CN118036272A - Diphase stainless steel processing technology based on stress mixing rule - Google Patents

Abstract

The present invention discloses a duplex stainless steel processing technology based on the stress mixing rule, comprising the following steps: S1: establishing a two-phase stress solution model for duplex materials, distinguishing and solving the two-phase stress of the duplex materials; S2: establishing a two-phase microhardness solution model considering the tool rake angle and cutting amount, revealing the influence of the tool rake angle and cutting amount on the two-phase microhardness; S3: revealing the influence of the tool rake angle and cutting amount on the distribution characteristics of the two-phase microhardness in the chips, and obtaining the matching relationship between the tool rake angle and the cutting amount under the condition that the two-phase microhardness distribution is consistent, so as to optimize the processing technology of duplex stainless steel. The present invention reveals the influence of the two-phase stress distribution of duplex materials on the two-phase microhardness through the knowledge related to material mechanics. In combination with the relationship between microhardness and plastic strain, a two-phase microhardness solution model considering the tool rake angle and cutting amount is established, which solves the problem of uncertain distribution of the two-phase microhardness.

Description

A processing technology of duplex stainless steel based on stress mixing rule

This application is a divisional application with application number 202310278952.9 and application date March 21, 2023. The invention name at the time of application was “A duplex stainless steel processing technology based on consistency of two-phase hardness distribution”.

Technical Field

The invention belongs to the technical field of two-phase microhardness distribution of cutting duplex stainless steel, and in particular relates to a duplex stainless steel processing technology based on the stress mixing rule.

Background technique

During the cutting process of S32760, the two phases in the shear zone undergo severe plastic deformation, and the difference in the mechanical properties of the two phases and the different evolution forms lead to uneven distribution of the two-phase stress. In view of the problem that the existing models cannot solve the stress of the two phases of cutting materials separately during the cutting process, considering the inconsistency of the distribution of the two-phase stress of the two phases during the cutting process, a model for solving the two-phase stress of the two-phase material is established.

It is currently known that the tool rake angle and cutting amount have a significant effect on the microhardness of the two phases of the machined surface, but there is a lack of a microstructure microhardness solution model for cutting duplex stainless steel, and there is a lack of key conclusions on the mapping relationship between microstructure and cutting process. Therefore, the present invention establishes a two-phase microhardness solution model that takes into account the tool rake angle and cutting amount, reveals the influence of the tool rake angle and cutting amount on the two-phase microhardness, and uses this as the basis for optimizing the duplex stainless steel processing technology.

Traditional methods for improving processing technology only focus on modifying the tool rake angle or cutting amount, and do not consider the influence of the matching between the tool rake angle and the cutting amount on the hardness distribution of the two-phase microhardness. Therefore, based on the established two-phase microhardness solution model, the present invention reveals the influence of the tool rake angle and cutting amount on the two-phase microhardness distribution characteristics in the chips. Under the condition that the two-phase microhardness distribution is consistent, the matching relationship between the tool rake angle and the cutting amount is obtained, and the duplex stainless steel processing technology is optimized.

Summary of the invention

The object of the present invention is to provide a duplex stainless steel processing technology based on the stress mixing rule to solve the problems raised in the above background technology.

To achieve the above object, the present invention provides the following technical solution: a duplex stainless steel processing technology based on the stress mixing rule, comprising the following steps:

S1: Based on the stress mixing rule, a two-phase material two-phase stress solution model is established to distinguish and solve the two-phase stress of the two-phase material;

S2: Establish a two-phase microhardness calculation model considering the tool rake angle and cutting amount, and reveal the influence of tool rake angle and cutting amount on the two-phase microhardness;

S3: Based on the established two-phase microhardness solution model, the influence of tool rake angle and cutting amount on the two-phase microhardness distribution characteristics in the chip is revealed. Under the condition of consistent distribution of two-phase microhardness, the matching relationship between tool rake angle and cutting amount is obtained to optimize the processing technology of duplex stainless steel.

1. Extraction method of multi-physical field distribution in shear zone:

(1) The schematic diagram of the right-angle cutting shear zone is shown in Figure 2. The cutting force is predicted by analyzing the moment balance relationship in the shear zone and combining the S32760 two-phase constitutive model, and the cutting force is solved by the cutting parameters. FEBA and ABCD are the upper and lower halves of the shear zone, respectively, and AG is the tool-chip contact length, expressed as h _tc .

(2) Shear surface analysis

According to the equilibrium conditions of the shear plane and the tool-chip interface, each cutting component and the chip thickness _t2 can be obtained by the following formula:

F _t = _FR sin(λ-α) (1)

F _f = _FR sinλ (2)

_Fn = _FR cos(λ) (3)

F _N = _FR sinθ (5)

Where: α is the tool rake angle; φ is the angle between the shear plane AB and the cutting speed direction, i.e., the shear angle; λ is the friction angle; t1 is the undeformed chip thickness; w is the cutting width; Fc and Ft are the components of the cutting force in the cutting direction and perpendicular to the cutting direction; Ff is the friction force at the tool-chip interface; Fs is the cutting force on the shear plane; FN and Fn are the normal forces at the shear plane and the tool-chip interface, respectively; the resultant force of the normal force F _N at the shear plane and the cutting force F _s at the shear plane and the resultant force of the normal force F _n at the tool-chip interface and the friction force F _f at the tool-chip interface are a pair of balanced forces; the chip forming force _FR is decomposed into F _c and F _t along the cutting direction and perpendicular to the cutting direction. θ is the angle between FR and AB; σAB represents the average flow stress on the shear plane.

The velocity and displacement increments of any point from A to B along the cutting direction and perpendicular to the cutting direction are:

Where: V is the cutting speed; _ΔS1 is the vertical height between EF and CD.

The relationship between the velocity of any particle in the first deformation zone and the average shear strain rate in the shear zone is:

Substituting equations (7) and (8) into equation (9), we can obtain the expression of average shear strain rate:

The shear angle φ is calculated iteratively and determined based on the equilibrium condition of the shear zone. The average equivalent strain and equivalent strain rate of any particle at the shear surface AB can be expressed by the following formula:

According to the velocity vector relationship in Figure 2, the material flow velocity V _c of the chip and the material flow velocity V _s of the shear surface can be obtained:

Based on Oxley cutting theory, the average temperature in the shear zone is:

Where: _Tr is the workpiece temperature, η is the average temperature coefficient, which is taken as 0.9 in the analysis; ρ is the material density; _Cw is the specific heat capacity, where β is the ratio of the shear deformation heat conduction to the workpiece material in the first deformation zone of the shear zone, calculated as follows:

Where: Kw is the thermal conductivity coefficient.

Due to the plastic deformation of the workpiece, there is a high strain, high strain rate, and high temperature cutting environment in the shear zone. In the Oxley theoretical model, the S32760 two-phase constitutive model is used to predict the flow stress in the shear zone:

The angle between _Fn and _Fr in the shear zone is the friction angle, which can be Calculation. According to Oxley theory, we can get According to the iterative calculation of the shear angle/> The angle θ can be obtained.

The strain rate constant _C0 in the first deformation zone is based on the material work hardening mechanism and takes into account the influence of material strain. Its expression is:

Where: C _Oxley is the aspect ratio of the shear band in the first deformation zone; A _JC , B _JC and n _JC are the JC constitutive parameters, respectively.

In the Oxley right-angle cutting model considering the coupling of cutting heat and cutting force, when iteratively calculating the shear zone temperature, it is necessary to assume the rheological stress at the initial temperature of the shear zone, calculate the component force in the shear zone based on the obtained rheological stress, and then use the shear zone equilibrium temperature formula to update the shear zone temperature. Repeat this process until the difference between the updated temperature and the shear zone temperature is less than 0.1 degrees Celsius, that is, the temperature at this time is considered to be the shear zone temperature. Then, the rheological stress at the shear band AB is calculated based on the output shear band temperature, the equivalent strain of the shear band, and the shear band strain rate. Finally, _FR is calculated, and other component forces are analyzed based on the geometric relationship of the equally divided shear zone.

(3) Tool-chip interface analysis

The equivalent strain and equivalent strain rate of the tool-chip interface are:

Where: _htc is the tool-chip contact length.

The average temperature _Tint of the tool-chip interface is expressed as:

_Tint ＝ _Tr +ΔT _SZ + _ψΔTM (22)

Where: ψ is the correction coefficient; _ΔTM is the maximum temperature rise in the chip; _ΔTC is the average temperature rise in the chip; _ΔTSZ is the temperature rise in the first deformation zone.

(3) Multi-physics field extraction process

Due to the shear angle of the shear zone The shear zone strain rate coefficient C _Oxley and the ratio of the second deformation zone thickness to the chip thickness δ vary with cutting conditions, material properties and tool rake angle, so three variable ranges are set as the ranges of the three iterations, namely δ∈[0.005,0.2], C _Oxley ∈[2,10],/>

From the analysis of the shear surface geometry, we can know that the cutting force (F _c ) is:

F _c = _FR cos(λ-α) (25)

The normal stress σ′ _N at point B in Figure 2 can be obtained by combining the average flow stress of the shear surface:

Assuming that the tool-chip interface stress is uniformly distributed, the expressions of tool-chip interface stress τ _int and stress σ _N are obtained as follows:

(4) Extraction of multi-physics field distribution in shear zone

Extract the shear angle based on the model of dividing the shear zone into equal parts by right-angle cutting The first deformation zone aspect ratio C _Oxley , the second deformation zone thickness to cutting thickness ratio δ , the shear zone temperature T _AB , the shear zone strain ε _AB , the shear zone strain rate/> Shear stress σ _AB .

Table 1 Multi-physical field distribution in the shear zone under different cutting parameters

2. Method for solving the two-phase stress of two-phase materials:

During the cutting process of S32760, the two phases in the shear zone undergo severe plastic deformation. The difference in the mechanical properties of the two phases and their different evolution forms lead to a large difference in the degree of work hardening between the two phases. Therefore, by analyzing the influence of cutting parameters and the microhardness of the two phases, the difference in the dynamic mechanical behavior of the two phases during the cutting process is revealed.

Through the microhardness measurement of the two phases of the matrix, it can be seen that the ferrite phase of the matrix has a higher microhardness, which is consistent with the characteristics of the higher hardness of the ferrite phase in S32760. The two phases after cutting undergo plastic deformation, and the degree of work hardening is very different.

Table 2 Work hardening degree of two phases in shear zone under different feed rates

It can be seen from Figure 3 that the microhardness of the austenite phase and ferrite phase of the chip decreases with the increase of feed rate. It can be seen from Table 2 that the degree of work hardening of the two phases also decreases with the increase of feed rate. With the increase of feed rate, the shear strain decreases, the average shear strain rate decreases, the degree of hardening decreases, and the temperature is basically unaffected, so the thermal softening effect dominated by temperature remains basically unchanged. At this time, with the increase of feed rate, the work hardening effect of the two phases decreases, while the thermal softening effect dominated by temperature remains unchanged, so the degree of work hardening of the two phases in the shear zone decreases.

During the cutting process, S32760 is subjected to external forces such as tool extrusion and friction. Under the action of mechanical and thermal coupling, the rheological stress of the workpiece material in the shear zone generally has strain hardening effect, strain rate strengthening effect and thermal softening effect. The strain hardening effect refers to the increase of the rheological stress of the material with the increase of strain; the strain rate strengthening effect refers to the increase of the rheological stress of the material with the increase of strain rate; the thermal softening effect characterizes that the rheological stress of the material decreases with the increase of temperature. The rheological stress is proportional to the microhardness of the material. Therefore, the analysis of the two-phase rheological stress in the shear zone of the S32760 chip needs to consider the relationship between the temperature, strain and strain rate in the shear zone.

Based on material mechanics, the Vickers microhardness value is proportional to the flow stress, so:

HV＝Cσ (28)

Where: C is a constant.

Based on the above formula, it can be seen that the rheological stress of the two phases is required to predict the microhardness of the two phases. The rheological stress of the chips can be approximately regarded as the shear stress.

The prerequisite of the stress mixing law is to assume that the strains of the two phases are the same during the deformation of the material. However, whether it is a quasi-static tension or dynamic compression experiment, the huge difference in the mechanical properties of the two phases leads to a competitive coupling effect between the two phases during the plastic deformation process. Therefore, a general treatment method for multiphase materials is adopted, that is, on the basis of retaining the two-phase stress mixing law, the two-phase strains are also expressed in the form of a mixing law.

σ(ε)＝F·σ ₁ (ε ₁ )+(1-F)·σ ₂ (ε ₂ ) (29)

ε＝F·ε ₁ +(1-F)·ε ₂ (30)

Where: ε ₁ and ε ₂ are the strain values of the austenite phase and the ferrite phase, respectively.

At this time, it is necessary to consider the ratio of the two phases in the S32760 matrix. Therefore, the S32760 matrix is observed using a SEM scanning electron microscope to analyze the ratio of the two phases. The metallographic structure diagram of the S32760 matrix at 500 times is shown in Figure 23.

Analysis shows that the volume fraction ratio of austenite phase to ferrite phase is 23/27, so F=0.46.

The shear strain of the austenite phase and the shear strain of the ferrite phase are shown in Table 3.

Table 3 Shear strain and shear stress of two phases in shear zone

As can be seen from Figure 4, by comparing Groups 1-3 and 4-6, it can be found that the austenite phase strain increases as the cutting speed decreases, and the ferrite phase strain decreases as the cutting speed increases. As can be seen from Figure 5, by comparing Groups 1-3 and 4-6, the rheological stress of the austenite phase and the ferrite phase increases as the cutting speed increases.

3. Construction method of two-phase microhardness calculation model for dual-phase materials:

(1) The influence of tool rake angle and cutting amount on the microhardness of chip two phases

Table 4 Prediction of chip two-phase microhardness at different rake angles and different cutting parameters

Based on Table 4, Figure 6 shows the microhardness of austenite and ferrite phases at different cutting speeds with a feed rate of 0.3 mm/r.

It can be seen from Figure 6 that the microhardness of the two phases increases with the increasing cutting speed.

Based on Table 4, Figure 7 shows the microhardness of austenite and ferrite phases at different feed rates at a cutting speed of 106 m/min.

It can be seen from Figure 7 that under the same cutting speed, the microhardness of the two phases decreases with the increase of feed rate.

Based on Table 4, Figure 8 shows the influence of different rake angles on the shear strain in the shear zone.

As can be seen from Figure 8, the shear zone strain gradually decreases with the increase of the rake angle. The reason is that the larger the rake angle, the sharper the cutting edge, and the extrusion of the cutting layer gradually decreases. Therefore, the plastic deformation of the workpiece decreases with the increase of the tool rake angle.

As shown in Figure 9, the average shear strain rate in the shear zone gradually decreases with the increase of the tool rake angle, and the tool rake angle directly affects the magnitude of the shear strain rate.

It can be seen from Figure 10 that as the tool rake angle increases, the average temperature in the shear zone decreases.

It can be seen from Figure 11 that with the increase of the front angle, the microhardness of the austenite phase and the ferrite phase continues to increase.

(2) Two-phase microhardness prediction model considering tool rake angle and cutting amount

In the actual processing, it is difficult to extract the multi-physical field distribution of the shear zone during the cutting process. Therefore, starting from the tool rake angle and cutting amount, the two-phase microhardness is used as the independent variable and the two-phase microhardness is used as the dependent variable to establish a two-phase microhardness prediction model considering the tool rake angle and cutting amount.

An exponential empirical model of the microhardness of the austenite and ferrite phases of S32760 considering cutting factors is established and expressed as:

Where: HV ^* ₁ is the predicted value of austenite microhardness, HV ^* ₂ is the predicted value of ferrite microhardness; Z ₁ , Z ₂ are coefficients related to cutting conditions, etc.; p, q, m are correlation coefficients.

The regression equation of the multi-objective optimization model for obtaining the microhardness values of the austenite phase and the ferrite phase is:

HV ^* ₁ = 25.3581v ^0.1307 f ^-0.1632 α ^0.7030 (33)

HV ^* ₂ = 119.152v ^0.0372 f ^-0.0696 α ^0.3291 (34)

The validity of the obtained regression equation model was tested for significance, and the test structure obtained is shown in Table 5.

Table 5 Statistics for testing the two-phase microhardness regression model

The number of experiments was n=8, the number of independent variables was m=3, and the significance level of cutting speed, feed rate, and tool rake angle was selected as α=0.05. According to the query of the F distribution critical value table, F _0.05 (3,4)=6.59. Through variance analysis, it can be seen that the statistical F values corresponding to the regression equation of the two-phase microhardness are all greater than the critical value of 4.07, and the corresponding P values are all less than 0.05. Finally, it can be proved that the established regression equation of the two-phase microhardness is significant.

4. Duplex stainless steel processing method based on the consistency of two-phase hardness distribution:

(1) Optimization of rough machining process parameters

Combined with the stability of the process system in the actual processing, considering the large feed rate and low cutting speed in rough processing, the process parameter range suitable for the actual processing is selected as the constraint condition for the consistency of the microhardness of the two phases. The specific parameter range is as follows:

Table 6 Cutting parameters and tool rake angle optimized based on the consistency of two-phase microhardness

It can be seen from Figure 12 that when the microhardness difference between the two phases of the chip is the smallest, as the cutting speed increases, the feed rate continues to decrease. The possible reason is that the increase in cutting speed leads to an increase in shear strain in the shear zone, an increase in the average shear strain rate, and a continuous increase in the average temperature, while the increase in feed rate leads to a decrease in the shear strain in the shear zone, a decrease in the average shear strain rate, and a small temperature change, which can be ignored. At this time, the average strain rate and average temperature in the shear zone are increasing, while the shear strain is decreasing. The increase in strain rate causes the increase in rheological stress to be almost equal to the decrease in rheological stress caused by the decrease in strain and the increase in temperature. Therefore, as the cutting speed and feed rate increase, the ratio of the rheological stress of the two phases remains unchanged, while the microhardness is proportional to the rheological stress. Therefore, the microhardness of the two phases is not much different.

According to Table 6, the microhardness distribution of the two phases is consistent. Under the rough machining process parameters, the maximum difference between the two phases is 1.3596HV _0.05 , and the microhardness range of the two phases is between 379-390HV _0.05 . When the microhardness difference between the two phases is the smallest, the microhardness of the ferrite phase decreases with the increase of cutting speed, while the microhardness of the austenite phase has no obvious trend.

Table 7 Microhardness values of two phases

The two-phase microhardness prediction model predicts the two-phase microhardness under various cutting conditions in Table 6. It can be seen from Table 7 that the maximum difference in the two-phase microhardness of groups 1-6 does not exceed 16HV _0.05 , and the minimum is 13HV _0.05 . It can be seen that the two-phase microhardness empirical model considering cutting parameters and the cutting parameters optimized based on the consistency of the two-phase microhardness meet the standard of the consistency of the two-phase microhardness distribution.

(2) Optimization of finishing process parameters

Combined with the stability of the process system in the actual processing, considering that the finishing feed is small and the cutting speed is high, the process parameter range that fits the actual processing is selected as the constraint condition for the consistency of the microhardness of the two phases. The specific parameter range is as follows:

Table 8 shows the tool front and cutting parameters obtained after the consistency optimization of the microhardness distribution of the two phases. It can be seen from Table 8 that the microhardness distribution of the two phases is consistent. Under the finishing process parameters, the maximum difference between the two phases is 0.8892HV _0.05 , and the microhardness range of the two phases is between 352-359HV _0.05 .

Table 8 S32760 finishing process parameters

Table 9 Microhardness values of two phases

The two-phase microhardness prediction model predicts the two-phase microhardness under various cutting conditions in Table 8. It can be seen from Table 9 that the maximum difference in the two-phase microhardness of groups 1-3 does not exceed 18HV _0.05 , and the minimum is 16HV _0.05 . It can be seen that the two-phase microhardness empirical model considering cutting parameters and the cutting parameters optimized based on the consistency of the two-phase microhardness meet the standard of the consistency of the two-phase microhardness distribution.

The difference from the already disclosed technology is that the existing rheological stress solutions in the shear zone of cutting two-phase materials all combine the rheological stresses of the austenite phase and the ferrite phase, and do not solve the two-phase stresses of the two-phase materials separately, ignoring the competitive coupling phenomenon of the two-phase materials during the plastic deformation process. The present invention takes into account the multi-physical field distribution in the cutting process and the competitive coupling phenomenon of the two-phase materials, and models the two-phase stresses of the two-phase materials based on the stress mixing rule, and solves the two-phase stresses of the two-phase materials separately.

The existing duplex stainless steel processing technology does not consider the consistency of the microhardness distribution of the austenite phase and the ferrite phase in the chips, and only focuses on the modification of the tool rake angle or cutting amount. The present invention establishes a two-phase microhardness prediction model that considers the tool rake angle and cutting amount, and reveals the influence of the tool rake angle and cutting amount on the microhardness. Based on the established two-phase microhardness prediction model, the matching relationship between the tool rake angle and the cutting amount is obtained while fully considering the consistency of the two-phase hardness distribution, and the duplex stainless steel processing technology is optimized.

Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a duplex stainless steel processing technology based on the consistency of the hardness distribution of the two phases. The present invention is aimed at the problem of large difference in microhardness between the austenite phase and the ferrite phase in the shear zone of the S32760 cutting process. Combined with the shear deformation in the shear zone, the shear band strain, strain rate, temperature and other variables are extracted, and the two-phase stresses of the duplex material are modeled separately based on the stress mixing rule, and the two-phase stresses of the duplex material are solved. Through the relevant knowledge of material mechanics, the influence of the two-phase stress distribution of the duplex material on the microhardness of the two phases is revealed. Combined with the relationship between microhardness and plastic strain, a two-phase microhardness solution model considering the tool rake angle and cutting amount is established, which solves the problem of uncertain distribution of the two-phase microhardness.

The difference between the microhardness of the austenite phase and the microhardness of the ferrite phase is used as the objective function, and the minimum absolute value of the difference between the microhardness of the austenite phase and the microhardness of the ferrite phase is used as the constraint condition. The genetic algorithm is used to optimize and solve the model, and finally the tool rake angle and cutting amount with the optimal consistency of the microhardness of the two phases are obtained. The present invention has given, through algorithm verification, that during rough machining, the tool rake angle range is 3°-20°, the feed rate range is 0.5mm/r-1mm/r, and the cutting speed range is 100m/min-150m/min; during fine machining, the tool rake angle range is 3°-20°, the feed rate range is 0.1mm/r-0.3mm/r, and the cutting speed range is 200m/min-250m/min.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a logic block diagram of the present invention; Fig. 2 is a schematic diagram of the right-angle cutting shear zone of the present invention; Fig. 3 is a schematic diagram of the microhardness of the austenite phase and the ferrite phase at different feed rates at a cutting speed of 106 m/min of the present invention; Fig. 4 is a schematic diagram of the strain of the austenite phase and the ferrite phase of the present invention; Fig. 5 is a schematic diagram of the shear stress of the austenite phase and the ferrite phase of the present invention; Fig. 6 is a schematic diagram of the microhardness of the austenite phase and the ferrite phase at different cutting speeds at a feed rate of 0.3 mm/r of the present invention; Fig. 7 is a schematic diagram of the microhardness of the austenite phase and the ferrite phase at different feed rates at a cutting speed of 106 m/min of the present invention Figure; Figure 8 is a schematic diagram of the influence of different rake angles on the shear strain in the shear zone of the present invention; Figure 9 is a schematic diagram of the average shear strain rate in the shear zone of different tool rake angles when the cutting speed is 106m/min and the feed rate is 0.3mm/r; Figure 10 is a schematic diagram of the average temperature of the shear zone of different tool rake angles when the cutting speed is 106m/min and the feed rate is 0.3mm/r; Figure 11 is a schematic diagram of the microhardness of the austenite phase and the ferrite phase at different tool rake angles when the cutting speed is 106m/min and the feed rate is 0.3mm/r; Figure 12 is a schematic diagram of the microhardness of the austenite phase and the ferrite phase at different tool rake angles when the tool rake angle is 20° Fig. 13 is a schematic diagram of the raw data of the cutting force measured by the right-angle cutting test with a cutting speed of 214 mm/min and a feed rate of 0.3 mm according to the present invention; Fig. 14 is a schematic diagram of the filtered data of the present invention; Fig. 15 is a schematic diagram of the cutting force comparison of the experimental observation Fcx of the present invention with a feed rate of 0.3 mm/r; Fig. 16 is a schematic diagram of the cutting force comparison of the experimental observation Fcy of the present invention with a feed rate of 0.3 mm/r; Fig. 17 is a schematic diagram of the cutting force comparison of the experimental observation Fcx of the present invention with a feed rate of 0.4 mm/r; Fig. 18 is a schematic diagram of the cutting force comparison of the experimental observation Fcx of the present invention with a feed rate of 0. Figure 19 is a schematic diagram of the curve of the microhardness of the austenite phase and the ferrite phase of the right-angle cutting S32760 chips of the present invention changing with the cutting speed; Figure 20 is a schematic diagram of the thickness ratio of the second deformation zone at different cutting speeds of 0.3mm/r under the feed rate of the present invention; Figure 21 is a three-dimensional diagram of the diamond regular tetrahedron indenter of the present invention; Figure 22 is a schematic diagram of the microhardness test of the present invention; Figure 23 is a metallographic organization diagram of the S32760 matrix at 500 times of the present invention; Figure 24 is a metallographic diagram of the two-phase microhardness indentation of the chips of experimental group numbers 1, 2, and 3 of the present invention.

Detailed ways

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The present invention provides a duplex stainless steel processing process based on the consistency of two-phase hardness distribution as shown in Figures 1-24, comprising the following steps:

S1: Based on the stress mixing rule, a two-phase material two-phase stress solution model is established to distinguish and solve the two-phase stress of the two-phase material;

S2: Establish a two-phase microhardness calculation model considering the tool rake angle and cutting amount, and reveal the influence of tool rake angle and cutting amount on the two-phase microhardness;

S3: Based on the established two-phase microhardness solution model, the influence of tool rake angle and cutting amount on the two-phase microhardness distribution characteristics in the chip is revealed. Under the condition of consistent distribution of two-phase microhardness, the matching relationship between tool rake angle and cutting amount is obtained to optimize the processing technology of duplex stainless steel.

Implementation Example 1. Multi-physics field distribution extraction method in shear zone:

(1) Shear surface analysis

According to the geometric relationship of the shear zone and the equilibrium condition of the tool-chip contact zone, the cutting force components and the chip thickness t ₂ can be obtained:

F _t = _FR sin(λ-α) (1)

F _f = _FR sinλ (2)

_Fn = _FR cos(λ) (3)

F _N = _FR sinθ (5)

Where: α is the tool rake angle; is the angle between the shear plane AB and the cutting speed direction, i.e., the shear angle; λ is the friction angle; _t1 is the undeformed chip thickness; w is the cutting width; _Fc and _Ft are the components of the chip force in the cutting direction and perpendicular to the cutting direction; _Ff is the friction force at the tool-chip interface; _Fs is the cutting force on the shear plane; _FN and _Fn are the normal forces at the shear plane and the tool-chip interface, respectively. The resultant force of the normal force _FN at the shear plane and the cutting force _Fs at the shear plane and the resultant force of the normal force _Fn at the tool-chip interface and the friction force _Ff at the tool-chip interface are a pair of balanced forces; the chip forming force _FR is decomposed into _Fc and _Ft along the cutting direction and perpendicular to the cutting direction. θ is the angle between _FR and AB; _σAB represents the average flow stress on the shear plane.

The velocity and displacement increments of any point from A to B along the cutting direction and perpendicular to the cutting direction are:

Where: V is the cutting speed; _ΔS1 is the vertical height between EF and CD.

In Figure 2, the velocity component of any particle in the first deformation zone in the shear zone and the average shear strain rate in the shear zone have the following relationship:

Substituting equations (7) and (8) into equation (9), we can obtain the expression of average shear strain rate:

Calculate the shear angle by iteration Determine the shear angle based on the equilibrium condition of the shear zone/> The average equivalent strain and equivalent strain rate of any particle at the shear surface AB can be expressed by the following formula:

Assuming that shear deformation occurs on the shear surface, the workpiece becomes chips through shear deformation. The workpiece material that originally moves with the tool quickly passes through the shear zone and becomes chips due to the increase in cutting speed. This sudden change in speed is called shear velocity. According to the velocity vector relationship in Figure 2, the chip material flow velocity V _c and the material flow velocity V _s on the shear surface can be obtained:

The flow stress is related to the temperature, and the shear stress can be calculated based on the flow stress. Therefore, in order to obtain the shear stress, the temperature at AB must be iteratively calculated to a steady state. Based on the Oxley cutting theory, the average temperature of the shear zone is:

Where: _Tr is the workpiece temperature, η is the average temperature coefficient, which is taken as 0.9 in the analysis; ρ is the material density; _Cw is the specific heat capacity, where β is the ratio of the shear deformation heat conduction to the workpiece material in the first deformation zone of the shear zone, calculated as follows:

Where: Kw _is the thermal conductivity coefficient.

Due to the plastic deformation of the workpiece, there is a high strain, high strain rate and high temperature cutting environment in the shear zone. The S32760 two-phase constitutive model is used to predict the flow stress in the shear zone:

The angle between _Fn and _Fr in the shear zone is the friction angle, which can be Calculation. According to Oxley theory, we can get/> According to the iterative calculation of the shear angle/> The angle θ can be obtained.

The strain rate constant _C0 in the first deformation zone is based on the material work hardening mechanism and takes into account the influence of material strain. Its expression is:

Where: C _Oxley is the aspect ratio of the shear band in the first deformation zone; A _JC , B _JC and n _JC are the JC constitutive parameters, respectively.

In the Oxley right-angle cutting model considering the coupling of cutting heat and cutting force, when iteratively calculating the shear zone temperature, it is necessary to assume the rheological stress at the initial temperature of the shear zone, calculate the component force in the shear zone based on the obtained rheological stress, and then use the shear zone equilibrium temperature formula to update the shear zone temperature. Repeat this process until the difference between the updated temperature and the shear zone temperature is less than 0.1 degrees Celsius, that is, the temperature at this time is considered to be the shear zone temperature. Then, the rheological stress at the shear band AB is calculated based on the output shear band temperature, the equivalent strain of the shear band, and the shear band strain rate. Finally, _FR is calculated, and other component forces are analyzed based on the geometric relationship of the equally divided shear zone.

(2) Tool-chip interface analysis

Under the extrusion and friction of the rake face, the chip near the rake face is sheared again, the grain is elongated, and fiberized along the rake face. The thickness of the fiberized area is the thickness of the second deformation zone (ΔS ₂ ), as shown in Figure 2. ΔS ₂ = δt ₂ , δ is the ratio of the thickness of the second deformation zone to the thickness of the chip deformed after cutting. It can be seen that the equivalent strain and equivalent strain rate of the tool-chip interface are:

Where: _htc is the tool-chip contact length, which can be calculated using the moment balance formula of the shear plane:

The average temperature _Tint of the tool-chip interface is expressed as:

_Tint = _Tr + _ΔTsz + _ψΔTM (22)

Where: ψ is the correction coefficient, which is taken as 0.6; _ΔTM is the maximum temperature rise in the chip; _ΔTC is the average temperature rise in the chip; _ΔTsz is the temperature rise in the first deformation zone.

The characteristics of the rheological stress at the shear band are used to predict the rheological stress at the tool-chip contact interface using the S32760 two-phase constitutive model:

The right-angle cutting experiment is as follows:

In order to verify the right-angle cutting model, a right-angle cutting test platform was built, and the reliability of the model was analyzed by observing the cutting force of right-angle cutting of S32760 duplex stainless steel.

Right angle cutting test platform, bar size is Use a three-jaw fixture to clamp the bar, center it, and rough turn it once with a feed rate of 1mm/r to smooth the surface. Then use a grooving cutter with a tool width of 3mm to groove the bar. The groove depth is 3mm, the groove width is 3mm, and the interval is 2mm. A 2mm wide annular convex surface is retained between each groove. According to the test parameters in the table below, a right-angle cutting experiment is performed on each annular convex surface. Use a C6136HK lathe for turning the outer circle and grooving operations.

The force measuring instrument used for right-angle cutting is KISTLER piezoelectric dynamometer 9139AA, which is installed on the tool holder of the CNC machine tool. The dynamometer can measure the cutting force in three directions during the cutting process. To ensure the accuracy of the measurement results, each group of experiments was repeated three times and the average was taken. In order to verify the accuracy of the cutting force prediction model, the cutting test parameters are shown in Table 10.

Table 10 Cutting parameters for right angle cutting test

The parameters required for the prediction model of the shear zone divided equally by right-angle cutting of S32760 are shown in Table 11.

Table 11 S32760 material parameters of cutting model

According to the right-angle cutting equally divided shear zone model, the cutting parameters in Table 11 and the S32760 material properties in Table 11 are input, and the predicted cutting force values are shown in Table 12. The cutting forces measured by the right-angle cutting test are shown in Table 12. Figure 13 shows the original cutting force data measured by the right-angle cutting test with a cutting speed of 214 mm/min and a feed rate of 0.3 mm, and Figure 14 shows the filtered data.

Table 12 Comparison of experimental cutting force and model predicted cutting force

It can also be seen from Figures 15-18 that the right-angle cutting equally divided shear zone model predicts the cutting force more accurately. When the feed rate is 0.3mm/r, the maximum prediction error of the cutting force F _cx is 2.7%, the minimum prediction error is 0.7%, and the maximum prediction error of the cutting force F _cy is 10.7%, and the minimum prediction error is 1.7%. When the feed rate is 0.4mm/r, the maximum prediction error of the cutting force F _cx is 4.4%, the minimum prediction error is 3.9%, and the maximum prediction error of the cutting force F _cy is 6.0%, and the minimum prediction error is 0.6%. Compared with the experimental cutting force F _cx , the average error of the cutting force prediction is 2.9%, and the average error of the cutting force F _cy prediction is 4.6%. It can be seen from Figures 15-18 that compared with the experimental data, the error is small and the cutting force prediction is more accurate.

By comparing Figures 15-18, it can be seen that the increase in cutting speed and feed rate will increase the cutting force, but the effect of feed rate on cutting force is more obvious.

(3) Multi-physics field extraction process:

Due to the shear angle of the shear zone The shear zone strain rate coefficient C _Oxley and the ratio of the second deformation zone thickness to the chip thickness δ vary with cutting conditions, material properties and tool rake angle, so three variable ranges are set as the ranges of the three iterations, namely δ∈[0.005,0.2], C _Oxley ∈[2,10],/> According to Oxley cutting theory, the calculation will terminate when the output meets three equilibrium conditions: stress balance at the tool-cutting interface, where the tangential stress at the tool-cutting interface (τ _int ) is equal to the rheological stress in the chip (σ _chip ); second, stress balance at the tool tip, that is, the normal stress at the tool tip interface (σ _N ) calculated reasonably is equal to the normal stress (σ′ _N ) calculated using the tool tip stress boundary condition; third, the principle of minimum cutting force (F _c ). Therefore, the three equilibrium conditions of Oxley theory are used as the basis for the judgment of the iteration of the three variables. Therefore, it is necessary to calculate the tangential stress at the tool-cutting interface (τ _int ), the normal stress at the tool tip interface (σ _N ), the normal stress (σ′ _N ) calculated using the tool tip stress boundary condition, and the cutting force (F _c ).

F _c can be calculated based on the geometric conditions of the shear zone:

F _c = _FR cos(λ-α) (26)

The normal stress σ′ _N at point B in Figure 2 can be obtained by combining the average flow stress of the shear surface:

Assuming that the tool-chip interface stress is uniformly distributed, the expressions of tool-chip interface stress τ _int and stress σ _N are obtained as follows:

The absolute value of the difference between the obtained tangential stress at the tool-cutting interface (τ _int ) and the flow stress at the tool-chip interface (σ _chip ) is used as the basis for judgment. Take the value where the two are closest. At this time, according to the obtained shear angle/> After repeatedly calculating various parameters in the shear zone, the normal stress of the tool tip interface (σ _N ) and the normal stress calculated by the tool tip stress boundary condition (σ′ _N ) are solved, and the absolute value of the difference between the two is used as the basis for judging C _Oxley , and C _Oxley takes the closest value of the two. Continue to repeatedly calculate various parameters in the shear zone, and then compare the cutting force F _c , and determine the δ value when F _c is the smallest. In this way, the chip force model under different cutting conditions, material properties and tool geometry conditions is established, and the specific values of the three variables can be determined.

(4) Extraction of multi-physical field distribution in shear zone:

Extract the shear angle based on the model of dividing the shear zone into equal parts by right-angle cutting The first deformation zone aspect ratio C _Oxley , the second deformation zone thickness to cutting thickness ratio δ , the shear zone temperature T _AB , the shear zone strain ε _AB , the shear zone strain rate/> Shear stress σ _AB . Table 2 shows the multi-physics field distribution in the shear zone.

Implementation Example 2. Method for solving two-phase stress of dual-phase material:

During the cutting process of S32760, the two phases in the shear zone undergo severe plastic deformation. The difference in the mechanical properties of the two phases and their different evolution forms lead to a large difference in the degree of work hardening between the two phases. Therefore, by analyzing the influence of cutting parameters and the microhardness of the two phases, the difference in the dynamic mechanical behavior of the two phases during the cutting process is revealed.

When the feed rate is 0.3 mm/r and the cutting speed is different, the microhardness of the austenite phase and ferrite phase of the chip and the degree of hardening are shown in Table 13.

Table 13 Microhardness of two phases in shear zone and thickness ratio of second deformation zone at different cutting speeds

According to the comparison of test data, Figure 19 shows the curve of the microhardness of the austenite phase and ferrite phase of the right-angle cutting S32760 chips as a function of cutting speed.

Table 14 Work hardening degree of two phases in shear zone at different cutting speeds

According to Table 14, Figure 20 can be obtained, which shows the variation of the thickness ratio of the second deformation zone at different cutting speeds with a feed rate of 0.3 mm/r.

Through the microhardness measurement of the two phases of the matrix, it can be seen that the ferrite phase of the matrix has a higher microhardness, which is consistent with the characteristics of the higher hardness of the ferrite phase in S32760. The two phases after cutting undergo plastic deformation, and the degree of work hardening is very different.

It can be seen from Figure 3 that the microhardness of the austenite phase and ferrite phase of the chip decreases with the increase of feed rate. It can be seen from Table 2 that the work hardening degree of the two phases also decreases with the increase of feed rate. With the increase of feed rate, the shear strain decreases, the average shear strain rate decreases, the hardening degree decreases, and the temperature is basically unaffected, so the thermal softening effect dominated by temperature remains basically unchanged. At this time, with the increase of feed rate, the work hardening effect of the two phases decreases, while the thermal softening effect dominated by temperature remains unchanged, so the work hardening degree of the two phases in the shear zone decreases.

During the cutting process, S32760 is subjected to external forces such as tool extrusion and friction. Due to the coupling of force and heat, the rheological stress of the workpiece material in the shear zone generally has strain hardening effect, strain rate strengthening effect and thermal softening effect. The strain hardening effect refers to the increase of the rheological stress of the material with the increase of strain; the strain rate strengthening effect refers to the increase of the rheological stress of the material with the increase of strain rate; the thermal softening effect characterizes that the rheological stress of the material decreases with the increase of temperature. The rheological stress is proportional to the microhardness of the material. Therefore, the analysis of the two-phase rheological stress in the shear zone of the S32760 chip needs to consider the relationship between the temperature, strain and strain rate in the shear zone.

Based on material mechanics, the Vickers microhardness value is proportional to the flow stress, so:

HV＝Cσ (28)

Where: C is a constant.

Based on the above formula, it can be seen that the rheological stress of the two phases is required to predict the microhardness of the two phases. The rheological stress of the chips can be approximately regarded as the shear stress.

The prerequisite of the stress mixing law is to assume that the strains of the two phases are the same during the deformation of the material. However, whether it is a quasi-static tension or dynamic compression experiment, the huge difference in the mechanical properties of the two phases leads to a competitive coupling effect between the two phases during the plastic deformation process. Therefore, the general treatment method for multiphase materials is adopted, that is, on the basis of retaining the two-phase stress mixing law, the two-phase strains are also expressed in the form of a mixing law.

σ(ε)＝F·σ ₁ (ε ₁ )+(1-F)·σ ₂ (ε ₂ ) (29)

ε＝F·ε ₁ +(1-F)·ε ₂ (30)

Where: ε ₁ and ε ₂ are the strain values of the austenite phase and the ferrite phase, respectively.

At this time, it is necessary to consider the ratio of the two phases in the S32760 matrix, so the S32760 matrix is observed using a SEM scanning electron microscope to analyze the ratio of the two phases.

The volume fraction ratio of austenite phase to ferrite phase is 23/27, so F=0.46.

The shear strain of the austenite phase and the shear strain of the ferrite phase are shown in Table 3.

As can be seen from Figure 4, by comparing Groups 1-3 and 4-6, it can be found that the austenite phase strain increases as the cutting speed decreases, and the ferrite phase strain decreases as the cutting speed increases. As can be seen from Figure 5, by comparing Groups 1-3 and 4-6, the rheological stress of the austenite phase and the ferrite phase increases as the cutting speed increases.

Implementation Example 3. Construction Method of Microhardness Calculation Model of Dual-Phase Material

The S32760 chip microhardness test experiment is as follows:

The chips of right-angle cutting S32760 were collected in groups according to the test number, and the chips of 6 groups of right-angle cutting tests were tested respectively. The cutting amount of the chips is shown in Table 14. Since the chip size is small, it is necessary to keep the shape unchanged and protect the surface during the experiment, so the chips are embedded with resin for easy handling. In order to ensure that the embedded specimen is free of pollution, the first step is to clean the chips so that the chips and resin are well bonded, and to prevent bubbles from affecting the microhardness test indenter point. Use sandpaper No. 80, 320, 600, 1000, 1200, 1500, and 2000 to grind the resin embedded chips from coarse to fine. Each sandpaper is ground at least two crosses back and forth. For sandpaper above No. 1000, 4-5 crosses back and forth, and each back and forth requires that the vertical wear marks cannot be seen by the naked eye. Spray an appropriate amount of polishing agent on the polishing cloth, and hold the ground embedded specimen in the cross direction for polishing. During the polishing process, add an appropriate amount of water to prevent friction overheating, and also add an appropriate amount of polishing agent. After polishing, replace the polishing cloth with a new one and perform water polishing to clean the polishing agent. Use heated alcohol in an ultrasonic cleaner to clean the polished sample.

Table 15 Cutting parameters for testing the microhardness of S32760 chips

Since the two phases of duplex stainless steel cannot be seen under the metallographic microscope after polishing, corrosion and staining are required. According to the relevant knowledge of materials science, 20ml of distilled water, 20ml of hydrochloric acid and 4g of hydrochloric acid are used to prepare the corrosion solution. The polished sample is placed in the solution for etching for 30s at room temperature, and then the sample surface is cleaned to prepare for the subsequent microhardness experiment.

The basic principle of the micro-Vickers hardness test is to use a diamond regular tetrahedron indenter with an angle of 136° between two opposite faces (an angle of 148°6'42” between two opposite edges). Figure 21 is a three-dimensional diagram of the diamond regular tetrahedron indenter. Figure 22 is a schematic diagram of the micro-hardness test. The indenter is pressed into the sample surface under a test force of 50N. After holding for 10 seconds, the test force is removed and the diagonal length of the indentation is measured. The quotient obtained by the test cone surface area is the Vickers hardness HV value (kgf/mm ² ).

The microhardness of the austenite phase and the ferrite phase is measured in the shear zone in the chip. Figure 24 shows the measured chip area and the measurement position. This area is the first deformation zone in the shear zone. According to the analytical model of the right-angle cutting equally divided shear zone, the strain, strain rate and temperature of the first deformation zone in the shear zone are extracted, and the mapping relationship between the multi-physical field and the microhardness of the two phases is constructed.

(1) The influence of tool rake angle and cutting amount on the microhardness of chip two phases

Table 4 Prediction of chip two-phase microhardness at different rake angles and different cutting parameters

It can be seen from Figure 6 that the microhardness of the two phases increases with the increasing cutting speed.

It can be seen from Figure 7 that under the same cutting speed, the microhardness of the two phases decreases with the increase of feed rate.

As can be seen from Figure 8, the shear zone strain gradually decreases with the increase of the rake angle. The reason is that the larger the rake angle, the sharper the cutting edge, and the extrusion of the cutting layer gradually decreases. Therefore, the plastic deformation of the workpiece decreases with the increase of the tool rake angle.

It can be seen from Figure 9 that the average shear strain rate in the shear zone gradually decreases with the increase of the tool rake angle, and the tool rake angle directly affects the magnitude of the shear strain rate.

It can be seen from Figure 10 that as the tool rake angle increases, the average temperature in the shear zone decreases. Since the extrusion on the cutting layer is reduced, the deformation of the workpiece is reduced, resulting in a decrease in the heat generated by plastic deformation, so the average temperature in the shear zone decreases.

It can be seen from Figure 11 that with the increase of the front angle, the microhardness of the austenite phase and the ferrite phase continues to increase.

(2) Two-phase microhardness prediction model considering tool rake angle and cutting amount

In the actual processing, it is difficult to extract the multi-physical field distribution of the shear zone during the cutting process. Therefore, starting from the tool rake angle and cutting amount, the two-phase microhardness is used as the independent variable and the two-phase microhardness is used as the dependent variable to establish a two-phase microhardness prediction model considering the tool rake angle and cutting amount.

An exponential empirical model of the microhardness of the austenite and ferrite phases of S32760 considering cutting factors is established and expressed as:

Where: HV ^* ₁ is the predicted value of austenite microhardness, HV ^* ₂ is the predicted value of ferrite microhardness; Z ₁ , Z ₂ are coefficients related to cutting conditions, etc.; p, q, m are correlation coefficients.

The regression equation of the multi-objective optimization model for obtaining the microhardness values of the austenite phase and the ferrite phase is:

HV ^* ₁ = 25.3581v ^0.1307 f ^-0.1632 α ^0.7030 (33)

HV ^* ₂ = 119.152v ^0.0372 f ^-0.0696 α ^0.3291 (34)

The validity of the obtained regression equation model was tested for significance, and the test structure obtained is shown in Table 5.

The number of experiments was n=8, the number of independent variables was m=3, and the significance level of cutting speed, feed rate, and tool rake angle was selected as α=0.05. According to the F distribution critical value table, F _0.05 (3,4)=6.59. Through variance analysis, it can be seen that the statistical F values corresponding to the regression equation of the two-phase microhardness are all greater than the critical value of 4.07, and the corresponding P values are all less than 0.05. Finally, it can be proved that the established regression equation of the two-phase microhardness is significant.

Implementation Example 4. Duplex stainless steel processing method based on the consistency of two-phase hardness:

(1) Optimization of rough machining process parameters

By analyzing the influencing factors of the two-phase microhardness prediction model, the variation law of the microhardness values of the austenite phase and the ferrite phase as a function of the tool rake angle and the cutting amount was obtained.

Combined with the stability of the process system in the actual processing, considering the large feed rate and low cutting speed in rough processing, the process parameter range suitable for actual processing is selected as the constraint condition for the consistency of the microhardness of the two phases. The specific parameter range is as follows:

According to the two-phase microhardness prediction model established above, the absolute value of the difference between the two-phase microhardness is used as the multi-objective optimization function, and the optimization function of the cutting factor is as follows:

Using genetic algorithm for optimization, the constraints and optimization objective function are written into a program as follows:

Formula (37) is used as the criterion for determining the consistency of the microhardness distribution of the two phases, and is the determination coefficient of the consistency of the microhardness distribution of the two phases. Table 6 shows the tool rake angle and cutting amount obtained after the consistency optimization of the microhardness distribution of the two phases.

It can be seen from Figure 12 that when the microhardness difference between the two phases of the chip is the smallest, as the cutting speed increases, the feed rate continues to decrease. The possible reason is that the increase in cutting speed leads to an increase in shear strain in the shear zone, an increase in the average shear strain rate, and a continuous increase in the average temperature, while the increase in feed rate leads to a decrease in the shear strain in the shear zone, a decrease in the average shear strain rate, and a small temperature change, which can be ignored. At this time, the average strain rate and average temperature in the shear zone are increasing, while the shear strain is decreasing. The increase in strain rate causes the increase in rheological stress to be almost equal to the decrease in rheological stress caused by the decrease in strain and the increase in temperature. Therefore, as the cutting speed and feed rate increase, the ratio of the rheological stress of the two phases remains unchanged, while the microhardness is proportional to the rheological stress. Therefore, the microhardness of the two phases is not much different.

According to Table 6, the microhardness distribution of the two phases is consistent. Under the rough machining process parameters, the maximum difference between the two phases is 1.3596HV _0.05 , and the microhardness range of the two phases is between 379-390HV _0.05 . When the microhardness difference between the two phases is the smallest, the microhardness of the ferrite phase decreases with the increase of cutting speed, while the microhardness of the austenite phase has no obvious trend.

The two-phase microhardness prediction model predicts the two-phase microhardness under various cutting conditions in Table 6. It can be seen from Table 7 that the maximum difference in the two-phase microhardness of groups 1-6 does not exceed 16HV _0.05 , and the minimum is 13HV _0.05 . It can be seen that the two-phase microhardness empirical model considering cutting parameters and the cutting parameters optimized based on the consistency of the two-phase microhardness meet the standard of the consistency of the two-phase microhardness distribution.

(2) Optimization of finishing process parameters

Combined with the stability of the process system in the actual processing, considering that the finishing feed is small and the cutting speed is high, the process parameter range that fits the actual processing is selected as the constraint condition for the consistency of the microhardness of the two phases. The specific parameter range is as follows:

The optimization process is the same as rough machining and will not be described here.

Table 8 shows the tool rake angle and cutting amount obtained after the consistency optimization of the two-phase microhardness distribution. It can be seen from Table 8 that the microhardness distribution of the two phases is consistent. Under the finishing process parameters, the maximum difference between the two phases is 0.8892HV _0.05 , and the microhardness range of the two phases is between 352-359HV _0.05 .

The two-phase microhardness prediction model predicts the two-phase microhardness under various cutting conditions in Table 8. It can be seen from Table 9 that the maximum difference in the two-phase microhardness of groups 1-3 does not exceed 18HV _0.05 , and the minimum is 16HV _0.05 . It can be seen that the two-phase microhardness empirical model considering cutting parameters and the cutting parameters optimized based on the consistency of the two-phase microhardness meet the standard of the consistency of the two-phase microhardness distribution.

In summary, compared with the prior art, the present invention aims at the problem of large difference in microhardness between austenite phase and ferrite phase in the shear zone of S32760 cutting process. Combined with the shear deformation in the shear zone, the shear band strain, strain rate, temperature and other variables are extracted, and the two-phase stress of the two-phase material is modeled based on the stress mixing rule, and the two-phase stress of the two-phase material is solved. Through the relevant knowledge of material mechanics, the influence of the two-phase stress distribution of the two-phase material on the microhardness of the two phases is revealed. Combined with the relationship between microhardness and plastic strain, a two-phase microhardness solution model considering the tool rake angle and cutting amount is established, which solves the problem of uncertain distribution of the two-phase microhardness.

The difference between the microhardness of the austenite phase and the microhardness of the ferrite phase is used as the objective function, and the minimum absolute value of the difference between the microhardness of the austenite phase and the microhardness of the ferrite phase is used as the constraint condition. The genetic algorithm is used to optimize and solve the model, and finally the tool rake angle and cutting amount with the optimal consistency of the microhardness of the two phases are obtained. The algorithm of the present invention has been verified that during rough machining, the tool rake angle range is 3°-20°, the feed rate range is 0.5mm/r-1mm/r, and the cutting speed range is 100m/min-150m/min; during fine machining, the tool rake angle range is 3°-20°, the feed rate range is 0.1mm/r-0.3mm/r, and the cutting speed range is 200m/min-250m/min.

Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (2)

1. A duplex stainless steel processing technology based on the stress mixing rule, characterized in that it includes the following steps: S1: Based on the stress mixing rule, a two-phase material two-phase stress solution model is established to distinguish and solve the two-phase stress of the two-phase material; Method for extracting multi-physical field distribution in shear zone: by analyzing the moment balance relationship in shear zone, combining the S32760 two-phase constitutive model to predict cutting force, and solving cutting force by cutting parameters; shear surface analysis; tool-chip interface analysis; multi-physical field extraction; extraction of multi-physical field distribution in shear zone; Solution method for two-phase stress of two-phase material: During the cutting process of S32760, the two phases in the shear zone undergo severe plastic deformation, and the difference in the mechanical properties of the two phases and the different evolution forms lead to different degrees of work hardening. Therefore, by analyzing the influence of cutting parameters and the microhardness of the two phases, the difference in dynamic mechanical behavior of the two phases during the cutting process is revealed; During the cutting process, S32760 is subjected to external forces such as tool extrusion and friction. Under the action of mechanical and thermal coupling, the rheological stress of the workpiece material in the shear zone generally has strain hardening effect, strain rate strengthening effect and thermal softening effect. The rheological stress is proportional to the microhardness of the material. Based on material mechanics, the Vickers microhardness value is proportional to the flow stress, so: HV＝Cσ Where: C is a constant; Based on the above formula, it can be seen that the rheological stress of the two phases is required to predict the microhardness of the two phases. The rheological stress of the chips can be approximately regarded as the shear stress; The prerequisite of the stress mixing law is to assume that the strains of the two phases are the same during the deformation of the material. Due to the huge difference in the mechanical properties of the two phases, the two phases compete with each other during the plastic deformation process. Therefore, the general treatment method for multiphase materials is adopted, that is, on the basis of retaining the two-phase stress mixing law, the two-phase strains are also expressed in the form of a mixing law: σ(ε)＝F·σ ₁ (ε ₁ )+(1-F)·σ ₂ (ε ₂ ) ε＝F·ε ₁ +(1-F)·ε ₂ Where: ε ₁ and ε ₂ are the strain values of austenite phase and ferrite phase respectively; S2: Establish a two-phase microhardness calculation model considering the tool rake angle and cutting amount, and reveal the influence of tool rake angle and cutting amount on the two-phase microhardness; S3: Based on the established two-phase microhardness calculation model, the influence of tool rake angle and cutting amount on the two-phase microhardness distribution characteristics in the chip is revealed. Under the condition that the two-phase microhardness distribution is consistent, the matching relationship between tool rake angle and cutting amount is obtained to optimize the processing technology of duplex stainless steel. Method for constructing a two-phase microhardness calculation model for dual-phase materials: The influence of tool rake angle and cutting amount on the microhardness of the two phases of chips: With the continuous increase of cutting speed, the microhardness of the two phases continues to increase; Under the same cutting speed condition, the microhardness of the two phases decreases with the increase of feed rate; The strain in the shear zone decreases gradually with the increase of the rake angle. The reason is that the larger the rake angle, the sharper the cutting edge, and the extrusion of the cutting layer gradually decreases. Therefore, the plastic deformation of the workpiece decreases with the increase of the tool rake angle. The average shear strain rate in the shear zone decreases gradually with the increase of the tool rake angle, and the tool rake angle directly affects the magnitude of the shear strain rate; As the tool rake angle increases, the average temperature in the shear zone decreases; As the rake angle increases, the microhardness of the austenite phase and the ferrite phase increases; Two-phase microhardness calculation model considering tool rake angle and cutting amount: Starting from the tool rake angle and cutting amount, taking them as independent variables and the two-phase microhardness as dependent variables, a two-phase microhardness calculation model considering tool rake angle and cutting amount is established. The exponential empirical model of the microhardness of the S32760 austenite phase and ferrite phase considering cutting factors is expressed as: Where: HV* ₁ is the predicted value of austenite microhardness, HV* ₂ is the predicted value of ferrite microhardness; Z ₁ , Z ₂ are coefficients related to cutting conditions, etc.; p, q, m are correlation coefficients. 2. Application of the duplex stainless steel processing technology based on the stress mixing rule according to claim 1 in duplex stainless steel processing.