3D printing precision optimization method and system based on low-light modulation

Abstract

The invention provides a 3D printing precision optimization method and system based on low-light modulation, and relates to the technical field of material forming, and the method comprises the following steps: carrying out structure self-adaptive partition dicing on a 3D mathematical structure, and determining a plurality of partition structures; developing a light modulator to perform microscopic modulation on the layer projection pattern, and determining a first laser parameter; a base coordinate system based on a 3D mathematical structure is established, printing track decision making is conducted on the multiple partition structures, multi-axis coordinate system conversion under multi-laser-head combined driving is executed, and a second printing track is determined; the first laser parameter and the second printing track are coupled, and multi-axis co-drive printing control is executed; and if heterogeneous integration exists, micro-system deployment is carried out. The technical problems that in the prior art, due to the fact that a coupling mechanism is lacked between a material forming path and a structure level, the printing structure precision is limited, and heterogeneous structures are difficult to integrate are solved, the printing precision is improved, and the collaborative forming capacity of a complex structure is enhanced.

Description

Technical Field

[0001] This application relates to the technical field of material forming, and particularly relates to a method and system for optimizing 3D printing accuracy based on micro-light modulation. Background Art

[0002] With the rapid development of additive manufacturing technology in the fields of high-precision devices, micro-structural components, and multi-material composite components, higher requirements are put forward for the three-dimensional printing forming accuracy and structural integration ability. The existing three-dimensional printing methods based on the layer-by-layer forming principle generally adopt the strategies of fixed-thickness slicing and unified path planning, and insufficiently utilize the spatial features such as the inter-layer correlation and local structure repeatability of the target structure, making it difficult to adapt to three-dimensional entities with complex hierarchical features. In addition, during the existing material forming process, the path planning and control strategies are usually independent of the structural information evolution process, resulting in prominent problems such as cumulative structural errors, blurred details, and uneven local material stacking. Especially in the scenarios involving heterogeneous structures or multi-material collaborative printing, the traditional forming methods lack a targeted regulation mechanism and cannot achieve effective coordination in the forming path and material shaping process, further restricting the application expansion of complex micro-structures and multi-functional integrated structures. Summary of the Invention

[0003] This application provides a method and system for optimizing 3D printing accuracy based on micro-light modulation, which solves the technical problem that the existing technology has limited printing structure accuracy and difficult heterogeneous structure integration due to the lack of a coupling mechanism between the material forming path and the structural hierarchy, and achieves the technical effect of improving 3D printing accuracy and enhancing the collaborative forming ability of complex structures.

[0004] In view of the above problems, on the one hand, this application provides a method for optimizing 3D printing accuracy based on micro-light modulation. The method includes: obtaining the 3D mathematical structure of the printed product, performing structure adaptive partition cutting according to layer isomorphism to determine a plurality of partition structures, where each partition structure corresponds to a layer projection pattern; developing a light modulator in the control system of the 3D printing device, performing microscopic modulation under optical magnification on the layer projection pattern to determine the laser projection parameters and reduction magnification, as the first laser parameters; establishing a base coordinate system based on the 3D mathematical structure, making a printing trajectory decision for the plurality of partition structures based on the layer projection pattern, performing multi-axis coordinate system conversion under the drive of multiple laser heads to determine the second printing trajectory; coupling the first laser parameters and the second printing trajectory, and driving the 3D printing device to perform multi-axis co-drive printing control under layer projection stacking; where, if there is heterogeneous integration, performing micro-system deployment on the coupled first laser parameter - second printing trajectory.

[0005] On the other hand, the present application also provides a 3D printing accuracy optimization system based on low-light modulation. The system includes: a structure partitioning module, configured to obtain the 3D mathematical structure of a printed product, perform structure self-adaptive partitioning and cutting according to layer isomorphism, and determine a plurality of partition structures, where each partition structure corresponds to a layer projection pattern; a micro modulation module, configured to develop an optical modulator in the control system of the 3D printing device, perform micro modulation under optical magnification on the layer projection pattern, and determine laser projection parameters and reduction ratios as the first laser parameters; a trajectory decision module, configured to establish a base coordinate system based on the 3D mathematical structure, perform printing trajectory decision on the plurality of partition structures based on the layer projection pattern, perform multi-axis coordinate system conversion under the drive of multiple laser heads, and determine a second printing trajectory; a printing control module, configured to couple the first laser parameters and the second printing trajectory, and drive the 3D printing device to perform multi-axis co-drive printing control under layer projection stacking. If there is heterogeneous integration, perform micro-system deployment on the coupled first laser parameter - second printing trajectory.

[0006] One or more technical solutions provided in the present application have at least the following beneficial effects: By obtaining the 3D mathematical structure of the printed product and performing structure self-adaptive partitioning and cutting according to layer isomorphism, the complex structure of the printed product is decomposed into multiple partition structures. Each partition structure corresponds to a layer projection pattern, providing a prerequisite for subsequent differential control and parallel path planning. By developing an optical modulator in the control system of the 3D printing device, performing micro modulation under optical magnification on the layer projection pattern, and determining laser projection parameters and reduction ratios as the first laser parameters, the layer pattern can be accurately formed at the micro scale, providing physical support for subsequent high-precision path control. By establishing a base coordinate system based on the 3D mathematical structure, performing printing trajectory decision on the plurality of partition structures based on the layer projection pattern, performing multi-axis coordinate system conversion under the drive of multiple laser heads, and determining a second printing trajectory, accurate scheduling of multiple regional paths is ensured, effectively supporting the efficient collaborative printing of complex structures. By coupling the first laser parameters and the second printing trajectory, driving the 3D printing device to perform multi-axis co-drive printing control under layer projection stacking, the synergistic effect of forming parameters and trajectory strategies is realized, ensuring the accurate stacking and forming of material layers under multi-axis dynamic control. If there is heterogeneous integration, the control fusion problem between structures such as multi-scale and multi-materials is solved through the micro-system deployment strategy, enhancing the ability to adapt to complex application scenarios.

[0007] In summary, the present application realizes the intelligent division and regional mapping of three-dimensional structural information by introducing a structure adaptive partitioning mechanism based on layer isomorphism; significantly improves the resolution accuracy of pattern boundaries during the material forming process by performing microscopic modulation on the partition layer patterns; enhances the coordination and spatial consistency of the forming path by combining multi-axis coordinate system control and multi-path linkage strategies; and realizes high-precision multi-axis collaborative printing by coupling the laser parameters and trajectory control information, improving the dynamic consistency and structural restoration ability during the printing execution process. At the same time, for the problem of heterogeneous structure integration, a micro-system level deployment method is proposed, effectively improving the integration and printing adaptation ability of complex material structures, thereby achieving the technical effects of improving the 3D printing accuracy and enhancing the collaborative forming ability of complex structures.

[0008] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented in accordance with the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically exemplified below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a schematic flow chart of a 3D printing accuracy optimization method based on micro-light modulation provided by an embodiment of the present application.

[0010] Figure 2 It is a schematic flow chart of making a printing trajectory decision for multiple partition structures based on layer projection patterns in a 3D printing accuracy optimization method based on micro-light modulation provided by an embodiment of the present application.

[0011] Figure 3 It is a schematic logical diagram of a 3D printing accuracy optimization system based on micro-light modulation provided by an embodiment of the present application.

[0012] Description of the reference numerals: Structure partitioning module 10, Microscopic modulation module 20, Trajectory decision module 30, Printing control module 40. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] By providing a 3D printing accuracy optimization method and system based on micro-light modulation in an embodiment of the present application, the technical problem in the prior art that the printing structure accuracy is limited and the integration of heterogeneous structures is difficult due to the lack of a coupling mechanism between the material forming path and the structural level is solved, and the technical effects of improving the 3D printing accuracy and enhancing the collaborative forming ability of complex structures are achieved.

[0014] Embodiment 1, as Figure 1 shown, an embodiment of the present application provides a 3D printing accuracy optimization method based on micro-light modulation, and the method includes: Step S1: Obtain the 3D mathematical structure of the printed product, perform structure-adaptive partition cutting according to layer isomorphism, and determine multiple partition structures, where each partition structure corresponds to a layer projection pattern.

[0015] Specifically, the 3D mathematical structure refers to the 3D model data obtained through methods such as CAD modeling and 3D scanning, often expressed in formats such as STL, OBJ, and STEP, providing a geometric basis for subsequent printing path calculation. First, import the 3D model file of the printed product, and use a computational geometry library (such as OpenCASCADE, CGAL) to extract the geometric topology information of the model. Subsequently, perform layer-by-layer scanning through a layer slicing engine, and combine shape recognition algorithms (such as hash-based graph structure comparison and shape context matching) to determine the isomorphism between each sliced layer, that is, the similarity or repeatability of each sliced layer in terms of structural form, size, or topology. If several consecutive layers or local regions are detected to have similar contours or topologies, they are grouped together to form multiple partition structures. Each partition structure corresponds to a layer projection pattern, that is, the two-dimensional forming contour pattern of each partition structure, which is a black-and-white image. Taking the printing of a honeycomb structure bracket as an example, multiple repeating honeycomb units form the entire volume model, and this structure shows periodic isomorphic layering in the vertical direction. Through the layer slicing engine, combined with the shape recognition algorithm, each group of repeating honeycomb structures is automatically recognized and sliced into an independent partition, corresponding to a pattern unit.

[0016] This step significantly reduces the redundant slicing calculation amount through adaptive partition cutting based on structural isomorphism, improves the quality of the sliced pattern, and at the same time provides a spatial structure basis for subsequent regional differential optical control and trajectory optimization.

[0017] Step S2: Develop a light modulator in the control system of the 3D printing device, perform microscopic modulation under optical amplification on the layer projection pattern, and determine the laser projection parameters and reduction magnification as the first laser parameters.

[0018] Specifically, an optical modulator is a device that controls parameters such as the amplitude, phase, and frequency of light spatially or temporally, such as a DMD (Digital Micromirror Device), an LCD dimming panel, or a liquid crystal light valve. Integrate an optical modulation system within the control system of the 3D printing device. For example, in the DLP (Digital Light Processing) mode, generate patterns through the DMD chip array of TI. After loading the layer projection pattern generated in step S1 into the control system of the 3D printing device, use optical components such as an adjustable-focus projection lens group to optically magnify the pattern to ensure the clarity and uniformity of the pattern at the microscopic level. Then, finely modulate the magnified pattern, optimize the intensity, direction, and phase of the laser, determine the laser projection parameters and the reduction ratio, and define them as the first laser parameters. Among them, the laser projection parameters include parameters such as the power, frequency, and scanning speed of the laser, which directly affect the printing quality and accuracy; the reduction ratio is the reduction ratio of the projection pattern during actual printing, which is used to ensure the accuracy and consistency of the pattern.

[0019] This step improves the projection resolution and edge clarity, thus significantly enhancing the detail restoration ability and dimensional stability of the printed structure.

[0020] Step S3: Establish a base coordinate system based on the 3D mathematical structure, make a printing trajectory decision for the multiple partition structures based on the layer projection pattern, perform a multi-axis coordinate system conversion under the co-driving of multiple laser heads, and determine the second printing trajectory.

[0021] Specifically, establish a reference base coordinate system (such as the Cartesian XYZ coordinates) based on the three-dimensional space of the 3D mathematical structure to determine the position and direction relationship of each point during the printing process. Locate all partition structures in this coordinate system. Then, call a path planning algorithm (such as line filling algorithm, Hilbert scan, or spiral filling, etc.) for each partition to generate a local printing path. The 3D printing device is equipped with multiple laser heads, and each laser head is responsible for different partitions or paths. Convert the printing trajectory from the base coordinate system to the local coordinate system of each laser head to generate the final printing path, which is used to guide the multi-axis movement of the printing device.

[0022] This step realizes the accurate trajectory generation and coordinate synchronous conversion of the structural area in a multi-laser head parallel environment, effectively avoids path conflicts and positioning deviations, and significantly improves the spatial coordination and operation efficiency during the printing of complex structures.

[0023] Step S4: Couple the first laser parameters with the second printing trajectory, drive the 3D printing device to perform multi-axis co-driving printing control under layer projection stacking. Among them, if there is heterogeneous integration, perform microsystem deployment on the coupled first laser parameter - second printing trajectory.

[0024] Specifically, the laser control parameters generated in step S2 are coupled with the second printing trajectory generated in step S3, that is, the laser projection parameters and the second printing trajectory are synchronously bound in the control instruction, and the two types of information are packaged by the printing device control system and sent to the axis synchronization module of the printing device. Through the multi-axis synchronization module (such as the stepper motor control system, CNC controller), the motion platform and the light source are precisely coordinated to align the printed pattern and trajectory in time and space. Multiple axes are driven simultaneously to project and stack materials layer by layer to form the final 3D structure. If there is heterogeneous integration in the product structure, that is, sub-structures containing multiple materials, structural scales or different manufacturing parameters, then the microsystem deployment strategy is executed, and the coupling instructions are sent to the material control unit, temperature control system, scanning system, etc. respectively to achieve local customization of process parameters.

[0025] This step ensures the strict correspondence between the pattern and the path during printing by fusing the control parameters and trajectory information, effectively improving the forming accuracy and process stability; at the same time, through the microsystem deployment mechanism, the forming support ability for complex heterogeneous structures is expanded.

[0026] Furthermore, step S1 includes: Step S11: For the 3D mathematical structure, partition and cut it according to layer isomorphism to determine multiple partitioning schemes.

[0027] Step S12: Traverse the multiple partitioning schemes and determine the target partitioning scheme by balancing the complexity of the projected pattern and the number of partitions.

[0028] Step S13: According to the target partitioning scheme, partition and cut the 3D mathematical structure to determine the multiple partitioned structures.

[0029] Specifically, the geometric topology information of the 3D mathematical structure is extracted using a computational geometry library (such as OpenCASCADE, CGAL). Subsequently, layer-by-layer scanning is performed through a layer slicing engine (such as Slic3r, Cura Engine), and the structural similarity or consistency between each sliced layer is discriminated by combining shape recognition algorithms (such as graph structure comparison based on hashing, shape context matching). According to the layer isomorphism analysis results, multiple different partitioning schemes are generated based on different layer thicknesses and structural complexities.

[0030] Traverse the partitioning scheme, evaluate the projection pattern complexity and the number of partitions of each partitioning scheme one by one, quantitatively evaluate each scheme using evaluation metrics, and find the target partitioning scheme that achieves the best balance between the projection pattern complexity and the number of partitions (i.e., the optimal evaluation result). For example, for the projection pattern complexity, calculate the number of lines, the degree of curvature of curves, etc. in the projection pattern through an image analysis algorithm to obtain a complexity score. Then, according to different numbers of partitions, a scoring mapping table is preset in advance to match the corresponding quantity score for each partitioning scheme, and the complexity score and the quantity score are weighted and summed according to the preset balance criterion to obtain a comprehensive scheme evaluation result. Select the partitioning scheme with the highest evaluation as the target partitioning scheme. Call the model segmentation algorithm to execute the target partitioning scheme to partition and cut the 3D mathematical structure to determine multiple partition structures.

[0031] The above steps achieve the structural recognition and intelligent partitioning of the 3D printing model. Through the adaptive cutting guided by layer isomorphism, it effectively reduces the coordination conflicts in subsequent co-drive control, and achieves a balance between the pattern complexity and the control linkage amount, making the printing path more controllable and the pattern clearer, providing a clear logical unit structure basis for subsequent optical modulation, coordinate transformation, and linkage printing.

[0032] Further, in step S2, determine the laser projection parameters, including: Step S21: Determine the first-layer projection pattern, where the first-layer projection pattern is the two-dimensional structure of a single printing layer of any partition structure.

[0033] Step S22: For the first-layer projection pattern, through the optical modulator, perform magnification processing based on the first magnification ratio to determine the magnified projection pattern, where the first magnification ratio is defined by microscopic visibility.

[0034] Step S23: For the magnified projection pattern, perform light field modulation by locating projection defects to determine the laser projection parameters.

[0035] Specifically, after step S1 completes the structural adaptive partitioning and cutting and determines the partition structure, select any partition structure from numerous partition structures, and then for this partition structure, select any one of its layers, such as the kth layer, and use a slicing algorithm (such as scanline based on contour scanning or projection boundary extraction algorithm) to extract the corresponding cross-sectional information to generate a two-dimensional bitmap pattern, defined as the first-layer projection pattern. This pattern is used for subsequent optical modulation and laser control and is the basic layer unit of the entire printing process. For example, for a gear partition, the extracted first-layer projection pattern has an annular structure, a hollow circle in the middle, and a toothed outer edge around it. This pattern is then used for subsequent optical modulation and laser control and is the basic layer unit of the entire printing process.

[0036] Microscopic visibility refers to the minimum unit image clarity required for an imaging device to resolve microstructures. After obtaining the first-layer projection pattern, it is input into the light modulator. The light modulator magnifies the original pattern in the first-layer projection pattern according to the first magnification ratio determined in advance based on microscopic visibility through an embedded image processing library (such as OpenCV) to enhance the observation details and facilitate the discovery of pixel-level defects or structural discontinuities. For example, when detecting microstructural struts, if the pixels of the original pattern are too small and magnifying by 10 times can observe whether there are breakpoints, serrations, or pseudo-edge phenomena, then the first magnification ratio is 10 times.

[0037] Use image analysis algorithms (such as edge detection Sobel, Canny algorithms) to identify the projection defect areas in the pattern, that is, the discontinuous areas or overexposed and underexposed areas in the pattern caused by pixel errors, image distortion, boundary jitter, etc. After marking these defect areas, call the light modulator to adjust the spatial distribution of light to make the energy uniform and the edges clear, which can be achieved through DMD micromirrors, liquid crystal panels, or gray-scale modulation algorithms. For example, when manufacturing a microfluidic connection node, overly sharp edge lines will cause local overexposure. By modulating the gray value at that place to 85% of the exposure threshold, edge collapse can be avoided. Determine the laser projection parameters according to the modulated light field for actual control of the laser output. By accurately identifying pattern defects and performing light field compensation, the laser energy distribution can be made more uniform, improving the printing layer accuracy and surface quality, and reducing the forming error rate caused by edge errors.

[0038] Furthermore, determining the reduction magnification in step S2 includes: Step S24: Calculate the reduction magnification according to the size data of the printed product and the size data of the magnified projection pattern, where the reduction magnification is determined by the ratio of the size data of the printed product to the size data of the magnified projection pattern; wherein, the reduction magnification responds to the reduction lens assembly of the laser head to perform reduction modulation control.

[0039] Specifically, compare the original size data of each partition structure of the printed product with the size data of the magnified projection pattern of each partition structure in step S22, and calculate multiple reduction magnifications corresponding to multiple partitions. This reduction magnification is used to adjust the position and focal length of the imaging lens group on the laser head to perform scaling adjustment for different partitions to ensure that the pattern is accurately projected onto the target platform area. For example, when printing a composite structure including a microcolumn array and a macro shell, the microcolumn area requires a higher projection reduction magnification (such as 1:20), while the shell area can use 1:5. Then, the control system of the 3D printing device automatically performs lens group adjustment and pattern switching according to the reduction magnifications of different partitions to ensure that the patterns of different partitions are strictly restored in proportion on the printing platform, effectively avoiding pattern distortion and positioning deviation, and improving the accuracy and consistency of microstructural printing.

[0040] Further, as Figure 2 shown, in step S3, a base coordinate system based on the 3D mathematical structure is established, and printing trajectory decision-making for the multiple partition structures based on the layer projection pattern is performed, including: Step S31: Build the base coordinate system in the three-dimensional space of the 3D mathematical structure.

[0041] Step S32: According to the base coordinate system, for each partition structure, locate the starting structure coordinates based on the layer projection pattern, and determine a plurality of starting coordinates, where the plurality of starting coordinates correspond one-to-one to the plurality of partition structures.

[0042] Step S33: Using the plurality of starting coordinates, determine the layer printing trajectories for each partition structure, and determine a plurality of trajectory coordinate sequences.

[0043] Specifically, three-dimensional space information is extracted from the 3D mathematical structure obtained in step S1, such as the coordinate ranges of each point, the boundaries of geometric shapes, etc. Then, using the coordinate construction software in the control system of the 3D printing device, a base coordinate system is built based on this information. For example, for a printed product in the shape of a cuboid, a vertex of the cuboid is used as the origin, and the three edges are used as the coordinate axis directions to build the base coordinate system.

[0044] The layer projection pattern of each partition structure is mapped into the three-dimensional space, and the relative position relationship of the pattern in the base coordinate system is analyzed using the coordinate positioning algorithm in the control system of the 3D printing device, and the starting printing position coordinates of each partition structure, that is, the starting structure coordinates, are located. For example, when printing a model with multiple branch structures, the starting structure coordinates of each branch structure are determined by calculating the position of the layer projection pattern of each branch structure relative to the origin of the base coordinate system.

[0045] Using the determined starting coordinates of each partition structure as the initial data, according to the shape, structural characteristics of the layer projection pattern of each partition structure and the printing process requirements, a path planning algorithm (such as line filling algorithm, Hilbert scan or spiral filling, etc.) is used to determine the set of moving trajectory points of the laser head during the layer printing process of the partition structure, so as to obtain a plurality of trajectory coordinate sequences. For example, when printing a curved pipe structure, a series of coordinate points where the laser head moves along the pipe shape are the trajectory coordinate sequences.

[0046] Further, the 3D printing device has a multi-axis structure, including at least two laser head components. In step S3, multi-axis coordinate system conversion under multi-laser head co-driving is performed to determine the second printing trajectory, including: Step S34: For the multi-axis structure, determine the axis coordinate systems of each laser head component.

[0047] Step S35: performing coordinate transformation on the plurality of trajectory coordinate sequences according to the axis coordinate system to determine a plurality of axis coordinate sequences.

[0048] Step S36: Determine the second printing trajectory according to the multiple axis coordinate sequences.

[0049] Specifically, the 3D printing device is a multi-axis structure, including two or more laser head components, each of which has its own independent local coordinate system, namely the axis coordinate system, which is used to describe the position and movement direction of the laser head in the multi-axis structure. The relative installation parameters of the laser head in the mechanical structure are read from the control system of the 3D printing device to determine the multi-axis structure information, including the range and accuracy of each axis. The local coordinate system is established for each laser head component in combination with the coordinate setting software in the control system of the 3D printing device, usually with the current position of the laser head as the origin, and the X, Y, and Z axis directions are defined.

[0050] A coordinate transformation algorithm (such as rigid body transformation, Euler angle or quaternion calculation) is used to transform multiple trajectory coordinate sequences determined in the base coordinate system into coordinate sequences in the axis coordinate system of each laser head component itself, thereby obtaining multiple axis coordinate sequences.

[0051] The coordinate sequences of each axis are time-coordinated and path-joined to form a path set for synchronous execution of multiple laser heads, namely the second printing trajectory. The second printing trajectory is a path combination ultimately used for execution by the 3D printing device, which contains the conversion trajectories, time series, conflict avoidance information, etc. of all laser head components. It has execution priority and synchronous scheduling logic, and can achieve efficient, coordinated, and precise printing of multiple laser heads, improve space utilization and molding efficiency, and adapt to multi-structure heterogeneous printing scenarios. At the same time, the constraints of the conversion coordinates ensure that there will be no spatial dislocation under joint drive, and both printing control efficiency and accuracy can be taken into account.

[0052] Further, step S36 includes: Step S361: performing a print layer collision analysis under a synchronous timestamp on the plurality of axis coordinate sequences to locate the collision print layers.

[0053] Step S362: for the collision printing layer, control error frequency correction is performed, time series marking is performed on the multiple axis coordinate sequences, and the second printing trajectory is determined.

[0054] Specifically, timestamps are assigned to the coordinate points in each axis coordinate sequence through the time marking function in the 3D printing device control system to achieve alignment on the time axis. Time synchronization analysis is performed on the printing layers represented by different axis coordinate sequences according to the synchronized timestamp information. Collision detection algorithms (such as circumcircle collision detection, oriented bounding box algorithm, etc.) are used to perform collision analysis on the laser head components at the same timestamp to determine whether there is path intersection or head overlap between two or more laser heads during printing on the same layer, identify the specific printing layers where collisions may occur, that is, the collision printing layers, and record the positions and printing times of these layers.

[0055] For the located collision printing layers, according to the structural characteristics and printing requirements of the printed product, control misfrequency correction is performed through the frequency adjustment algorithm in the 3D printing device control system, the printing frequencies of the laser head components where collisions may occur are adjusted, and the execution timings of each laser head component are recalibrated. According to the corrected printing order, time series marking is performed on multiple axis coordinate sequences using the time marking software to determine the second printing trajectory. For example, if the printing frequencies of two laser heads are the same at a certain collision printing layer resulting in a collision, the printing frequency of one of the laser heads is adjusted to achieve out-of-time printing. Then, according to the corrected printing order, time series marking is performed on multiple axis coordinate sequences using the time marking software to determine the second printing trajectory.

[0056] The above steps, through the collision analysis of printing layers under synchronized timestamps, locate in advance the possible collision printing layers, and then ensure the orderliness of the printing process by correcting the frequency and marking the time series, avoid collision conflicts during the actual printing process, and improve the coordination and stability of multi-laser-head joint drive printing.

[0057] Further, step S35 includes: Step S351: According to the number of laser head components, perform a round of printing control deployment based on the multiple partition structures, where cyclic control deployment constraints are performed based on the relative positions of the multiple partition structures.

[0058] Step S352: On the basis of the round of printing control deployment, perform a cyclic printing control deployment based on the seamless connection of the printing drive to determine the joint drive printing mode.

[0059] Step S353: According to the joint drive printing mode, perform multi-axis coordinate system conversion.

[0060] Specifically, the round-robin control deployment constraint is a restrictive condition for print control deployment, which requires that the printed part cannot affect the subsequent printing process. For example, printing should be carried out in a bottom-up hierarchical structure. Read the number of laser head components in the 3D printing device, use the relative positions of multiple partition structures as the round-robin control deployment constraint, and perform a round of print control deployment according to the number of laser head components and partition structures, arranging the initial printing tasks for each laser head component to ensure that each laser head component corresponds to a partition structure.

[0061] Based on a round of print control deployment, according to the seamless connection requirement of the print driver (when a laser head completes the printing of a partition, it switches to execute the printing task of another partition without an idle state), continue to perform round-robin print control deployment on multiple partition structures through a task scheduling algorithm. According to the results of the round-robin print control deployment, determine the combined drive printing mode for multi-laser head collaborative work. According to the combined drive printing mode, convert multiple trajectory coordinate sequences from the base coordinate system to the axis coordinate systems of the corresponding laser head components to determine the corresponding multiple axis coordinate sequences.

[0062] The above steps make full use of multi-laser head resources through round-robin deployment and combined drive scheduling, improving printing efficiency and path coverage balance. At the same time, interference areas are automatically avoided in path scheduling to ensure a reasonable and uninterrupted printing order.

[0063] Further, after step S4 performs multi-axis co-drive print control under layer projection stacking, it includes: Step S41: Couple the first laser parameter and the second printing trajectory to determine the 3D printing strategy.

[0064] Step S42: Locate the key strategy points of the 3D printing strategy based on the error probability of process control variables.

[0065] Step S43: Perform feedback deployment based on print monitoring for the key strategy points.

[0066] Specifically, jointly arrange the first laser parameter and the second printing trajectory, and through the control system, comprehensively form a control instruction sequence with layer-by-layer binding of "partition - layer - path - laser output", and output it as a 3D printing strategy, which includes specific operation plans such as path instructions, laser intensity changes, speed synchronization, and frequency offset scheduling.

[0067] Identify key control variables during the printing process, such as laser power, scanning speed, etc. Based on the variation curve of the control parameters and the partition printing path, conduct process simulation, and statistically analyze the error probability of each control node according to the simulation results. For example, the laser deviation caused by the sudden change of the reduction ratio in a certain layer, or the ghosting caused by the large speed fluctuation at the path switching point. Identify the nodes with the error probability exceeding a certain threshold and mark them as key strategy points.

[0068] During the printing process, use the monitoring devices of the printing equipment (such as data acquisition systems, sensor networks) to monitor the control variables of the key strategy points in real time. For example, start high-frame image sampling at the path intersection points; read the power stability in real time at the laser parameter switching points, etc. According to the monitoring data, use the control system of the printing equipment for feedback adjustment, such as adjusting the laser parameters or the printing trajectory, etc., to ensure the stability and accuracy of the printing process.

[0069] The above steps effectively avoid the forming errors caused by process fluctuations by identifying key strategy points and performing feedback deployment, realize the intelligent closed-loop optimization of key parts, and significantly improve the printing quality and success rate.

[0070] In summary, the method for optimizing the 3D printing accuracy based on micro-light modulation provided by the embodiments of the present application has the following beneficial effects: The embodiments of the present application realize the intelligent division and regional mapping of three-dimensional structure information by introducing a structure adaptive partition mechanism based on layer isomorphism; significantly improve the resolution accuracy of the pattern boundary during the material forming process by performing micro-modulation on the partition layer patterns; enhance the coordination and spatial consistency of the forming path by combining multi-axis coordinate system control and multi-path linkage strategies; and realize high-precision multi-axis collaborative printing by coupling and controlling the laser parameters and trajectory control information, improving the dynamic consistency and structure restoration ability during the printing execution process. At the same time, aiming at the problem of heterogeneous structure integration, a micro-system level deployment method is proposed, which effectively improves the integration and printing adaptation ability of complex material structures, thereby achieving the technical effects of improving the 3D printing accuracy and enhancing the collaborative forming ability of complex structures.

[0071] Embodiment 2, as Figure 3 shown, based on the same inventive concept as the foregoing Embodiment 1, the embodiments of the present application provide a 3D printing accuracy optimization system based on micro-light modulation. The system includes: A structure partition module 10, configured to obtain the 3D mathematical structure of the printed product, perform structure adaptive partition cutting according to layer isomorphism, and determine a plurality of partition structures, where each partition structure corresponds to a layer projection pattern.

[0072] The micro-modulation module 20 is used to develop an optical modulator within the control system of the 3D printing device, perform micro-modulation under optical magnification on the layer projection pattern, and determine the laser projection parameters and reduction magnification as the first laser parameters.

[0073] The trajectory decision-making module 30 is used to establish a base coordinate system based on the 3D mathematical structure, make a printing trajectory decision for the multiple partition structures based on the layer projection pattern, perform multi-axis coordinate system conversion under the co-driving of multiple laser heads, and determine the second printing trajectory.

[0074] The printing control module 40 is used to couple the first laser parameters with the second printing trajectory, and drive the 3D printing device to perform multi-axis co-driving printing control under layer projection stacking. Among them, if there is heterogeneous integration, micro-system deployment is performed on the coupled first laser parameter - second printing trajectory.

[0075] Furthermore, the micro-modulation module 20 of the embodiment of the present application is further used to perform the following steps: Determine the first layer projection pattern, where the first layer projection pattern is a two-dimensional structure of a single printing layer of any partition structure; for the first layer projection pattern, through the optical modulator, perform magnification processing based on the first magnification ratio to determine the magnified projection pattern, where the first magnification ratio is defined by micro-visibility; for the magnified projection pattern, perform light field modulation by positioning projection defects to determine the laser projection parameters.

[0076] Furthermore, the micro-modulation module 20 of the embodiment of the present application is further used to perform the following steps: According to the size data of the printed product and the size data of the magnified projection pattern, calculate the reduction magnification, where the reduction magnification is determined by the ratio of the size data of the printed product to the size data of the magnified projection pattern; among them, the reduction magnification responds to the reduction lens assembly of the laser head to perform reduction modulation control.

[0077] Furthermore, the trajectory decision-making module 30 of the embodiment of the present application is further used to perform the following steps: Build the base coordinate system in the three-dimensional space of the 3D mathematical structure; according to the base coordinate system, for each partition structure, locate the starting structure coordinates based on the layer projection pattern to determine multiple starting coordinates, where the multiple starting coordinates correspond to the multiple partition structures one by one; use the multiple starting coordinates to determine the layer printing trajectories for each partition structure to determine multiple trajectory coordinate sequences.

[0078] Furthermore, the 3D printing device is a multi-axis structure and includes at least two laser head components. The trajectory decision-making module 30 of the embodiment of the present application is further used to perform the following steps: For the multi-axis structure, determine the axis coordinate systems of the laser head assemblies; according to the axis coordinate systems, perform coordinate transformation on the multiple trajectory coordinate sequences to determine multiple axis coordinate sequences; according to the multiple axis coordinate sequences, determine the second printing trajectory.

[0079] Further, the trajectory decision module 30 in the embodiment of the present application is further configured to perform the following steps: Perform printing layer collision analysis under synchronized timestamps on the multiple axis coordinate sequences to locate the collision printing layers; for the collision printing layers, perform control frequency offset correction, perform time series marking on the multiple axis coordinate sequences, and determine the second printing trajectory.

[0080] Further, the trajectory decision module 30 in the embodiment of the present application is further configured to perform the following steps: According to the number of laser head assemblies, perform a round of printing control deployment based on the multiple partition structures, where cyclic control deployment constraints are performed based on the relative positions of the multiple partition structures; on the basis of the round of printing control deployment, perform cyclic printing control deployment based on the multiple partition structures with seamless connection of printing drives to determine the combined drive printing mode; according to the combined drive printing mode, perform multi-axis coordinate system transformation.

[0081] Further, the structure partitioning module 10 in the embodiment of the present application is further configured to perform the following steps: For the 3D mathematical structure, perform partitioning and cutting according to layer isomorphism to determine multiple partitioning schemes; traverse the multiple partitioning schemes, and determine the target partitioning scheme by balancing the complexity of the projection pattern and the number of partitions; according to the target partitioning scheme, perform partitioning and cutting on the 3D mathematical structure to determine the multiple partition structures.

[0082] Further, the printing control module 40 in the embodiment of the present application is further configured to perform the following steps: Couple the first laser parameters with the second printing trajectory to determine the 3D printing strategy; locate the key strategy points of the 3D printing strategy based on the error probability of process control variables; for the key strategy points, perform feedback deployment based on printing monitoring.

[0083] Through the foregoing detailed description of a 3D printing accuracy optimization method based on micro-light modulation in this specification, those skilled in the art can clearly know a 3D printing accuracy optimization system in this embodiment. For the system disclosed in Embodiment 2, since it corresponds to the method disclosed in Embodiment 1, it has corresponding functional modules and beneficial effects. For the relevant parts, refer to the description in the method part.

[0084] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A 3D printing accuracy optimization method based on micro-light modulation, characterized in that: The method comprises: Obtaining the 3D mathematical structure of the printed product, performing adaptive partitioning and slicing of the structure according to layer isomorphism, and determining multiple partition structures, wherein each partition structure corresponds to a layer projection pattern; Developing a light modulator in a control system of the 3D printing device to perform microscopic modulation under optical magnification on the layer projection pattern, and determining laser projection parameters and reduction magnification as first laser parameters; Establishing a base coordinate system based on the 3D mathematical structure, making printing trajectory decisions based on layer projection patterns for the multiple partition structures, performing multi-axis coordinate system conversion under multi-laser head joint drive, and determining a second printing trajectory; coupling the first laser parameter and the second printing trajectory to drive the 3D printing device to perform multi-axis co-drive printing control under layer projection stacking; Among them, if heterogeneous integration exists, a microsystem deployment is performed on the coupled first laser parameter-second printing trajectory.

2. A 3D printing precision optimization method based on micro-light modulation as claimed in claim 1, characterized in that: Determine laser projection parameters, including: Determine a first layer projection pattern, wherein the first layer projection pattern is a two-dimensional structure of a single printing layer of any partition structure; For the first layer of projection patterns, performing a magnification process based on a first magnification through the light modulator to determine a magnified projection pattern, wherein the first magnification is defined by microscopic visibility; With respect to the magnified projection pattern, light field modulation is performed by locating projection defects to determine laser projection parameters.

3. A 3D printing precision optimization method based on micro-light modulation as claimed in claim 2, characterized in that: Determine the reduction ratio, including: Calculating the reduction ratio according to the size data of the printed product and the size data of the enlarged projection pattern, wherein the reduction ratio is determined by the ratio of the size data of the printed product to the size data of the enlarged projection pattern; The reduction magnification is responsive to a reduction lens assembly of a laser head to perform reduction modulation control.

4. The 3D printing precision optimization method based on micro-light modulation according to claim 1, characterized in that: Establishing a base coordinate system based on the 3D mathematical structure, and making printing trajectory decisions based on layer projection patterns for the multiple partition structures, including: Constructing the base coordinate system in the three-dimensional space of the 3D mathematical structure; According to the base coordinate system, for each partition structure, a starting structure coordinate based on the layer projection pattern is located to determine a plurality of starting coordinates, wherein the plurality of starting coordinates correspond one-to-one to the plurality of partition structures; The layer printing trajectory of each partition structure is determined based on the multiple starting coordinates to determine multiple trajectory coordinate sequences.

5. A 3D printing precision optimization method based on micro-light modulation as claimed in claim 4, characterized in that: The 3D printing device is a multi-axis structure, including at least two laser head assemblies; For the multi-axis structure, determining the axis coordinate system of each laser head assembly; According to the axis coordinate system, coordinate transformation is performed on the multiple trajectory coordinate sequences to determine multiple axis coordinate sequences; The second printing trajectory is determined according to the multiple axis coordinate sequences.

6. A 3D printing precision optimization method based on micro-light modulation as claimed in claim 5, characterized in that: Determining the second printing trajectory according to the plurality of axis coordinate sequences includes: Performing a print layer collision analysis under a synchronous timestamp on the multiple axis coordinate sequences to locate the collision print layers; For the collision printing layer, control error frequency correction is performed, the multiple axis coordinate sequences are marked as time series, and the second printing trajectory is determined.

7. The 3D printing precision optimization method based on micro-light modulation according to claim 5, characterized in that: Performing coordinate transformation on the plurality of trajectory coordinate sequences includes: According to the number of laser head assemblies, a round of printing control deployment based on the multiple partition structures is executed, wherein the round-robin control deployment constraint is performed based on the relative positions of the multiple partition structures; Based on the one round of printing control deployment, the round-robin printing control deployment based on the multiple partition structures is executed with seamless connection of the printing driver to determine the joint drive printing mode; According to the joint drive printing mode, multi-axis coordinate system conversion is performed.

8. The 3D printing precision optimization method based on micro-light modulation according to claim 1, characterized in that: According to the layer isomorphism, the structure is adaptively partitioned and cut into blocks to determine multiple partition structures, including: For the 3D mathematical structure, partition and cut the structure according to layer isomorphism to determine multiple partitioning schemes; Traversing the multiple partitioning schemes, and determining a target partitioning scheme by balancing the complexity of the projection pattern and the number of partitions; According to the target partitioning scheme, the 3D mathematical structure is partitioned and cut into blocks to determine the multiple partition structures.

9. The 3D printing precision optimization method based on micro-light modulation according to claim 1, characterized in that: After executing multi-axis co-drive printing control under layer projection stacking, it includes: coupling the first laser parameter and the second printing trajectory to determine a 3D printing strategy; Locating key strategic points of the 3D printing strategy based on error probabilities of process control variables; For the key strategic points, feedback deployment based on printing monitoring is carried out.

10. A 3D printing precision optimization system based on micro-light modulation, characterized in that: The system is used to execute a 3D printing precision optimization method based on micro-light modulation according to any one of claims 1 to 9, comprising: The structural partitioning module is used to obtain the 3D mathematical structure of the printed product, perform structural adaptive partitioning and slicing according to layer isomorphism, and determine multiple partition structures, where each partition structure corresponds to a layer projection pattern; A micro-modulation module is used to develop a light modulator in a control system of a 3D printing device, perform micro-modulation under optical magnification on the layer projection pattern, and determine laser projection parameters and reduction magnification as first laser parameters; A trajectory decision module is used to establish a base coordinate system based on the 3D mathematical structure, make printing trajectory decisions based on layer projection patterns for the multiple partition structures, perform multi-axis coordinate system conversion under multi-laser head joint drive, and determine a second printing trajectory; A printing control module is used to couple the first laser parameter and the second printing trajectory to drive the 3D printing device to perform multi-axis co-drive printing control under layer projection stacking, wherein, if heterogeneous integration exists, a microsystem deployment is performed on the coupled first laser parameter-second printing trajectory.

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