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

Abstract

The present application provides a method and system for optimizing 3D printing accuracy based on micro-light modulation, which relates to the field of material forming technology, including: structurally adaptive partitioning and dicing of 3D mathematical structures to determine multiple partition structures; developing a light modulator to perform micro-modulation on the layer projection pattern to determine the first laser parameter; establishing a base coordinate system based on the 3D mathematical structure, making printing trajectory decisions for multiple partition structures, performing multi-axis coordinate system conversion under multi-laser head joint drive, and determining the second printing trajectory; coupling the first laser parameter with the second printing trajectory to perform multi-axis co-drive printing control; if heterogeneous integration exists, microsystem deployment is performed. The present application solves 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, thereby improving the printing accuracy and enhancing the collaborative forming capability of complex structures.

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 principle of layer-by-layer forming 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, and the method includes: obtaining the 3D mathematical structure of the printed product, performing structure adaptive partition cutting according to layer isomorphism to determine multiple partition structures, where each partition structure corresponds to a layer projection pattern; developing an optical 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 multiple 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 execute multi-axis co-drive printing control under layer projection stacking; where, if there is heterogeneous integration, a microsystem deployment is performed on the coupled first laser parameter - second printing trajectory.

[0005] On the other hand, the present application also provides a 3D printing precision 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 adaptive partitioning and cutting according to layer isomorphism, and determine multiple 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 a 3D printing device, perform micro modulation under optical magnification on the layer projection pattern, and determine laser projection parameters and a reduction ratio as 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 multiple partition structures based on the layer projection pattern, perform multi-axis coordinate system conversion under multi-laser head co-driving, and determine a second printing trajectory; a printing control module, configured 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. 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:

[0007] By obtaining the 3D mathematical structure of a printed product and performing structure 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 a 3D printing device, performing micro modulation under optical magnification on the layer projection pattern, and determining laser projection parameters and a reduction ratio as 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 multiple partition structures based on the layer projection pattern, performing multi-axis coordinate system conversion under multi-laser head co-driving, 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 with the second printing trajectory, driving the 3D printing device to perform multi-axis co-driving 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 a micro-system deployment strategy, enhancing the ability to adapt to complex application scenarios.

[0008] 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 structure 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.

[0009] 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 according to 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 following specifically gives the specific implementation manners of the present application. Brief Description of the Drawings

[0010] Figure 1 It is a schematic flowchart of a method for optimizing 3D printing accuracy based on micro-light modulation provided by an embodiment of the present application.

[0011] Figure 2 It is a schematic flowchart of making a printing trajectory decision based on layer projection patterns for multiple partition structures in a method for optimizing 3D printing accuracy based on micro-light modulation provided by an embodiment of the present application.

[0012] Figure 3 It is a schematic logical diagram of a system for optimizing 3D printing accuracy based on micro-light modulation provided by an embodiment of the present application.

[0013] 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 Embodiment

[0014] By providing a method and system for optimizing 3D printing accuracy 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 hierarchy is solved, and the technical effects of improving the 3D printing accuracy and enhancing the collaborative forming ability of complex structures are achieved.

[0015] Embodiment 1, as Figure 1 shown, an embodiment of the present application provides a method for optimizing 3D printing accuracy based on micro-light modulation, and the method includes:

[0016] Step S1: Obtain the 3D mathematical structure of the printed product, perform structure-adaptive partition slicing according to layer isomorphism, and determine multiple partition structures, where each partition structure corresponds to a layer projection pattern.

[0017] Specifically, the 3D mathematical structure refers to the three-dimensional 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 three-dimensional 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, 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 constitute 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.

[0018] This step significantly reduces the redundant slicing calculation amount through structure-isomorphism-based adaptive partition slicing, 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.

[0019] Step S2: Develop a light modulator in the control system of the 3D printing device, perform microscopic modulation under optical magnification on the layer projection pattern, and determine the laser projection parameters and reduction magnification as the first laser parameters.

[0020] 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, patterns are generated through an array of DMD chips from 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.

[0021] This step improves the projection resolution and edge clarity, thus significantly enhancing the detail restoration ability and dimensional stability of the printed structure.

[0022] Step S3: Establish a base coordinate system based on the 3D mathematical structure, make a printing trajectory decision for the multiple partitioned structures based on the layer projection pattern, perform a multi-axis coordinate transformation under the co-drive of multiple laser heads, and determine the second printing trajectory.

[0023] Specifically, establish a reference base coordinate system (such as Cartesian XYZ coordinates) based on the three-dimensional space of the 3D mathematical structure to determine the position and direction relationships of each point during the printing process. Locate all the partitioned 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 a different partition or path. 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.

[0024] This step realizes the accurate trajectory generation and coordinate synchronization transformation 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.

[0025] Step S4: Couple the first laser parameters with the second printing trajectory, drive the 3D printing device to perform multi-axis co-drive 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.

[0026] 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 a stepper motor control system, a CNC controller), the motion platform and the light source are precisely coordinated, so that the printed pattern and the trajectory are aligned in time and space, and 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, the microsystem deployment strategy is executed, and the coupling instructions are sent to the material control unit, the temperature control system, the scanning system, etc. respectively to achieve local customization of process parameters.

[0027] This step ensures the strict correspondence between the pattern and the path during the printing process by fusing the control parameters and the 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.

[0028] Further, step S1 includes:

[0029] Step S11: For the 3D mathematical structure, partition and cut it according to layer isomorphism to determine multiple partition schemes.

[0030] Step S12: Traverse the multiple partition schemes and determine the target partition scheme by balancing the complexity of the projection pattern and the number of partitions.

[0031] Step S13: According to the target partition scheme, partition and cut the 3D mathematical structure to determine the multiple partition structures.

[0032] 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 the sliced layers 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 partition schemes are generated based on different layer thicknesses and structural complexities.

[0033] 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, pre-set a score mapping table, match the corresponding quantity score for each partitioning scheme, and perform weighted summation on the complexity score and the quantity score according to the pre-set 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.

[0034] The above steps realize 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.

[0035] Furthermore, in step S2, determine the laser projection parameters, including:

[0036] 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.

[0037] Step S22: For the first-layer projection pattern, perform magnification processing based on the first magnification factor through the optical modulator to determine the magnified projection pattern, where the first magnification factor is defined by microscopic visibility.

[0038] Step S23: For the magnified projection pattern, perform light field modulation by locating projection defects to determine the laser projection parameters.

[0039] Specifically, after completing the structural adaptive partitioning and cutting and determining the partition structure in step S1, select any partition structure from among the numerous partition structures. Then, for this partition structure, select any one of its layers, such as the k-th 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, which is defined as the first-layer projection pattern. This pattern is used for subsequent optical modulation and laser control and is the basic layer unit for the entire printing process. For example, for a gear partition, the first-layer projection pattern extracted is in a ring structure, with 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 for the entire printing process.

[0040] 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 by a first magnification factor determined based on the preset microscopic visibility standard 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 original pattern pixels are too small and magnifying by 10 times can observe whether there are breakpoints, serrations, or pseudo-edge phenomena, then the first magnification factor is 10 times.

[0041] 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 microchannel connection nodes, overly sharp edge lines will cause local overexposure. By modulating the gray value at that place to 85% of the exposure threshold, edge collapse is 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 becomes more uniform, improving the printing layer accuracy and surface quality, and reducing the forming error rate caused by edge errors.

[0042] Further, determining the reduction magnification in step S2 includes:

[0043] Step S24: Calculate the reduction magnification according to the size data of the printed product and the size data of the enlarged 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 enlarged projection pattern; wherein, the reduction magnification responds to the reduction lens assembly of the laser head and performs reduction modulation control.

[0044] Specifically, compare the original size data of each partition structure of the printed product with the size data of the enlarged projection pattern of each partition structure in step S22, and calculate multiple reduction ratios for multiple corresponding partitions. This reduction ratio 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, ensuring 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 housing, the microcolumn area requires a higher projection reduction ratio (such as 1:20), while the housing 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 ratios of different partitions, ensuring 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 micro-structure printing.

[0045] Further, as Figure 2 shown, in step S3, establish a base coordinate system based on the 3D mathematical structure, and make a printing trajectory decision for the multiple partition structures based on the layer projection pattern, including:

[0046] Step S31: Build the base coordinate system in the three-dimensional space of the 3D mathematical structure.

[0047] 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 multiple starting coordinates, where the multiple starting coordinates correspond to the multiple partition structures one by one.

[0048] Step S33: Use the multiple starting coordinates to determine the layer printing trajectory for each partition structure, and determine multiple trajectory coordinate sequences.

[0049] Specifically, extract three-dimensional space information from the 3D mathematical structure obtained in step S1, such as the coordinate range of each point, the boundary of the geometric shape, etc. Then, use the coordinate construction software in the control system of the 3D printing device to build a base coordinate system based on this information. For example, for a printed product in the shape of a cuboid, use a vertex of the cuboid as the origin and the three edges as the coordinate axis directions to build the base coordinate system.

[0050] Map the layer projection pattern of each partition structure into the three-dimensional space, and use the coordinate positioning algorithm in the control system of the 3D printing device to analyze the relative position relationship of the pattern in the base coordinate system, and locate the starting printing position coordinates of each partition structure, that is, the starting structure coordinates. For example, when printing a model with multiple branch structures, determine the starting structure coordinates of each branch structure by calculating the position of the layer projection pattern of each branch structure relative to the origin of the base coordinate system.

[0051] Taking the starting coordinates of each determined partition structure as initial data, according to the shape, structural characteristics of the layer projection pattern of each partition structure and the printing process requirements, using path planning algorithms (such as line filling algorithm, Hilbert scan or spiral filling, etc.) to determine the set of moving trajectory points of the laser head during the printing process of the partition structure layer, so as to obtain multiple trajectory coordinate sequences. For example, when printing a curved pipe structure, a series of coordinate points along which the laser head moves along the pipe shape is the trajectory coordinate sequence.

[0052] Further, the 3D printing device is of a multi-axis structure, including at least two laser head assemblies. In step S3, multi-axis coordinate system conversion under multi-laser head co-driving is performed to determine the second printing trajectory, including:

[0053] Step S34: For the multi-axis structure, determine the axis coordinate systems of each laser head assembly.

[0054] Step S35: According to the axis coordinate systems, perform coordinate conversion on the multiple trajectory coordinate sequences to determine multiple axis coordinate sequences.

[0055] Step S36: According to the multiple axis coordinate sequences, determine the second printing trajectory.

[0056] Specifically, the 3D printing device is of a multi-axis structure, including two or more laser head assemblies. Each laser head assembly has its own independent local coordinate system, that is, the axis coordinate system, which is used to describe the position and movement direction of the laser head in the multi-axis structure. Read the relative installation parameters of the laser head in the mechanical structure from the control system of the 3D printing device to determine the multi-axis structure information, including the range and accuracy of each axis. Combine the coordinate setting software in the control system of the 3D printing device to establish its local coordinate system for each laser head assembly, usually with the current position of the laser head as the origin, and define the X, Y, and Z axis directions.

[0057] Use coordinate transformation algorithms (such as rigid body transformation, Euler angles or quaternion calculations) to convert the multiple trajectory coordinate sequences determined in the base coordinate system into coordinate sequences in the axis coordinate systems of each laser head assembly, obtaining multiple axis coordinate sequences.

[0058] Perform time coordination and path splicing on each axis coordinate sequence to form a path set for multi-laser head synchronous execution, that is, the second printing trajectory. This second printing trajectory is the final path combination for the 3D printing device to execute, including the transformation trajectories, time sequences, conflict avoidance information, etc. of all laser head assemblies, with execution priorities and synchronous scheduling logics, which can achieve efficient, collaborative and precise printing of multi-laser heads, improve space utilization and forming efficiency, and adapt to multi-structure heterogeneous printing scenarios. At the same time, the constraints of the converted coordinates ensure that there will be no spatial misalignment under co-driving, and both printing control efficiency and accuracy can be taken into account.

[0059] Further, step S36 includes:

[0060] Step S361: Perform print layer collision analysis under synchronized timestamps for the multiple axis coordinate sequences to locate the collision print layers.

[0061] Step S362: For the located collision print layers, perform control frequency offset correction, mark the multiple axis coordinate sequences in a time series, and determine the second printing trajectory.

[0062] Specifically, the time marking function in the 3D printing device control system is used to assign timestamps to the coordinate points in each axis coordinate sequence to achieve alignment on the time axis. According to the synchronized timestamp information, time synchronization analysis is performed on the print layers represented by different axis coordinate sequences. The collision detection algorithm (such as circumscribed circle collision detection, oriented bounding box algorithm, etc.) is used to perform collision analysis on the laser head components at the same timestamp to determine whether there is path intersection or head overlap when two or more laser heads print on the same layer, identify the specific print layers where collisions may occur, that is, the collision print layers, and record the positions and printing times of these layers.

[0063] For the located collision print layers, according to the structural characteristics and printing requirements of the printed product, control frequency offset 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, the multiple axis coordinate sequences are marked in a time series using 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 print layer resulting in a collision, the printing frequency of one of the laser heads is adjusted to achieve staggered printing. Then, according to the corrected printing order, the multiple axis coordinate sequences are marked in a time series using time marking software to determine the second printing trajectory.

[0064] The above steps locate the possible collision print layers in advance through print layer collision analysis under synchronized timestamps, 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.

[0065] Further, step S35 includes:

[0066] Step S351: According to the number of laser head components, perform one round of print control deployment based on the multiple partition structures, where cyclic control deployment constraints are imposed according to the relative positions of the multiple partition structures.

[0067] Step S352: On the basis of the one-round printing control deployment, with seamless connection of the printing driver, perform round-robin printing control deployment based on the multiple partition structures to determine the multi-drive printing mode.

[0068] Step S353: According to the multi-drive printing mode, perform multi-axis coordinate system conversion.

[0069] Specifically, the round-robin control deployment constraint is a limiting condition for the printing control deployment, requiring that the printed part cannot affect the subsequent printing process, such as printing in a bottom-up hierarchical structure. Read the number of laser head components in the 3D printing device, use the relative positions of the multiple partition structures as the round-robin control deployment constraint, perform one-round printing control deployment according to the number of laser head components and partition structures, and arrange the initial printing tasks for each laser head component to ensure that each laser head component corresponds to a partition structure.

[0070] On the basis of the one-round printing control deployment, according to the seamless connection requirement of the printing 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 printing control deployment on the multiple partition structures through the task scheduling algorithm. According to the result of the round-robin printing control deployment, determine the multi-drive printing mode in which multiple laser heads work together. According to the multi-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.

[0071] The above steps make full use of the multi-laser head resources through round-robin deployment and multi-drive scheduling, improve the printing efficiency and path coverage balance, and at the same time automatically avoid the interference area in the path scheduling to ensure a reasonable printing order and no interruption.

[0072] Further, after step S4 performs multi-axis co-drive printing control under layer projection stacking, it includes:

[0073] Step S41: Couple the first laser parameter and the second printing trajectory to determine the 3D printing strategy.

[0074] Step S42: Locate the key strategy points of the 3D printing strategy based on the error probability of the process control variables.

[0075] Step S43: Perform feedback deployment based on printing monitoring for the key strategy points.

[0076] Specifically, jointly arrange the first laser parameter and the second printing trajectory, and through the control system, synthesize a control instruction sequence of "partition - layer - path - laser output" layer-by-layer binding, and output it as the 3D printing strategy, which includes specific operation plans such as path instructions, laser intensity changes, speed synchronization, and frequency offset scheduling.

[0077] Identify key control variables in the printing process, such as laser power, scanning speed, etc. Based on the variation curve of the controlled parameters and the sectional 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 whose error probability exceeds a certain threshold and mark them as key strategy points.

[0078] 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 point; read the power stability in real time at the laser parameter switching point, etc. According to the monitoring data, use the control system of the printing equipment to perform feedback adjustment, such as adjusting the laser parameters or the printing trajectory, etc., to ensure the stability and accuracy of the printing process.

[0079] 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.

[0080] 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:

[0081] The embodiments of the present application realize the intelligent division and regional mapping of three-dimensional structure information by introducing a structure adaptive partitioning mechanism based on layer isomorphism; significantly improve the resolution accuracy of the pattern boundary in the material forming process by performing micro-modulation on the sectional layer pattern; enhance the coordination and spatial consistency of the forming path by combining multi-axis coordinate system control and multi-path linkage strategy; and realize high-precision multi-axis collaborative printing by coupling the control of 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 microsystem-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.

[0082] 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, and the system includes:

[0083] A structure partitioning module 10, configured to obtain the 3D mathematical structure of the printed product, perform structure adaptive partitioning and cutting according to layer isomorphism, and determine a plurality of partition structures, wherein each partition structure corresponds to a layer projection pattern.

[0084] 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 the reduction magnification as the first laser parameters.

[0085] 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.

[0086] The printing control module 40 is used to couple the first laser parameters and 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.

[0087] Furthermore, the micro-modulation module 20 of the embodiment of the present application is further used to perform the following steps:

[0088] 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, perform magnification processing based on the first magnification ratio through the optical modulator 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.

[0089] Furthermore, the micro-modulation module 20 of the embodiment of the present application is further used to perform the following steps:

[0090] 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.

[0091] Furthermore, the trajectory decision-making module 30 of the embodiment of the present application is further used to perform the following steps:

[0092] Build the base coordinate system in the three-dimensional space of the 3D mathematical structure; according to the base coordinate system, position the starting structure coordinates of each partition structure based on the layer projection pattern to determine a plurality of starting coordinates, where the plurality of starting coordinates correspond one-to-one to the plurality of partition structures; use the plurality of starting coordinates to determine the layer printing trajectories of each partition structure to determine a plurality of trajectory coordinate sequences.

[0093] Further, the 3D printing device is of a multi-axis structure and includes at least two laser head components. The trajectory decision module 30 in the embodiment of the present application is further configured to perform the following steps:

[0094] For the multi-axis structure, determine the axis coordinate systems of the laser head components; 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.

[0095] Further, the trajectory decision module 30 in the embodiment of the present application is further configured to perform the following steps:

[0096] Perform printing layer collision analysis under synchronous timestamps on the multiple axis coordinate sequences to locate the collision printing layer; for the collision printing layer, perform control frequency offset correction, perform time series marking on the multiple axis coordinate sequences, and determine the second printing trajectory.

[0097] Further, the trajectory decision module 30 in the embodiment of the present application is further configured to perform the following steps:

[0098] 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; 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 conversion.

[0099] Further, the structure partitioning module 10 in the embodiment of the present application is further configured to perform the following steps:

[0100] For the 3D mathematical structure, perform partition cutting according to layer isomorphism to determine multiple partition schemes; traverse the multiple partition schemes, and determine the target partition scheme by balancing the complexity of the projection pattern and the number of partitions; according to the target partition scheme, perform partition cutting on the 3D mathematical structure to determine the multiple partition structures.

[0101] Further, the printing control module 40 in the embodiment of the present application is further configured to perform the following steps:

[0102] 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.

[0103] Through the foregoing detailed description of a method for optimizing 3D printing accuracy based on low-light modulation, those skilled in the art can clearly know a system for optimizing 3D printing accuracy based on low-light modulation 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 section.

[0104] 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 apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not 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 method for optimizing 3D printing accuracy based on low-light modulation, characterized in that The method includes: Obtain the 3D mathematical structure of the printed product, perform structure adaptive partitioning and slicing according to layer isomorphism, and determine multiple partition structures, where each partition structure corresponds to a layer projection pattern; Develop an optical modulator in the control system of the 3D printing device, perform microscopic modulation under optical magnification on the layer projection pattern, and determine the laser projection parameters and reduction magnification, which are used as the first laser parameters; Establish a base coordinate system based on the 3D mathematical structure, make printing trajectory decisions 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; Couple the first laser parameters and 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, perform microsystem deployment on the coupled first laser parameter - second printing trajectory; Among them, determining the laser projection parameters includes: 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; For the first layer projection pattern, perform magnification processing based on the first magnification ratio through the optical modulator to determine the magnified projection pattern, where the first magnification ratio is defined by microscopic visibility; For the magnified projection pattern, perform light field modulation by locating projection defects to determine the laser projection parameters; Among them, determining the reduction magnification includes: 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; Among them, the reduction magnification responds to the reduction lens assembly of the laser head and performs reduction modulation control.

2. The 3D printing accuracy optimization method based on low-light modulation according to claim 1, characterized in that, Establish a base coordinate system based on the 3D mathematical structure, and making printing trajectory decisions for the multiple partition structures based on the layer projection pattern includes: 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 one-to-one to the multiple partition structures; Use the multiple starting coordinates to determine the layer printing trajectories for each partition structure and determine multiple trajectory coordinate sequences.

3. The 3D printing accuracy optimization method based on low-light modulation according to claim 2, wherein, The 3D printing device has a multi-axis structure and includes at least two laser head assemblies; For the multi-axis structure, determine the axis coordinate systems of each laser head assembly; According to the axis coordinate systems, perform coordinate conversion on the multiple trajectory coordinate sequences to determine multiple axis coordinate sequences; According to the multiple axis coordinate sequences, determine the second printing trajectory.

4. The 3D printing precision optimization method based on low-light modulation according to claim 3, wherein, According to the multiple axis coordinate sequences, determining the second printing trajectory includes: Perform printing layer collision analysis under synchronous timestamps on the multiple axis coordinate sequences to locate the collision printing layers; For the collision printing layers, perform control frequency offset correction, mark the multiple axis coordinate sequences with time series, and determine the second printing trajectory.

5. The 3D printing accuracy optimization method based on low-light modulation according to claim 3, characterized in that, Performing coordinate conversion on the multiple trajectory coordinate sequences includes: Execute a round of print control deployment based on the multiple partition structures according to the number of laser head components, wherein cyclic control deployment constraints are performed based on the relative positions of the multiple partition structures; Based on the round of print control deployment, perform cyclic print control deployment based on the multiple partition structures with seamless connection of print drivers to determine the multi-drive print mode; Execute multi-axis coordinate system conversion according to the multi-drive print mode.

6. The 3D printing accuracy optimization method based on low-light modulation according to claim 1, characterized in that Perform structure adaptive partition cutting according to layer isomorphism to determine multiple partition structures, including: For the 3D mathematical structure, perform partition cutting according to layer isomorphism to determine multiple partition schemes; Traverse the multiple partition schemes and determine the target partition scheme by balancing the complexity of the projection pattern and the number of partitions; According to the target partition scheme, perform partition cutting on the 3D mathematical structure to determine the multiple partition structures.

7. The 3D printing precision optimization method based on low-light modulation according to claim 1, characterized in that, After performing multi-axis co-drive print control under layer projection stacking, including: Couple the first laser parameter and the second print 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; Perform feedback deployment based on print monitoring for the key strategy points.

8. A 3D printing precision optimization system based on micro-light modulation, characterized in that: The system is used to execute a 3D printing accuracy optimization method according to any one of claims 1-7, including: A structure partitioning module, configured to obtain the 3D mathematical structure of the printed product, perform structure adaptive partition cutting according to layer isomorphism to determine multiple partition structures, wherein 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 amplification on the layer projection pattern to determine the laser projection parameter and the reduction magnification as the first laser parameter; A trajectory decision module, configured to establish a base coordinate system based on the 3D mathematical structure, perform print trajectory decision on the multiple partition structures based on the layer projection pattern, execute multi-axis coordinate system conversion under multi-laser head co-drive to determine the second print trajectory; A print control module, configured to couple the first laser parameter and the second print trajectory, drive the 3D printing device to perform multi-axis co-drive print control under layer projection stacking, wherein if there is heterogeneous integration, perform micro-system deployment on the coupled first laser parameter - second print trajectory.

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