A method for predicting the roughness of FDM samples of polymer materials

Abstract

The present invention provides a method for predicting the roughness of a polymer material FDM sample, comprising the following steps: step S1, preparing and drying the polymer material wire to be printed, leveling the printing base plate, and generating a G-Code code for the printed sample; step S2, building a temperature measurement platform device, fixing a thermocouple at the starting position of the filling path of the first layer of printing, directly contacting the printing surface of the printing process to measure the temperature, collecting the information of the thermocouple through a dynamic signal acquisition analyzer, and converting the digital signal into a real-time temperature curve chart for real-time output on a computer; step S3, performing FDM printing on the polymer material, and calculating the surface roughness according to the formula using the collected temperature. The technical solution of the present invention has a simple calculation process, can achieve accurate prediction of the nozzle temperature within 10% above 500°C, and is suitable for both pure polymer materials and fiber-reinforced polymer composite materials.

Description

Technical Field

[0001] The invention belongs to the technical field of additive manufacturing, and in particular relates to a method for predicting the roughness of a polymer material FDM sample. Background Art

[0002] Fused deposition modeling (FDM) is widely used in the manufacturing field due to its advantages of low cost, easy maintenance and simple operation. The processing principle is that thermoplastic filaments are injected into a heated, melted or liquefied nozzle, and then extruded and deposited on the base plate. Due to insufficient melting and diffusion of the filament, obvious stripes will form on the surface of the FDM printed part. These stripes will increase the surface roughness of the FDM printed part, thereby affecting the surface accuracy of the printed part, thus hindering the further application of FDM printing technology.

[0003] In order to reduce the problem of large surface roughness of FDM printed parts, many scholars are committed to establishing an accurate FDM surface roughness prediction model to accurately predict the roughness of the printed surface, so as to find a way to reduce the surface roughness of FDM printed parts. From this perspective, Hu Weiyue et al. established a surface roughness prediction model based on the two parameters of layer thickness and extrusion line width, focusing on the analysis of the influence of the two factors of layer thickness and extrusion width on the surface roughness of FDM parts. The prediction error of this model is within 10% compared with the actual measurement, but this study is mainly aimed at PLA pure polymer materials, and the study does not specifically describe whether it is applicable to composite materials with complex properties of matrix materials and reinforcement materials and more complex interface properties. Boschetto et al. proposed a method to use process parameters and part geometry to represent the surface profile of FDM printed parts as a function, and designed a suitable model to verify the feasibility of this method for predicting FDM surface roughness, but the model lacks consideration of the step effect when the deposition angle is not 0°. Irene et al. proposed a geometric model to simulate the roughness profile of PLA prints at different printing direction angles during the FDM process to determine the average height Ra of the roughness profile. The model can achieve a relatively satisfactory prediction effect when the printing angle is lower than 80°. However, the assumption based on this study is that the printing temperature is low enough and the polymer macromolecules between the layers do not diffuse further. For composite materials, especially carbon fiber composite materials, the nozzle temperature is relatively high and this factor cannot be ignored. Especially for high-melting-point carbon fiber reinforced polymer composites, it is difficult to study due to the high melting temperature and the complex carbon fiber properties of the matrix material and the reinforcement material. The assumptions of many roughness models are that the nozzle temperature is relatively low (about 200°C), the material properties are relatively simple (ABS material, PLA material), and the computational engineering is complex. The existing prediction methods are difficult to predict such materials. The accuracy of the prediction of the roughness of FDM samples of carbon fiber composites needs to be improved. Summary of the invention

[0004] In view of the above technical problems, the present invention discloses a method for predicting the roughness of FDM samples of polymer materials, which monitors the temperature history during the FDM process to accurately predict the surface roughness of FDM printed parts online in real time.

[0005] To this end, the technical solution adopted by the present invention is:

[0006] A method for predicting the roughness of a polymer material FDM sample comprises the following steps:

[0007] Step S1, preparing and drying the polymer material wire for printing, leveling the printing base plate, and generating the G-Code code of the printed sample;

[0008] Step S2, build a temperature measurement platform device, fix the thermocouple at the starting position of the filling path of the first layer of printing, directly contact the printing surface during the printing process to measure the temperature, collect the information of the thermocouple through the dynamic signal acquisition analyzer, and convert the digital signal into a real-time temperature curve graph and output it in real time on the computer;

[0009] Step S3, perform FDM printing on the carbon fiber polyetheretherketone, and calculate the surface roughness R according to the following formula using the collected temperature: z ,

[0010]

[0011] Among them, H3 is the diameter of the sphere in the polymer contact bonding state, that is, the thickness of the printed layer;

[0012] θ(t) is calculated using the following formula:

[0013] Among them, θ(t ∞ ) is the bonding angle after printing the final state, t ∞ is the time for the printed polymer material to completely diffuse, which is calculated based on the collected temperature and the time the polymer is above the glass transition temperature during printing; η is the dynamic viscosity of the printed polymer material at the FDM printing temperature, Γ is the surface tension coefficient of the printed polymer material at the FDM printing temperature, and r is the diameter of the sphere of the polymer material in the initial state; wherein the FDM printing temperature is the temperature value of the print nozzle.

[0014] Among them, the carbon fiber polyetheretherketone, CF-PEEK material, uses polyetheretherketone as a matrix, and carbon fiber is embedded in the matrix as a reinforcing phase material. This technical solution selects the important parameter of temperature change during the printing process, establishes the functional relationship between the temperature history of the FDM printing process and the roughness of the FDM printed parts, and names it OTTP-R (Online time and temperature roughness prediction). After verification, the average relative error rate of this prediction method is 7.70%, which can realize the prediction function of the surface roughness of CF-PEEK.

[0015] As a further improvement of the present invention, the polymer material is a carbon fiber polyetheretherketone composite material. Further, in the carbon fiber polyetheretherketone composite material, the volume fractions of polyetheretherketone and carbon fiber are 70% and 30% respectively.

[0016] As a further improvement of the present invention, in step S1, the printed wire is placed in a vacuum drying oven for vacuum drying, the drying temperature is not less than 100°C, and the drying time is not less than 6 hours. Further, the drying temperature is 120°C, and the drying time is 12 hours.

[0017] As a further improvement of the present invention, in step S1, a linear filling pattern with a desired grating angle is set, and the gap between the nozzle and the printing bed is leveled several times before the experiment starts until a standard A4 paper can be moved, and glue is applied to the bottom plate to ensure successful adhesion of the bottom layer.

[0018] As a further improvement of the present invention, in step S2, during the temperature measurement process, the thermocouple is fixed at multiple points, and a gap of 0.1 to 0.2 mm is reserved on the basis of leveling the printing base plate to prevent the print head from colliding with the thermocouple on the printing path.

[0019] As a further improvement of the present invention, in step S2, the temperature signal sampling frequency of the dynamic signal acquisition and analysis instrument is preferably 25.6 Hz.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] First, the technical solution of the present invention selects the important parameter of temperature change in the printing process, and establishes the functional relationship between the temperature history of the FDM printing process and the roughness of the FDM printed parts. The prediction method has an average relative error rate of 7.70% after verification, and can achieve accurate prediction of the nozzle temperature within 10% above 500°C, and is suitable for both pure polymer materials and fiber-reinforced polymer composite materials.

[0022] Secondly, the roughness of the technical solution of the present invention is obtained by directly obtaining the time for complete diffusion of the polymer through temperature monitoring and substituting it into the formula for calculation. There is no need to go through a complicated calculation process in the middle, and the calculation is simple. Moreover, it can be applied to situations where the melting temperature is high and the carbon fiber characteristics of the matrix material and the reinforcing material are complex, and it can achieve accurate prediction of CF-PEEK material within 10% when the nozzle temperature is above 500°C.

[0023] Third, in view of the predicted surface roughness caused by stripes formed on the surface due to insufficient melting of the printing fuse and insufficient diffusion between each other during the FDM printing process, the method of the present invention finds a new method to reduce the surface roughness and thus improve the surface accuracy of the printed part. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the experimental device of the present invention.

[0025] Figure 2Schematic diagram of the bonding process between polymer fuses of the present invention; wherein (a) is the initial state, and (b) is the contact bonding state.

[0026] Figure 3 The bonding angle and surface roughness of the CF-PEEK material of Example 1 of the present invention at different nozzle temperatures.

[0027] Figure 4 The laser confocal morphology and surface roughness of the CF-PEEK sample at different nozzle temperatures in Example 1 of the present invention are shown.

[0028] Figure 5 The OTTP-R and laser confocal results of different nozzle temperatures in Example 1 of the present invention are compared and the average relative error rate.

[0029] Figure 6 The bonding angle and surface roughness of the CF-PEEK material of Example 1 of the present invention at different printing speeds.

[0030] Figure 7 The laser confocal morphology and surface roughness of the CF-PEEK sample at different printing speeds in Example 1 of the present invention.

[0031] Figure 8 The figures are the comparison of OTTP-R and laser confocal results at different printing speeds and the average relative error rate of Example 1 of the present invention.

[0032] Fig. 9 The bonding angle and surface roughness of the CF-PEEK material of Example 1 of the present invention at different grating angles.

[0033] Fig.10 The laser confocal morphology and surface roughness of CF-PEEK samples with different grating angles in Example 1 of the present invention are shown.

[0034] Fig.11 It is a comparison chart of OTTP-R and laser confocal results with different grating angles in Example 1 of the present invention and an analysis chart of the average relative error rate.

[0035] Fig.12 This is the temperature measurement result collected in Example 2 of the present invention.

[0036] Fig.13 This is the result of laser confocal measurement of PLA in Example 2 of the present invention.

[0037] Reference numerals include:

[0038] 1- Printer, 2- Test point, 3- Thermocouple, 4- Printing base plate, 5- First layer filling path, 6- Dynamic signal acquisition analyzer, 7- Computer. DETAILED DESCRIPTION

[0039] The preferred embodiments of the present invention are described in further detail below.

[0040] A method for predicting the roughness of a polymer material FDM sample comprises the following steps:

[0041] Step 1: Experimental material preparation, including vacuum drying of printing wire, leveling of printing base plate 4, and G-Code generation of printing sample.

[0042] Step 2: Build a temperature measurement platform device, such as Figure 1 As shown, the device includes an FDM printer 1, a K-type thermocouple 3, a dynamic signal acquisition and analysis instrument 6 and a computer 7.

[0043] Fix the thermocouple 3 at the starting position of printing the first layer of filling path 5, that is, Figure 1 At test point 2 in the printing process, the temperature is measured by directly contacting the printing surface. The collected temperature simulation signal is collected by the dynamic signal test and analysis system, and the digital signal is converted into a real-time temperature curve chart through the dynamic signal analysis software and output in real time on the computer 7.

[0044] Step 3: Measure the temperature during the FDM printing process and obtain temperature data.

[0045] Step 4: Process the collected temperature according to the following derivation formula, which specifically includes the following steps:

[0046] The derivation process of the above technical solution is as follows:

[0047] 1) The geometric assumption of the model is that when the initial time t is zero, there is a contact point O for the sphere with a cross-sectional radius of H1 (i.e., the diameter of the sphere in the initial state of the polymer); as time t progresses, the two centers approach each other, and at this time the intersection length and radius of the two circles are set to H2 and H3, the bonding angle is set to θ(t), and the surface roughness is set to R z In order to simplify the formula, H1≈H3 is set. The geometric diagram is as follows Figure 2 shown.

[0048] 2) Define the surface roughness. According to the geometric assumption, the height difference R between the lowest point and the highest point on the contact line is z As a measure of the surface roughness value, based on the sintering model established by Pokluda et al., the intersection length and radius are defined by H2 and H3:

[0049]

[0050] Wherein, H2 is the intersection length of the polymer under the contact bonding state, in mm; H3 is the diameter of the sphere under the contact bonding state of the polymer, in mm; R z It is the surface roughness, the height difference between the lowest point and the highest point on the contact line, in mm.

[0051] 3) According to Figure 1 As shown, the sine of the bonding angle θ(t) is exactly the ratio of the half-lengths of H2 and H3:

[0052]

[0053] Where θ(t) is the polymer bonding angle, in degrees.

[0054] 4) Substitute formula 2 into formula 1 to obtain the surface roughness R z And the relationship between the bonding angle θ(t) is:

[0055]

[0056] 5) In the polymer bonding process, if all other forces are ignored, only surface tension and viscous dissipation force exist on the polymer surface. Viscous dissipation is the heat energy generated by the viscous friction force in the melt flow. The calculation formula of viscous dissipation work is: Assume W v is the viscous dissipated work, η is the viscosity, r is the initial polymer sphere diameter H1, and the viscous dissipated work can be obtained as:

[0057]

[0058] Among them, W v is the viscous dissipation work of the polymer bonding process, in J; η is the dynamic viscosity of the polymer, in Pa·s; r is the initial polymer sphere diameter H1, in mm, where θ is the θ(t) mentioned above.

[0059] 6) In addition, the polymer surface will generate surface tension acting on the contact interface line along the surface due to the imbalance of molecular attraction. The calculation formula is:

[0060]

[0061] Among them, W s is the surface tension work of the polymer bonding process, with the unit of J; Γ is the surface tension coefficient of the polymer, with the unit of N / m, where θ is θ(t) mentioned above.

[0062] 7) According to Pokluda et al., the two works remain balanced when the sign of θ(t) does not change, so:

[0063] W v =Ws (6)

[0064] 8) The evolution of the bonding angle is based on the balance between the surface tension work and the viscous dissipation work. After the bonding is completed, there should be a certain bonding angle value. Substituting into formulas (4), (5), and (6), the automatic step size Runge-Kutta-Fehlberg integral solution method used by Burden and Faires et al. is used to perform numerical solutions and obtain:

[0065]

[0066] Among them, θ(t ∞ ) refers to the bonding angle after printing the final state, in degrees; t ∞ It is the time for the polymer to diffuse completely, that is, the time for the polymer to be above the glass transition temperature during FDM printing, and the unit is s.

[0067] 9) The newly obtained θ(t ∞ ) is substituted into formula (3) to obtain the surface roughness value R z ,The results calculated here are verified to be applicable to the surface roughness prediction of CF-PEEK.

[0068] The following describes the invention in conjunction with specific embodiments.

[0069] Example 1

[0070] Roughness prediction of carbon fiber reinforced polyetheretherketone (CF-PEEK) composite materials, where the volume fractions of polyetheretherketone and carbon fiber account for 70% and 30% respectively. The steps are as follows:

[0071] Step 1: Preparation of experimental materials

[0072] After the CF-PEEK printing filament was placed in a vacuum drying oven at a constant temperature of 120°C for 12 hours, the printed sample was modeled and generated in STL format and imported into the Simplify-3D slicing software for G-code code generation, and a linear fill pattern with the required grating angle was set. Before the experiment began, the gap between the nozzle and the print bed was leveled several times until a standard A4 paper could be moved, and glue was applied to the bottom plate to ensure successful adhesion of the bottom layer.

[0073] Step 2: Build a temperature measurement platform

[0074] according to Figure 1The temperature measurement platform is displayed to complete the preliminary connection preparation work. First, a K-type thermocouple is selected for measurement, and the thermocouple is fixed at the starting position of the filling path of the first layer of printing. During the temperature measurement process, tape is used to fix multiple positions to ensure the stability of the measurement point position. At this time, a gap of 0.1 to 0.2 mm is reserved on the basis of leveling the printing base plate to prevent the print head from colliding with the thermocouple on the printing path. After that, the thermocouple is connected to the dynamic test signal analysis system and the power switch of the instrument is turned on. After that, the dynamic test signal analysis system is connected to the laptop computer using a network cable, and the dynamic signal acquisition and analysis system on the computer is turned on. After setting the ambient temperature, sampling frequency and other related parameters, the stability of the temperature signal is tested.

[0075] Step 3: Temperature data collection

[0076] Import the G-code with the set process parameters into the FFF fused deposition modeling (FDM) printer, wait for the nozzle and the base plate to heat up successfully before starting printing, place the thermocouple at the measuring point when the nozzle prints to the first layer of filling path, fix the thermocouple and start temperature collection. The time for collecting temperature is the filling time of the first layer, which is determined by the printing speed and the printing path, generally about 30 to 50 seconds. During this process, pay attention to the temperature curve in the dynamic signal acquisition and analysis system in real time, and pay attention to the stability of the signal output. If the signal stability is too poor to be recognized, stop the temperature measurement work immediately, repeat step 3 until a clear temperature curve is output, and complete the temperature collection work. Each temperature collection needs to be repeated 3 to 4 times and the clearest curve is selected as a preparation for the next step.

[0077] Step 4: Derivation of temperature data formula to predict roughness

[0078] 1) Make geometric assumptions about the model. When the initial time t is zero, there is a contact point O for a sphere with a cross-sectional radius of H1. As time t progresses, the two centers approach each other. At this time, the intersection length and radius of the two circles are set to H2 and H3, the bonding angle is set to θ(t), and the surface roughness is set to R. z In order to simplify the formula, H1≈H3 is set at this time, and the geometric diagram is as follows Figure 2 shown.

[0079] 2) Define the surface roughness. According to the geometric assumption, the height difference R between the lowest point and the highest point on the contact line is z As a measure of surface roughness value, it is defined by H2 and H3, see formula (1).

[0080] 3) The sine of the bonding angle θ(t) is exactly the half-length ratio of H2 and H3, see formula (2).

[0081] 4) Substitute formula 2 into formula 1 to obtain the surface roughness R z The relationship between the bonding angle θ(t) is shown in formula (3).

[0082] 5) Calculate the viscous dissipation work, where the dynamic viscosity η of CF-PEEK is 1000 Pa·s and substitute it into formula (4).

[0083] 6) Calculate the surface tension work, where the surface tension coefficient Γ of CF-PEEK is 2.20 N / m and substitute it into formula (5).

[0084] 7) The viscous dissipation work and the surface tension work are balanced, see formula (7).

[0085] 8) The bonding angle after printing the final state is obtained by using the automatic step integral value, and formula 8 is obtained:

[0086]

[0087] 9) t obtained by temperature measurement ∞ Substituting in the above equation, we can get the corresponding roughness prediction result OTTP-R.

[0088] The temperature variation of CF-PEEK (445℃, 485℃, 525℃) during the printing process at different nozzle temperatures designed in the experiment is shown in the figure. Figure 3 As shown in Figure 2, the calculated bonding angle, surface roughness and micromorphology of CF-PEEK at different nozzle temperatures are as follows: Figure 4 As shown in the figure, the surface roughness of the test sample measured in the laser confocal microscope is compared with the results of OTTP-R. The predicted relative average error rates are 8.31%, 6.37% and 9.86%, respectively. Figure 5 shown.

[0089] The temperature variation of CF-PEEK during the printing process at different printing speeds (20mm / s, 30mm / s, 40mm / s) is shown in the figure. Figure 6 As shown in Figure 2, the bonding angle, surface roughness and micromorphology of CF-PEEK at different printing speeds are calculated, as shown in Figure 2. Figure 7 As shown in the figure, the surface roughness of the test sample measured in the laser confocal microscope is compared with the results of OTTP-R. The predicted relative average error rates are 8.31%, 9.61% and 9.25%, respectively. Figure 8 shown.

[0090] The temperature variation of CF-PEEK (0°, 30°, 45°) during the printing process under different grating angles designed in the experiment is shown in the figure. Fig. 9As shown in Figure 2, the bonding angle, surface roughness and micromorphology of CF-PEEK at different printing speeds are calculated, as shown in Figure 2. Fig.10 As shown in the figure, the surface roughness of the test sample measured in the laser confocal microscope is compared with the results of OTTP-R. The predicted relative average error rates are 1.90%, 8.54% and 0.43%, respectively. Fig.11 shown.

[0091] Example 2

[0092] The above prediction method is used to predict the roughness of pure polymer PLAFDM samples. The PLA printing parameters are: layer thickness 0.4 mm, printing temperature 210 ° C, printing speed 40 mm / s, filling rate 100%, and raster angle 0°.

[0093] The temperature measurement results of PLA polymer are as follows Fig.12 As shown, according to Fig.12 The glass transition temperature boundary of PLA can be used to calculate the complete diffusion time t of PLA polymer. ∞ The dynamic viscosity η of PLA is about 3 Pa·s at 210℃, and the surface tension coefficient Γ of PLA is about 2.50 N / m at 210℃. Substituting into formula (7) for calculation, the bonding angle is about 33°. Substituting into formula (3) with a layer thickness of 0.4 mm for the surface roughness R z The calculation is about 91μm. Here, laser confocal measurement of PLA is performed. Fig.13 As shown, the measured result is 94.264 μm. It is calculated that the relative error rate of the roughness obtained by the method of this embodiment is 3.46%.

[0094] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for predicting the roughness of a polymer material FDM sample, characterized by: The steps include: Step S1, preparing and drying the polymer material wire for printing, leveling the printing base plate, and generating the G-Code code of the printed sample; Step S2, build a temperature measurement platform device, fix the thermocouple at the starting position of the filling path of the first layer of printing, directly contact the printing surface during the printing process to measure the temperature, collect the information of the thermocouple through the dynamic signal acquisition analyzer, and convert the digital signal into a real-time temperature curve graph and output it in real time on the computer; Step S3, perform FDM printing on the polymer material, and calculate the surface roughness R according to the following formula using the collected temperature: z , Among them, H3 is the diameter of the sphere in the polymer contact bonding state, that is, the thickness of the printed layer; θ(t) is calculated using the following formula: Among them, θ(t ∞ ) is the bonding angle after printing the final state, t ∞ is the time for the polymer material to diffuse completely, which is calculated based on the collected temperature and the time the polymer is above the glass transition temperature during printing; η is the dynamic viscosity of the polymer material at the FDM printing temperature, Γ is the surface tension coefficient of the polymer material at the FDM printing temperature, and r is the diameter of the sphere in the initial state of the polymer material.

2. The method for predicting the roughness of a polymer material FDM sample according to claim 1, characterized in that: The polymer material is a carbon fiber polyetheretherketone composite material, wherein the volume fractions of polyetheretherketone and carbon fiber are 70% and 30% respectively.

3. The method for predicting the roughness of a polymer material FDM sample according to claim 1, characterized in that: In step S1, the printed polymer material wire is placed in a vacuum drying oven for vacuum drying, the drying temperature is not less than 100° C., and the drying time is not less than 6 hours.

4. The method for predicting the roughness of a polymer material FDM sample according to claim 1, characterized in that: In step S1, a linear fill pattern with the required raster angle is set. Before the experiment begins, the gap between the nozzle and the print bed is leveled several times until a standard A4 paper can be moved. At the same time, glue is applied to the bottom plate to ensure successful adhesion of the bottom layer.

5. The method for predicting the roughness of a polymer material FDM sample according to claim 4, characterized in that: In step S2, during the temperature measurement process, the thermocouple is fixed at multiple points, and a gap of 0.1 to 0.2 mm is reserved on the basis of leveling the printing base plate.

6. The method for predicting the roughness of a polymer material FDM sample according to claim 1, characterized in that: In step S2, the temperature signal sampling frequency of the dynamic signal acquisition and analysis instrument is preferably 25.6 Hz.

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