A method for predicting flank wear of large pitch thread turning tools considering vibration

Abstract

The invention relates to a method for predicting the back face wear of a turning large pitch thread tool considering vibration, and the steps are: step one, solving the correlation between a vibration characteristic value and the wear amount of the tool back face, and taking the correlation value of 0.85 as a criterion to determine whether to consider a vibration wear rate equation caused by vibration; step two, establishing a relative speed equation of the tool and the workpiece considering the influence of vibration; step three: establishing an average stress equation for the back face of the tool; step four, establishing a temperature equation for the back face of the tool under wear conditions; step five, judging the wear form according to the processing temperature, and establishing a total wear rate equation considering vibration; step six, establishing an equation for the cumulative wear amount of the tool back face under time history; step seven, obtaining the cumulative value of the wear amount of multiple feeds, and completing the prediction of the wear of the tool back face through simulation software; the prediction method constructed by the invention can realize the accurate prediction of the wear amount of the back face of the large pitch thread tool.

Description

Technical Field

[0001] The invention relates to the technical field of tool wear assessment during a cutting process, and in particular to a method for predicting flank wear of a turning large-pitch thread tool taking vibration into consideration. Background Art

[0002] Large pitch threads are important components of presses, playing the role of connection and power transmission. The quality of their machined surface directly determines the working performance of the equipment. Flank wear caused by vibration generated by large pitch screw turning is the main controlling factor leading to tool performance degradation and reduced surface quality of large pitch threaded parts.

[0003] The surface quality of the thread is affected by the wear of the flank face, so improving the surface quality of the workpiece requires controlling the wear of the flank face. The forms of flank wear include abrasive wear, oxidation wear, adhesive wear and diffusion wear. Through temperature collection during the large-pitch thread turning process, it was found that when the processing temperature is not higher than 500°C, the main wear forms of the flank face of the cutting tool are abrasive wear and adhesive wear. At the same time, considering that the tool is involved in the long cutting edge and the vibration is severe during the large-pitch processing, the tool wear is further aggravated. However, the existing tool wear model does not consider the impact of vibration on tool wear, and the predicted tool wear is greatly deviated from the actual measured value. Therefore, how to effectively design a method that can effectively predict tool wear is a technical problem that needs to be solved urgently.

[0004] In view of the fact that the existing tool wear model does not consider the influence of vibration on tool wear, a method for predicting the flank wear of cutting tools for turning large pitch threads taking into account vibration is proposed. This method can more accurately predict the wear amount of the flank face when turning large pitch threaded parts through the established tool wear model, and provide a theoretical basis and technical guarantee for predicting the wear amount of the flank face of cutting tools for turning large pitch threaded parts, which is of very important research value. Summary of the invention

[0005] In order to solve the technical problems existing in the known technology, the present invention provides a method for predicting the flank wear of a turning tool for large pitch threads taking into account vibration. The construction method takes the tool wear caused by vibration as the research object. The flank wear prediction model constructed by the construction method can more accurately predict the wear amount of the flank when turning large pitch threaded parts.

[0006] The technical solution adopted by the present invention to solve the technical problems existing in the known technology is:

[0007] 1. A method for predicting the flank wear of a large pitch thread turning tool taking into account vibration, characterized in that it comprises the following steps:

[0008] Step 1: Based on the experimental data collected in the experiment, the correlation analysis of the vibration characteristic value and the tool flank wear was carried out, and the correlation degree between the vibration characteristic value and the tool flank wear was obtained. The correlation value of 0.85 was used as a criterion to determine whether to consider the vibration wear rate equation caused by vibration;

[0009] Step 2: Establish the relative speed v between the tool and the workpiece considering the influence of vibration wc equation;

[0010] Step 3: Determine the size of VB and VB*, determine different friction force solution formulas, and establish the average stress equation of the tool back face;

[0011] Step 4: Establish the temperature equation of the tool flank under wear;

[0012] Step 5: Determine the wear form according to the cutting temperature and establish the total wear rate equation;

[0013] Step 6: Establish the cumulative wear equation of the tool flank under time history;

[0014] Step 7: Obtain the cumulative wear ΔVB of multiple feeds to complete the prediction of tool flank wear VB.

[0015] 2. In the step 1, it is characterized in that: the collected vibration characteristic value factors include: effective value of vibration acceleration, margin factor, kurtosis factor, waveform factor, peak factor; the grey system theory modeling software is used to perform correlation analysis on the tool flank wear and vibration characteristic value factors;

[0016] In the step 2, it is characterized in that: firstly, the relative speed v between the tool and the workpiece considering the vibration effect is established. wc Model, satisfying the formula:

[0017]

[0018] In formula (1), v f is the feed speed, v c is the cutting speed, v x is the velocity component of the vibration velocity in the x direction, v y is the velocity component of the vibration velocity in the y direction, v z is the velocity component of the vibration velocity in the z direction, is the helix angle, i.e. the angle between the cutting speed and the z direction of the coordinate axis, v w is the composite speed of the feed plane, v wx v w The velocity component in the x direction in the feed plane, v wz v w Velocity component in the z direction in the feed plane, v wcThe relative velocity considering the vibration effect for the tool and the workpiece.

[0019] In the third step, it is characterized in that: the magnitudes of VB and VB* are determined to obtain different friction force solution formulas:

[0020] If VB ≥ VB*, the following formula is satisfied:

[0021]

[0022] If VB < VB*, the following formula is satisfied:

[0023]

[0024] The established average stress equation of the tool flank should satisfy the following formula:

[0025]

[0026] In formulas (2) and (3), the tangential stress in the plastic flow region of the flank is represented by τ 0 ; the normal stress is represented by σ 0 ; the length of the elastic contact region is represented by VB*, and the values of τ 0 , σ 0 and VB* are obtained through experiments. F tw (VB) is the tangential friction force per unit contact length of the flank, and F rw (VB) is the radial friction force per unit contact length of the flank; in formula (4) is the average shear stress, is the average normal stress.

[0027] In the fourth step, it is characterized in that: the temperature equation of the flank under the condition of wear should satisfy the following formula:

[0028] T f = T f ′ + KVB 0.25 (5)

[0029] In formula (5), T f ′ is the flank temperature in the ideal state, which is related to the feed rate f z in the cutting coefficient, the cutting width b Dl , and the radial cutting depth a p .

[0030] The K satisfies the following formula:

[0031]

[0032] In formula (6), k w (= 48.3 - 0.023T) is the thermal conductivity of the workpiece; ρ wis the workpiece density; c w (=420+0.504T) is the specific heat capacity of the workpiece; b Dl is the cutting width; T is the average temperature of the flank surface.

[0033] In the step 5, it is characterized in that: an abrasive wear rate equation is established, which should satisfy the formula:

[0034]

[0035] In formula (7), K abr is the abrasive wear coefficient; v wc is the relative speed; Average normal stress on the flank surface.

[0036] The bonding wear rate equation should satisfy the following formula:

[0037]

[0038] In formula (8), A w =7.8×10-9; B w =5.302×103, T is the average temperature of the back cutting edge.

[0039] The total wear rate equation should satisfy the following formula:

[0040]

[0041] In the step six, it is characterized in that: an equation for the cumulative wear of the tool back face under time history is established, which should satisfy the formula:

[0042]

[0043] In formula (10), α is the tool back angle; γ is the tool rake angle.

[0044] 3. In the step 7, it is characterized in that: the cumulative value ΔVB of the wear amount of multiple feeds is obtained, when time t=0, ΔVB is the initial flank wear amount VB 0 , complete the prediction of the flank wear VB; when time t>0, ΔVB is the intermediate amount VB in the calculation process of flank wear, when t=t a When t a is the total cutting time; the above wear rate is combined with the geometric shape change rate, and the stress value of the plastic flow area of ​​the flank and the cutting parameters are used as input conditions, and the flank wear prediction curve is obtained through the simulation software.

[0045] Beneficial effects of the present invention:

[0046] 1. A vibration-based prediction method for tool flank wear of large-pitch thread turning tools was established, filling the gap in existing tool flank wear prediction methods that do not consider tool wear caused by vibration;

[0047] 2. The predicted value of the existing tool flank wear prediction method is quite different from the actual value. The method proposed in the present invention can accurately predict the wear amount of the flank when cutting large pitch threads, and effectively provide a reference basis. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is the overall implementation flow chart of the method of the present invention;

[0049] Figure 2 A simulation flow chart provided for an example of the present invention;

[0050] Figure 3 Predicted wear maps provided for examples of the present invention;

[0051] Figure 4 is a schematic diagram of velocity components in an example of the present invention;

[0052] Figure 5 A schematic diagram of stress distribution on the back face of a worn tool in an example of the present invention;

[0053] Figure 6 It is the experimental equipment in the example of the present invention;

[0054] Figure 7 This is a measurement diagram of the ultra-depth of field microscope and the wear amount of the back face of the turning tool in an example of the present invention. DETAILED DESCRIPTION

[0055] The present invention proposes a method for predicting the back face wear of a large pitch thread turning tool considering vibration, and its flow chart is as follows: Figure 1 As shown in the figure, the proposed tool wear prediction method is divided into the following steps:

[0056] Step 1: Based on the experimental data collected in the experiment, the correlation analysis of the vibration characteristic value and the tool flank wear was carried out, and the correlation degree between the vibration characteristic value and the tool flank wear was obtained. The correlation value of 0.85 was used as the criterion to determine whether to consider the vibration wear rate equation caused by vibration.

[0057] The present invention uses an experimental method to collect the wear amount and vibration characteristic value of the tool back face during turning and conduct correlation analysis. The workpiece selected in the experiment is a trapezoidal screw with a pitch of 18mm (the axial length of the thread is 200mm and the major diameter is 140mm). The tool and workpiece materials are W18Cr4v and AISI1045 steel, respectively, with densities of 8120 and 7800kg / m 3The cutting edge inclination angle and the left and right cutting edge rake angles are all 0°, the left and right cutting edge clearance angles are 8° and 5°, and the turning process is carried out on a conventional lathe CA6140.

[0058] The vibration characteristic value factors collected include: effective value of vibration acceleration, margin factor, kurtosis factor, waveform factor, peak factor; the signal acquisition system and sensor for collecting signals such as Figure 6 As shown, the sensor is a PCB (353A02) piezoelectric three-axis acceleration sensor, the sensitivity of which is 2.4620mV / EU, 2.4870mV / EU and 25340mV / EU respectively; the ultra-depth microscope for collecting tool wear is as shown in Figure 7 The model is VHX-1000; the data collected in the experiment are shown in Table 1. The collected tool flank wear and vibration characteristic values ​​are subjected to grey correlation analysis using grey system theory modeling software to obtain the absolute correlation value between the tool flank wear and the vibration characteristic value factor.

[0059] Table 1 Vibration characteristic parameters and tool wear

[0060]

[0061] r v 、r va 、r m 、r k 、r w 、r p and r mf They respectively represent the absolute correlation values ​​of the maximum value of tool flank wear and the effective value of vibration acceleration, amplitude, maximum cutting force, kurtosis factor, waveform factor, peak factor and margin factor. The centralization method is selected as the method of dimensionless factor column to process the data in Table 1, and the absolute correlation between the tool wear in the x, y and z directions of the left and right cutting edges and the cutting force, amplitude and vibration characteristic parameters under the same cutting parameters is analyzed. The absolute correlation and factor ranking calculated by the grey system theory modeling software are shown in Table 2.

[0062] Table 2 Absolute correlation and its factor ranking

[0063]

[0064] Step 2: Establish the relative speed v between the tool and the workpiece considering the influence of vibration wc equation.

[0065]

[0066] In formula (1), v f is the feed speed, v c is the cutting speed, v xis the velocity component of the vibration velocity in the x direction, v y is the velocity component of the vibration velocity in the y direction, v z is the velocity component of the vibration velocity in the z direction is the helix angle, i.e., the angle between the cutting velocity and the z-axis of the coordinate system, v w is the resultant velocity in the feed plane, v wx is v w is the velocity component in the x direction in the feed plane, v wz is v w is the velocity component in the z direction in the feed plane, v wc is the relative velocity of the tool and the workpiece considering the influence of vibration; the schematic diagram of the velocity components is as shown in Figure 4 shown

[0067] Step 3: Determine the magnitudes of VB and VB*, determine the friction force solution formula, and solve for the average stress on the flank face of the tool

[0068] If VB ≥ VB*, then the following equation is satisfied

[0069]

[0070] If VB < VB*, then the following equation is satisfied

[0071]

[0072] The established equation for the average stress on the flank face of the tool should satisfy the following equation

[0073]

[0074] In Equations (2) and (3), the tangential stress in the plastic flow region on the flank face is represented by τ 0 The normal stress is represented by σ 0 The length of the elastic contact region is represented by VB*, and the values of τ 0 , σ 0 and VB* are obtained through experiments. The experiment uses a cutting force measurement system of model KISTLER9257B, F tw (VB) is the tangential friction force per unit contact length on the flank face, F rw (VB) is the radial friction force per unit contact length on the flank face; in Equation (4) is the average shear stress is the average normal stress; as shown in Figure 5 is the schematic diagram of the stress distribution on the flank face of the worn tool. σ(x) and τ(x) are the distributions of the normal stress and the shear stress in the elastic contact region respectively; VB pIt is the boundary value that divides the flank wear area into the elastic contact area and the plastic contact area. When the flank of the tool contacts the machined surface, elastic deformation occurs first. As the cutting proceeds, when the wear reaches the critical value, the length of the elastic contact area remains unchanged at VB*, and the length of the plastic contact area increases with the increase of flank wear.

[0075] Step 4: Establish the temperature equation of the flank surface under wear:

[0076] T f =T′ f +KVB 0.25 (5)

[0077] In formula (5), T′ f is the flank temperature under ideal conditions, and the feed rate f in the cutting coefficient z , cutting width b Dl , radial cutting depth a p related.

[0078] The K satisfies formula (6):

[0079]

[0080] In formula (6), k w (=48.3-0.023T) is the thermal conductivity of the workpiece; ρ w is the workpiece density; c w (=420+0.504T) is the specific heat capacity of the workpiece; b Dl is the cutting width; T is the average temperature of the flank surface.

[0081] Step 5: Establish equations for abrasive wear rate and adhesive wear rate, and obtain the total wear rate equation.

[0082] Abrasive wear rate equation during turning:

[0083]

[0084] In formula (7), K abr is the abrasive wear coefficient; v wc is the relative speed; Average normal stress on the flank surface.

[0085] Wear rate equation for adhesive wear:

[0086]

[0087] In formula (8), A w =7.8×10-9; B w =5.302×103, T is the average temperature of the back cutting edge.

[0088] The total wear rate equation of thread turning tool:

[0089]

[0090] Step 6: Establish the cumulative wear equation of the tool back face under time history:

[0091]

[0092] In formula (10), α is the tool back angle; γ is the tool rake angle.

[0093] Step 7: Obtain the cumulative value ΔVB of multiple feed wear to complete the prediction of tool flank wear VB.

[0094] Among them, when time t = 0, ΔVB is equal to the initial flank wear VB 0 , when time t>0, ΔVB is the intermediate amount VB in the calculation process of flank wear, when t=t a When t a is the total cutting time; the above wear rate is combined with the geometric shape change rate, and the stress value of the plastic flow area of ​​the back tool face and the cutting parameters are used as input conditions, and the prediction result curve is obtained by SIMLINK simulation through MATLAB software.

[0095] The simulation flow chart for predicting the wear amount of the back tool face is as follows: Figure 2 As shown in the figure, the simulation software is used to predict the wear of the back face of the large pitch thread. The simulation processing parameters for the initial wear of the left cutting edge are axial cutting depth z = 0.05mm, speed n = 10rpm, feed rate f z is 16mm / r and radial cutting depth a p =9mm, the wear amount prediction diagram is as follows Figure 3 As shown. The simulation results show that the wear amount increases sharply in the initial stage of wear, which is in line with the law of initial wear. The thread tool wear experiment was carried out to obtain the wear amount under the corresponding stroke to verify the accuracy of the simulation results. The experimental value is close to the simulation result. The wear amount simulation value corresponding to the cutting stroke of 10m is 69μm, and the experimental value is 62μm; the wear amount simulation value corresponding to the cutting stroke of 20m is 105μm, and the experimental value is 98μm; the error is no more than 15%, which proves that the method is effective.

[0096] It should be noted that the protection scope of the present invention is based on the claims and is not limited by the above-mentioned specific implementation. Any modifications, equivalent substitutions, improvements, etc. within the scope of the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the flank wear of a large pitch thread turning tool considering vibration, characterized in that: It includes the following steps: Step 1: Based on the experimental data collected in the experiment, a correlation analysis is carried out on the vibration characteristic value and the flank wear amount of the tool, and the correlation degree between the vibration characteristic value and the flank wear amount of the tool is obtained. Taking the correlation degree value of 0.85 as the criterion, it is judged whether to consider the vibration wear rate equation caused by vibration; Step 2: Establish the relative speed v between the tool and the workpiece considering the influence of vibration wc equation; Step 3: Determine the size of the flank wear amount VB of the tool and the length VB* of the elastic contact area, determine different friction force solution formulas, and establish the average stress equation of the tool flank; Step 4: Establish the temperature equation of the tool flank under the condition of wear; Step 5: Judge the wear form according to the cutting temperature and establish the total wear rate equation; Step 6: Establish the cumulative wear amount equation of the tool flank under the time history; Step 7: Obtain the cumulative value ΔVB of the wear amount during multiple tool feedings, and complete the prediction of the flank wear amount VB of the tool through the simulation software; The collected vibration characteristic value factors include: the effective value of vibration acceleration, the margin factor, the kurtosis factor, the waveform factor, and the peak factor; the gray system theory modeling software is used to carry out the correlation analysis on the flank wear amount of the tool and the vibration characteristic value factors; The relative speed v between the tool and the workpiece considering the influence of vibration is established wc Model, satisfying the formula: In formula (1), v f is the feed speed, v c is the cutting speed, v x is the velocity component of the vibration velocity in the x direction, v y is the velocity component of the vibration velocity in the y direction, v z is the velocity component of the vibration velocity in the z direction, is the helix angle, i.e. the angle between the cutting speed and the z direction of the coordinate axis, v w is the composite speed of the feed plane, v wx v w The velocity component in the x direction in the feed plane, v wz v w Velocity component in the z direction in the feed plane, v wc Relative speeds for tool and workpiece taking into account vibration effects; The determination of the size of VB and VB*, and the determination of different friction force solution formulas should satisfy: If VB≥VB*, then it satisfies the formula: If VB<VB*, then it satisfies the formula: The establishment of the average stress equation of the tool flank should satisfy the formula: In formulas (2) and (3), the flank wear VB is collected through experiments; the tangential stress in the plastic flow area of ​​the flank is represented by τ0; the normal stress is represented by σ0; the length of the elastic contact area is represented by VB*, and the values ​​of τ0, σ0 and VB* are obtained from experiments; F tw (VB) is the tangential friction force per unit contact length of the back tool face, F rw (VB) is the radial friction force per unit contact length of the back tool surface; in formula (4) is the average shear stress, is the average normal stress; The temperature equation of the tool flank under the condition of wear should satisfy the formula: In formula (5), T f ′ is the flank temperature under ideal conditions, and is related to the feed rate f in the cutting coefficient z , cutting width b Dl , radial cutting depth a p related; The K satisfies the formula: In formula (6), k w (=48.3-0.023T) is the thermal conductivity of the workpiece; ρ w is the workpiece density; c w (=420+0.504T) is the specific heat capacity of the workpiece; b Dl is the cutting width; T is the average temperature of the flank surface; The establishment of the abrasive wear rate equation considering the influence of vibration should satisfy the formula: In formula (7), K abr is the abrasive wear coefficient; v wc is the relative speed; Average normal stress on the flank surface; The establishment of the adhesive wear rate equation considering the influence of vibration should satisfy the formula: In formula (8), A w =7.8×10-9; B w =5.302×103, T is the average temperature of the flank surface; The establishment of the total wear rate equation should satisfy the formula: The establishment of the cumulative wear amount equation of the tool flank under the time history should satisfy the formula: In formula (10), α is the tool flank angle; γ is the tool rake angle.

2. According to claim 1, a method for predicting the flank wear of a large pitch thread turning tool taking into account vibration, characterized in that: The accumulated wear of multiple feeds ΔVB is obtained. When time t = 0, ΔVB is the initial flank wear VB0. When time t> 0, ΔVB is the intermediate amount VB in the calculation process of flank wear. When t = t a When t a is the total cutting time; the above wear rate is combined with the geometric shape change rate, and the stress value of the plastic flow area of ​​the flank and the cutting parameters are used as input conditions, and the flank wear prediction curve is obtained through the simulation software.

Images