Diameter prediction method for pillar of additive manufacturing lattice structure

Abstract

The invention belongs to the technical field of additive manufacturing, and particularly relates to an additive manufacturing lattice structure pillar diameter prediction method, which comprises the following operation steps: S1, selecting additive manufacturing process parameters, and manufacturing a lattice structure; according to the prediction method, the method for rapidly predicting the diameter of the additive manufacturing titanium alloy lattice structure supporting column is arranged, and only the diameters of the titanium alloy lattice structure supporting column manufactured under several different technological parameters need to be counted, so that a relation formula can be fitted according to the method provided by the invention; predication of the diameter of the titanium alloy lattice structure supporting column of additive manufacturing under any technological parameters is achieved; the proposed formula is only related to the laser energy density, has the advantages of simple form and fewer parameters, and can solve the problem of predicting the pillar diameter of the lattice structure of the same material under different process parameters especially for the lattice structure manufactured by the same material under different process parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of additive manufacturing, and in particular to a method for predicting the diameter of a pillar of an additively manufactured lattice structure. Background Art

[0002] Additive manufacturing technology, also known as 3D printing technology, is a new processing method that has developed rapidly in recent years. This technology uses the discrete-accumulation principle to melt and accumulate materials layer by layer to manufacture solid parts. Compared with traditional material removal processing technology, it is a "bottom-up" manufacturing method. It has obvious advantages such as high design freedom, high production efficiency, strong ability to manufacture complex structures, and the ability to meet personalized small-batch production.

[0003] Lightweight design is an important requirement for the development of equipment in the aerospace, automotive, medical and other industries. It has many advantages in reducing energy consumption, environmental protection, and improving structural performance. In the aerospace field, lightweight structure can reduce aircraft fuel consumption, improve endurance and maneuverability, and is one of the key technologies for the development of future aerospace equipment.

[0004] In recent years, the application of lattice structure in the field of lightweight design has attracted wide attention due to its light weight and high strength. Lattice structure is an ordered structure composed of a series of unit cells with specific structural forms and pore shapes arranged periodically according to certain rules.

[0005] Since the lattice structure has a complex internal structure, the traditional processing methods are no longer suitable. The traditional lattice structure preparation methods include investment casting, stamping and additive manufacturing. However, the investment casting method has the problems of very complex process flow and high cost, and is prone to defects. The stamping method has the problems of needing to manufacture molds, high cost, and serious waste of metal sheets. The development and maturity of additive manufacturing technology has provided new ideas for the manufacture of lattice structures, so that the lattice structure, which has many characteristics and advantages, can have a broader application prospect.

[0006] However, due to the characteristics of the raw materials of the additive manufacturing powder of the metal lattice structure and the limitations of the laser selective melting process, the size of the lattice structure of the additive manufacturing deviates from the original design, which in turn affects the mechanical properties of the lattice structure. The additive manufacturing process parameters will affect the pillar diameter of the lattice structure, and the experimental workload is very large. Therefore, how to predict the pillar diameter of the lattice structure has always been the focus and difficulty of the additive manufacturing lattice structure.

[0007] In fact, there is a regularity between the additive manufacturing process parameters and the diameter of the lattice structure pillars. Generally speaking, the diameter of the titanium alloy lattice structure pillars is related to the size of the molten pool. The size of the molten pool is determined by the energy density of the laser input into the molten pool, and the energy density is related to the process parameters. Therefore, starting from the energy density, by designing different process parameter tests, the quantitative relationship between the process parameters and the diameter of the titanium alloy lattice structure pillars can be obtained, and the diameter of the titanium alloy lattice structure pillars under different process parameters can be predicted, thereby greatly reducing the test time and saving costs.

[0008] The present invention intends to provide a method for predicting the diameter of pillars in an additively manufactured titanium alloy lattice structure from the perspective of the molten pool input energy density. Summary of the invention

[0009] Based on the existing technical problem of predicting the diameter of a pillar of a lattice structure in additive manufacturing, the present invention proposes a method for predicting the diameter of a pillar of a lattice structure in additive manufacturing.

[0010] The present invention proposes a method for predicting the diameter of a pillar of an additively manufactured lattice structure, and the operating steps are as follows:

[0011] S1. Selecting additive manufacturing process parameters to manufacture a lattice structure;

[0012] S11, select TC4 titanium alloy as the manufacturing material, design the FCCZ lattice structure by CAD software, wherein the lattice structure is designed with a diameter of 1 mm;

[0013] S12. Determine the range of additive manufacturing process parameters according to engineering requirements, including laser power P of 200W-600W, scanning speed V of 100mm / s-500mm / s, scanning spacing H of 80μm-200μm, and powder layer thickness T of 50μm-150μm;

[0014] S13. Three groups of representative process parameter combinations were selected by orthogonal design method, and FCCZ lattice structures of titanium alloy were manufactured by laser selective melting additive manufacturing technology using the selected process parameters.

[0015] S2. Calculate the laser energy density and measure the diameter of the lattice structure pillars:

[0016] S21, according to the formula Calculate the laser energy density E corresponding to different process parameter combinations, where P is the laser power in Watts (W); V is the scanning speed in millimeters per second (mm / s); H is the scanning spacing in millimeters (mm); T is the powder layer thickness in millimeters (mm);

[0017] S22, using CT scanning technology to scan the titanium alloy FCCZ lattice structure manufactured under different process parameters to obtain tomographic image data of its internal structure;

[0018] S23, importing the scanned data into Avizo software for 3D visualization reconstruction, selecting 10-20 pillars at different positions in each lattice structure for diameter measurement through the image processing and measurement tools of the software, and calculating the average value as the pillar diameter of the lattice structure;

[0019] S3. Fitting the relationship between laser energy density and the diameter of the pillars of the additively manufactured titanium alloy lattice structure:

[0020] S31, arranging the calculated laser energy density values ​​and the corresponding average values ​​of the diameters of the pillars of the lattice structure into a data file, with the first column being the laser energy density and the second column being the pillar diameter;

[0021] S32, importing the data file into the Origin analysis software, selecting the linear regression fitting method, fitting the relationship between the laser energy density and the pillar diameter of the FCCZ lattice structure of the additively manufactured titanium alloy according to the principle of the least squares method, the formula D=0.0083E+0.6838, where D is the pillar diameter, E is the laser energy density, a and b are coefficients to be determined, and obtaining the fitting curve, fitting equation and related statistical parameters at the same time;

[0022] S4. Prediction of the diameter of the lattice structure pillars:

[0023] S41. For any new set of process parameters, first follow the formula Calculate its laser energy density E, and then substitute E into the prediction model formula D pred =0.0083E+0.6838, and the corresponding predicted value of the diameter of the lattice structure pillar D is obtained. pred ;

[0024] S42. Actually manufacture the titanium alloy FCCZ lattice structure with the new process parameters, and obtain the actual pillar diameter D according to the above measurement method. actual ;

[0025] S43. Calculate relative error If the relative error is within the acceptable range determined according to specific engineering requirements, the prediction model is reliable; if the error is large, the process parameter range is readjusted.

[0026] Preferably, in S2, a temperature field distribution correction factor is introduced into the laser energy density calculation formula E, so that Where F(T) is the temperature field distribution function, which is used to compensate for the influence of the heat affected zone on the actual laser energy density. T is the local temperature, T 0 is the substrate temperature, T meltis the melting point of titanium alloy, α is a parameter related to temperature gradient, which indicates the speed of temperature drop when moving away from the center of the molten pool, β and γ are coefficients related to the change of thermal conductivity and specific heat capacity with temperature, which are used to adjust the attenuation degree after the temperature exceeds the melting point, and σ is the standard deviation, which is used to control the width of the temperature distribution curve.

[0027] Preferably, in S23, artificial intelligence image recognition technology is used to automatically extract the pillar positions from the CT scan data and perform diameter measurement to reduce human errors.

[0028] Preferably, in said S32, in addition to linear regression fitting, nonlinear regression analysis is also used, including polynomial regression and exponential regression.

[0029] Preferably, in S41, an online monitoring system is established to monitor the laser energy density changes in the manufacturing process in real time, and dynamically adjust the prediction model parameters to ensure the accuracy of the prediction value.

[0030] Preferably, in S2, an adaptive algorithm is used to adjust the correction factor according to real-time data in the manufacturing process.

[0031] Preferably, in S2, the deformation behavior of the lattice structure during the molding process is predicted by combining finite element analysis, and the design is optimized to reduce molding defects.

[0032] Preferably, in S43, the relative error range of the prediction result is between 5% and 10%.

[0033] The beneficial effects of the present invention are:

[0034] By setting up a method for quickly predicting the diameter of the pillars of the titanium alloy lattice structure manufactured by additive manufacturing, it is only necessary to count the diameters of the pillars of the titanium alloy lattice structure manufactured under several different process parameters, and the relationship formula can be fitted according to the method provided by the present invention to achieve the prediction of the diameter of the pillars of the titanium alloy lattice structure manufactured by additive manufacturing under any process parameters; the proposed formula is only related to the laser energy density, and has the advantages of simple form and fewer parameters. Especially for the lattice structure manufactured by the same material with different process parameters, it can solve the problem of predicting the diameter of the pillars of the lattice structure of this type of material under different process parameters. The prediction through the formula can greatly save the test materials, time and cost, improve efficiency, and is of great value for the optimization of the diameter of the pillars of the lattice structure and high-quality and efficient manufacturing. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of a method for predicting the diameter of a pillar of an additively manufactured lattice structure proposed by the present invention;

[0036] Figure 2A three-dimensional visualization reconstruction diagram of CT data of a lattice structure of an additive manufacturing lattice structure pillar diameter prediction method proposed by the present invention;

[0037] Figure 3 A schematic diagram of the relationship between laser energy density and lattice structure pillar diameter in a method for predicting the diameter of lattice structure pillars in additive manufacturing proposed by the present invention. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0039] Reference Figure 1-Figure 3 , a method for predicting the diameter of pillars of additively manufactured lattice structures, the operation steps are as follows:

[0040] S1. Selecting additive manufacturing process parameters to manufacture a lattice structure;

[0041] S11, select TC4 titanium alloy as the manufacturing material, design the FCCZ lattice structure by CAD software, wherein the lattice structure is designed with a diameter of 1 mm;

[0042] S12. Determine the range of additive manufacturing process parameters according to engineering requirements, including laser power P of 200W-600W, scanning speed V of 100mm / s-500mm / s, scanning spacing H of 80μm-200μm, and powder layer thickness T of 50μm-150μm;

[0043] When the laser power is less than 200W, the titanium alloy powder cannot be completely melted, resulting in poor formation of the lattice structure; when the laser power is greater than 600W, it will cause excessive melting and a large heat-affected zone, affecting the accuracy and performance of the structure; S13. Use the orthogonal design method to select three groups of representative process parameter combinations, use laser selective melting additive manufacturing technology, and use the selected process parameters to manufacture titanium alloy FCCZ lattice structure. Combination 1: laser power P1=300W, scanning speed V1=200mm / s, scanning spacing H1=100μm, powder layer thickness T1=80μm; Combination 2: laser power P2=450W, scanning speed V2=300mm / s, scanning spacing H2=150μm, powder layer thickness T2=100μm; Combination 3: laser power P3=500W, scanning speed V3=400mm / s, scanning spacing H3=120μm, powder layer thickness T3=120μm. During the manufacturing process, strictly control the environmental conditions such as temperature, humidity and oxygen content; S2. Calculate the laser energy density and measure the diameter of the lattice structure pillars; S21. According to the formula Calculate the laser energy density E corresponding to different process parameter combinations, where P is the laser power in Watts (W); V is the scanning speed in millimeters per second (mm / s); H is the scanning spacing in millimeters (mm); T is the powder layer thickness in millimeters (mm): For combination 1, For combination 2, For combination 2, S22, using CT scanning technology to scan the titanium alloy FCCZ lattice structure manufactured under different process parameters, to obtain the tomographic image data of its internal structure, using a medical CT scanner, setting the scanning parameters to a voltage of 120 kV, a current of 200 mA, and a scanning resolution of 0.1 mm;

[0044] S23, importing the scanned data into Avizo software for 3D visualization reconstruction, selecting 10-20 pillars at different positions in each lattice structure for diameter measurement through the image processing and measurement tools of the software, and calculating the average value as the pillar diameter of the lattice structure;

[0045] For the lattice structure manufactured by combination 1, pillars at 15 positions were randomly selected for measurement, and the diameters were [0.8mm, 0.78mm, 0.82mm, 0.79mm, 0.81mm, 0.8mm, 0.77mm, 0.83mm, 0.81mm, 0.79mm, 0.8mm, 0.82mm, 0.78mm, 0.81mm, 0.79mm], and the average value was calculated as:

[0046]

[0047] ; For the lattice structure manufactured by combination 2, pillars at 18 positions were selected for measurement, and the diameters were [0.9mm, 0.88mm, 0.92mm, 0.89mm, 0.91mm, 0.9mm, 0.87mm, 0.93mm, 0.91mm, 0.89mm, 0.9mm, 0.92mm, 0.88mm, 0.91mm, 0.89mm, 0.9mm, 0.91mm, 0.92mm], and the average value was calculated as

[0048] For the lattice structure manufactured by combination three, 16 pillars were selected for measurement, and the diameters were [0.85mm, 0.83mm, 0.87mm, 0.84mm, 0.86mm, 0.85mm, 0.82mm, 0.88mm, 0.86mm, 0.84mm, 0.85mm, 0.87mm, 0.83mm, 0.86mm, 0.84mm, 0.85mm], and the average value was calculated as:

[0049]

[0050] S3. Fitting the relationship between laser energy density and the diameter of the pillars of the additively manufactured titanium alloy lattice structure:

[0051] S31. The calculated laser energy density values ​​and the corresponding average values ​​of the diameter of the lattice structure pillars are sorted into a data file, with the first column as the laser energy density and the second column as the pillar diameter, as follows:

[0052] <![CDATA[Laser energy density E (W / mm 3 )]]> Pillar diameter D(mm) 18.75 0.8 10 0.9 8.68 0.85 ;

[0053] S32, importing the data file into Origin analysis software, selecting the linear regression fitting method, and fitting the relationship between the laser energy density and the pillar diameter of the FCCZ lattice structure of the additively manufactured titanium alloy according to the principle of least squares method. The formula D=0.0083E+0.6838, where D is the pillar diameter and E is the laser energy density;

[0054] S4. Prediction of the diameter of the lattice structure pillars:

[0055] S41. For any new set of process parameters, first follow the formula Calculate its laser energy density E, and then substitute E into the prediction model formula D pred =αE+b, and the corresponding predicted value of the lattice structure pillar diameter D is obtained. pred , the process parameters are laser power P4 = 400W, scanning speed V4 = 250mm / s, scanning spacing H4 = 120μm, and powder layer thickness T4 = 100μm, then the laser energy density E 4 Substitute into the quadratic polynomial regression equation D = -0.00003E 2 +0.014E+0.53 to get the predicted value of the pillar diameter: D pred =-0.00003*13.33 2 +0.014*13.33+0.53≈0.716mm;

[0056] S42. Actually manufacture the titanium alloy FCCZ lattice structure with the new process parameters, and obtain the actual pillar diameter D according to the above measurement method. actual , measured by CT scanning and Avizo software, the actual pillar diameter is D actual =0.7mm;

[0057] S43. Calculate relative error If the relative error is within the acceptable range determined according to the specific engineering requirements, the prediction model is reliable; if the error is large, the process parameter range is readjusted and the relative error is calculated according to the above formula: In this embodiment, the relative error range of the prediction result is between 5% and 10%. The relative error of this prediction is 2.88%, which is within an acceptable range.

[0058] In this embodiment, in S2, the temperature field distribution correction factor is introduced into the laser energy density calculation formula E, so that Where F(T) is the temperature field distribution function, which is used to compensate for the influence of the heat affected zone on the actual laser energy density. T is the local temperature, T 0 is the substrate temperature, T melt is the melting point of titanium alloy, α is a parameter related to temperature gradient, which indicates the speed of temperature drop when moving away from the center of the molten pool, β and γ are coefficients related to the change of thermal conductivity and specific heat capacity with temperature, which are used to adjust the attenuation degree after the temperature exceeds the melting point, and σ is the standard deviation, which is used to control the width of the temperature distribution curve.

[0059] Specifically, the substrate temperature T 0 The melting point of titanium alloy is 30℃. melt The local temperature at different locations is 1720℃ near the center of the molten pool, 1680℃ at 1mm away from the center of the molten pool, 1650℃ at 2mm away from the center of the molten pool, and 1720℃ at 1mm away from the center of the molten pool.

[0060] The temperature field distribution function value near the center of the molten pool:

[0061]

[0062] The temperature field distribution function value 1mm near the center of the molten pool:

[0063]

[0064] The temperature field distribution function value 2mm near the center of the molten pool:

[0065]

[0066] The value of the temperature field distribution function F(T) is calculated based on these data, and then the value in the laser energy density calculation formula is corrected.

[0067] In this embodiment, in S23, artificial intelligence image recognition technology is used to automatically extract the pillar position from the CT scan data and measure the diameter, thereby reducing human error;

[0068] Specifically, the diameter of a pillar of a lattice structure was measured by the traditional manual measurement method, and 15 positions were selected. The average diameter was D 1 =0.85mm, the measurement process took 30 minutes, and then the same lattice structure was measured using artificial intelligence image recognition technology, and the average diameter was D 2 =0.83mm, the measurement process only takes 5 minutes. Compared with and, the difference between the two is within an acceptable range, and the artificial intelligence image recognition technology greatly improves the measurement efficiency.

[0069] In this embodiment, in S32, in addition to linear regression fitting, nonlinear regression analysis is also used, including polynomial regression and exponential regression;

[0070] Specifically, the laser energy densities are [30, 42, 48.5, 58, 67.8], and the corresponding pillar diameters are measured to be [0.93, 1.02, 1.06, 1.09, 1.22]. The linear regression equation is D = 0.0083E + 0.6838, and the determination coefficient R 2 =0.839;

[0071] The polynomial regression fitting equation is D = -0.00003E 2 +0.014E+0.53, coefficient of determination R 2 =0.459;

[0072] The exponential regression fitting equation is D = 0.727e 0.0077E , coefficient of determination R 2 =-1.37. After the above three regression methods, the linear regression has the highest coefficient of determination and is more suitable for this group of data.

[0073] In this embodiment, in S41, an online monitoring system is established to monitor the laser energy density changes in the manufacturing process in real time, and dynamically adjust the prediction model parameters to ensure the accuracy of the prediction value.

[0074] Specifically, a set of process parameters were set for manufacturing, including laser power of 400W, scanning speed of 250mm / s, scanning spacing of 120μm, and powder layer thickness of 100μm. The online monitoring system detected in real time that the laser power fluctuated slightly during the manufacturing process, from 400W to 410W, and the scanning speed dropped to 245mm / s due to equipment reasons. The system dynamically adjusted the prediction model parameters according to real-time data, and recalculated the laser energy density and pillar diameter prediction values. When the online monitoring system was not used, the predicted pillar diameter was 0.8mm, and the actual measured value was 0.78mm, with an error of 2.56%. After using the online monitoring system, the predicted pillar diameter was 0.79mm, with an error of 1.28%. After using the online monitoring system, the prediction error of the pillar diameter was significantly reduced, and the prediction accuracy was improved.

[0075] In this embodiment, in S2, an adaptive algorithm is used to adjust the correction factor according to real-time data in the manufacturing process.

[0076] Specifically, the initial process parameters are laser power 350W, scanning speed 200mm / s, scanning spacing 100μm, and powder layer thickness 80μm. The calculated laser energy density is E 1 During the manufacturing process, the real-time monitoring system detected that the laser power rose to 360W due to equipment fluctuations, and the scanning speed dropped slightly to 195mm / s. The adaptive algorithm adjusted the parameters in the temperature field distribution correction factor based on these real-time data and recalculated the laser energy density as E 2 ,Through the comparison between the two methods, we can see the ,dynamic adjustment effect of the adaptive algorithm on the laser energy density.

[0077] In this embodiment, in S2, the deformation behavior of the lattice structure during the forming process is predicted by combining finite element analysis, and the design is optimized to reduce forming defects.

[0078] Specifically, a set of process parameters were set: laser power 450W, scanning speed 300mm / s, scanning spacing 150μm, powder layer thickness 120μm. The simulation showed that the maximum deformation of the lattice structure during the forming process was 0.4mm, and the stress concentration area was mainly distributed at the connection between the pillars and the nodes. According to the analysis results, the connection method between the pillars and the nodes was improved by optimizing the design, and the transition radius was increased. Finite element analysis was performed again, and it was found that the maximum deformation was reduced to 0.25mm, and the stress concentration was also significantly improved.

[0079] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for predicting the diameter of a pillar of an additively manufactured lattice structure, characterized in that: The steps are as follows: S1. Selecting additive manufacturing process parameters to manufacture a lattice structure; S11, select TC4 titanium alloy as the manufacturing material, design the FCCZ lattice structure by CAD software, wherein the lattice structure is designed with a diameter of 1 mm; S12. Determine the range of additive manufacturing process parameters according to engineering requirements, including laser power P of 200W-600W, scanning speed V of 100mm / s-500mm / s, scanning spacing H of 80μm-200μm, and powder layer thickness T of 50μm-150μm; S13. Three groups of representative process parameter combinations were selected by orthogonal design method, and FCCZ lattice structures of titanium alloy were manufactured by laser selective melting additive manufacturing technology using the selected process parameters. S2. Calculate the laser energy density and measure the diameter of the lattice structure pillars: S21, according to the formula Calculate the laser energy density E corresponding to different process parameter combinations, where P is the laser power in Watts (W); V is the scanning speed in millimeters per second (mm / s); H is the scanning spacing in millimeters (mm); T is the powder layer thickness in millimeters (mm); S22, using CT scanning technology to scan the titanium alloy FCCZ lattice structure manufactured under different process parameters to obtain tomographic image data of its internal structure; S23, importing the scanned data into Avizo software for 3D visualization reconstruction, selecting 10-20 pillars at different positions in each lattice structure for diameter measurement through the image processing and measurement tools of the software, and calculating the average value as the pillar diameter of the lattice structure; S3. Fitting the relationship between laser energy density and the diameter of the pillars of the additively manufactured titanium alloy lattice structure: S31, arranging the calculated laser energy density values ​​and the corresponding average values ​​of the diameters of the pillars of the lattice structure into a data file, with the first column being the laser energy density and the second column being the pillar diameter; S32, importing the data file into Origin analysis software, selecting the linear regression fitting method, and fitting the relationship between the laser energy density and the pillar diameter of the FCCZ lattice structure of the additively manufactured titanium alloy according to the principle of least squares method. The formula D=0.0083E+0.6838, where D is the pillar diameter and E is the laser energy density; S4. Prediction of the diameter of the lattice structure pillars: S41. For any new set of process parameters, first follow the formula Calculate its laser energy density E, and then substitute E into the prediction model formula D pred =0.0083E+0.6838, and the corresponding predicted value of the diameter of the lattice structure pillar D is obtained. pred ; S42. Actually manufacture the titanium alloy FCCZ lattice structure with the new process parameters, and obtain the actual pillar diameter D according to the above measurement method. actual ; S43. Calculate relative error If the relative error is within the acceptable range determined according to specific engineering requirements, the prediction model is reliable; if the error is large, the process parameter range is readjusted.

2. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S2, the temperature field distribution correction factor is introduced into the laser energy density calculation formula E, so that Where F(T) is the temperature field distribution function, which is used to compensate for the influence of the heat affected zone on the actual laser energy density. T is the local temperature, T0 is the substrate temperature, T melt is the melting point of titanium alloy, α is a parameter related to temperature gradient, which indicates the speed of temperature drop when moving away from the center of the molten pool, β and γ are coefficients related to the change of thermal conductivity and specific heat capacity with temperature, which are used to adjust the attenuation degree after the temperature exceeds the melting point, and σ is the standard deviation, which is used to control the width of the temperature distribution curve.

3. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S23, artificial intelligence image recognition technology is used to automatically extract the pillar position from the CT scan data and measure the diameter, thereby reducing human errors.

4. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In the S32, in addition to the linear regression fitting, nonlinear regression analysis is also used, including polynomial regression and exponential regression.

5. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S41, an online monitoring system is established to monitor the laser energy density changes in the manufacturing process in real time, and dynamically adjust the prediction model parameters to ensure the accuracy of the prediction value.

6. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S2, an adaptive algorithm is used to adjust the correction factor according to real-time data in the manufacturing process.

7. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S2, the deformation behavior of the lattice structure during the forming process is predicted by combining finite element analysis, and the design is optimized to reduce forming defects.

8. The method for predicting the diameter of a pillar of an additively manufactured lattice structure according to claim 1, characterized in that: In S43, the relative error range of the prediction result is between 5% and 10%.

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