Curing shrinkage compensation and forming precision control method and system for 3D printing

Abstract

The invention discloses a curing shrinkage compensation and forming precision control method and system for 3D printing, and relates to the technical field of 3D printing additive manufacturing, and the method comprises the steps that three-dimensional model data and printing process parameters of a to-be-formed part are obtained, and a compensation model is established and called; generating hierarchical data according to the three-dimensional model and generating target exposure information of each layer; in the printing process, target exposure information is corrected based on the compensation model and the technological parameters to obtain execution exposure information, and curing forming is completed; acquiring an intra-layer image and comparing the intra-layer image with layered data to calculate a deviation field of the current layer; and updating the compensation model according to the deviation field increment, generating a next layer of compensation quantity, and circulating until forming is completed. A deviation field is adopted to drive closed-loop updating, self-adaptive convergence of working condition drifting is achieved, critical dimension consistency, boundary fidelity and shape stability are improved, test participation experience dependence is reduced, three-dimensional collaborative correction according to contours, doses and beats is supported, and therefore repeatability of batch manufacturing of precision parts is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of 3D printing additive manufacturing technology, in particular to a 3D printing solidification shrinkage compensation and forming precision control method and system. BACKGROUND

[0002] In recent years, additive manufacturing has gradually moved from rapid prototyping to small batch and even large-scale manufacturing. Among them, SLA, DLP and MSLA, as representatives of light-cured 3D printing, have been widely used in precise molds, medical devices, micro-structure devices and dental repair due to their high resolution and surface quality advantages. With the progress of projection light machines, resin formulations and motion platform control, single-layer exposure and peeling beat have achieved higher repeatability, and slicing software has also developed from simple contour generation to integrated control platform supporting gray-scale control, zoned exposure and process parameter management. Forming precision control has gradually become an important competitive indicator for light-cured equipment.

[0003] However, the size compensation of existing light-cured printing is still mainly offline calibration and empirical correction, which mostly uses overall proportional scaling, fixed contour offset or lookup table compensation for a small number of typical structures, making it difficult to describe the nonlinear coupling relationship between "local geometry-energy input-shrinkage stress". Therefore, in structures with thin walls / thick solids coexisting, dense holes or cross-section mutations, non-uniform shrinkage, systematic hole size reduction and boundary warping accumulation are prone to occur. At the same time, resin batch differences, environmental temperature fluctuations, release film aging and light source attenuation will introduce working condition drift, making it difficult for fixed parameters to adaptively adjust with layers, and errors are often amplified by layer-by-layer stacking. Although some solutions introduce cameras or final detection quantities, they mostly stop at defect alarms or overall comparisons after printing, lack layer-by-layer deviation field calculations consistent with the layer reference, and lack stable updating mechanisms that can be completed between two layers, which are easily affected by measurement noise and prone to compensation shocks, making it difficult to achieve "online, continuous, convergent" solidification shrinkage compensation and forming precision closed-loop control. In addition, existing compensation usually only modifies the geometric boundary, lacks coordinated regulation of exposure dose and layer-to-layer beat, and is difficult to reduce internal stress locking without sacrificing forming strength; at the same time, process data lacks correlation storage and traceability, limiting model iteration and batch reproduction. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the present application solves the technical problems of the prior art, i.e., the existing curing shrinkage compensation and forming precision control method for light-curing 3D printing has the problems of relying on offline static calibration, being difficult to adapt to non-uniform shrinkage and working condition drift, lacking a layer-in deviation field feedback mechanism consistent with a layer reference, online updating being easily affected by noise to cause compensation oscillation and being difficult to converge, and how to update a compensation model based on a layer-in image during layer-by-layer printing and generate an executable exposure correction amount to realize continuous closed-loop precision control.

[0006] To solve the above technical problems, the present application provides the following technical solutions. In a first aspect, an embodiment of the present application provides a curing shrinkage compensation and forming precision control method for 3D printing, characterized in that it comprises the following steps: obtaining three-dimensional model data of a part to be formed and corresponding printing process parameters, and establishing and calling a compensation model for representing the corresponding relationship between curing shrinkage forming deviation and compensation amount; generating layering data from the three-dimensional model data and generating target exposure information for each layer; During printing, the target exposure information is corrected based on the compensation model and the printing process parameters for the current layer to obtain execution exposure information for the current layer, and the current layer is formed according to the execution exposure information; obtaining layer-in image data after curing of the current layer, and calculating a deviation field for the current layer based on the layer-in image data and the layering data; updating the compensation model according to the deviation field and generating a compensation amount for the next layer, correcting the target exposure information for the next layer based on the compensation amount, and repeating the above steps until the curing and forming of all layers are completed, thereby obtaining a three-dimensional formed part after curing shrinkage compensation.

[0007] As a preferred solution of the curing shrinkage compensation and forming precision control method for 3D printing, the obtaining of the three-dimensional model data of the part to be formed and the corresponding printing process parameters comprises: performing geometric consistency processing and coordinate unification processing on the three-dimensional model data, the geometric consistency processing comprising closedness checking and repairing holes and broken surfaces, and the coordinate unification processing comprising unifying the three-dimensional model data to a printer coordinate system and recording its placement posture on a forming platform; obtaining printing process parameters corresponding to the current printing task, the printing process parameters comprising energy input parameters and forming beat parameters affecting curing shrinkage, and further comprising material and environmental parameters representing the current working condition; The printing process parameters are obtained by reading from a device control interface, a device operation log, an integrated sensor, and a material management module, and input by a user, and are stored in association with a current printing task for subsequent calling.

[0008] As a preferred solution of the 3D printing solidification shrinkage compensation and forming precision control method, the establishment and calling of the compensation model for representing the correspondence between the solidification shrinkage forming deviation and the compensation amount comprises: Geometric description information related to solidification shrinkage sensitivity is extracted based on the three-dimensional model data; A compensation model is constructed and called, which is configured to output an exposure compensation amount for correcting the target exposure information according to the layering data of the current printing layer, the geometric description information, and the printing process parameters when subsequently calculating for the current printing layer; The exposure compensation amount includes a contour boundary bias amount, a local exposure dose correction amount, and an exposure beat parameter correction amount; The implementation form of the compensation model is a lookup table and a rule base, a parameterized mapping model, and a data-driven model; Moreover, the compensation model is configured to update its internal parameters and rules according to the deviation field.

[0009] As a preferred solution of the 3D printing solidification shrinkage compensation and forming precision control method, the generation of layering data based on the three-dimensional model data comprises: The layering spacing is set along the printing construction direction according to the layer thickness in the printing process parameters, and a plurality of mutually parallel section planes are established; The intersection operation is performed on each of the section planes and the three-dimensional model data to obtain one or more closed two-dimensional contours corresponding to each layer, and the outer contour and the inner contour are organized into a layering contour set of the same layer when there are holes and cavities; The contour consistency processing is performed on the layering contour set, which includes contour smoothing and denoising, removing isolated islands, merging adjacent contours, and topological consistency verification; Moreover, when the contour size is close to the projection pixel resolution, the connectivity repair and boundary reconstruction processing based on the raster mask is performed on the corresponding contour to form layering data that can be stably formed.

[0010] As a preferred solution of the 3D printing solidification shrinkage compensation and forming precision control method, the generation of layering data based on the three-dimensional model data comprises: According to the resolution of the projection system and the pixel size, the layered profile set of each layer is converted to the projection coordinate system and rasterized to generate an exposure pattern corresponding to the layer, wherein the area to be shaped is marked as an exposure area, and the hole and cavity areas are marked as non-exposure areas; Based on the printing process parameters, target exposure parameters corresponding to the exposure pattern are configured for each layer, and the target exposure parameters include exposure time, gray scale, and light intensity level; Anti-aliasing processing is performed on the profile boundary of the exposure pattern, and the anti-aliasing processing includes boundary gray transition and sub-pixel boundary reconstruction; And, the target exposure information is structured and stored, which includes the exposure pattern of the layer, the target exposure parameters, the profile data representation for subsequent exposure correction, the attribute label for exposure area partition control, and the reference information for coordinate registration with the image data in the layer.

[0011] As a preferred scheme of the 3D printing solidification shrinkage compensation and forming precision control method of the present application, wherein: The compensation model is called to calculate the exposure compensation amount for correcting the target exposure information based on the printing process parameters and the layered data and geometric description information corresponding to the current layer; Wherein, the exposure compensation amount includes profile boundary offset amount, local exposure dose correction amount, and exposure beat parameter correction amount; The target exposure information of the current layer is corrected according to the exposure compensation amount to obtain the execution exposure information of the current layer, and the correction includes correction of the exposure pattern and the exposure parameter; According to the execution exposure information, the printing equipment is controlled to complete the solidification forming of the current layer, and the execution exposure information includes the execution exposure pattern and the execution exposure parameter corresponding thereto; And, the execution exposure information of the current layer is stored in association with the exposure compensation amount and the key working condition information corresponding to the current layer, for subsequent layer deviation field calculation and compensation model updating.

[0012] As a preferred scheme of the 3D printing solidification shrinkage compensation and forming precision control method of the present application, wherein: The layer image data after solidification is collected by the imaging module arranged in the printing equipment; The in-layer image data is coordinate-registered with the layered data of the corresponding layer based on the pre-set and associated reference information, and the reference information includes reference marks, alignment mark areas, and the calibration relationship between the projection coordinate system and the platform coordinate system; extracting actual forming contours and features from the layer image data after completing coordinate registration, and comparing with expected contours and expected features in the layering data to calculate the deviation field; wherein the deviation field is used to represent contour boundary offset, feature size error and area scale variation; and the deviation field is subjected to confidence evaluation and stabilization processing to form deviation information for updating the compensation model.

[0013] As a preferred scheme of the 3D printing solidification shrinkage compensation and forming precision control method of the present application, wherein: the compensation model is updated according to the deviation field and the compensation amount of the next layer is generated, and the target exposure information of the next layer is corrected based on the compensation amount and the cycle is executed, including: The deviation field is regionally summarized and characterized to obtain error information for representing systematic deviation, wherein the regional summary and characterization includes processing of contour boundary offset, feature size error and area scale variation according to preset region type, geometric category and attribute label; Based on the error information, the update basis of the compensation model is constructed, so that the update direction of the compensation model can reduce the expected deviation of the subsequent printing layer, and the incremental update of the compensation model is executed when the preset update trigger condition is met, the preset update trigger condition includes error amplitude threshold and error direction consistency condition; Based on the updated compensation model, the compensation amount of the next printing layer is calculated based on the corresponding layering data and geometric description information of the next printing layer and the printing process parameters, the compensation amount includes contour boundary offset amount, local exposure dose correction amount and exposure beat parameter correction amount; After the compensation amount is subjected to amplitude constraint and change rate constraint, the compensation amount is used to correct the target exposure information of the next printing layer to generate the execution exposure information of the next printing layer, and the cycle is executed until the solidification forming of all layers is completed; And the version management of the incremental update process of the compensation model is performed, so that when deviation anomaly and imaging quality anomaly are detected, the compensation model of the last stable version can be rolled back and the last stable compensation amount can be continued to execute.

[0014] In a second aspect, the embodiments of the present application provide a 3D printing solidification shrinkage compensation and forming precision control system, comprising: Data acquisition and compensation model preparation module: acquiring three-dimensional model data of a part to be formed and corresponding printing process parameters, and establishing and calling a compensation model for representing the corresponding relationship between solidification shrinkage forming deviation and compensation amount; Layering and target exposure information generation module: generating layering data according to the three-dimensional model data, and generating target exposure information of each layer; Layer-by-layer exposure correction and solidification forming execution module: during the printing process, the target exposure information is corrected based on the compensation model and the printing process parameters to obtain the execution exposure information of the current layer, and the current layer is completed according to the execution exposure information; Intra-layer image acquisition and deviation field calculation module: intra-layer image data after curing of the current layer is obtained, and a deviation field of the current layer is calculated based on the intra-layer image data and the layering data; Compensation model updating and next layer compensation amount generation module: the compensation model is updated according to the deviation field, and the compensation amount of the next layer is generated. The target exposure information of the next layer is corrected based on the compensation amount, and the correction is repeatedly executed until the solidification and forming of all layers are completed, so that a three-dimensional formed part after solidification and shrinkage compensation is obtained.

[0015] The beneficial effects of the present application: through the layer-by-layer model incremental update driven by the deviation field of "target exposure information - execution exposure information - intra-layer image - deviation field - model update", the compensation strategy can be adjusted according to the resin, temperature, peeling and optical closed loop, and the solidification and shrinkage error is moved from offline correction after printing to online suppression during printing; the state and working condition drift self-adapting convergence, so as to improve the key dimension consistency, boundary fidelity and overall shape stability under complex geometry and variable working condition, and reduce the dependence on operation experience and repeated test parameters. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating laborious work. Figure 1 A whole flow chart of a 3D printing solidification shrinkage compensation and forming precision control method is provided for the first embodiment of the present application; Figure 2 A module connection diagram of a 3D printing solidification shrinkage compensation and forming precision control system is provided for the third embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creating laborious work should belong to the protection scope of the present application.

[0018] Embodiment 1, refer to Figure 1 For an embodiment of the present application, a 3D printing solidification shrinkage compensation and forming precision control method is provided.

[0019] S1: Obtain the three-dimensional model data of the part to be formed and the corresponding printing process parameters, and establish and call the compensation model for representing the corresponding relationship between the solidification shrinkage forming deviation and the compensation amount.

[0020] The purpose of step S1 is to convert the to-be-formed geometry and actual working conditions into structured input that can be directly used for exposure correction and closed-loop update in the subsequent steps, and on this basis, to establish and call a compensation model that can output exposure compensation amounts, so that the execution exposure information of each subsequent layer has a computable generation basis. To make this step directly implementable in engineering, the following examples are provided in combination with specific scenarios.

[0021] The three-dimensional model data of the part to be formed can be the process of reading a standard three-dimensional model file and importing it into the printing control system. For example, when the imported model is in STL format, the control system can first identify whether the model has holes and broken surfaces; for example, for a part with a thin-walled cavity, if the STL has missing surface patches at the corner of the cavity, the layered model will have a broken contour, resulting in missing target exposure information, which will cause the solidification boundary to have a notch. To avoid such problems, the control system can perform automatic repair: fill in missing surface patches, delete duplicate surfaces, unify surface normals, and merge adjacent vertices, so that the model forms a closed contour when it is cut at any height. It should also be noted that to ensure that the image data and layered data in the subsequent layers can be aligned, the control system can unify the model to the printer coordinate system, for example, taking the center of the platform as the origin and recording the model attitude; for example, if the same part is placed on the platform with a rotation, the hole position in the in-layer image will be rotated as a whole, and if the attitude is not recorded, the deviation calculation will be incorrect, so recording the placement attitude helps to stabilize the calculation of the subsequent deviation field.

[0022] Further, to enable the compensation model to respond to the non-uniformity of the solidification shrinkage, the control system can extract the shrinkage-sensitive geometric description information from the three-dimensional model data as model input and index information. For example, for a structure containing both thick solid areas and thin-walled cantilever areas, the heat release and cross-linking degree of the thick solid areas during the solidification process are more likely to form local stress concentration, and the thin-walled cantilever areas are more likely to accumulate warping during the peeling stage; therefore, the control system can mark the categories such as "thick solid area", "thin-walled area", "long cantilever area" and "hole boundary area" in the layer-by-layer pre-analysis, and store the categories with the layer. For another example, for a screen structure with dense micro-holes, the aperture deviation usually shows local profile inward shrinkage, and the control system can record the description information such as the number of holes, the length ratio of hole boundary, and the minimum distance between holes, so that the compensation model outputs more targeted exposure compensation. It should be noted that such geometric description information can be obtained by conventional algorithms such as grid traversal, cross-section projection, contour extraction and neighborhood thickness estimation, and does not depend on complex formulas.

[0023] It should be noted that the printing process parameters are used to represent the energy input conditions and working conditions of the current printing task, and the parameter set should be able to be called by the compensation model. For example, in MSLA and DLP devices, the single-layer exposure time and gray level together determine the energy dose, when the ambient temperature is low and the resin viscosity is high, the leveling slows down and the solidification rate may change, if the same exposure strategy is still used, boundary over-curing and local under-curing often occur, resulting in layer-to-layer drift of shrinkage error; therefore, the ambient temperature, resin model and batch identification are recorded together, which helps the compensation model to output differentiated compensation under different working conditions. For another example, the increase in the number of times of using the release film will increase the peeling force, and the long and thin wall area is more likely to produce a small displacement at the peeling moment and accumulate as a size deviation, recording the state and number of times of using the release film as the process parameter helps to explain and correct such deviation. It should also be noted that parameter acquisition can be reading preset values from the device control interface, reading actual execution values from the device log, collecting by temperature and humidity sensors, reading batch information by resin management module, and inputting material identification by user; the control system preferably stores the parameters with the printing task to facilitate subsequent model updating and tracing.

[0024] The compensation model is used to represent the corresponding relationship between the solidification shrinkage forming deviation and the compensation amount, and the input is the layering data, geometric description information and printing process parameters related to the current layer, and the output is the exposure compensation amount for correcting the target exposure information. For example, the compensation amount can be represented as the outward expansion and inward contraction adjustment of the current layer exposure pattern boundary, and as the increase and decrease adjustment of the exposure gray scale of some regions; for example, for the hole boundary area, the compensation model can output the outward expansion compensation amount in the hole diameter direction to offset the decrease of the hole diameter caused by the hole solidification shrinkage; for the long and thin wall cantilever area, the compensation model can output the compensation amount of reducing the local exposure dose to reduce the stress locking caused by the rapid solidification, thereby reducing the warping risk. It should be noted that, in order to avoid the compensation model becoming an abstract concept that cannot be implemented, the compensation model in this embodiment has an executable implementation form: one is in the form of lookup table and rule base, for example, according to the resin model, layer thickness interval and geometric category label to select the corresponding boundary bias and dose correction amount; the second is in the form of parameterized regression, for example, according to the exposure time, temperature and geometric category to output the compensation amount; the third is in the form of data-driven model, for example, calling the trained model file and inputting the features to output the compensation amount. Further, the compensation model is preferably configured as an updateable model, that is, after the deviation field is obtained in the subsequent step, the lookup table entries and model parameters can be adjusted; for example, when consistent direction contour inward deviation occurs in the same thin wall area for a plurality of consecutive layers, the control system can write the deviation information into the update queue, so that the compensation model outputs a larger outward expansion compensation amount in the next layer, thereby realizing convergent correction within the same printing task.

[0025] Further, step S1 processes the three-dimensional model data into reference data that can be layered, compared and calibrated, and organizes the printing process parameters into working condition descriptions that can be called by the model, so that the compensation model has the necessary input conditions to generate exposure compensation amounts, thereby making the subsequent exposure correction have a clear control object. Especially in the scene where the solidification shrinkage presents nonlinear differences with the local thickness, cross-section changes and energy input distribution, this step introduces geometric description information and process parameters, so that the compensation amount can be generated layer by layer and region by region, rather than a single proportional scaling of the overall model; this mechanism provides an implementable data interface for the closed-loop control of updating the model based on the image calculation of the deviation field in the layer, so that the present application can still maintain the stability and repeatability of the forming precision control in the case of working condition drift.

[0026] S2: generating layering data according to the three-dimensional model data, and generating target exposure information of each layer.

[0027] The purpose of step S2 is to convert the three-dimensional model data obtained in step S1 into layered data discretized in the printing direction, and to form target exposure information that can be directly executed by the light-curing equipment on the basis of the layered data, thereby providing a unified expected reference for the subsequent closed-loop control of "exposure correction - exposure execution - deviation feedback". The layered data is used not only to generate the target exposure information, but also to align and compare with the in-layer image data subsequently, so this step preferably simultaneously completes the consistency processing of the layered profile, the small feature retention processing, and the structured packaging of the exposure information.

[0028] The generation of layered data can be achieved by a cross-section discretization method based on layer thickness, that is, the control system sets the layer spacing according to the layer thickness in the printing process parameters, and cuts the cross-section profile from the three-dimensional model data layer by layer. Specifically, the control system establishes a series of equally spaced cross-section planes along the printing direction, and performs intersection operation on each cross-section plane and the three-dimensional model to obtain one or more closed two-dimensional profiles of the layer. When the part has cavities and holes, the outer profile and the inner profile can be obtained simultaneously for the same layer, and the control system organizes the outer profile and the corresponding inner profile as a layered profile set for the same layer. It should be noted that the layering process should strictly follow the printing machine coordinate system and the model placement attitude determined in step S1, so as to ensure that the layered data can be used as the only geometric reference for subsequent deviation field calculation; for example, for a part with thread and bevel features, if the layered reference is inconsistent with the model attitude, the resulting cross-section profile will introduce projection distortion, which will in turn cause the deviation obtained by subsequent comparison to mix in non-shrinkage factors, so this step ensures stable and reliable layered reference through coordinate unification and attitude locking.

[0029] Further, to ensure the manufacturability and boundary stability of the subsequent exposure pattern, the control system can simplify and process the consistency of the two-dimensional profile, such as performing denoising and smoothing on the profile point sequence, removing isolated islands smaller than a preset area threshold, merging adjacent profiles with a distance less than a preset threshold, and performing topological consistency verification on the profile to avoid profile non-closure, self-intersection, and appearance of pseudo-small features due to grid discretization errors. Further, to address the common problems of small feature loss and thin wall breakage in light-curing forming, the control system can perform feature retention processing at the level of layered data; for example, when there are fine line structures and micro-hole structures in a layer and their sizes are close to the projection pixel resolution, the control system can first convert the cross-section profile into a pixel mask, and then perform connectivity repair and boundary reconstruction processing to make the fine line continuous and the hole boundary closed, thereby ensuring that the target exposure information generated subsequently can be stably formed. It should be noted that when the part has cross-section mutations (such as transition from a thin column to a large plane) in some layers, the control system can record the cross-sectional area change markers and thickness category markers in the layered data, which are used to compensate for the risk of model identification stress mutation in subsequent layers, and provide prior basis for exposure correction.

[0030] It should be noted that the target exposure information is used to represent the planned exposure content and planned exposure conditions of each layer before closed-loop correction, which includes exposure patterns and corresponding exposure parameters. Specifically, the exposure pattern can be a binary and multi-gray bitmap of the layer, or a combination of vectorized contour and filling strategy; the exposure parameters include exposure time, gray level and light intensity level, and can further include different exposure strategies of the bottom layer and the general layer, interlayer waiting time, and lifting and falling beat parameters related to peeling. Further, the target exposure information is preferably stored in a structured manner associated with the layer number and the exposure pattern and exposure parameter, so that the subsequent steps can clearly locate the expected reference of the current layer and correct to obtain the execution exposure information.

[0031] Further, the target exposure information of each layer can be generated by the following method: the control system converts the layered contour set of the layer into an exposure pattern in the projection coordinate system. Specifically, the control system rasterizes the contour on the projection plane to generate a bitmap mask according to the projection system resolution and pixel size; for the area that needs to be formed into a solid, the mask area is marked as an exposure area; for the hole and cavity area, the mask area is marked as a non-exposure area; for example, for a part with a cavity, the outer contour and the inner contour of the same layer form an outer solid and inner hollow mask structure after rasterization, so that the projection light field is only exposed to the outer solid area, thereby reducing the risk of mis-curing and blocking the inner cavity. It should also be noted that for projection devices such as DLP and MSLA, in order to reduce the influence of the sawtooth boundary on the size accuracy, the control system can perform anti-aliasing processing on the contour boundary, such as introducing gray transition at the boundary pixels and sub-pixel boundary reconstruction, so that the boundary energy distribution is closer to the continuous contour; the target exposure information formed by this processing can still be further corrected by the compensation model.

[0032] In order to support the correction operation of the target exposure information in the subsequent step S3, the target exposure information is preferably represented by a parameterizable data structure. For example, the control system can retain the vector contour data of the layer before generating the bitmap, so that when the compensation model outputs the contour bias, a geometric offset operation can be directly performed on the vector contour and rasterized again, thereby avoiding the boundary distortion and resolution loss caused by direct morphological transformation of the bitmap. For another example, the control system can divide the exposure area of the same layer into a near boundary area and an internal core area, and into a support adjacent area and a free boundary area, and add attribute labels to different areas, so that the subsequent compensation amount can apply different exposure dose corrections according to the area, thereby realizing zoned exposure control and providing a data interface for internal stress distribution regulation.

[0033] Further, to facilitate reliable comparison between the in-layer image data and the layered data, the embodiment preferably synchronously saves reference information for alignment in the target exposure information. For example, reference points and alignment mark areas that do not participate in part forming can be set at the edges of the printing area, so that the in-layer image captured by the camera can quickly complete coordinate registration based on the reference points; and / or the calibration relationship between the platform coordinate system and the projection coordinate system is written into the target exposure information as task-level metadata, so that the image pixel coordinates can be accurately mapped to the layered profile coordinates when the subsequent deviation field is calculated. It should be noted that the reference information does not change the forming geometry of the part, but only serves to improve the stability of measurement and comparison, thereby supporting the implementability of subsequent closed-loop updating.

[0034] Further, step S2, on the one hand, forms layered data that can be directly used as an expected geometric reference by layer-by-layer intercepting the three-dimensional model and performing consistency processing and feature reservation processing on the profile, so that the subsequent deviation field calculation has a unified reference; on the other hand, by converting the layered data into structured and parameterizable target exposure information, the compensation output by the subsequent compensation model can be efficiently applied in the form of profile offset and subzone dose correction, thereby avoiding the roughness and boundary distortion caused by traditional dependence on overall bitmap deformation. Thus, step S2 provides a stable data reference and executable control primitive for subsequent exposure correction and closed-loop compensation, so that the solidification shrinkage compensation and forming precision control have the prerequisite for engineering landing.

[0035] S3: During printing, the target exposure information is modified based on the compensation model and the printing process parameters for the current layer to obtain execution exposure information of the current layer, and the current layer is formed by solidification according to the execution exposure information.

[0036] The purpose of step S3 is to convert the target exposure information obtained in step S2 into execution exposure information that can achieve solidification shrinkage compensation under the current working condition, and to complete the solidification forming of the current layer. Unlike the conventional method of directly exposing according to fixed exposure parameters, step S3 introduces the compensation model and the printing process parameters in the layer-by-layer printing process, so that the exposure pattern and the exposure parameter can be controllably adjusted according to the layer, the region, and the working condition, thereby feeding forward and suppressing the size deviation caused by non-uniform shrinkage while solidification occurs, and providing a convergent initial control amount for subsequent deviation field feedback update.

[0037] When the target exposure information is corrected by the current layer, the control system preferably determines the input set of the current layer first and calls the compensation model to output the compensation amount according to the input set. The input set includes the hierarchical data of the current layer and the corresponding target exposure pattern, the target exposure parameters, and the layer thickness, the exposure time, the gray level and the light intensity level, the resin model and batch identification, the resin tank temperature and the environmental temperature, the lifting and falling beat parameters related to peeling, etc. in the printing process parameters. Further, to improve the pertinence of compensation, the control system can also introduce the region attribute label formed in step S2, such as the near boundary region, the core region, the support adjacent region, the free boundary region, the thin wall region and the hole boundary region, so that the compensation model can output differentiated compensation amounts for different regions. It should be noted that the above inputs can be directly obtained by the equipment and generated by the slicing process, so that the present step is engineering implementable.

[0038] Further, the compensation amount output by the compensation model is used to generate the execution exposure information, and the compensation amount includes the boundary bias amount of the exposure pattern profile, the correction amount of the local exposure dose, and the correction amount of the exposure beat parameter. Specifically, when the compensation amount is the profile boundary bias amount, the control system can perform a geometric offset operation on the vector profile retained in the target exposure information to form an execution profile after outward expansion and inward shrinkage, and then rasterize the execution profile to generate an execution exposure pattern. For example, when the hole boundary region presents a stable hole diameter reduction trend in historical printing, the compensation model can output an outward expansion bias in the hole diameter direction, so that the hole in the execution exposure pattern is slightly larger than the target hole, so that the hole diameter approaches the design value after solidification shrinkage. It should be noted that the method of offsetting the vector profile and rasterizing again can avoid the stair-shaped sawtooth distortion and resolution loss caused by directly performing morphological processing such as dilation and erosion on the bitmap, thereby improving the geometric fidelity of the compensation execution.

[0039] When the compensation amount is the local exposure dose correction amount, the control system can set different gray levels and exposure times in different regions in the execution exposure pattern to realize zoned dose control; for example, for the free boundary thin wall region, the control system can reduce the local dose to reduce the solidification rate peak value and reduce the risk of stress locking and warping accumulation; for the support adjacent region and the thick entity region, the control system can appropriately increase the local dose to enhance the early solidification stiffness and improve the anti-peeling disturbance ability. It should be noted that when the equipment adopts a binary exposure mode, the dose correction can be realized by exposure time fine adjustment and multiple short exposure accumulation, so that the local dose can still be adjusted, thereby not relying on specific hardware for implementation.

[0040] When the compensation amount relates to the exposure beat parameters, the control system can correct the interlayer waiting time, lifting speed, falling speed, lifting height and segmented lifting strategy in the execution exposure parameters, so that the pattern compensation and process beat form a coordinated control. For example, when the ambient temperature is low and the resin viscosity is high, the control system can appropriately increase the interlayer waiting time to ensure that the resin fully flows back and reduce local material shortage and boundary defects caused by insufficient leveling; for example, when the release film state causes the peeling force to increase, the control system can reduce the lifting speed and use the segmented lifting mode to reduce the disturbance to the thin-walled area at the peeling moment, thereby reducing the interlayer cumulative deviation. It should be noted that the above beat parameters belong to the category of printing process parameters, and the correction of this step can enhance the robustness of the compensation strategy to the working condition drift.

[0041] It should be noted that the execution exposure information of the current layer refers to the final instruction set formed after the above correction, which can directly drive the printing equipment, includes the execution exposure pattern and the corresponding execution exposure parameters, and is used to replace the target exposure information for manufacturing the current layer. Further, to ensure process traceability and reliable subsequent closed-loop update, the control system preferably stores the execution exposure information of the current layer in association with the compensation amount of the current layer and the key process state information of the current layer, including the actual exposure time, the actual gray level and the light intensity level, the resin tank temperature, the actual lifting and falling beat execution value, etc., and binds it with the layer number, providing data basis for the deviation field calculation of the subsequent step S4 and the model update of step S5.

[0042] It should also be noted that when the current layer is completed, the control system loads the execution exposure pattern to the projection system and controls the light source output and platform motion according to the execution exposure parameters. Specifically, for DLP and MSLA devices, the control system maps the execution exposure pattern to the projection pixel array and triggers the exposure; for SLA scanning devices, the control system can convert the corrected execution profile into a scanning path, and determine the scanning speed and laser power in combination with the execution exposure parameters, so that the curing trajectory and energy input meet the requirements of the execution exposure information, thereby completing the curing of the current layer and bonding with the lower layer to form a shape.

[0043] Further, step S3 acts on the profile, dose and beat of the target exposure information by the compensation amount output by the compensation model before each layer is formed, forms the execution exposure information, so that the compensation is improved from the traditional overall proportional scaling to the fine control of layers and regions, and the size deviation caused by non-uniform shrinkage can be fed forward and inhibited at the same time of curing; at the same time, by including the printing process parameters in the correction calculation and allowing the beat parameters to be adjusted coordinately, this step can respond to the working condition drift caused by changes in temperature, resin state and peeling conditions, reduce the cumulative trend of errors between layers and improve the stability and repeatability of the control of forming precision.

[0044] S4: Obtain the in-layer image data of the current layer after solidification, and calculate the deviation field of the current layer based on the in-layer image data and the layering data.

[0045] The purpose of step S4 is to obtain the difference between the actual forming geometry and the expected geometry of the current layer after it is solidified and formed in a quantifiable manner, and to characterize the difference as a deviation field that can be directly utilized by subsequent step S5. Unlike overall measurement only after printing is completed, this step obtains deviation information at the layer level, enabling deviations to be identified and used for compensation updates of subsequent layers before they have accumulated, thereby improving the convergence speed and stability of closed-loop control. The deviation field is preferably a two-dimensional spatial distribution data consistent with the projection plane coordinates of the current layer, used to describe deviations related to solidification shrinkage such as outer contour boundary offset, aperture error, line width error, and local area scale variation.

[0046] The in-layer image data of the current layer after solidification can be obtained by an imaging module provided in the printing device. The imaging module can be a top-view camera, a side-view camera, and a coaxial imaging assembly turned by a mirror, and preferably cooperates with an illumination unit to improve image contrast and contour distinguishability. Further, the illumination unit can use coaxial light and low-angle ring light to enhance the bright-dark gradient of the contour edge and suppress the interference of the liquid resin surface reflection; the control system can automatically adjust the illumination intensity and camera exposure time, and perform white balance and background correction before each batch of printing to obtain stable and repeatable imaging quality. Further, the imaging trigger timing can be set after the current layer exposure is completed and the platform completes a lifting and peeling, and after the platform completes a falling and the resin is re-spread stable; preferably, the imaging trigger timing is consistent in the same printing task to avoid introducing non-geometric factors due to liquid surface disturbance and reflection differences.

[0047] Further, the imaging module preferably performs basic calibration and registration preparation to enable mapping of image pixel coordinates to projection coordinates and platform coordinates. For example, a reference mark area not involved in part forming can be set at the edge of the printing area, and the reference mark can be a cross target, concentric circles, and a specific arrangement of dot matrix; the actual position of the reference mark is obtained synchronously when the in-layer image is collected, and is matched with the theoretical position of the reference mark stored in step S2, thereby calculating the coordinate mapping relationship between the image and the layering data, so that the subsequent deviation calculation has a consistent coordinate reference. It should also be noted that in the case where it is not convenient to set the reference mark, the control system can also estimate the translation and rotation deviation by matching the overall shape of the outer contour to complete the registration, thereby ensuring that the deviation field calculation does not rely on a single alignment method.

[0048] Further, before the deviation field calculation, the control system preferably pre-processes the in-layer image data to reduce the interference of uneven illumination, liquid surface reflection, resin residue and motion blur on the boundary extraction. Specifically, the pre-processing can include denoising filtering, brightness normalization, background subtraction, and contrast enhancement processing of exposed and unexposed regions; when there are local high-reflectance regions in the image, the control system can use multi-frame acquisition and select stable frames, and threshold clipping for high-light regions to avoid false detection; when the resin liquid surface is still flowing at the imaging time, the control system can reduce motion blur by using delay acquisition and short exposure shutter mode, thereby improving the stability of boundary positioning.

[0049] It should be noted that the deviation field of the current layer is calculated based on the in-layer image data and the layered data, the core of which is to align the actual forming geometry extracted from the in-layer image with the expected geometry represented by the layered data generated in step S2, and to calculate the difference in the same coordinate system after alignment. Specifically, after registration is completed, the control system extracts the actual contour and feature information from the in-layer image, and the feature information includes the outer contour boundary, the hole boundary, the key dimension boundary, and the edge line in the preset detection area. Further, to improve the robustness of contour extraction, the control system can determine the boundary position by combining threshold segmentation and gradient detection; for example, when the solidification boundary has a solidification halo due to light scattering, there may be a low-contrast diffusion area outside the boundary on the image, at which time the control system can take the center of the high-gradient position as the true contour position to eliminate the influence of scattered light and reduce false outer expansion error. For micro-hole and fine-line features close to pixel resolution, the control system can also use sub-pixel edge positioning to refine the boundary position to improve the measurement accuracy of hole diameter and line width.

[0050] Further, the calculation of the deviation field can be performed separately according to the feature type. Specifically, for the contour boundary deviation, the control system can sample boundary points on the expected contour at a preset interval, and search for the corresponding actual edge position in the image in the normal direction of each boundary point to obtain the normal offset of the point, and then form a boundary offset deviation along the boundary distribution; for the size deviation of holes and local features, the control system can calculate the difference between the actual hole diameter and the expected hole diameter, and map it to the hole boundary neighborhood to form a local deviation distribution; for the area scale change deviation, the control system can perform area overlap analysis on the actual exposed area and the expected exposed area in the image to obtain the local area difference and the local shape difference, and convert them into a deviation distribution on the projection plane. Further, to improve the available correlation between the deviation field and the compensation amount, the control system can aggregate and statistics the deviation field according to the region attribute labels in step S2, for example, to calculate the average boundary offset and the average size error of the near-boundary region, the core region, the support adjacent region, the thin-wall region and the hole boundary region, respectively, so that the subsequent compensation model update obtains more stable error signals.

[0051] To avoid compensation oscillations caused by measurement noise, this embodiment preferably performs effectiveness screening and stabilization processing on the deviation field. Specifically, the control system can set a reliable threshold rule. For example, when the deviation amplitude is less than the minimum resolvable size corresponding to the imaging resolution, it is regarded as measurement noise and no model update is triggered. When the deviation in a certain local area is abnormally large and accompanied by abnormal image quality, it is marked as an abnormal layer and a conservative update strategy is adopted. The control system can also perform moving average and weighted fusion on the deviation fields of several adjacent layers to reduce the impact of occasional disturbances in a single layer on the model update, thereby improving the stability and repeatability of closed-loop control.

[0052] Furthermore, step S4 acquires and quantifies the difference between the actual forming geometry and the expected layering reference at the hierarchical scale, forming a deviation field that can be used to generate compensation amounts and update the compensation model. This allows the closed-loop control of the present invention to no longer rely on overall measurements after printing, thereby enabling earlier identification and suppression of error accumulation caused by curing shrinkage, peeling disturbances, and operating condition drift. Simultaneously, through reference mark registration, robust contour extraction, and deviation stabilization processing, this step can still output a reliable deviation signal in the actual environment of resin surface reflection and noise, providing a stable data basis for the adaptive update in the subsequent step S5, thereby improving the stability and repeatability of forming accuracy control.

[0053] S5: Update the compensation model according to the deviation field and generate the compensation amount of the next layer. Based on the compensation amount, correct the target exposure information of the next layer and repeat the process until the curing of all layers is completed, thereby obtaining a three-dimensional molded part with curing shrinkage compensation.

[0054] The purpose of step S5 is to transform the deviation field obtained in step S4 into an adaptive correction basis for the compensation model, and based on this, generate the next layer of directly executable compensation amount, so that the compensation strategy can continuously converge as the working conditions drift and error accumulation trend during the printing process. Unlike the approach that relies solely on initial calibration and fixed empirical parameters, this step uses a recursive mechanism of "deviation field - model update - next layer compensation amount" to make the compensation model conform to the current resin state, temperature conditions, peeling conditions and optical state layer by layer within the same printing task, thereby improving the stability and repeatability of forming accuracy control, and obtaining a three-dimensional formed part with curing shrinkage compensation after all layers have been cured and formed.

[0055] The process of updating the compensation model based on the deviation field preferably includes extracting usable error signals from the deviation field, constructing an error metric for updating and determining the adjustment direction of model parameters accordingly, executing the update, and managing the version. Specifically, the control system can first perform regional summarization and feature representation of the deviation field to reduce the impact of measurement noise on the update and improve the update's targeting. For example, the average boundary offset, aperture deviation, and linewidth deviation of the near-boundary region, hole boundary region, thin-walled free boundary region, support adjacent region, and core region can be calculated separately, and the consistency of deviation direction and the number of continuous layers can be recorded to determine whether the deviation is a random disturbance or a systematic drift. Furthermore, when the deviation of the same feature region shows a stable trend with the same direction and similar amplitude within several consecutive layers, the control system can determine it as a compensable systematic deviation and trigger a model update; when the deviation shows unstable fluctuations and is associated with abnormal image quality, the control system can adopt a conservative update strategy and postpone the update to avoid compensation oscillations.

[0056] Furthermore, the error metric is used to guide the updates of the compensation model towards reducing the system bias. It can be constructed based on the degree of deviation between the compensation model output and the bias field, enabling the adjustment of model parameters to reduce the expected bias of the next layer. For example, when the bias field indicates a persistent contour shrinkage bias in a certain region, the error metric will guide the compensation model to increase the outward contour bias of that region in the next prediction, and simultaneously adjust the dose and beat corrections for that region, so that the actual contour of subsequent layers reverts to the design baseline. When the bias field indicates a general shrinkage of the pore boundaries, the error metric will guide the compensation model to increase the outward bias of the pore boundaries, thereby reducing the tendency for the pore size to decrease with cumulative layer growth. It should be noted that the above guiding relationship can be achieved through rule weight adjustment, parameter recursive correction, and model fine-tuning, without requiring precise inversion of the material mechanism.

[0057] The update method of the compensation model can be set according to the implementation form of the compensation model, and preferably adopts a lightweight update mechanism that can be executed in real time within the printing cycle. It should be noted that the lightweight update mechanism aims to ensure that the model update calculation can be completed within a finite time interval between two printing layers, thereby not interrupting the continuous printing process and maintaining the established forming cycle. Furthermore, when the compensation model is in the form of a lookup table and rule base, the update can be manifested as incremental correction of the corresponding entries, such as adding or subtracting adjustments to the boundary bias, dosage correction, and cycle correction amounts indexed by "resin type—layer thickness range—region label," and setting an upper limit for the update step size and a trigger threshold to avoid overcompensation. Furthermore, when the compensation model is in the form of a parametric mapping, the update can be manifested as recursive correction of the model parameters, such as adjusting the boundary bias coefficient, dosage coefficient, and cycle correction coefficient with small steps, so that the model output tends to offset the systematic errors reflected in the deviation locations in the next layer. It should also be noted that when the compensation model is a data-driven model, the update can adopt online fine-tuning and incremental learning: the control system forms an online sample with the input set of the current layer and the deviation field, and uses the error metric as the update signal to fine-tune the model parameters in a limited small step size; in order to avoid model drift leading to instability, online updates are preferably limited to relevant parameters at the output end and a small number of controllable parameters, and a model version rollback mechanism is set to restore to the previous stable version when abnormal deviations occur.

[0058] Furthermore, after updating the compensation model, the control system generates the compensation amount for the next layer based on the updated compensation model. The compensation amount preferably matches the executable control dimension used in step S3, including contour boundary offset, local dose correction, and cycle time parameter correction. For example, when the deviation field shows that the hole boundaries are generally shrinking inward, the compensation model outputs a larger outward offset for the hole boundaries in the next layer; when the deviation field shows abnormal boundary offset in the free boundary thin-walled region accompanied by peeling disturbance characteristics, the compensation model can output a correction amount that reduces the dose and increases the interlayer waiting time for that region in the next layer to reduce the peak curing rate and improve leveling, thereby suppressing further error propagation. Furthermore, to improve the stability and safety of the compensation amount application, the control system can set constraint rules for the compensation amount, including the maximum offset amplitude, the maximum dose adjustment range, and the maximum cycle adjustment range, and can implement layer-by-layer gradual restriction on the compensation amount according to the layer number; for example, in the transition layer between the abrupt cross-section layer and the thin-walled to thick solid, the control system can limit the rate of change of the compensation amount to avoid introducing new boundary distortion and local under-curing risks due to excessive single-layer compensation.

[0059] It should be noted that the step of correcting the target exposure information of the next layer based on the compensation amount and executing it cyclically means that the control system uses the compensation amount generated in step S5 as the input to step S3, so that the target exposure information of the next layer is corrected to the execution exposure information and solidified. Then, the image within the layer is acquired again and the deviation field is calculated. Subsequently, the compensation model is updated and the compensation amount of the next layer is generated, thus forming a closed-loop iterative process that runs through all layers. Furthermore, the control system preferably establishes a closed-loop log for each layer, and stores the target exposure information, execution exposure information, compensation amount, deviation field summary and model version number of that layer in association to achieve process traceability and anomaly rollback. When the deviation of a certain layer exceeds the confidence threshold and the image quality is abnormal, the control system can mark the layer as a sample that does not participate in the update and continue to execute using the compensation amount generated by the previous stable model version, thereby ensuring system stability.

[0060] Furthermore, step S5 transforms the deviation field into an error signal that can be used to update the compensation model, and applies the update result as a compensation amount to the next layer's exposure correction in real time. This allows the compensation model to adapt layer by layer to time-varying factors such as resin batch variations, temperature fluctuations, release condition changes, and optical state drift within the same printing task, suppressing the accumulation trend of errors between layers. Simultaneously, through mechanisms such as regional aggregation, trigger thresholds, conservative updates, amplitude constraints, and version rollback, this step maintains the stability of closed-loop updates in real-world environments with measurement noise and occasional disturbances, making the compensation process exhibit convergence characteristics. In summary, step S5 transforms the precision control of 3D printing from a mode relying on pre-process offline, static calibration to an online, dynamic, self-optimizing process throughout the entire manufacturing process. This reduces the reliance on repeated manual parameter testing and relaxes the requirements for environmental constancy and material consistency, thus providing crucial support for the application of photopolymerization technology in stable manufacturing scenarios for high-precision parts.

[0061] Example 2 is the second embodiment of the present invention, which differs from the previous embodiment in that: If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art or the current technical solution, can be embodied in the form of a software product. This current computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0062] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0063] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0064] Example 3, referring to Figure 2 As an embodiment of the present invention, a curing shrinkage compensation and forming accuracy control system for 3D printing is provided, which includes a data acquisition and compensation model preparation module, a layer and target exposure information generation module, a layer-by-layer exposure correction and curing forming execution module, an intra-layer image acquisition and deviation field calculation module, and a compensation model update and next layer compensation amount generation module. Data acquisition and compensation model preparation module: acquire the three-dimensional model data of the part to be formed and the corresponding printing process parameters, and establish and call the compensation model to characterize the relationship between curing shrinkage forming deviation and compensation amount; Layering and Target Exposure Information Generation Module: Generates layered data based on the 3D model data, and generates target exposure information for each layer; Layer-by-layer exposure correction and curing execution module: During the printing process, the target exposure information of the current layer is corrected based on the compensation model and the printing process parameters to obtain the execution exposure information of the current layer, and the curing of the current layer is completed accordingly; Intra-layer image acquisition and deviation field calculation module: acquires intra-layer image data after solidification of the current layer, and calculates the deviation field of the current layer based on the intra-layer image data and the layer data; Compensation model update and next layer compensation amount generation module: Update the compensation model according to the deviation field and generate the compensation amount of the next layer. Based on the compensation amount, correct the target exposure information of the next layer and repeat the process until the curing and forming of all layers is completed, thereby obtaining a three-dimensional formed part with curing shrinkage compensation.

[0065] Example 4 is an embodiment of the present invention, which provides a method for curing shrinkage compensation and forming accuracy control in 3D printing. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / comparative experiments.

[0066] This embodiment uses a 405nm DLP photopolymerization printer (projection resolution 3840×2160, pixel size approximately 50μm) to comparatively print seven typical structural parts under constant temperature conditions: stepped perforated plate calibration parts, thin-walled cantilever structures, precision threaded joints, microporous screens, fine-module gears, internal cavity flow channel manifolds, and multi-pin connector seats. Each type of part is mounted on the same platform and uses the same resin batch, with consistent basic process windows (layer thickness 35–50μm, exposure time approximately 2.18–2.72s, light intensity level approximately 75.6%–80.2%, and lift-off speed approximately 4.3–5.4mm / s). Two strategies are implemented: one is a conventional "overall scaling + fixed exposure / beat" comparison strategy (scaling factor set empirically); the other is the closed-loop strategy of the present invention. Under the closed-loop strategy, firstly, 3D model files such as STL are imported and geometric consistency processing is performed (closure check, hole / damage repair, normal unification, and nearest neighbor vertex merging). Then, the model is unified to the printer coordinate system and the placement posture is recorded. Further, the model is pre-analyzed to extract geometric description information related to shrinkage sensitivity (e.g., thin-walled / thick solid classification, free boundary / support adjacency zone labels, hole boundary and feature boundary sets, cross-sectional abrupt layer markings, etc.). A compensation model is then established and invoked as the initial mapping relationship, combined with printing process parameters. Subsequently, slices are generated based on layer thickness, generating layered data and target exposure information for each layer. In addition to exposure patterns and parameters, the target exposure information also includes structured encapsulation of vector contour representation, partition attribute labels, and image registration reference information. During the printing process, a compensation model is invoked before each layer exposure. This model integrates the current layer's layer data, geometric description information, and real-time / task-level process parameters to calculate compensation amounts such as contour boundary offset, local dose correction, and cycle time correction. This generates the layer's exposure information and completes curing. After curing, the in-machine imaging module acquires image data within the layer, performs coordinate registration using reference information, extracts the actual contour and feature boundaries, and compares them with the layer benchmark to calculate the deviation field. After confidence evaluation and stabilization, the deviation field forms usable deviation information, used for incremental updates to the compensation model and generating the compensation amount for the next layer. To ensure online cycle time continuity, update calculations are limited to the interval between two layers. When imaging quality anomalies and deviation anomalies are detected, anomaly filtering is triggered, and the model can be rolled back to the previous stable model version. After the part is printed and cleaned, a tool microscope and coordinate measuring machine are used to verify key dimensions, aperture / equivalent aperture, and warpage. The comparison results shown in the table below are statistically analyzed (the terms "traditional" and "invention" in the table refer to the statistical values ​​of the same part under the two strategies).

[0067] The key data recorded is shown in Table 1: Table 1: Experimental Data Recording Table

[0068] As can be seen from the mean absolute error (MAE) of critical dimensions, the conventional "overall scaling + fixed exposure / beat" comparison strategy exhibits obvious non-uniform error characteristics on parts with different geometric categories, and the error amplitude increases significantly with thin walls, small features, and internal cavity structures. For example, the conventional MAE for microporous screens and flow channel manifolds reaches 95.4 μm and 104.8 μm, respectively, while that for connectors and thin-walled cantilever structures is 89.6 μm and 83.1 μm, respectively. This reflects that the conventional method is difficult to simultaneously account for multiple sources of error such as "hole boundary shrinkage," "free boundary shrinkage / warping," and "stress locking in abrupt cross-section layers." In comparison, the closed-loop method of this invention reduces the MAE of the aforementioned parts to 31.2 μm, 36.7 μm, 29.8 μm, and 27.6 μm, respectively, under the same equipment and material window. For structures with boundary accuracy as the primary concern, such as stepped hole plates, gears, and threaded joints, the MAE is also reduced from 62.7 μm, 58.3 μm, and 71.8 μm to 18.9 μm, 17.4 μm, and 22.1 μm. This result indicates that the layer-by-layer update mechanism driven by the deviation field can suppress the interlayer accumulation of errors and enable the compensation amount to adaptively converge with the structure and operating conditions, rather than relying on a single empirical scaling factor.

[0069] Further observation of the maximum boundary offset index revealed that traditional strategies exhibited a boundary drift phenomenon of "coexistence of local over-curing and local under-curing" on most parts, with the maximum boundary offset fluctuating within the range of 126.6–221.4 μm. Particularly, the offset reached 206.7 μm and 221.4 μm for microporous screens and internal manifolds, respectively, indicating that boundary control is more prone to instability near small features and complex cavities. The method of this invention reduces the corresponding index to the range of 41.8–93.5 μm, with the stepped perforated plate and gears showing offsets of only 44.7 μm and 41.8 μm, respectively. This demonstrates that the executable control dimension of "contour boundary offset" can directly affect the boundary normal error, avoiding the boundary distortion caused by traditional coarse-grained processing using bitmap morphology and overall scaling. Meanwhile, the aperture / equivalent aperture error data further corroborates this point: for orifice plates, threaded joints, microporous screens, gear holes, manifold interfaces, and connector hole groups, the traditional error ranges from 47.6 to 88.9 μm, while the present invention reduces it to the range of 14.2 to 28.6 μm, demonstrating that the model has a stronger directional compensation capability in the highly sensitive area of ​​"hole boundaries"; although the aperture error of the manifold is reduced to 28.6 μm, it is still higher than that of the gear / orifice plate, which is consistent with the engineering fact that the internal cavity structure is affected by both light scattering and peeling disturbance, and the error mechanism is more complex.

[0070] Regarding shape stability, the peak-to-peak warpage is a typical weakness of traditional methods, reaching 268.6 μm for thin-walled cantilever and 312.7 μm for internal manifold, indicating that fixed exposure and overall scaling alone cannot manage the amplification effect of curing stress and peeling disturbance on the free boundary of thin walls. The method of this invention reduces these peaks to 112.4 μm and 146.5 μm, respectively, a significant reduction. This is because the compensation in this invention does not merely adjust the geometric boundary, but simultaneously introduces two types of synergistic control measures: "local dose correction" and "exposure beat parameter correction." This reduces the peak curing rate in the thin-walled region of the free boundary, maintains necessary stiffness in the adjacent support region and thick solid region, and improves leveling and peeling load through beat fine-tuning, thereby suppressing the conditions for warpage formation at the process level. This three-dimensional coupled compensation of "geometry-energy-beat" provides a control granularity and path that traditional overall scaling strategies cannot achieve.

[0071] From the perspective of online feasibility and robustness, the additional inter-layer computation time of this invention is 52–76 ms, and the total printing time increases by only 0.8%–1.7%, indicating that model inference, deviation field calculation, and incremental updates can be completed within the interval between two layer cycles without disrupting printing continuity. Simultaneously, the number of abnormal layer filtering triggers is 0–2 times, and the number of model version rollbacks is 0–1 times, demonstrating that in the presence of actual imaging noise and occasional disturbances, the confidence assessment / stabilization and version management mechanisms can effectively block the "erroneous injection" of abnormal data into model updates, ensuring closed-loop convergence rather than oscillation. In summary, the comparative results of this embodiment objectively demonstrate that compared to existing compensation methods that rely primarily on empirical scaling and fixed parameters, this invention, through a recursive closed loop of "intra-layer imaging deviation field—model update—next layer compensation amount," elevates forming accuracy control from static calibration to an online adaptive optimization process, achieving significant and reproducible comprehensive improvements in key dimensions, boundary offset, aperture preservation, and warpage suppression.

[0072] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications and equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method of 3D printing with solidification shrinkage compensation and form accuracy control, characterized in that, The method comprises the following steps: obtaining three-dimensional model data of a part to be formed and corresponding printing process parameters, and establishing and calling a compensation model for representing the corresponding relationship between the forming deviation caused by solidification shrinkage and the compensation amount; generating layered data according to the three-dimensional model data, and generating target exposure information of each layer; in the printing process, the target exposure information is corrected based on the compensation model and the printing process parameters for the current layer to obtain execution exposure information of the current layer, and the current layer is solidified and formed according to the execution exposure information; obtaining in-layer image data after the current layer is solidified, and calculating the deviation field of the current layer based on the in-layer image data and the layered data; updating the compensation model according to the deviation field and generating the compensation amount of the next layer, correcting the target exposure information of the next layer based on the compensation amount, and repeating the above steps until the solidification and formation of all layers are completed, so that a three-dimensional formed part compensated by solidification shrinkage is obtained.

2. The method of claim 1, wherein, The method comprises the following steps: performing geometric consistency processing and coordinate unification processing on the three-dimensional model data, the geometric consistency processing includes closedness checking and repairing holes and broken surfaces, and the coordinate unification processing includes unifying the three-dimensional model data to the printer coordinate system and recording the placement posture on the forming platform; obtaining the printing process parameters corresponding to the current printing task, the printing process parameters include energy input parameters and forming beat parameters affecting solidification shrinkage, and further include material and environmental parameters representing the current working condition; wherein the printing process parameters are obtained by reading from the device control interface, device operation log, integrated sensor and material management module, and input by the user, and are stored in binding with the current printing task for subsequent calling.

3. The method of claim 2, wherein the 3D printing of the solidification shrinkage compensation and form precision control is performed by a 3D printer. The method comprises the following steps: extracting geometric description information related to solidification shrinkage sensitivity based on the three-dimensional model data; constructing and calling a compensation model, the compensation model is configured to output exposure compensation amount for correcting the target exposure information according to the layered data of the current printing layer, the geometric description information and the printing process parameters when calculating the current printing layer subsequently; wherein the exposure compensation amount includes contour boundary bias amount, local exposure dose correction amount and exposure beat parameter correction amount; the implementation form of the compensation model is lookup table and rule base, parameterized mapping model, data driven model; and the compensation model is configured to update its internal parameters and rules according to the deviation field.

4. The method of claim 3, wherein, The method comprises the following steps: setting the layer spacing along the printing construction direction according to the layer thickness in the printing process parameters, and establishing a plurality of mutually parallel section planes; performing intersection operation on each section plane and the three-dimensional model data to obtain one or more closed two-dimensional contours corresponding to each layer, and organizing the outer contour and the inner contour into a layered contour set of the same layer when there are holes and cavities; performing contour consistency processing on the set of layered contours, the contour consistency processing including contour smoothing and denoising, removing isolated islands, merging adjacent contours, and topology consistency checking; and, when the contour size approaches the resolution of the projection pixels, performing raster mask based connectivity repair and boundary reconstruction processing on the corresponding contour to form layered data that can be stably shaped.

5. The method of claim 4, wherein, The generating of the target exposure information of each layer includes: According to the resolution and pixel size of the projection system, the set of layered contours of each layer is converted to the projection coordinate system and rasterized to generate an exposure pattern corresponding to the layer, wherein the area to be shaped is marked as an exposure area, and the hole and cavity areas are marked as non-exposure areas; Based on the printing process parameters, target exposure parameters corresponding to the exposure pattern are configured for each layer, including exposure time, gray scale, and light intensity level; performing anti-aliasing processing on the contour boundaries of the exposure pattern, the anti-aliasing processing including boundary gray scale transition and sub-pixel boundary reconstruction; and, structuring and storing the target exposure information, including the exposure pattern of the layer, the target exposure parameters, the contour data representation for subsequent exposure correction, the attribute label for exposure area partition control, and the reference information for coordinate registration with the image data in the layer.

6. The method of claim 5, wherein, The obtaining of the execution exposure information of the current layer, and the completion of the solidification shaping of the current layer according to the execution exposure information include: calling the compensation model, based on the printing process parameters and the layered data and geometric description information corresponding to the current layer, to calculate the exposure compensation amount for correcting the target exposure information; wherein the exposure compensation amount includes contour boundary offset amount, local exposure dose correction amount, and exposure beat parameter correction amount; According to the exposure compensation amount, the target exposure information of the current layer is corrected to obtain the execution exposure information of the current layer, and the correction includes correction of the exposure pattern and the exposure parameter; According to the execution exposure information, the printing equipment is controlled to complete the solidification shaping of the current layer, and the execution exposure information includes the execution exposure pattern and the execution exposure parameter corresponding thereto; and, the execution exposure information of the current layer is stored in association with the exposure compensation amount and the key working condition information corresponding to the current layer, for the deviation field calculation and compensation model updating of the subsequent layer.

7. The method of claim 6, wherein, The calculation of the deviation field of the current layer includes: acquiring layer image data after solidification of the current layer by an imaging module provided in the printing equipment; based on the pre-set and associated reference information, the layer image data is coordinate-registered with the layered data of the corresponding layer, and the reference information includes reference marks, alignment mark areas, and the calibration relationship between the projection coordinate system and the platform coordinate system; from the layer image data after coordinate registration, actual shaped contours and features are extracted and compared with expected contours and expected features in the layered data to calculate the deviation field; wherein the deviation field is used to represent contour boundary offset, feature size error, and area scale change; and, the deviation field is subjected to confidence evaluation and stabilization processing to form deviation information for updating the compensation model.

8. The method of claim 7, wherein, The compensation model is updated according to the deviation field, and a compensation amount of a next layer is generated, target exposure information of the next layer is corrected based on the compensation amount, and the above steps are repeatedly executed until the whole layer is solidified and formed. The error information is obtained by regionally aggregating and characterizing the deviation field, and the regionally aggregating and characterizing includes processing of statistically calculating contour boundary offset, feature size error and region scale change according to preset region types, geometric categories and attribute labels; The update basis of the compensation model is constructed based on the error information, so that the update direction of the compensation model can reduce the expected deviation of the subsequent printing layer, and the incremental update of the compensation model is performed when the preset update trigger condition is met, and the preset update trigger condition includes an error amplitude threshold and an error direction consistency condition; Based on the updated compensation model, the compensation amount of the next printing layer is calculated by combining the layering data and geometric description information corresponding to the next printing layer and the printing process parameters, and the compensation amount includes contour boundary offset amount, local exposure dose correction amount and exposure beat parameter correction amount; After the compensation amount is subjected to amplitude constraint and change rate constraint, the compensation amount is used to correct the target exposure information of the next printing layer to generate execution exposure information of the next printing layer, and the above steps are repeatedly executed until the whole layer is solidified and formed. The version management is performed on the incremental update process of the compensation model, so that when deviation anomaly and imaging quality anomaly are detected, the compensation model of the last stable version can be rolled back and the last stable compensation amount can be used for continuous execution.

9. A 3D printing solidification shrinkage compensation and forming accuracy control system for implementing the 3D printing solidification shrinkage compensation and forming accuracy control method as claimed in any one of claims 1 to 8, characterized by, The data acquisition and compensation model preparation module acquires three-dimensional model data of a part to be formed and corresponding printing process parameters, and establishes and calls a compensation model for representing a correspondence between solidification shrinkage forming deviation and compensation amount. The layering and target exposure information generation module generates layering data according to the three-dimensional model data, and generates target exposure information of each layer. The layer-by-layer exposure correction and solidification forming execution module corrects the target exposure information based on the compensation model and the printing process parameters to obtain execution exposure information of the current layer, and completes solidification and formation of the current layer according to the execution exposure information. The in-layer image acquisition and deviation field calculation module acquires in-layer image data after the current layer is solidified, and calculates a deviation field of the current layer based on the in-layer image data and the layering data. The compensation model update and next layer compensation amount generation module updates the compensation model according to the deviation field, generates a compensation amount of a next layer, corrects target exposure information of the next layer based on the compensation amount, and repeatedly executes the above steps until the whole layer is solidified and formed, so as to obtain a three-dimensional formed part compensated by solidification shrinkage. ​

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