Drilling force prediction method based on Clarii graph

Abstract

The invention discloses a drilling force prediction method based on a Clarii figure, which comprises the following steps: representing drilling vibration of a composite material with carbon fibers in unidirectional arrangement through the Clarii figure to obtain a frequency value of self-excited vibration of a workpiece, then solving a dynamic cutting force coefficient under the influence of the drilling vibration, and in the dynamic cutting process, calculating the dynamic cutting force coefficient of the workpiece. And predicting the dynamic cutting force according to the dynamic cutting force coefficient, the cutter rotating speed, the cutter feeding speed and the cutting area at the feeding time. By predicting the change of the cutting force, machining vibration caused by violent fluctuation of the cutting force can be avoided, so that the risks of cutter damage and workpiece surface defects are reduced, cutting parameters can be helped to be adjusted, the stability of the cutting process is kept, and the machining precision and the surface quality are improved.

Description

Technical Field

[0001] The invention belongs to the field of automated processing, and in particular relates to a drilling force prediction method based on Chladni figures. Background Art

[0002] During the drilling process of a workpiece, the cutting force between the tool and the workpiece will exert a periodic excitation force on the workpiece. The cutting force of the drilling process changes periodically with the rotation of the tool. This change may match the natural frequency of the workpiece, resulting in resonance. The resulting resonance will have a significant impact on the machining process and the quality of the final workpiece. When the workpiece is in a resonant state, it will exhibit specific vibration modes. These vibration modes depend on the rigidity, mass distribution and boundary conditions of the workpiece. The vibration values ​​measured by traditional vibration sensors cannot fully reflect the vibration modes and drilling forces of the workpiece in a resonant state. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a drilling force prediction method based on Chladni figures. The research on vibration characterization and drilling force prediction based on Chladni figures is of great significance for controlling drilling resonance, optimizing cutting parameters, improving machining accuracy and extending tool life.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] The present invention provides a drilling force prediction method based on Chladni figures, which is specifically as follows:

[0006] Step 1: Use different tool speed n and feed speed v f Different workpiece samples are drilled in turn. Before drilling, the workpiece samples are clamped on the fixture and sand is evenly sprinkled on the workpiece samples. During drilling, the self-excited vibration frequency of the workpiece samples is measured by a vibration sensor, and various Chladni figures and the corresponding self-excited vibration frequencies of the workpiece samples are recorded.

[0007] Step 2: According to the relationship between the self-excited vibration frequency ω of the workpiece sample and the modal numbers m and s of the Chladni figure in formula (1), the material correction parameter a is used as the parameter to be fitted, and the modal numbers m and s of the Chladni figure and the corresponding self-excited vibration frequency ω of the workpiece sample of the Chladni figure are fitted to obtain the specific value of the material correction parameter a.

[0008] The relationship between the self-excited vibration frequency ω of the workpiece sample and the Chladni figure modal numbers m and s is as follows:

[0009]

[0010] Where m and s are the modal numbers, corresponding to the number of nodes in the row and column with the largest number of nodes in the horizontal and vertical directions of the workpiece specimen in the machining surface, respectively; E is the elastic modulus of the workpiece specimen material; ρ is the density of the workpiece specimen material; L x and L y are the length and width of the workpiece specimen respectively.

[0011] Step 3: Clamp the workpiece to be processed on the fixture, sprinkle sand evenly on the workpiece to be processed, set the tool speed n and feed speed v f , drill the workpiece to be processed, record the Chladni figure of the sand grain arrangement on the workpiece to be processed, and obtain the relationship between the tool speed n and the feed speed v f The corresponding Chladni figure modal numbers m and s are calculated according to formula (1) to obtain the real-time self-excited vibration frequency ω of the workpiece to be processed during drilling, and then according to the dynamic cutting force coefficient K d The dynamic cutting force coefficient K is calculated by the relationship between the self-excited vibration frequency ω d ;

[0012] Step 4: During the dynamic cutting process, according to the dynamic cutting force coefficient K d , tool speed n, tool feed speed v f and cutting area A at feed time t c (t), the predicted dynamic cutting force F(t) is as follows:

[0013] F(t)=K d *A c (t)*n p *v f q

[0014] Among them, p and q are empirical coefficients, p takes values ​​in the range of -0.1 to 0.2, and q takes values ​​in the range of 0.2 to 0.5.

[0015] Preferably, the dynamic cutting force coefficient K d The relationship with the self-excited vibration frequency ω is:

[0016]

[0017] Among them, b is the tool diameter, θ is the phase difference between two adjacent cutting edges of the tool, M is the mass of the workpiece to be machined before drilling, and k is the stiffness of the workpiece to be machined.

[0018] More preferably, the phase difference θ between two adjacent cutting edges of the tool is calculated as follows:

[0019]

[0020] Where N w is the number of cutting edges of the tool.

[0021] Preferably, when drilling the workpiece to be processed in step three, the vibration state of each part of the workpiece to be processed is observed by observing the Chladni figures presented by the sand grains on the workpiece to be processed.

[0022] Preferably, the cutting area A at the feed time t is c (t) = π*d*v f *t, d are the drilling hole diameters.

[0023] The beneficial effects of the present invention are as follows:

[0024] 1. The present invention can characterize the drilling vibration of composite materials (such as CF / PEEK materials) with unidirectional carbon fiber arrangement through Chladni patterns. By observing the modal numbers in the length (transverse) and width (longitudinal) directions of the Chladni patterns, the frequency value of the self-excited vibration of the workpiece can be obtained. By observing the Chladni patterns presented by the sand grains on the workpiece, the vibration state of each part of the workpiece can also be intuitively observed, thereby presenting the vibration mode of the workpiece during the drilling process that cannot be shown by the detection values ​​of traditional vibration sensors, thereby controlling the resonance of the workpiece during drilling.

[0025] 2. In the present invention, the dynamic cutting force coefficient under the influence of drilling vibration can be obtained by using the Chladni figure. The dynamic cutting force coefficient can help optimize cutting parameters, improve processing quality and increase production efficiency. During the workpiece drilling process, the dynamic cutting force coefficient can help predict and control the change of cutting force, and effectively avoid vibration or tool wear during the cutting process.

[0026] 3. The present invention can obtain the corresponding dynamic cutting force coefficient based on the Chladni figure, and then combine the dynamic cutting force coefficient, tool speed, tool feed speed and cutting area during feed time to predict the dynamic cutting force during drilling of composite materials with unidirectional carbon fiber arrangement. By predicting the change of cutting force, the processing vibration caused by the drastic fluctuation of cutting force can be avoided, thereby reducing the risk of tool breakage and workpiece surface defects, and can help adjust the cutting parameters to maintain the stability of the cutting process, thereby improving the processing accuracy and surface quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the Chladni figure displayed by the sand grains on the composite material workpiece with unidirectional carbon fibers arranged in this embodiment when the workpiece is drilled at a specific rotation speed and feed speed. DETAILED DESCRIPTION

[0028] The present invention will be further described below in conjunction with the embodiments.

[0029] A drilling force prediction method based on Chladni figures is as follows:

[0030] Step 1: Use different tool speed n and feed speed v f Different workpiece samples are drilled in sequence. Before drilling, the workpiece sample (a flat workpiece, a composite material with unidirectional carbon fiber arrangement) is clamped on a fixture, and sand is evenly sprinkled on the workpiece sample. During drilling, the self-excited vibration frequency of the workpiece sample is measured by a vibration sensor, and various Chladni figures that appear and the corresponding self-excited vibration frequency of the workpiece sample are recorded (photographed). Among them, drilling at different rotation speeds and feed speeds will produce self-excited vibrations of different frequencies on the workpiece sample, and the sand will show different Chladni figures due to vibration (although the specific styles of the Chladni figures are different, the sand grains on the composite material with unidirectional carbon fiber arrangement are all arranged in a horizontal and vertical staggered layout on the processing surface, that is, the sand grains are distributed in rows in the horizontal direction and in columns in the vertical direction). Each Chladni figure that appears due to vibration corresponds to the self-excited vibration frequency ω of a workpiece sample.

[0031] Step 2: According to the relationship between the self-excited vibration frequency ω of the workpiece sample and the Chladni figure modal numbers m and s in formula (1), the material correction parameter a is used as the parameter to be fitted, and the Chladni figure modal numbers m and s and the corresponding workpiece sample self-excited vibration frequency ω data are fitted to obtain the specific value of the material correction parameter a.

[0032] The relationship between the self-excited vibration frequency ω of the workpiece sample and the Chladni figure modal numbers m and s is as follows:

[0033]

[0034] Where m and s are modal numbers, corresponding to the number of nodes in the row and column with the largest number of nodes in the horizontal and vertical directions of the workpiece sample on the processing surface (i.e., in the layout of the sand particles on the composite material with unidirectional carbon fiber arrangement, the number of horizontal and vertical intersections in a certain row in the horizontal direction and a certain column in the vertical direction is the largest, then the number of horizontal and vertical intersections in the row in the horizontal direction and the column in the vertical direction is taken as m and s respectively), which can be obtained by observing the Chladni figure; the specific value of the material correction parameter a should be in the range of 0.07 to 0.09; E is the elastic modulus of the workpiece sample material; ρ is the density of the workpiece sample material; L x and L y are the length and width of the workpiece specimen respectively.

[0035] Step 3: Clamp the workpiece to be processed on the fixture, sprinkle sand evenly on the workpiece to be processed, set the tool speed n and feed speed v f , drilling the workpiece to be processed, such as Figure 1 As shown, the Chladni figure of the arrangement of sand grains on the workpiece to be processed is recorded and obtained (manually counted or through image recognition) and the tool speed n and feed speed v fThe corresponding Chladni figure modal numbers m and s are calculated according to formula (1) to obtain the real-time self-excited vibration frequency ω of the workpiece to be processed during drilling, and then according to the dynamic cutting force coefficient K d The dynamic cutting force coefficient K is calculated by the relationship between the self-excited vibration frequency ω d ;

[0036] Dynamic cutting force coefficient K d The relationship with the self-excited vibration frequency ω is:

[0037]

[0038] Among them, b is the diameter of the tool (drill or milling cutter), θ is the phase difference between two adjacent cutting edges of the tool, M is the mass of the workpiece to be processed before drilling, and k is the stiffness of the workpiece to be processed.

[0039] The phase difference θ between two adjacent cutting edges of the tool is calculated as follows:

[0040]

[0041] Where N w is the number of cutting edges of the tool.

[0042] Step 4: During the dynamic cutting process, the cutting force will be affected by vibration, drilling parameters (tool speed n and feed speed v f ) and the real-time cutting area. According to the dynamic cutting force coefficient K d , tool speed n, tool feed speed v f and cutting area A at feed time t c (t), the predicted dynamic cutting force F(t) is as follows:

[0043] F(t)=K d *A c (t)*n p *v f q

[0044] Among them, A c (t) = π*d*v f *t, d are the diameters of the drilled holes, p and q are empirical coefficients, p is in the range of -0.1 to 0.2, and q is in the range of 0.2 to 0.5.

Claims

1. A drilling force prediction method based on Chladni figures, characterized in that: The method is as follows: Step 1: Use different tool speed n and feed speed v f Different workpiece samples are drilled in sequence. Before drilling, the workpiece samples are clamped on a fixture and sand is evenly sprinkled on the workpiece samples. During drilling, the self-excited vibration frequency of the workpiece samples is measured by a vibration sensor, and various Chladni figures that appear and the corresponding self-excited vibration frequency of the workpiece samples are recorded. Step 2: according to the relationship between the self-excited vibration frequency ω of the workpiece sample and the modal numbers m and s of the Chladni figure in formula (1), the material correction parameter a is used as the parameter to be fitted, and the modal numbers m and s of the Chladni figure and the self-excited vibration frequency ω of the workpiece sample corresponding to the Chladni figure are fitted to obtain the specific value of the material correction parameter a; The relationship between the self-excited vibration frequency ω of the workpiece sample and the Chladni figure modal numbers m and s is as follows: Where m and s are the modal numbers, corresponding to the number of nodes in the row and column with the largest number of nodes in the horizontal and vertical directions of the workpiece specimen in the machining surface; E is the elastic modulus of the workpiece specimen material; ρ is the density of the workpiece sample material; L x and L y are the length and width of the workpiece specimen, respectively; Step 3: Clamp the workpiece to be processed on the fixture, sprinkle sand evenly on the workpiece to be processed, set the tool speed n and feed speed v f , drill the workpiece to be processed, record the Chladni figure of the sand grain arrangement on the workpiece to be processed, and obtain the relationship between the tool speed n and the feed speed v f The corresponding Chladni figure modal numbers m and s are calculated according to formula (1) to obtain the real-time self-excited vibration frequency ω of the workpiece to be processed during drilling, and then according to the dynamic cutting force coefficient K d The dynamic cutting force coefficient K is calculated by the relationship between the self-excited vibration frequency ω d ; Step 4: During the dynamic cutting process, according to the dynamic cutting force coefficient K d , tool speed n, tool feed speed v f and cutting area A at feed time t c (t), the predicted dynamic cutting force F(t) is as follows: F(t)=K d *A c (t)*n p *v f q Among them, p and q are empirical coefficients, p takes values ​​in the range of -0.1 to 0.2, and q takes values ​​in the range of 0.2 to 0.

5.

2. The drilling force prediction method based on Chladni figures according to claim 1, characterized in that: The dynamic cutting force coefficient K d The relationship with the self-excited vibration frequency ω is: Among them, b is the tool diameter, θ is the phase difference between two adjacent cutting edges of the tool, M is the mass of the workpiece to be machined before drilling, and k is the stiffness of the workpiece to be machined.

3. The drilling force prediction method based on Chladni figures according to claim 2, characterized in that: The phase difference θ between two adjacent cutting edges of the tool is calculated as follows: Where N w is the number of cutting edges of the tool.

4. The drilling force prediction method based on Chladni figures according to claim 1, characterized in that: When drilling the workpiece to be processed in step three, the vibration state of each part of the workpiece to be processed can be observed by observing the Chladni figure presented by the sand grains on the workpiece to be processed.

5. The drilling force prediction method based on Chladni figures according to claim 1, characterized in that: The cutting area A at the feed time t c (t) = π*d*v f *t, d are the drilling hole diameters.

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