A method and system for controlling omnidirectional energy field in a photocuring 3D printing process

Abstract

The present application relates to the field of photocuring control technology, and specifically to an omnidirectional energy field control method and system for a photocuring 3D printing process, the method comprising: dividing the projection photo of the calibration block matrix on the focal plane in the photocuring 3D printing process into a number of blocks on average; performing threshold analysis on all image points in the blocks, unifying the light diffusion degree of the calibration blocks in each block by correcting the morphological diffusion coefficient of the blocks, and obtaining the morphological coefficient of each pixel point at the same position on the focal plane by smooth scaling; obtaining the actual light intensity of each projection point according to the light intensity of all points on the focal plane corrected by the morphological coefficient on each projection point; obtaining an omnidirectional energy field model according to the accumulation of the actual light intensity of each projection point by the slices during the printing process, adjusting the initial light intensity mask of each layer of slices, and obtaining the optimal light intensity mask. The present application can improve the omnidirectional energy field control accuracy of the photocuring 3D printing process.

Description

Technical Field

[0001] The present application relates to the field of photocuring control technology, and in particular to an omnidirectional energy field control method and system for a photocuring 3D printing process. Background Art

[0002] A photocuring 3D printer is a device that uses ultraviolet light to cure photosensitive resin and build 3D objects layer by layer or continuously. Photocuring is divided into several types, such as SLA point scanning, DLP surface imaging and two-photon. Among them, DLP uses a DMD digital micro-projection chip, which is composed of many tiny reflectors. Each reflector can adjust the transmission direction of light, and the data of the reflector determines the resolution of the printing device. Therefore, DLP projects the entire slice image of the model at one time, cures the resin of a single image point, and cures it into the required printing shape, and gradually prints the entire model layer by layer. Because DLP 3D printing technology transmits the entire layer of image, there is no need to scan layer by layer. Therefore, DLP is widely used in large-scale industrial manufacturing due to its advantages of high speed and high precision.

[0003] Ideally, the light intensity at each projection point is consistent, but in practice, due to the limitation of equipment accuracy, the light intensity at different points in the entire slice projection plane is inconsistent. As a result, at points with higher light intensity, the resin is more fully irradiated by ultraviolet light, resulting in greater horizontal diffusion and vertical penetration depth. On the contrary, for points with lower light intensity, the horizontal diffusion and vertical penetration depth are smaller. Therefore, in the traditional control process, the light intensity of each projection point needs to be adjusted to suppress the projection points with strong light intensity and enhance the projection points with low light intensity.

[0004] However, in ultra-large-scale industrial manufacturing, due to the long-term uninterrupted printing of the equipment, the light-transmitting film ages, and due to different printing habits, the aging degree of the light-transmitting film corresponding to different projection points in the slice projection plane is different, resulting in uneven patches on the light-transmitting film. The transparency of the film in the patch area is poor, and there will be greater scattering, which will cause the horizontal diffusion to increase and the penetration depth to decrease. At this time, if the light intensity is controlled in the traditional way, it will further aggravate the horizontal diffusion and reduce the penetration depth, and even lead to incomplete resin photocuring and printing failure. In addition, in the photocuring printing process, the layers of the slices are adhered to each other, which will cause the irradiation of the subsequent layers to cause repeated exposure to the previously cured parts, thereby accumulating exposure layer by layer in the vertical direction to cause deformation; ultimately, the omnidirectional energy field control accuracy of the photocuring 3D printing process is low, resulting in low accuracy of the printed product and deviation from the design model. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of this application is to provide an omnidirectional energy field control method and system for a photocuring 3D printing process. The technical solutions adopted are as follows:

[0006] In a first aspect, an embodiment of the present application provides an omnidirectional energy field control method for a photocuring 3D printing process, the method comprising the following steps:

[0007] Obtain a projection photo of the calibration block matrix on the focal plane during the light-curing 3D printing process, and divide the projection photo into a number of blocks evenly according to the calibration block matrix; wherein each block contains a calibration block;

[0008] Perform threshold analysis on all image points in the block, screen exposure points, and obtain the morphological diffusion coefficient of each block according to the difference in the number of exposure points of all blocks; adjust the grayscale value of each image point according to the morphological diffusion coefficient of each block and the grayscale value distribution of the local area of ​​each image point in the block to obtain the grayscale correction value of each image point; repeat the threshold analysis and morphological diffusion coefficient adjustment until the number of exposure points of all blocks is the same; use the grayscale correction value of each image point on the projected photo as the light intensity of the same position point on the focal plane;

[0009] Obtain the slice projection plane of each slice of the 3D model to be printed on the focal plane; obtain the probability that each projection point is affected by the brightness of each point on the focal plane according to the light intensity of each point on the focal plane and the distance between each projection point and the slice projection plane; set the initial light intensity mask according to the slice projection plane of each slice; obtain the actual light intensity of each projection point by combining the probability that each projection point is affected by the brightness of all points on the focal plane and the initial light intensity mask;

[0010] An omnidirectional energy field model is obtained according to the accumulation of actual light intensity of each projection point on the slice projection plane of all slice layers; the initial light intensity mask of each slice layer is adjusted according to the omnidirectional energy field model to obtain an optimal light intensity mask.

[0011] Furthermore, the threshold analysis is performed on all image points in the block, the exposure points are screened, and the morphological diffusion coefficient of each block is obtained according to the difference in the number of exposure points of all blocks, including:

[0012] The image points in each block whose grayscale value is greater than or equal to the preset grayscale threshold are marked as exposure points; the average value of the number of exposure points in all blocks in the projected photo is obtained; and the difference between the number of exposure points in each block and the average value is used as the morphological diffusion coefficient of each block.

[0013] Furthermore, the method for obtaining the grayscale correction value of each image point includes:

[0014] The morphological diffusion coefficients of all blocks are smoothly enlarged according to the image composed of block positions to the size of the projected photo to obtain the morphological coefficients of each image point; the morphological coefficients of all image points are mapped to ;

[0015] Let the grayscale value and grayscale correction value of the image point in the i-th row and j-th column of the projection photo be , , grayscale correction function ;

[0016] The morphological coefficient of the image point in the i-th row and j-th column of the projected photo is recorded as ;when When it is less than 0, if ,but ;on the contrary, ; Among them, min() is the minimum value function; floor{} is the floor rounding function;

[0017] when When greater than or equal to 0, if ,but On the contrary, .

[0018] Furthermore, the method for obtaining the probability that each projection point is affected by the brightness of each point on the focal plane includes:

[0019]

[0020] In the formula, It indicates the probability that the projection point (x, y) on the slice projection plane is affected by the brightness of the point (i, j) on the focal plane. represents the light intensity at point (i, j) on the focal plane, exp() represents an exponential function with a natural constant as the base, Represents the distance from the projection point (x, y) on the slice projection plane to the point (i, j) on the focal plane. Indicates the preset Gaussian radius.

[0021] Further, the initial light intensity mask is set according to the slice projection plane of each slice layer, including:

[0022] For the slice projection plane of each slice, set an initial light intensity mask with the same size as the slice projection plane; if the projection point is located in the projection area of ​​the slice, the light intensity mask value of the projection point position on the initial light intensity mask is recorded as 1; otherwise, the light intensity mask value of the projection point position on the initial light intensity mask is recorded as 0.

[0023] Furthermore, the method for obtaining the actual light intensity of each projection point includes: recording the actual light intensity of the projection point (x, y) on the slice projection plane of the k-th slice as , ; Where W and H represent the width and height of the slice projection plane, respectively. is the grayscale correction function, represents the intensity mask value of point (i, j) on the intensity mask of the k-th slice. is the morphological coefficient of the image point in the i-th row and j-th column of the projected photo; Represents the probability that the projection point (x, y) on the slice projection plane of the k-th slice is affected by the brightness of the point (i, j) on the focal plane.

[0024] Furthermore, the method for obtaining the omnidirectional energy field model comprises:

[0025] For each slice, the distance from each 3D point on the slice to the slice projection plane is obtained, which is recorded as the spatial height of each 3D point; an exponential function with a natural constant as the base and the spatial height as the exponent is obtained; the product of the actual light intensity of each 3D point projected on the slice projection plane and the calculation result of the exponential function is taken as the spatial light intensity of each 3D point on the slice;

[0026] According to the accumulation of the spatial light intensity of the corresponding three-dimensional points of each three-dimensional point on the three-dimensional model to be printed on all slices, the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed is obtained;

[0027] The exposure time of each slice is obtained, and the product of the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed and the exposure time is used as the exposure cumulative amount of each three-dimensional point; the set of the exposure cumulative amounts of all three-dimensional points on the three-dimensional model to be printed is used as the omnidirectional energy field model.

[0028] Furthermore, the method for obtaining the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed specifically comprises: The accumulated light intensity of exposure is recorded as , ;in, is the height of the 3D model to be printed; is the number of layers of all slices; is the thickness of a single slice; Point the 3D model to be printed Euclidean distance to the slice projection plane; is the 3D point on the k-th slice spatial light intensity.

[0029] Further, the initial light intensity mask of each slice is adjusted according to the omnidirectional energy field model to obtain the optimal light intensity mask, including:

[0030] The critical exposure amount of the resin is obtained, and the modulus of the difference vector between the exposure accumulation amount of each 3D point and the critical exposure amount of the resin is used as the objective function of the scheduling optimization algorithm. The initial light intensity mask of each layer of slices is adjusted using the scheduling optimization algorithm to obtain the optimal light intensity mask of each layer of slices.

[0031] In a second aspect, an embodiment of the present application further provides an omnidirectional energy field control system for a photocuring 3D printing process, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of an omnidirectional energy field control method for a photocuring 3D printing process as described above are implemented.

[0032] This application has at least the following beneficial effects:

[0033] This application obtains the projection difference on the light-curing 3D printing device through a light intensity meter, and obtains the morphological diffusion ratio of each block according to the difference in horizontal diffusion on different blocks on the slice projection plane, reflecting the diffusion and convergence of the current area relative to the entire slice projection plane, and combines the morphological mask to realize the correction of the horizontal light intensity. In addition, the exposure cumulative light intensity and the corresponding exposure accumulation of each point on the model in the vertical direction are obtained through derivation and analysis, reflecting the influence of the post-printing slice division on the printed slice division, thereby obtaining the omnidirectional energy field model, and finally obtaining the layered light intensity mask of each slice according to the particle swarm optimization algorithm, so as to realize the control of each slice layer. Compared with the traditional slicing exposure method that only considers reducing the light intensity to suppress diffusion, the present application is combined with the actual ultra-large-scale industrial manufacturing process. Due to the serious aging of the light-transmitting film in the commonly used printing positions, the aged area of ​​the light-transmitting film presents the imaging effect of frosted glass, which causes the lower the light intensity, the more serious the diffusion. Therefore, the morphological mask is used to achieve horizontal control, and the accumulated error of light intensity penetration in the vertical direction is analyzed to obtain an omnidirectional energy field model, thereby realizing omnidirectional energy field control of the printing process, improving control accuracy, and thus improving the overall printing accuracy of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 A flowchart of a method for controlling an omnidirectional energy field in a photocuring 3D printing process provided by an embodiment of the present application;

[0036] Figure 2A schematic diagram showing a comparison of light-transmitting films provided in one embodiment of the present application;

[0037] Figure 3 A schematic diagram of the light transmission effect of an aged light-transmitting film provided in one embodiment of the present application;

[0038] Figure 4 A schematic diagram of a morphological mask control effect experiment comparison provided by an embodiment of the present application;

[0039] Figure 5 A schematic diagram comparing the cumulative exposure control effects of an omnidirectional energy field provided in one embodiment of the present application. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0042] The following is a detailed description of a specific scheme of an omnidirectional energy field control method and system for a photocuring 3D printing process provided by the present application in conjunction with the accompanying drawings.

[0043] See also Figure 1 , which shows a flowchart of a method for controlling an omnidirectional energy field in a photocuring 3D printing process provided by an embodiment of the present application, the method comprising the following steps:

[0044] S1, obtaining a projection photo of the calibration block matrix on the focal plane during the light-curing 3D printing process, and evenly dividing the projection photo into a plurality of blocks according to the calibration block matrix.

[0045] In the process of photocuring 3D printing, since it is a process of overall control of each projection point in the horizontal and vertical directions, it is named omnidirectional energy field control. In order to obtain the overall situation of the light-transmitting film, the high-definition camera obtains the projection state of the focal plane, that is, a single projection photo is obtained. The larger the gray value, the higher the brightness, and the position of each image point in the projection photo corresponds to the position of the focal plane projection point.

[0046] In order to obtain the diffusion of the light-transmitting film on the entire focal plane, the projectable size of the entire focal plane is obtained as , which is projected onto the focal plane The calibration block matrix is ​​used to divide the entire focal plane into Each block contains a calibration block. It should be noted that the calibration block can be of any shape, but the shape and area of ​​each calibration block must be the same.

[0047] S2, perform threshold analysis on all image points in the block, screen exposure points, and obtain the morphological diffusion coefficient of each block according to the difference in the number of exposure points of all blocks; adjust the grayscale value of each image point according to the morphological diffusion coefficient of each block and the grayscale value distribution of the local area of ​​each image point in the block to obtain the grayscale correction value of each image point; repeat the threshold analysis and morphological diffusion coefficient adjustment until the number of exposure points of all blocks is the same; use the grayscale correction value of each image point on the projected photo as the light intensity of the same position point on the focal plane.

[0048] In large-scale industrial manufacturing, due to uninterrupted use, uneven patches will appear on the light-transmitting film in the entire focal plane, which will cause differences in the resin curing effect in the XY direction and the Z direction. Figure 2 As shown in the figure, the left side is the area of ​​the light-transmitting film where the model is not printed frequently, with good light transmittance, while the right side is the area where the light-transmitting film is aged due to frequent printing, with poor light transmittance. Due to the poor light transmittance, a transmission effect similar to frosted glass will be presented, making the projection point with poor light transmittance have a larger diffusion in the XY direction and a smaller penetration depth in the Z direction. Therefore, if the traditional method of reducing light intensity to suppress diffusion is adopted, the penetration depth in the Z direction will be further reduced, and the forming strength cannot be met, resulting in printing failure. Therefore, it is necessary to further adjust the diffusion situation in combination with the light transmittance of the light-transmitting film.

[0049] In the process of projecting the entire focal plane with the calibration block matrix, the aging degree of the transparent film in each area is different, which will cause the projection difference on the XY plane. Figure 3 As shown, each calibration block may correspond to a diffuse bright spot area.

[0050] For bright spots with poor light transmittance, the grayscale value in the corresponding image will gradually diffuse from the center to the edge, resulting in blurred edges and strong diffusion, so a certain processing method is needed to make it converge in shape. For bright spots with good light transmittance, the edges are clearer and the diffusion is smaller. In order to make the overall diffusion more consistent, the bright spots with good light transmittance need to be expanded in shape.

[0051] For each block in the projected photo, by setting a grayscale threshold T, the image points in the block whose grayscale value is greater than or equal to the grayscale threshold are marked as exposure points. In this embodiment, T=240. The number of exposure points in each block is counted to obtain the average number of exposure points in all blocks in the projected photo; the difference between the number of exposure points in each block and the average is used as the morphological diffusion ratio of each block.

[0052] In this embodiment, the calculation formula for the morphological diffusion ratio of the i-th block is:

[0053]

[0054] in, represents the morphological diffusion ratio of the i-th block, represents the number of exposure points in the i-th block, It represents the average number of exposure points of all blocks in the entire projection photo.

[0055] If you get If it is a positive value, it means that the light-transmitting film corresponding to the current block is seriously aged, causing the light spot area in the block to diffuse more seriously and need to be shrunk; on the contrary, if the obtained A negative value indicates that the light transmittance of the light-transmitting film corresponding to the current block is good, which makes the diffusion of the light spot area in the block poor. However, in order to maintain the uniformity of the printed model morphology, expansion is required.

[0056] The morphological diffusion ratio reflects the light transmittance of the light-transmitting film in the current block. The larger the absolute value of the morphological diffusion ratio, the greater the difference between the diffusion or convergence of the light-transmitting film in the current block in the XY plane and the entire light-transmitting film, and the greater the adjustment required.

[0057] To obtain the morphological diffusion ratio of all blocks in the projected photo, the range of its value is controlled within the range of In this embodiment, the linear normalized value of the morphological diffusion ratio of each block is calculated, and the product of the linear normalized value and 255 is used as the morphological diffusion coefficient of each block; thereby, the morphological diffusion ratios of all blocks are linearly mapped to obtain the adjusted morphological diffusion ratio, which is used represents the adjusted morphological diffusion coefficient of the i-th block.

[0058] The morphological diffusion coefficients of all blocks are smoothly enlarged according to the image composed of block positions to the size of the projected photo to obtain the morphological coefficients of each image point; the morphological coefficients of all image points are mapped to In this embodiment, the image smoothing and magnification method is a linear interpolation method.

[0059] If the morphological coefficient of the image point in the i-th row and j-th column in the projected photo , indicating that the current block has good light transmittance. In order to unify the shape, the brightness value in the block needs to be expanded. Therefore, the adjustment method of a certain image point under the block is: let the grayscale value and grayscale correction value of the image point in the i-th row and j-th column of the projection photo be , , grayscale correction function ;like ,but ;on the contrary, ; Among them, min() is the minimum value function; floor{} is the floor rounding function.

[0060] The bright spot area will gradually spread outwards in the entire block, so the area around the bright spot is blurred. Judgment condition, if , indicating that the brightness of the current image point should be within the actual diffusion range, and the actual brightness of the image point needs to be improved. On the contrary, if , which indicates that the brightness of the current image point is outside the diffusion range, and the brightness of the image point is directly set to zero.

[0061] If the morphological coefficient of the image point in the i-th row and j-th column in the projected photo , indicating that the light transmittance of the current block is poor and morphological convergence is required. For a certain image point in the block, if ,but On the contrary, .

[0062] For a single image point, if the image point , indicating that the image point is located at the edge of the block. In order to suppress the frosted glass effect caused by aging of the light-transmitting film, it is necessary to increase the light intensity to suppress diffusion. , indicating that the image point is located in the center of the bright spot area. At this time, the brightness of the center of the area is directly set to the maximum value, that is, 255.

[0063] In this way, all image points are traversed, and the above threshold analysis and morphological diffusion coefficient adjustment are repeated until the number of exposure points in all blocks is the same, and the final grayscale correction value of each image point is obtained; the grayscale correction value of each image point on the projected photo is used as the light intensity of the point at the same position on the focal plane; thereby improving the consistency of diffusion in the entire XY plane and reducing the requirements for the uniformity of light intensity of the equipment.

[0064] S3, obtaining the slice projection plane of each layer of the slice of the 3D model to be printed on the focal plane; obtaining the probability that each projection point is affected by the brightness of each point on the focal plane according to the light intensity of each point on the focal plane and the distance between each projection point and the slice projection plane; setting the initial light intensity mask according to the slice projection plane of each layer of slices; combining the probability that each projection point is affected by the brightness of all points on the focal plane and the initial light intensity mask, obtaining the actual light intensity of each projection point.

[0065] Through step S2, the deformation of the XY plane caused by various factors is basically controlled. During the printing process, the light behind will also affect the solidified layer in front in a gradual and cumulative manner, causing the shape to change. Therefore, it is necessary to further analyze the diffusion in the Z direction in combination with the sliced ​​layered structure of the printed model.

[0066] Ideally, the light intensity of each projection point is independent of each other, but in the actual printing process, the model is usually sliced ​​into several layers according to the model to be printed, and each slice is projected on the focal plane corresponding to a slice projection plane; for any projection point on the slice projection plane, if the projection point requires a certain light intensity to cure the resin, it will have a certain impact on the surrounding projection points. In addition, the brightness attenuation of a single projection point on other projection points follows a Gaussian distribution, and the farther the distance, the smaller the brightness impact.

[0067] Based on the above analysis, the probability that each projection point in the slice projection plane is affected by the brightness of each point on the focal plane is constructed:

[0068]

[0069] In the formula, It indicates the probability that the projection point (x, y) on the slice projection plane is affected by the brightness of the point (i, j) on the focal plane. represents the light intensity at point (i, j) on the focal plane, exp() represents an exponential function with the natural number e as the base, Represents the Euclidean distance from the projection point (x, y) on the slice projection plane to the point (i, j) on the focal plane. Represents the preset Gaussian radius, which is related to the light transmittance of the material and is defined in this application as the peak brightness attenuation of the current center projection point (i, j) The distance between points, where e is a natural constant.

[0070] The influence of point (x, y) on the slice projection plane by point (i, j) can be measured by the brightness influence probability. The farther the distance from (i, j), the smaller the influence on the point (x, y). On the contrary, the closer the distance, the greater the influence, and the larger the value of the brightness influence probability.

[0071] Under normal circumstances, the brightness of each position on the slice projection plane is formed by the superposition of multiple projection points. It is a projection image of a slice layer of the entire model, and the projection area of ​​the slice belongs to the position that needs to be exposed. First, for the slice projection plane of each layer of slices, set an initial intensity mask with the same size as the slice projection plane; if the projection point is located in the projection area of ​​the slice, the intensity mask value of the projection point position on the initial intensity mask is recorded as 1; otherwise, the intensity mask value of the projection point position on the initial intensity mask is recorded as 0. It should be noted that the size of the slice projection plane is the same as the size of the intensity mask, both of which are the size of the focal plane.

[0072] For the projection points on the projection image, there will be ultraviolet light irradiation, and for the projection points not on the projection image, there will be no ultraviolet light irradiation. Therefore, for the slice projection plane of the k-th slice, the calculation method of the actual light intensity of any point on the entire slice projection plane is:

[0073]

[0074] In the formula, represents the actual light intensity of the projection point (x, y) on the slice projection plane of the k-th slice, W and H represent the width and height of the projected image on the slice projection plane, respectively. represents the intensity mask value of point (i, j) on the intensity mask of the k-th slice. is the grayscale correction function, which corrects the morphological diffusion difference in the XY plane. Represents the probability that the projection point (x, y) on the slice projection plane of the k-th slice is affected by the brightness of the point (i, j) on the focal plane.

[0075] The above formula can determine the light intensity of all the positions that need to be exposed on the kth slice layer of the entire model for any point on the entire projection plane. If the number of exposure points on the current slice layer is large, then The number of 1s is relatively large, and the light intensity at any point on the current layer is relatively high.

[0076] S4, obtaining an omnidirectional energy field model according to the accumulation of actual light intensity of each projection point on the slice projection plane of all slice layers; adjusting the initial light intensity mask of each slice layer according to the omnidirectional energy field model to obtain an optimal light intensity mask.

[0077] Light has a penetrating effect in the resin, and each layer of slice has a certain thickness. The penetration of light will show an exponential decay characteristic. Therefore, when determining in the omnidirectional energy field model, for each layer of slice, obtain the distance from each three-dimensional point on the slice to the slice projection plane, which is recorded as the spatial height of each three-dimensional point; obtain an exponential function with a natural constant as the base and the spatial height as the exponent; and take the product of the actual light intensity of each three-dimensional point projected on the slice projection plane and the calculation result of the exponential function as the spatial light intensity of each three-dimensional point on the slice.

[0078] In this embodiment, the calculation formula for the spatial light intensity of a three-dimensional point on the k-th slice of the three-dimensional model to be printed is:

[0079]

[0080] in, Represents a 3D point on the k-th slice The spatial light intensity, Represents the projection point on the slice projection plane of the k-th slice ( ), exp() represents the exponential function with the natural number e as the base, and c represents the three-dimensional point The spatial height of , specifically the Euclidean distance to the slice projection plane, .

[0081] In this way, the light intensity at any point in the space above the projection plane can be determined based on the exposure point on the kth slice layer. The farther a point in the space is from the projection plane, the more severe the light attenuation in the resin will be, and the weaker the light intensity at the corresponding point in the space will be.

[0082] In the process of photocuring 3D printing, printing is performed layer by layer according to the slice layering. Each time, the projection area of ​​a slice is projected. When the slice layer is solidified, the molding platform moves up a little distance to project the projection area of ​​the next slice, and gradually rises until the printing is completed. Therefore, except for the first printed slice layer, the area above that has been formed will be repeatedly irradiated when each slice layer is exposed. Therefore, in the omnidirectional energy field model, the light intensity received by the points on the three-dimensional model to be printed is the amount that accumulates continuously during the exposure process. With each layer printed, the distance from the new slice layer k increases, and it will be attenuated accordingly. According to the accumulation of the spatial light intensity of each three-dimensional point on the three-dimensional model to be printed and the corresponding three-dimensional point on all slices, the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed can be obtained.

[0083] Specifically, the points on the 3D model to be printed The accumulated light intensity of exposure is recorded as , ;in, is the height of the 3D model to be printed; is the number of layers of all slices; is the thickness of a single slice; Point the 3D model to be printed Euclidean distance to the slice projection plane; is the 3D point on the k-th slice spatial light intensity.

[0084] And obtain the exposure time t when printing each slice layer, so that the point Accumulated exposure .

[0085] For a point on the model , assuming that it is printed on the kth layer, the point is solidified in the subsequent exposure process. As the number of layers is continuously printed, the corresponding z value increases, the distance from the point to the projection plane increases, and the intensity of the irradiated light decreases gradually until the entire model is printed.

[0086] As the printing progresses, when the model is printed, the exposure accumulation of any point on the model can be obtained. The exposure accumulation of all points is calculated using It means that the omnidirectional energy field model of the printed model can be obtained.

[0087] During the resin curing process, there is a critical exposure amount of resin. Since different types of photosensitive resins have different critical exposure during the curing process, it can be obtained from the relevant parameter manual of light-curing 3D printing. Therefore, the cumulative exposure at any point in the omnidirectional energy field model is .

[0088] In the actual manufacturing process, only the intensity mask of each layer is exposed. It can be controlled at any time, while other materials and model shapes cannot be changed. Therefore, the only way is to adjust the light intensity mask of each layer to make the exposure of each point on the entire printed model constant, and the goal is to make the cumulative exposure of each point on the model approach the critical exposure of the resin. .

[0089] This application uses the particle swarm optimization algorithm to achieve optimal control of the light intensity mask. The specific processing method is:

[0090] Initialize the population size num=200, set the dimensions of each individual to W, H, , get the three-dimensional matrix of the initialized population, and set the number of iterations to 500, the inertia weight w to 0.9, and it decreases linearly with the increase of the number of iterations. When the number of iterations is 200, it reaches a minimum of 0.4. In the subsequent iterations, the inertia weight is always 0.4. In addition, the acceleration constants c1 and c2 are both 2. And the population is randomly initialized, ;in, is the critical exposure of the resin; For a 3D point The accumulated exposure amount; The algorithm takes the minimum as the objective function and takes the initial intensity masks of all slices of the model to be printed as input. The algorithm outputs the optimal intensity mask for each slice layer. The value of the intensity mask is (0,1] for exposure, and 0 for no exposure.

[0091] The printing effect that can be achieved by using this application is shown in the figure. Figure 4 The figure shows the control effect of the morphological mask on the horizontal plane, where (a) represents the printing effect under ideal conditions, which is a standard triangle, (b) represents the printing effect of traditional slice exposure technology. Since it cannot effectively suppress the frosted glass effect of the light-transmitting film in ultra-large-scale industrial manufacturing, the printed image diffusion is more serious, and (c) is the control effect of the present application. The present application uses a morphological mask to suppress the diffusion effect and achieve diffusion consistency on the entire projection plane. Therefore, the printing effect boundary of the present application is more convergent and closer to the ideal printing effect.

[0092] exist Figure 5 The control effect of the cumulative exposure error in the z direction is shown in the figure on the left, where the omnidirectional energy field control technology of the present application is shown in the figure. As can be seen from the figure, the control effect of the present application makes each slice layer of the model smoother. The right figure shows the traditional slice exposure technology. Since the influence of the next slice layer on the exposure of the previous layer cannot be effectively controlled, the model has an uneven edge similar to a thread on the boundary of the z direction, which reduces the printing accuracy of the model.

[0093] Based on the same inventive concept as the above method, an embodiment of the present application also provides an omnidirectional energy field control system for a photocuring 3D printing process, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned omnidirectional energy field control methods for a photocuring 3D printing process are implemented.

[0094] Through the above description of the implementation method in combination with the accompanying drawings, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0095] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for controlling an omnidirectional energy field in a photocuring 3D printing process, characterized in that: The method comprises the following steps: Obtain a projection photo of the calibration block matrix on the focal plane during the light-curing 3D printing process, and divide the projection photo into a number of blocks evenly according to the calibration block matrix; wherein each block contains a calibration block; Perform threshold analysis on all image points in the block, screen exposure points, and obtain the morphological diffusion coefficient of each block according to the difference in the number of exposure points of all blocks; adjust the grayscale value of each image point according to the morphological diffusion coefficient of each block and the grayscale value distribution of the local area of ​​each image point in the block to obtain the grayscale correction value of each image point; repeat the threshold analysis and morphological diffusion coefficient adjustment until the number of exposure points of all blocks is the same; use the grayscale correction value of each image point on the projected photo as the light intensity of the same position point on the focal plane; Obtain the slice projection plane of each slice of the 3D model to be printed on the focal plane; obtain the probability that each projection point is affected by the brightness of each point on the focal plane according to the light intensity of each point on the focal plane and the distance between each projection point and the slice projection plane; set the initial light intensity mask according to the slice projection plane of each slice; obtain the actual light intensity of each projection point by combining the probability that each projection point is affected by the brightness of all points on the focal plane and the initial light intensity mask; An omnidirectional energy field model is obtained according to the accumulation of actual light intensity of each projection point on the slice projection plane of all slice layers; the initial light intensity mask of each slice layer is adjusted according to the omnidirectional energy field model to obtain an optimal light intensity mask.

2. The omnidirectional energy field control method of a photocuring 3D printing process according to claim 1, characterized in that: The threshold analysis is performed on all image points in the block, the exposure points are screened, and the morphological diffusion coefficient of each block is obtained according to the difference in the number of exposure points of all blocks, including: The image points in each block whose grayscale value is greater than or equal to the preset grayscale threshold are marked as exposure points; the average value of the number of exposure points in all blocks in the projected photo is obtained; and the difference between the number of exposure points in each block and the average value is used as the morphological diffusion coefficient of each block.

3. The omnidirectional energy field control method of a photocuring 3D printing process according to claim 1, characterized in that: The method for obtaining the grayscale correction value of each image point includes: The morphological diffusion coefficients of all blocks are smoothly enlarged according to the image composed of block positions to the size of the projected photo to obtain the morphological coefficients of each image point; the morphological coefficients of all image points are mapped to ; Let the grayscale value and grayscale correction value of the image point in the i-th row and j-th column of the projection photo be , , grayscale correction function ; The morphological coefficient of the image point in the i-th row and j-th column of the projected photo is recorded as ;when When it is less than 0, if ,but ;on the contrary, ; Among them, min() is the minimum value function; floor{} is the floor rounding function; when When greater than or equal to 0, if ,but On the contrary, .

4. The omnidirectional energy field control method for a photocuring 3D printing process according to claim 1, characterized in that: The method for obtaining the probability that each projection point is affected by the brightness of each point on the focal plane comprises: In the formula, It indicates the probability that the projection point (x, y) on the slice projection plane is affected by the brightness of the point (i, j) on the focal plane. represents the light intensity at point (i, j) on the focal plane, exp() represents an exponential function with a natural constant as the base, Represents the distance from the projection point (x, y) on the slice projection plane to the point (i, j) on the focal plane. Indicates the preset Gaussian radius.

5. The omnidirectional energy field control method for a photocuring 3D printing process according to claim 3, characterized in that: The step of setting an initial light intensity mask according to the slice projection plane of each slice layer comprises: For the slice projection plane of each slice, set an initial light intensity mask with the same size as the slice projection plane; if the projection point is located in the projection area of ​​the slice, the light intensity mask value of the projection point position on the initial light intensity mask is recorded as 1; otherwise, the light intensity mask value of the projection point position on the initial light intensity mask is recorded as 0.

6. The omnidirectional energy field control method of the photocuring 3D printing process according to claim 5, characterized in that: The method for obtaining the actual light intensity of each projection point includes: recording the actual light intensity of the projection point (x, y) on the slice projection plane of the k-th slice as , ; Where W and H represent the width and height of the slice projection plane, respectively. is the grayscale correction function, represents the intensity mask value of point (i, j) on the intensity mask of the k-th slice. is the morphological coefficient of the image point in the i-th row and j-th column of the projected photo; Represents the probability that the projection point (x, y) on the slice projection plane of the k-th slice is affected by the brightness of the point (i, j) on the focal plane.

7. The omnidirectional energy field control method for a photocuring 3D printing process according to claim 1, characterized in that: The method for obtaining the omnidirectional energy field model comprises: For each slice, the distance from each 3D point on the slice to the slice projection plane is obtained, which is recorded as the spatial height of each 3D point; an exponential function with a natural constant as the base and the spatial height as the exponent is obtained; the product of the actual light intensity of each 3D point projected on the slice projection plane and the calculation result of the exponential function is taken as the spatial light intensity of each 3D point on the slice; According to the accumulation of the spatial light intensity of the corresponding three-dimensional points of each three-dimensional point on the three-dimensional model to be printed on all slices, the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed is obtained; The exposure time of each slice is obtained, and the product of the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed and the exposure time is used as the exposure cumulative amount of each three-dimensional point; the set of the exposure cumulative amounts of all three-dimensional points on the three-dimensional model to be printed is used as the omnidirectional energy field model.

8. The omnidirectional energy field control method of the photocuring 3D printing process according to claim 7, characterized in that: The method for obtaining the exposure cumulative light intensity of each three-dimensional point on the three-dimensional model to be printed specifically comprises: The accumulated light intensity of exposure is recorded as , ;in, is the height of the 3D model to be printed; is the number of layers of all slices; is the thickness of a single slice; Point the 3D model to be printed Euclidean distance to the slice projection plane; is the 3D point on the k-th slice spatial light intensity.

9. The omnidirectional energy field control method in a photocuring 3D printing process according to claim 7, characterized in that: The initial light intensity mask of each slice is adjusted according to the omnidirectional energy field model to obtain the optimal light intensity mask, including: The critical exposure amount of the resin is obtained, and the modulus of the difference vector between the exposure accumulation amount of each 3D point and the critical exposure amount of the resin is used as the objective function of the scheduling optimization algorithm. The initial light intensity mask of each layer of slices is adjusted using the scheduling optimization algorithm to obtain the optimal light intensity mask of each layer of slices.

10. An omnidirectional energy field control system for a photocuring 3D printing process, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the omnidirectional energy field control method for a photocuring 3D printing process as described in any one of claims 1 to 9 are implemented.

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