3D printing control method based on multi-material gradient transition

Abstract

The invention belongs to the technical field of 3D printing, and particularly relates to a 3D printing control method based on multi-material gradient transition, which comprises the steps of model processing, multi-material distribution, path planning, dynamic parameter control, online monitoring and feedback optimization. According to the method, through dynamic mixing of a nonlinear gradient function and multiple materials, limitation of traditional discrete material switching is broken through, continuous smooth transition of material attributes is achieved, printing parameters are dynamically adjusted, and the forming consistency of gradient materials under complex working conditions is remarkably improved; local strengthening is carried out according to the thermodynamic property difference of a multi-material interface, interface embrittlement caused by a traditional single process is avoided, the curing degree is detected in real time through a spectrum sensor, the problem that the curing degree of a traditional light curing process is uncontrollable is solved by combining partitioned UV light intensity adjustment and control, and precise gradient forming of a soft and hard alternate structure is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of 3D printing, and specifically discloses a 3D printing control method based on multi-material gradient transition. Background Art

[0002] In recent years, due to its high design freedom and complex structure manufacturing capabilities, 3D printing technology has been widely used in fields such as aerospace, biomedicine, and flexible electronics.

[0003] The existing technology generates a three-dimensional digital model through CAD software or a 3D scanner, uses slicing software to decompose the three-dimensional model into two-dimensional layers, sets parameters such as layer thickness, filling rate, and support structure, calibrates the equipment to load materials, heats the thermoplastic material to a molten state, extrudes it through a nozzle and stacks it layer by layer, and uses ultraviolet laser or projector to cure the liquid resin. Layers are stacked to form a solid, and complex components can be formed without a support structure. However, it is difficult to achieve continuous gradient transition of material properties, and there are the following defects:

[0004] Sudden change in material interface performance: In traditional multi-material printing, due to sudden changes in properties such as elastic modulus and thermal expansion coefficient at the material interface, stress concentration is easily caused, leading to interface cracking or delamination.

[0005] Lack of gradient transition process: The existing multi-channel extrusion system relies on preset fixed mixing ratios and lacks dynamic regulation capabilities. The G-code generated by traditional slicing software only supports static parameters and is difficult to adapt to the dynamically changing rheological properties in gradient material printing.

[0006] Insufficient process control and defect suppression: The existing technology lacks online monitoring of material distribution, temperature field, and curing degree during the printing process, cannot correct parameter deviations in a timely manner, and the multi-material interface relies on a single process and is not dynamically optimized according to material property differences.

[0007] Defects in photocuring technology: In traditional photocuring printing, the UV light intensity and exposure time are fixed, and it is difficult to achieve a gradient distribution of resin curing degree. Over-curing will cause the material to become brittle, while insufficient curing will lead to structural collapse.

[0008] Therefore, a new control method that integrates dynamic parameter regulation, multi-dimensional online monitoring, and closed-loop feedback optimization is needed to solve the above problems. Summary of the Invention

[0009] In view of this, the present invention proposes a 3D printing control method based on multi-material gradient transition. First, the three-dimensional model of the target object is divided into material distribution regions according to functional requirements, and the gradient transition direction is defined. A non-linear gradient function is generated based on material properties to guide the dynamic adjustment of the mixing ratio of multi-channel extrusion or photocurable resin. The printing path, speed, and temperature are regulated in real time, combined with the interface optimization process of laser power and interlayer annealing. Finally, an optical sensor and an infrared thermal imager are integrated to online monitor the material distribution and temperature field, and the feedback is sent to the control system to dynamically correct the parameters, realizing the closed-loop control of material gradient, curing accuracy, and interface strength, ultimately avoiding thermal deformation and pore defects and ensuring the functional reliability of complex components.

[0010] The object of the present invention can be achieved by the following technical solutions:

[0011] A 3D printing control method based on multi-material gradient transition, including a model processing end, a material distribution end, a printing control end, a printing output end, and a printing environment acquisition end, is characterized in that it specifically includes the following steps:

[0012] S1. Model processing: Based on the model processing end, the number of materials and the single material properties of the 3D model of the target object are collected, and the corresponding printing gradient transition direction is defined according to the single material properties.

[0013] S2. Multi-material distribution: According to the printing gradient transition direction, the material distribution end calculates the mixing ratio of multiple single materials in cooperation with the gradient transition function and generates the corresponding instruction text to the printing control end.

[0014] S3. Path planning: The printing path instruction text is output to the printing output end, where the printing path instruction text includes printing path parameters, speed parameters, layer thickness parameters, and temperature parameters.

[0015] S4. Dynamic parameter control: During the printing process, the laser power and the interlayer annealing temperature are dynamically adjusted at the interfaces of multiple single materials.

[0016] S5. Online monitoring and feedback optimization: The material distribution and temperature distribution during the printing process are collected through the environment acquisition end, analyzed according to the collected data, and the gradient function and printing parameters are dynamically corrected through the analysis results.

[0017] Combined with all the above technical solutions, the positive effects of the present invention are as follows:

[0018] 1. Through the non-linear gradient function and multi-material dynamic mixing, the present invention breaks through the limitations of traditional discrete material switching, realizes the continuous and smooth transition of material properties, and completely eliminates the stress concentration and functional mismatch caused by sudden changes in interface performance.

[0019] 2. Based on real-time sensor feedback, the present invention dynamically adjusts parameters such as extrusion ratio, UV light intensity, and temperature field, solves the limitations of static parameters of traditional curing G-code, and significantly improves the forming consistency of gradient materials under complex working conditions.

[0020] 3. Through dynamic regulation of laser power and interlayer annealing process, the present invention locally strengthens the thermodynamic property differences at the interfaces of multiple materials, avoiding interface embrittlement caused by traditional single processes.

[0021] 4. The present invention uses a spectral sensor to detect the degree of curing in real time and combines zonal UV light intensity regulation to break through the problem of uncontrollable degree of curing in traditional photocuring processes and achieve precise gradient forming of soft-hard alternating structures. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for describing the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Attached Figure 1 is the implementation step diagram of the present invention.

[0024] Attached Figure 2 is the work flow diagram of the present invention.

[0025] Attached Figure 3 is the material distribution step diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0027] See Figure 1 As shown, the present invention proposes a 3D printing control method based on multi-material gradient transition, which includes model processing, multi-material distribution, path planning, dynamic parameter control, online monitoring and feedback optimization steps. The present invention includes a model processing terminal, a material distribution terminal, a printing control terminal, a printing output terminal, and a printing environment acquisition terminal, as Figure 2 shown.

[0028] The specific implementation steps of the present invention include the following steps:

[0029] S1. Model Processing: Based on the model processing terminal, collect the material quantity and single material properties of the 3D model of the target object, and define the corresponding printing gradient transition direction according to the single material properties.

[0030] Specifically, determine the functional area types according to the product performance requirements, such as high-strength areas and flexible areas, clarify the mechanical property targets of each area, and identify the stress concentration areas as high-strength areas and the dynamic activity areas as flexible areas through finite element analysis.

[0031] Utilize the geometric modeling function of the CAD system to perform preliminary spatial segmentation on the 3D model, mark the physical boundaries of different areas, and specify the main material parameters for each functional area in the software, such as metals and polymers, directly call through the material library or customize the parameters, and determine the transition direction based on the material property changes, including structural gradient transition, composition gradient transition, and performance gradient transition.

[0032] Among them, the structural gradient transition is specifically: the porosity and grain size of the material microstructure change continuously along a specific path. For example, the grain size in the metal-ceramic composite layer decreases from the dense area to the porous area, improving the impact resistance.

[0033] Among them, the composition gradient transition is specifically: the proportion of material components changes continuously along a specific direction. For example, the mixing ratio of titanium alloy and ceramic decreases from the high-temperature contact surface to the low-temperature area to balance the thermal stress.

[0034] Among them, the performance gradient transition is specifically: the mechanical / physical properties such as elastic modulus and thermal conductivity change gradually according to the requirements. For example, the conductivity of flexible electronic devices increases along the electrode contact direction to achieve efficient energy transmission.

[0035] It should be noted that based on material properties such as elastic modulus and thermal conductivity, a non-linear gradient function is generated, and the function includes linear, exponential, or custom non-linear distributions.

[0036] Specifically, the linear gradient function is specifically:

[0037]

[0038] Among them, E(x) is the material property at position x, such as elastic modulus and thermal conductivity; E1 and E2 are the material property values at the starting point and the ending point; L is the total length of the gradient transition area; x is the coordinate of the current calculation point in the transition area, from the starting point 0 to the ending point L.

[0039] It is applicable to scenarios where the material properties need to change uniformly, such as the interlayer transition design of gradient composites, such as the thermal expansion matching layer of metal-ceramic composite structures.

[0040] Among them, the exponential gradient function is specifically:

[0041]

[0042] Where k is the attenuation / enhancement coefficient, which controls the steepness of the gradient change; k>0 indicates that the material property increases exponentially with the increase of x; k<0 indicates that the property decays exponentially with the increase of x.

[0043] It is applicable to the situation where the material properties change rapidly and significant fluctuations in properties in local regions are required. The exponential function can quickly adjust the material properties to adapt to the non-linear temperature field or stress field distribution.

[0044] For example, in the heat dissipation layer of a thermal management device, the thermal conductivity drops sharply over a short distance from copper to an insulating material.

[0045] Another example is at the interface between a brittle material such as ceramics and a ductile material such as titanium alloy, where the stress concentration is reduced by a negative exponential function.

[0046] Among them, for the custom non-linear function, taking the quadratic function as an example, it is specifically:

[0047] E(x) = ax 2 + bx + c;

[0048] Where a, b, and c are coefficients fitted from experimental or simulation data, and need to satisfy E(0) = E1, E(L) = E2 and additional constraints, such as specifying the property value at the midpoint.

[0049] For example, assume that a transition zone with L = 8 mm needs to be designed, and the boundary conditions are:

[0050]

[0051] Among them, E(4) = 30 GPa is the specified midpoint value, and a system of equations is established:

[0052]

[0053] It is solved that a = 1.875, b = -18.75, c = 100, and the gradient function is E(x) = 1.875x 2 - 18.75x + 100.

[0054] It is applicable to complex stress field matching, reverse fitting the material distribution according to the finite element analysis results, such as in the non-uniform load area of aerospace parts; or in bio-inspired structures, mimicking the non-linear property distribution of natural materials such as bones and wood.

[0055] Verify the gradient function, and the process includes parameter sensitivity analysis, prototype testing, and optimization iteration.

[0056] Among them, the parameter sensitivity analysis is specifically as follows: Through COMSOL multi-physics simulation, the influence of different k values on the maximum stress is tested.

[0057] Among them, the prototype test is specifically as follows: 3D print gradient specimens, conduct three-point bending tests, and compare the simulated and measured strain data.

[0058] Among them, the optimization iteration is specifically as follows: Based on the error feedback, adjust the function parameters, such as correcting the k value from 2.5 to 3.1.

[0059] S2. Multi-material distribution: According to the printing gradient transition direction, the material distribution end calculates the mixing ratios of multiple single materials in combination with the gradient transition function and generates the corresponding instruction text to the printing control end, as Figure 3 shown. The specific steps are as follows:

[0060] A1. Select the gradient function type: According to the material property requirements, such as uniform transition or rapid decay, select linear, exponential or custom functions;

[0061] A2. Define the mixing ratio mapping relationship: Convert the material properties into a mixing ratio formula;

[0062] A3. Numerical calculation and verification: Verify the rationality of the mixing ratio through simulation or experiment, and iteratively optimize the gradient function parameters if necessary;

[0063] A4. Generate instruction text: Generate the mixing ratio formula into instruction text to the printing control end;

[0064] It should be noted that: The principle of selecting the gradient function type includes giving priority to mechanical requirements, manufacturability, and thermo-mechanical coupling analysis.

[0065] Among them, giving priority to mechanical requirements is specifically as follows: Select gentle gradients, linear or low-k exponential in high stress concentration areas to avoid mutations.

[0066] Among them, manufacturability is specifically as follows: Stereolithography printing is suitable for steep gradients and high k values, while extrusion printing needs to limit the gradient change rate.

[0067] Among them, thermo-mechanical coupling analysis is specifically as follows: For temperature-sensitive materials, it is necessary to verify the stability of the gradient function under heating.

[0068] It should be noted that the conversion of the mixing ratio formula is as follows:

[0069] The linear gradient mixing ratio formula is specifically as follows:

[0070]

[0071] Derived from the requirement of uniform distribution of material properties in space, its core is to achieve a smooth transition between two materials through linear interpolation.

[0072] Assume that the material property E(x) varies linearly within the transition interval [0, L], and is actually mapped to a percentage through normalization, where 0% corresponds to pure material 1 and 100% corresponds to pure material 2. This formula directly relates the material property to the mixing ratio and is applicable to the feeding control of extrusion-based 3D printing.

[0073] The exponential gradient mixing ratio is specifically as follows:

[0074]

[0075] For scenarios that require rapid property changes, such as buffer layers or thermal stress concentration areas, the exponential gradient.

[0076] Based on the exponential decay / growth model of material properties, the parameter k controls the steepness of the gradient. For example, in the transition from carbon fiber to rubber, k = 2 can cause the mixing ratio to change rapidly within a short distance, effectively reducing the interfacial stress.

[0077] The specific formula for the mixing ratio corresponding to the custom non-linear function is as follows:

[0078]

[0079] It is necessary to fit the coefficients a, b, c through the boundary conditions E(0) = E1 and E(L) = E2, and then substitute the coordinates x of the target point to calculate the mixing ratio.

[0080] It should be noted that the mixing ratio verification method includes numerical simulation verification and experimental calibration.

[0081] Among them, the numerical simulation verification is specifically as follows: Calculate the derivative of the gradient function to verify whether the mixing ratio conforms to the change trend of the material property.

[0082] Among them, the experimental calibration is specifically as follows: Sample and test the gradient transition area, and compare the errors between the actual material properties such as hardness and conductivity and the theoretical calculated values.

[0083] It should be noted that the conversion of material properties to printing parameters is specifically as follows:

[0084] Density and feeding ratio refer to the mixing ratio formula Among them, S1 and S2 are the material densities, and R is the set ratio. This formula can be used for the mixing of calcium carbonate and PVC in PVC floor tiles.

[0085] S3, Path planning: Output the print path instruction text to the print output terminal, where the print path instruction text includes print path parameters, speed parameters, layer thickness parameters, and temperature parameters;

[0086] Among them, the dynamic adjustment of layer thickness is specifically as follows:

[0087] In regions where material properties change drastically, such as the hard-to-soft transition zone, automatically reduce the layer thickness and improve the structural accuracy through denser deposition.

[0088] Among them, the path overlap optimization is specifically as follows:

[0089] At the junction of two materials, the printing path will be designed with an overlapping area of 10 - 15%, ensuring sufficient material mixing and avoiding gaps at the interface.

[0090] Among them, the conversion of elastic modulus gradient to extrusion speed is specifically as follows:

[0091]

[0092] Among them, E(x) is the elastic modulus at the current position, such as the gradient change from mGPa to nGPa; E r is the reference elastic modulus, usually taking the initial value of the substrate; V b is the base extrusion speed, determined by the rheological properties of the material.

[0093] Based on the rheological properties of non-Newtonian fluids, the square root relationship of elastic modulus reflects the non-linear effect of shear rate on fluidity, ensuring stable interlayer bonding of the material during deposition. The higher the elastic modulus of the material, that is, the harder the material, the lower the extrusion speed needs to be accordingly; for example, when printing from a high-modulus cermet to a low-modulus polymer, the extrusion speed will gradually increase from low speed to high speed, avoiding interlayer fracture caused by excessive extrusion resistance of high-modulus materials.

[0094] Among them, the conversion of thermal conductivity gradient to temperature control is specifically as follows:

[0095]

[0096] Among them, K(x) is the local thermal conductivity of the material, K max is the maximum thermal conductivity in the material system, T g is the glass transition temperature, T m is the melting temperature. This formula ensures a stable transition of the material between the glass transition temperature T g and the melting temperature T m to prevent thermal deformation.

[0097] The square term of thermal conductivity compensates for the thermal hysteresis effect of thermally sensitive materials, preventing interlayer shrinkage cracking in low-temperature regions due to excessive heat dissipation. The higher the thermal conductivity of the material, that is, the faster the heat dissipation, the higher the printing temperature needs to be appropriately. For example, copper alloys have fast heat dissipation, and the heating plate temperature needs to be increased to compensate for the rapid heat dissipation and prevent warping caused by material cooling and shrinkage.

[0098] S4, Dynamic parameter control: During the printing process, dynamically adjust the laser power and interlayer annealing temperature at the interfaces where multiple single materials alternate;

[0099] The specific formula for dynamically adjusting the laser power is as follows:

[0100]

[0101] where μ is the laser absorption rate of the material, V s is the laser scanning speed, ρ·C p is the volumetric specific heat capacity of the material, ΔT is the target temperature rise value, and A s is the spot area.

[0102] The depth control of the interface molten pool is achieved through energy density balance, avoiding incomplete fusion caused by insufficient power or thermal cracks caused by excessive power. Materials with high absorption rates use lower laser powers, while materials with low absorption rates need to increase the power.

[0103] The specific formula for the interlayer annealing temperature gradient is as follows:

[0104] T a = T g1 + x(T g2 - T g1 )·(1 - e -kt );

[0105] where T g1 , T g2 are the glass transition temperatures of the two materials, k is the annealing rate constant, t is the annealing time, the exponential decay function simulates the polymer chain relaxation process, the value of the coefficient x is between 0.7 - 0.8, optimizing the balance of crystallinity and residual stress. The greater the layer thickness, the longer the annealing time, ensuring sufficient reorganization of the internal molecular chains of the material.

[0106] S5. On-line monitoring and feedback optimization: The environmental acquisition terminal collects the material distribution and temperature distribution during the printing process, analyzes the collected data, and dynamically corrects the gradient function and printing parameters based on the analysis results.

[0107] The environmental acquisition terminal includes an optical sensor, an infrared thermal imager, and a spectral sensor.

[0108] It should be noted that the optical sensor monitors the material distribution, including high-precision material tracking and defect warning intervention.

[0109] The high-precision material tracking is specifically as follows: During the printing process, a laser line scanner or a structured light sensor is used to capture the surface topography of the deposited layer in real time. For example, when it is detected that there is a local depression in the polymer material due to insufficient extrusion, the system immediately increases the extrusion speed in this area or repeats the filling to ensure uniform material distribution.

[0110] In metal-ceramic gradient printing, a high-resolution camera combined with an image recognition algorithm is used to accurately identify the transition region between the two materials. If the interface deviation exceeds the preset threshold, the nozzle switching timing or path offset is automatically adjusted to ensure the geometric accuracy of the gradient transition.

[0111] Among them, defect warning and intervention are specifically as follows: Using X-ray real-time imaging or ultrasonic flaw detection technology, non-destructive detection of internal pores in the printed layer. When the porosity exceeds the critical value, the system triggers a pause and refills the defective area, or adjusts the subsequent layer thickness and path density.

[0112] The propagation of microscopic cracks during the printing process is tracked by a high-speed camera. For example, when sintering ceramic materials at high temperature, if the crack length exceeds the threshold, the laser power is immediately reduced and the interlayer cooling time is extended to inhibit the concentration of thermal stress.

[0113] It should be noted that the dynamic regulation of the temperature field by the infrared thermal imager includes global temperature visualization and rapid response to thermal anomalies.

[0114] Among them, global temperature visualization is specifically as follows: The infrared thermal imager scans the printing area at a frequency of 30 frames per second to generate a thermal map of the temperature field. For example, in titanium alloy printing, if a sudden temperature drop is detected in a certain area, the system automatically increases the laser power or reduces the scanning speed at that position to ensure a consistent melt pool depth.

[0115] For polymer-metal composite structures, maintain a high temperature in the metal area to promote interface diffusion, and at the same time control the temperature in the polymer area below the glass transition temperature to prevent material softening and deformation.

[0116] Among them, the rapid response to thermal anomalies is specifically as follows:

[0117] When the local temperature exceeds the melting point of the material, immediately stop the energy input and start forced air cooling to avoid melt pool collapse or material evaporation.

[0118] For material combinations with large differences in thermal conductivity, such as copper to plastic, when rapid heat dissipation is detected in the copper area, dynamically increase the power of the auxiliary heating plate to compensate for heat loss.

[0119] It should be noted that the spectral feedback control in the photocuring printing includes on-line detection of resin curing degree and ensuring interface curing consistency.

[0120] Among them, on-line detection of resin curing degree is specifically as follows:

[0121] Using a UV-visible spectral sensor, the absorbance change of the resin at a specific wavelength is monitored in real time. When the absorbance drops to the threshold, it indicates that the resin has been fully cured, and the system automatically turns off the UV light source in that area to prevent brittleness caused by over-crosslinking.

[0122] In functional gradient hydrogel printing, by controlling the UV light intensity in zones, a high light intensity is used in the hard regions to accelerate curing, and the light intensity is reduced in the soft regions to maintain elasticity, achieving a continuous transition in mechanical properties.

[0123] Among them, ensuring the consistency of interface curing is specifically as follows:

[0124] At the junction of the two resins, the slope of the UV light intensity is dynamically adjusted according to spectral data. For example, during the transition from a high-hardness resin to a low-hardness resin, the light intensity decreases to ensure a smooth change in the degree of curing.

[0125] For free-radical curing resins exposed to air, the surface oxygen inhibition effect is identified through real-time spectral data, and the light intensity in the edge region is specifically increased to eliminate the uncured surface layer.

[0126] It should be noted that the closed-loop feedback and parameter optimization logic include data fusion decision-making and dynamic gradient function correction.

[0127] Among them, data fusion and decision-making are specifically as follows:

[0128] Optical topography data, temperature field distribution, and spectral information are input into the central processing unit, and a comprehensive control instruction is generated through a weighted algorithm. For example, when it is detected that the temperature is too high and the surface topography is abnormal, the cooling instruction is preferentially executed instead of the feeding operation.

[0129] Based on historical printing data, a model is trained to predict the best parameter combination. For example, after continuously printing several layers, the system automatically recommends reducing the scanning speed to match the cumulative thermal effect.

[0130] Among them, dynamic gradient function correction is specifically as follows:

[0131] Reprogramming of material distribution: When it is monitored that the actual material distribution deviates from the designed gradient curve, the extrusion ratio or photocuring parameters of the subsequent path are updated in real time to gradually approach the target gradient.

[0132] For irreversible defects, an emergency mode is activated to reprogram the remaining structure. For example, in bone scaffold printing, the damaged area is skipped, and the subsequent layers automatically supplement the mechanical support path through topological optimization.

Claims

1. A 3D printing control method based on multi-material gradient transition, comprising a model processing end, a material distribution end, a printing control end, a printing output end, and a printing environment acquisition end, characterized in that: The specific steps include: S1. Model processing: The material quantity and single material properties of the 3D model of the target object are collected based on the model processing end, and the corresponding printing gradient transition direction is defined according to the single material properties; S2. Multi-material allocation: According to the printing gradient transition direction, the material allocation end calculates the mixing ratio of multiple single materials with the gradient transition function, and generates corresponding instruction text to the printing control end; S3, path planning: outputting the printing path instruction text to the printing output terminal, wherein the printing path instruction text includes printing path parameters, speed parameters, layer thickness parameters and temperature parameters; S4, Dynamic parameter control: During the printing process, the laser power and interlayer annealing temperature are dynamically adjusted at multiple single material alternating interfaces; S5. Online monitoring and feedback optimization: The material distribution and temperature distribution of the printing process are collected through the environment collection terminal, and the collected data are analyzed. The gradient function and printing parameters are dynamically corrected based on the analysis results.

2. A 3D printing control method based on multi-material gradient transition according to claim 1, characterized in that: The definition corresponds to the gradient transition direction as follows: Through finite element analysis, stress concentration areas are identified as high-strength areas, and dynamic activity areas are identified as flexible areas. The main material parameters of each functional area are collected through the data acquisition terminal, and the transition direction is determined based on the change of material properties. The transition direction includes structural gradient transition, composition gradient transition and performance gradient transition; The structural gradient transition is specifically: the porosity and grain size of the material microstructure change continuously along a specific path; The composition gradient transition is specifically: the proportion of material components changes continuously along a specific direction; The performance gradient transition is specifically as follows: the elastic modulus and thermal conductivity of mechanical / physical properties change gradually according to demand.

3. A 3D printing control method based on multi-material gradient transition according to claim 1, characterized in that: The specific steps of the multi-material allocation strategy are as follows: A1. Select the gradient function type: select linear, exponential or custom function according to the material performance requirements, such as uniform transition or rapid attenuation; A2. Define the mixing ratio mapping relationship: convert material properties into mixing ratio formulas; A3. Numerical calculation and verification: verify the rationality of the mixing ratio through simulation or experiment, and iteratively optimize the gradient function parameters when necessary; A4. Generate instruction text: Generate instruction text from the mixing ratio formula to the print control terminal.

4. A 3D printing control method based on multi-material gradient transition as claimed in claim 3, characterized in that: The specific principle for selecting the gradient function type is: For high stress concentration areas, choose gentle gradients, linear or low k-value indexes; Steep gradients and high k-values ​​are suitable for photocuring printing; For temperature-sensitive materials, verify the stability of the gradient function under increasing temperature; The mixing ratio formula is converted as follows: The linear gradient mixing ratio formula is as follows: It comes from the requirement of uniform distribution of material properties in space. Its core is to achieve smooth transition between two materials through linear interpolation. The exponential gradient mixing ratio is as follows: Used in scenarios where rapid attribute changes are required; The mixing ratio formula corresponding to the custom nonlinear function is as follows: The mixing ratio verification method is specifically as follows: Calculate the derivative of the gradient function to verify whether the mixing ratio conforms to the trend of material property changes; conduct sampling tests on the gradient transition area to compare the errors between the actual material properties such as hardness and conductivity and the theoretical calculated values; The material properties are converted into printing parameters as follows: Density and feed ratio refer to the mixing ratio formula Where S1 and S2 are material densities, and R is the set ratio.

5. A 3D printing control method based on multi-material gradient transition according to claim 1, characterized in that: The printing path instruction text includes printing path parameters, speed parameters, layer thickness parameters and temperature parameters: The dynamic adjustment of layer thickness is as follows: Automatically reduce layer thickness in areas where material properties change dramatically, such as hard-to-soft transitions, improving structure accuracy through denser deposition; The path overlap optimization is as follows: At the junction of the two materials, the printing path will be designed with a 10-15% overlap area to ensure that the materials are fully mixed and avoid gaps at the interface; The elastic modulus gradient is converted into extrusion speed as follows: Where E(x) is the elastic modulus at the current position, E r is the reference elastic modulus, V b Is the basic extrusion speed; The square root relationship of the elastic modulus reflects the nonlinear effect of shear rate on fluidity. The higher the elastic modulus of the material, i.e., the softness and hardness, the lower the extrusion speed needs to be. The thermal conductivity gradient is converted into temperature control as follows: Where K(x) is the local thermal conductivity of the material, K max is the maximum thermal conductivity in the material system, T g is the glass transition temperature, T m is the melting temperature, and the square term of thermal conductivity compensates for the thermal hysteresis effect of heat-sensitive materials. The higher the thermal conductivity of the material, that is, the faster the heat dissipation, the higher the printing temperature needs to be.

6. A 3D printing control method based on multi-material gradient transition according to claim 1, characterized in that: The laser power dynamic adjustment formula is specifically: Where μ is the laser absorptivity of the material, V s is the laser scanning speed, ρ·C p is the volume specific heat capacity of the material, ΔT is the target temperature rise value, A s is the spot area, The interface molten pool depth is controlled by energy density balance. High absorption materials use lower laser power, while low absorption materials require higher power. The interlayer annealing temperature gradient formula is specifically: T a =T g1 +x(T g2 -T g1 )·(1-e -kt ); Where T g1 , T g2 is the glass transition temperature of the two materials, k is the annealing rate constant, t is the annealing time, the exponential decay function simulates the polymer chain relaxation process, the value of the coefficient x is between 0.7-0.8, the thicker the layer, the longer the annealing time.

7. A 3D printing control method based on multi-material gradient transition according to claim 1, characterized in that: The environment collection end includes an optical sensor, an infrared thermal imager and a spectral sensor; The optical sensor monitoring material is divided into the following steps: High-precision material tracking: During the printing process, laser line scanning or structured light sensors are used to capture the surface morphology of the deposited layer in real time. High-resolution cameras combined with image recognition algorithms can accurately identify the transition area between two materials. If the interface offset exceeds the preset threshold, the nozzle switching timing or path offset is automatically adjusted. Defect warning and intervention: Use X-ray real-time imaging or ultrasonic flaw detection technology to perform non-destructive detection of the internal pores of the printed layer. When the porosity exceeds the critical value, the system triggers a pause and refills the defective area, or adjusts the subsequent layer thickness and path density; track the micro crack propagation during the printing process through a high-speed camera; The infrared thermal imager dynamically controls the temperature field as follows: Global temperature visualization: An infrared thermal imager is used to scan the printing area at a frequency of x frames per second to generate a temperature field thermogram; for polymer-metal composite structures, high temperatures are maintained in the metal area to promote interface diffusion, while the temperature in the polymer area is controlled below the glass transition temperature; Rapid response to thermal anomalies: When the local temperature exceeds the melting point of the material, the energy input is immediately stopped and forced air cooling is started; for material combinations with large differences in thermal conductivity, such as copper to plastic, when excessive heat dissipation is detected in the copper area, the power of the auxiliary heating plate is dynamically increased to compensate for heat loss; The spectral feedback control in light-curing printing is as follows: Online detection of resin curing degree: Using UV-visible spectrum sensor, the absorbance change of resin at a specific wavelength is monitored in real time. When the absorbance drops to the threshold, it indicates that the resin has been fully cured. The system automatically turns off the UV light source in this area to prevent brittleness caused by excessive cross-linking. In functional gradient hydrogel printing, UV light intensity is controlled by partitioning, high light intensity is used to accelerate curing in hard areas, and light intensity is reduced in soft areas to maintain elasticity; Guaranteeing the consistency of interface curing: At the interface between two resins, the slope of UV light intensity is dynamically adjusted according to the spectral data; for free radical curing resins exposed to air, the surface oxygen inhibition effect is identified through real-time spectral data, and the light intensity in the edge area is specifically increased to eliminate the uncured surface layer. The closed-loop feedback and parameter optimization logic are as follows: Data fusion and decision-making: Input optical morphology data, temperature field distribution and spectral information into the central processor, generate comprehensive control instructions through weighted algorithms; train models based on historical printing data to predict the best parameter combination; Dynamic gradient function correction: When it is monitored that the actual material distribution deviates from the designed gradient curve, the extrusion ratio or photocuring parameters of the subsequent path are updated in real time to gradually approach the target gradient; for irreversible defects, the emergency mode is activated to replan the remaining structure.

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