of the synthesized sample blank is slightly concave or convex. There is a high requirement for flatness during brazing. At a brazing temperature of 850℃, an average heating rate of 30K / min and a cooling rate of 25K / min, a process-reliable brazed joint can be produced between the tungsten carbide tool base and the nanocrystalline binderless cubic boron nitride sample, so that the blank will not fall off the tool bar base during subsequent grinding process and cutting process. The tool bar is tungsten carbide K20 with an average grain size of 0.7μm, 92% WC, 8% Co; the density is 14.55g / cm 3 ; the tensile strength is 1710N / mm 2 , and the hardness is HV30. The grain size of the nanocrystalline binderless cubic boron nitride sample is 45-50nm.

[0049] ④The relative motion relationship between the grinding wheel and the tool bar is constructed, and the nanocrystalline binderless cubic boron nitride tool is processed;

[0050] ⑤Cutting experiments are carried out, and a tool cutting force coefficient identification model based on tool wear is constructed;

[0051] 501The cutting tool is measured on a three-dimensional profile instrument, the scanning interval is set to 24°, the tool is scanned 15 times, the three-dimensional profile of the tool is extracted, the new tool cutting edge profile is fitted, and the effective cutting radius function r(t) of the tool is determined according to the wear amount;

[0052] 502Considering the tool runout factor, the motion trajectory equation of the tool center point (x o (t), y o (t)) is as follows:

[0053]

[0054] Where v is the feed speed, w is the angular velocity, Ω is the spindle speed, N is the number of teeth, f z is the feed per tooth, e is the runout eccentricity, and λ is the runout angle;

[0055] The motion trajectory of the tool cutting point P(x p (t), y p (t)) is:

[0056]

[0057] 503 Combining formulas (I) and (II), using the cutting time t of the kth cutting tooth k and the cutting time t of the (k-1)th cutter tooth k-1 The expression for obtaining the instantaneous undeformed chip thickness is as follows:

[0058]

[0059] in

[0060] 504. Construct an objective function, which consists of the measured cutting force values ​​and the cutting force model, with the cutting force coefficient as the optimization objective. The objective function is as follows:

[0061]

[0062] in This is the measured value of the cutting force. For the cutting force model, the cutting force coefficient matrix K = [K tc ,K te ;K rc ,K re ], K tc and K rc These are the tangential and normal cutting force coefficients, K. te and K re These are the tangential and normal cutting edge force coefficients, respectively; the cutting force model expression is:

[0063]

[0064] Where F t F r They are tangential force and normal force, respectively. Let be the instantaneous position angle function of the milling cutter, and 'a' be the axial cutting depth; in equation (v), Δt is the phase difference between the measured cutting force value and the cutting force model in the objective function, such as... Figure 2 As shown;

[0065] 505 uses a genetic algorithm in the global optimization algorithm to identify the cutting coefficient matrix, such as Figure 3 , 4 As shown; the cutting force coefficient matrix K = [K tc ,K te ;K rc ,K re The cutting force coefficients are 2000 N / mm. 2 270N / mm, 500N / mm 2 50 N / mm. ⑥ Construct a tool rake face average friction coefficient identification model based on tool wear; using the cutting force model in steps 504 and 505, determine the expression for the average friction coefficient of the rake face:

[0066]

[0067] wherein δ is the tool rake angle, and the average friction coefficient is 0.25.

[0068] The step ④ comprises: 401 constructing a grinding wheel kinematics equation, in the grinding wheel coordinate system OXYZ, the coordinates R A are:

[0069]

[0070] wherein R0 is the grinding wheel outer circumferential radius, α is the instantaneous azimuth angle, which is formed by the line connecting the point A and the grinding wheel center and the normal vector on the grinding wheel perpendicular to the tool bar axis, and u is the height along the vector perpendicular to the grinding wheel outer circumferential vector;

[0071] 402 converting the coordinates of any point A on the grinding wheel circumferential surface into the tool bar fixed coordinate system, and the converted coordinates R AF are:

[0072]

[0073] wherein γ is the included angle between the tool bar axis and the vector perpendicular to the grinding wheel outer circumferential vector, l x , l y and l z are the distances between the grinding wheel coordinate system and the tool bar fixed coordinate system;

[0074] 403 converting the tool bar fixed coordinate system into the to-be-processed milling cutter coordinate system as the grinding processing proceeds, and the converted coordinates R AFT are:

[0075]

[0076] wherein r is the tool radius of the to-be-processed milling cutter, β is the helix angle of the tool, is the instantaneous position angle of the milling cutter in the to-be-processed milling cutter coordinate system;

[0077] 404 executing steps 401-403 to obtain the binderless nanocrystalline cubic boron nitride tool, and the prepared series of integral end milling cutters are two-blade milling cutters, the diameter of which is 3 mm, the rake angle is 8°, the helix angle is 0, 15° and 30°, and the cutting edge length is 10 mm.

[0078] The above-described embodiments are merely preferred embodiments of the present application, and are not exhaustive of the feasible implementations of the present application. Any obvious modifications made by those skilled in the art without departing from the principles and spirit of the present application shall be considered to be included in the protection scope of the claims of the present application.

Claims

1. A method for identifying nanocrystalline cubic boron nitride tool machining performance parameters, characterized in that The steps are as follows: ①Put the cubic boron nitride powder into a cavity press, set the pressure value of the cavity press to 10 GPa, and set the temperature to 1600 ℃, and perform high-temperature and high-pressure conversion on the cubic boron nitride powder; ②Maintain the temperature and pressure conditions of the cavity press for 6 minutes, the content of the cubic boron nitride component in the sample is greater than 97%, and the content of the hexagonal boron nitride component is less than 3%; restore the cavity press to normal temperature and pressure, obtain a nanocrystalline binderless cubic boron nitride blank sample, the diameter size is 5 mm, and the height is 2.6 mm; ③Use tungsten carbide as a tool bar substrate, use active solder AgCuTi to connect the nanocrystalline binderless cubic boron nitride blank sample to the tool bar through a high-vacuum process at a brazing temperature of 850 ℃, an average heating rate of 30 K / min, and a cooling rate of 25 K / min; ④Construct the relative motion relationship between the grinding wheel and the tool bar, and process the nanocrystalline binderless cubic boron nitride tool; ⑤Perform cutting experiments, and construct a tool cutting force coefficient identification model based on tool wear; 501Measure the cutting tool on a three-dimensional profile instrument, set the scanning interval to 24°, scan the tool 15 times to complete the extraction of the three-dimensional profile of the tool, fit a new tool cutting edge profile, and determine the effective cutting radius function r(t) of the tool according to the wear amount; 502Considering the tool runout factor, the motion trajectory equation of the tool center point (x o (t), y o (t)) is as follows: where v is the feed speed, w is the angular velocity, Ω is the spindle speed, N is the number of teeth, f z is the feed per tooth, e is the run-out eccentricity, and λ is the run-out angle. The movement trajectory of the tool cutting point P(x p (t), y p (t)) is: 503Combining equations (one) and (two), the instantaneous undeformed chip thickness expression is obtained as: k and the k-1th cutter tooth cutting time t k-1 obtained instantaneous undeformed chip thickness expression: wherein 504Construct a target function, which is composed of a cutting force measurement value and a cutting force model, and take the cutting force coefficient as the optimization target, and the target function is as follows: wherein is a cutting force measurement value, is a cutting force model, the cutting force coefficient matrix K = [K tc , K te ; K rc , K re ], K tc and K rc are tangential and normal cutting force coefficients, respectively, K te and K re are tangential and normal edge force coefficients, respectively; the cutting force model expression is: where F t， F r are the tangential and normal forces, respectively, is the instantaneous position angle function of the milling cutter, a is the axial cutting depth; Δt in the equation (5) is the phase difference between the cutting force measurement value in the objective function and the cutting force model; 505Identify the cutting coefficient matrix by using a genetic algorithm in a global optimization algorithm; ⑥Construct a tool rake face average friction coefficient identification model based on tool wear; Use the cutting force model in steps 504 and 505 to determine the rake face average friction coefficient expression: Where δ is the tool rake angle.

2. The method according to claim 1, wherein, The step ④ comprises: 401 Construct the kinematic equation of the grinding wheel, in the grinding wheel coordinate system OXYZ, the coordinates R of any point A on the circumferential surface of the grinding wheel A is: Where R0 is the outer circumferential radius of the grinding wheel, α is the instantaneous azimuth angle, which is composed of the line connecting point A and the center of the grinding wheel and the normal vector perpendicular to the tool bar axis on the grinding wheel, and u is the height along the vector perpendicular to the outer circle of the grinding wheel; 402 convert the coordinates of any point A on the circumference surface of the grinding wheel into the tool bar fixed coordinate system, the converted coordinates R AF are: where γ is the angle between the tool bar axis and the vector perpendicular to the outer circle of the grinding wheel, l x , y and l z is the distance between the grinding wheel coordinate system and the tool bar fixed coordinate system; 403With the grinding process, the tool bar fixed coordinate system is converted to the coordinate system of the milling cutter to be processed, and the converted coordinates R AFT are: wherein r is the tool radius of the milling cutter to be processed, and β is the helix angle of the tool, is the instantaneous position angle of the milling cutter in the coordinate system of the milling cutter to be processed; 404Perform steps 401-403 to obtain a binderless nanocrystalline cubic boron nitride tool.

3. The method according to claim 1, wherein The grain size of the nanocrystalline binderless cubic boron nitride blank sample is 45-50 nm.

4. The method according to claim 2, wherein the method is characterized by: The prepared series of solid end mills are two-blade milling tools, the diameter is 3 mm, the rake angle is 8°, the helix angle is 0°, 15° and 30° respectively, and the cutting edge length is 10 mm.

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