CN114841440B - Optimal machining parameters method based on high pressure cooling cutting tool durability prediction - Google Patents
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- 238000005520 cutting process Methods 0.000 title claims abstract description 107
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- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000003754 machining Methods 0.000 title claims abstract description 25
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- 238000002474 experimental method Methods 0.000 claims abstract description 11
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- 238000012545 processing Methods 0.000 claims description 24
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- 239000000463 material Substances 0.000 claims description 4
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- GJNGXPDXRVXSEH-UHFFFAOYSA-N 4-chlorobenzonitrile Chemical compound ClC1=CC=C(C#N)C=C1 GJNGXPDXRVXSEH-UHFFFAOYSA-N 0.000 abstract description 17
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Abstract
一种基于高压冷却切削刀具耐用度预测的优选加工参数方法，包括：以刀具在高压冷却切削时的加工参数中的冷却压力,以及三个切削用量：切削速度、进给量、切削深度为因素，并以刀具耐用度为响应，进行四因素n水平正交切削试验形成4*n组数据；根据刀具耐用度随切削用量的变化规律，得到高压冷却下刀具耐用度的计算公式；根据公式将试验得到的4*n组数据进行回归分析运算后，得到高压冷却下刀具耐用度的经验预测模型；并根据单因素实验法，分析并得到单因素对刀具耐用度的影响结果，从而确定最优的加工参数。本发明实现了采用刀具耐用度预测模型优选加工参数，可对高温合金加工工艺进行预测优化和建议，以及为高压冷却下PCBN刀具切削研究提供了理论支撑。
A method for optimizing machining parameters based on the prediction of tool durability under high-pressure cooling includes: taking the cooling pressure in the machining parameters of the tool during high-pressure cooling cutting, and three cutting parameters: cutting speed, feed rate, and cutting depth as factors, and taking tool durability as a response, a four-factor n-level orthogonal cutting test is performed to form 4*n groups of data; according to the variation law of tool durability with cutting parameters, a calculation formula for tool durability under high-pressure cooling is obtained; after performing regression analysis on the 4*n groups of data obtained from the test according to the formula, an empirical prediction model for tool durability under high-pressure cooling is obtained; and according to the single-factor experimental method, the influence of a single factor on tool durability is analyzed and obtained, thereby determining the optimal machining parameters. The present invention realizes the optimization of machining parameters using a tool durability prediction model, can predict, optimize and suggest high-temperature alloy machining processes, and provides theoretical support for PCBN tool cutting research under high-pressure cooling.
Description
Technical Field
The invention relates to the technical field of cutter durability test, in particular to a method for optimizing processing parameters based on high-pressure cooling cutting cutter durability prediction.
Background
As the most basic unit in machining, the durability of a tool is one of the important factors in the field of machine fabrication, which affects the cutting efficiency and the surface quality of a workpiece to some extent. In recent years, nickel-based superalloy is widely applied to the fields of aerospace, ships, nuclear power and the like, and can still keep good tissue stability under the high-temperature environment condition of 600-1200 ℃, however, the superalloy is a typical difficult-to-machine material, and has the defects of large cutting force, high cutting temperature, serious plastic deformation and work hardening during the cutting process, and aggravates cutter abrasion. When the cutter is worn to a certain degree, the cutter is not used continuously, and the cutter needs to be regrind. If the durability of the cutter is too low, the regrinding times will be increased, so that the production efficiency is reduced, the frequent cutter changing times will also lead to the reduction of the surface processing quality of the part, and the processing parameters such as cooling pressure, cutting dosage and the like are too large or too small, which will have important influence on the durability of the cutter.
Therefore, a proper mathematical prediction model of the tool durability needs to be established, and the machining parameters of the model are reasonably predicted, so that an optimal machining parameter result is obtained.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a method for optimizing machining parameters based on the prediction of the durability of a high-pressure cooling cutting tool, which realizes the optimization and suggestion of the machining parameters by adopting a tool durability prediction model, can perform prediction optimization and suggestion on a high-temperature alloy machining process, provides theoretical support for PCBN tool cutting research under high-pressure cooling, and simultaneously provides effective reference for other similar cutting performance comparison research and tool wear research.
To achieve the above object, the present invention provides a method for predicting preferred machining parameters based on durability of a high-pressure cooled cutting tool, comprising the steps of:
1) The method comprises the steps of taking the cooling pressure P in the processing parameters of a cutter during high-pressure cooling cutting and three cutting dosages, namely cutting speed v c, feeding quantity f and cutting depth a p, as factors, wherein each factor corresponds to n levels, n is greater than 1, and taking the cutter durability as a response, carrying out a four-factor n-level orthogonal cutting test, selecting an L 16(4n) orthogonal test table, taking a cutter face abrasion value larger than a preset threshold value as a cutter grinding standard in the orthogonal cutting test, and measuring the cutting time required by the cutter to reach the cutter grinding standard so as to form 4*n groups of data;
2) In the cutting process, a generalized Taylor formula is used according to the rule of the variation of the cutter durability along with the cutting dosage Performing approximate description, and obtaining a calculation formula of the tool durability under high-pressure cooling under the machining condition of adding high-pressure cooling:
Wherein, C T is the coefficient of the durability of the cutter, x T、yT、zT、wT is the index of the cutting speed v c, the feed f, the cutting depth a p and the cooling pressure P respectively;
3) Adopting a multiple linear regression equation to analyze and solve a calculation formula of the tool durability under high-pressure cooling, and taking natural logarithms from two sides of the formula (1) to obtain:
lnT=lnCT-xTlnvc-yTlnf-zTlnap-wTlnP
：y＝lnT、x1＝lnvc、x2＝lnf、x4＝lnp、k0＝lnCT、k1＝xT、k2＝yT、k3＝zT、k4＝wT, can then be converted into:
y＝k0-k1x1-k2x2-k3x3-k4x4 (2)
And substituting the 4*n groups of data results into a formula (2) respectively to obtain the following multiple linear regression equation:
y1＝k0-k1x11-k2x21-k3x31-k4x41
y2＝k0-k1x12-k2x22-k3x32-k4x42
......
y15＝k0-k1x115-k2x215-k3x315-k4x415
y16＝k0-k1x116-k2x216-k3x316-k4x416
And (3) making:
then it can be converted into a matrix:
Y=XK
finally, the method is obtained by using a least square method:
K=(XTX)-1XTY (3)
4) Carrying out regression analysis operation on 4*n groups of data obtained by the test according to a formula (3), obtaining a k 0、k1、k2、k3、k4 value, and enabling: x T＝k1、yT＝k2、zT＝k3、wT＝k4, the empirical prediction model for cutter durability under high pressure cooling is obtained as follows:
5) According to a single factor experiment method, under the condition that all other three factors are fixed, a cutter durability curve graph is constructed by using a formula (4) through changing one of the factors, and the influence result of the single factor on cutter durability is analyzed and obtained, so that the optimal processing parameters are determined.
In step 1), four levels are selected for each factor, and then four-factor four-level orthogonal cutting test is performed, and 16 groups of data are finally obtained according to the L 16(44) orthogonal test table.
As a further preferable technical scheme of the invention, the high-pressure cooling cutting experiment in the step 1) is carried out by selecting a machine tool, a cutter and a workpiece material under the same condition.
As a further preferable embodiment of the present invention, in step 4), the regression analysis operation is performed using Excel software.
In step 5), four groups of single-factor experiments are respectively carried out by taking one factor of the four factors as a variable, and finally, the optimal processing parameters corresponding to the factors are obtained.
The optimized processing parameter method based on the high-pressure cooling cutting tool durability prediction has the following beneficial effects that by adopting the technical scheme:
1) The method for optimizing the machining parameters realizes optimization of the machining parameters by adopting a cutter durability prediction model, can predict, optimize and suggest a high-temperature alloy machining process, provides theoretical support for PCBN cutter cutting research under high-pressure cooling, and simultaneously provides effective reference for other similar cutting performance comparison researches and cutter abrasion researches;
2) The method for optimizing the processing parameters realizes optimizing the processing parameters by adopting the cutter durability prediction model, provides a certain technical reference for researchers and enterprise application personnel engaged in high-temperature alloy cutting processing, and improves the working efficiency and the processing quality by optimizing the processing parameters;
3) The method for optimizing the processing parameters realizes optimization of the processing parameters by adopting the cutter durability prediction model, not only provides important value for the cutter durability to the superalloy processing technology, but also provides a certain theoretical basis for controlling cutter abrasion and optimizing the processing parameters.
Drawings
The invention will be described in further detail with reference to the drawings and the detailed description.
FIG. 1 is a flow chart of a method of one example provided by the preferred process parameter method of the present invention based on high pressure cooling cutting tool durability prediction;
FIG. 2 is a graph of tool wear resistance under different cutting parameters in a single factor experiment, wherein (a) shows the graph of tool wear resistance under different cooling pressures, (b) shows the graph of tool wear resistance under different cutting speeds, (c) shows the graph of tool wear resistance under different feed rates, and (d) shows the graph of tool wear resistance under different cutting depths;
FIG. 3 shows the wear patterns of the rake face at different times according to the present invention, wherein (a) shows the wear patterns of the rake face at 100s, (b) shows the wear patterns of the rake face at 120s, and (c) shows the wear patterns of the rake face at 140 s.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The invention will be further described with reference to the drawings and detailed description. The terms such as "upper", "lower", "left", "right", "middle" and "a" in the preferred embodiments are merely descriptive, but are not intended to limit the scope of the invention, as the relative relationship changes or modifications may be otherwise deemed to be within the scope of the invention without substantial modification to the technical context.
As shown in fig. 1, the present invention provides a method of optimizing machining parameters based on high pressure cooling cutting tool durability predictions, comprising the steps of:
Step 1, selecting a CKA6150 machine tool produced by Dalian machine tool factory, namely a high-pressure cooling cutter bar with the model number of DCLNL2525X12JETI of Katsumadai diamond, namely a PCBN blade with the model number of CNGA120408-2, and a nickel-based superalloy workpiece material with the model number of GH4169, and adopting an orthogonal test method to carry out a high-pressure cooling cutting test on processing parameters, wherein in the test, the cooling pressure P in the processing parameters of the cutter during high-pressure cooling cutting is used, three cutting dosages, namely the cutting speed v c, the feeding amount f and the cutting depth a p are used as factors, each factor is selected to respectively correspond to four levels, and the cutter durability is used as response, a four-factor four-level orthogonal cutting test is carried out, L 16(44) is selected, in the orthogonal cutting test, the cutter face abrasion value is larger than a preset threshold value of 0.6mm as a cutter grinding standard, the cutting time required by the cutter to reach the cutter grinding standard is measured, and 16 groups of data are obtained, and the data are shown in a table 1;
Table 1 pcbn tool durability test chart
Step2, in the cutting process, a generalized Taylor formula is used according to the rule of the variation of the cutter durability along with the cutting dosagePerforming approximate description, and obtaining a calculation formula of the tool durability under high-pressure cooling under the machining condition of adding high-pressure cooling:
Wherein, C T is the coefficient of the durability of the cutter, x T、yT、zT、wT is the index of the cutting speed v c, the feed f, the cutting depth a p and the cooling pressure P respectively;
And 3, analyzing and solving a calculation formula of the tool durability under high-pressure cooling by adopting a multiple linear regression equation, and taking natural logarithms from two sides of the formula (1) to obtain:
lnT=lnCT-xTlnvc-yTlnf-zTlnap-wTlnP
：y＝lnT、x1＝lnvc、x2＝lnf、x4＝lnp、k0＝lnCT、k1＝xT、k2＝yT、k3＝zT、k4＝wT, can then be converted into:
y＝k0-k1x1-k2x2-k3x3-k4x4 (2)
Then, the 16 sets of data results obtained by the test are respectively substituted into the formula (2) to obtain the following multiple linear regression equation:
y1＝k0-k1x11-k2x21-k3x31-k4x41
y2＝k0-k1x12-k2x22-k3x32-k4x42
......
y15＝k0-k1x115-k2x215-k3x315-k4x415
y16＝k0-k1x116-k2x216-k3x316-k4x416
And (3) making:
then it can be converted into a matrix:
Y=XK
finally, the method is obtained by using a least square method:
K=(XTX)-1XTY (3)
Step 4, carrying out regression analysis operation on 4*n groups of data obtained by the test by using Excel software according to the formula (3) to obtain
k0＝6.1105、k1＝1.2434、k2＝1.5765、k3＝2.4774、k4=0.1161
The values for C T、xT、yT、zT、wT obtained were as follows:
C T＝e6.1105、xT＝1.2434、yT＝1.5765、zT＝2.4774、wT = 0.1161, and substituting the model into the formula (1) to obtain an empirical prediction model of the cutter durability under high-pressure cooling, wherein the model is as follows:
And 5, under the condition that all other three factors are fixed according to a single factor experiment method, constructing a durability curve graph of the cutter by using the formula (4) through changing one of the factors, analyzing and obtaining an influence result of the single factor on the durability of the cutter, and determining the optimal processing parameters.
In specific implementation, in combination with step 5), four groups of single-factor experiments are respectively carried out by taking one factor of four factors as a variable, and the influence result of the single factor on the durability of the cutter is analyzed, wherein the method comprises the following steps:
In the case of a fixed cutting amount (v c＝125m/min、f＝0.05mm/r、ap =0.4 mm), different values of the cooling pressure P were substituted into the tool durability prediction model to construct a durability graph of the PCBN tool, as shown in fig. 2 (a). As can be seen from fig. 2 (a), the wear amount of the tool flank groove is not very different at the early stage of wear of the PCBN tool with increasing cooling pressure. After the tool cuts for 100 seconds, the tool wear value starts to rise sharply at 90bar cooling pressure, and the wear value fluctuates greatly. The tool wear amounts at the cooling pressures of 30bar and 70bar are relatively similar, and the tool wear value is also increased sharply after the tool is cut for 100s, which means that the tool enters a later intense wear stage. This is because the increase in cooling pressure can improve the cooling and lubrication conditions between the tool, the chip and the workpiece, reduce the cutting force, and thereby improve the tool wear, but with the continuous increase in cooling pressure, more cutting heat can be taken away in unit time, so that the work hardening effect of the superalloy is enhanced, the cutting force is increased, the tool wear is increased, and the tool durability is reduced. As can also be seen from fig. 2 (a), at a cooling pressure of 50bar, no large fluctuations in the wear value of the tool occur and the wear state is relatively smooth.
When the cooling pressure p=50 bar, the feed rate f=0.05 mm/r, and the cutting depth a p =0.4 mm, different cutting speed values were substituted into the tool durability prediction model, and a durability graph of the PCBN tool was constructed as shown in fig. 2 (b). As can be seen from fig. 2 (b), the wear rate of the PCBN tool was substantially uniform in the initial wear stage before 120 s. After 120s, the wear rate of the PCBN cutters at different cutting speeds begins to rapidly increase, and when the wear rates of the cutters at the cutting speeds of 150m/min and 100m/min are the fastest, the fluctuation of the wear amount in the same time period is more intense, the normal wear period is longer when the cutting speeds are 75m/min and 125m/min, the fluctuation of the wear amount in the same time period is more stable, but after 200s, the wear amount of the cutter at the cutting speed of 75m/min rapidly increases, and the wear blunting standard is rapidly reached. This is because the tool has a relatively sharp cutting edge at the early stage of the tool wear, the area of contact between the flank face and the workpiece to be machined is relatively small, the cutting force applied thereto is relatively small, and the heat generated during the cutting process is timely removed due to the lubricating and cooling effects of the high-pressure coolant.
When the cooling pressure is p=50 bar and the cutting speed v c =125 m/min and the cutting depth a p =0.4 mm, different feeding amounts are substituted into the cutter durability prediction model, and a durability curve chart of the PCBN cutter is constructed, as shown in fig. 2 (c). As can be seen from fig. 2 (c), there is a large difference in the durability of the PCBN tools at different feed rates during the same wear period. In the front 80s, the cutter is in a normal abrasion stage, and the trend of cutter abrasion values under different feeding amounts is similar. After 80s, the tool wear increases rapidly with feed f=0.07 mm/r and f=0.09 mm/r, whereas the tool wear is more gradual with feed f=0.05 mm/r. The cutter abrasion morphology is observed through a VHX-1000C super-depth-of-field microscope, the cutter with the feeding quantity f=0.09 mm/r is slightly damaged in the cutting process of 40s and is severely worn after the cutting process of 100s, so that the cutter fails, the cutter with the feeding quantity f=0.07 mm/r is subjected to massive built-up bits on the front cutter surface of the cutter when the cutting time is 100s, as shown in fig. 3 (a), the built-up bits disappear when the cutting time is 120s, as shown in fig. 3 (b), but the cutter is damaged by 165 mu m, and the cutter is rapidly worn to 433 mu m when the cutting time is 140s, as shown in fig. 3 (C), so that the grinding standard is reached. This is because the feed rate increases, the cutting thickness increases, and the tool is required to overcome more frictional resistance, so the corresponding cutting force increases, resulting in reduced tool wear and durability. When the PCBN tool cuts the nickel-based superalloy, smaller feed is selected as much as possible, which is beneficial to prolonging the service life of the tool and obtaining better machining precision.
When the cooling pressure p=50 bar, the cutting speed v c =125 m/min, and the feed rate f=0.05 mm/r, different cutting depths are substituted into the tool durability prediction model, and a durability curve of the PCBN tool is constructed, as shown in fig. 2 (d). As can be seen from fig. 2 (d), the effect of PCBN tool durability under high-pressure cooling appears to be increasing with increasing cutting depth as a whole. But different from that, in the same wear period, the wear degree of the PCBN cutter is different at different cutting depths, the wear amount of the cutter increases faster when the cutting depth a p =0.6 mm and a p =0.8 mm, approximately in proportion to the cutting time, and the wear amount of the cutter increases relatively slower as the cutting time increases when the cutting depth a p =0.4 mm. This is because the cutting depth increases, and the cutting thickness also increases, resulting in the cutter overcoming greater frictional resistance, increased cutting force, severe cutter wear, and reduced durability. In the whole, the influence of the durability of the PCBN tool under high-pressure cooling tends to be increased along with the increase of the cutting depth.
Considering the results of the four sets of single factor analyses, it is found that the PCBN tool has the smallest wear and the longest durability when the cooling pressure p=50 bar, the cutting speed v c =125 m/min, the feed rate f=0.05 mm/r, and the cutting depth a p =0.4 mm.
While particular embodiments of the present invention have been described above, it will be appreciated by those skilled in the art that these are merely illustrative, and that many variations or modifications may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined only by the appended claims.
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