A method for measuring and correcting distortion of 3D printer optical system

Abstract

This invention provides a method for measuring and correcting distortion in the optical system of a 3D printer, comprising: image generation and projection; iterative point finding; and function model approximation. Based on the measured inherent error of the optical system, this invention corrects the original projected image to ensure that the image projected onto the exposure plane matches the theoretical image, thereby ensuring the accuracy of the printing system. Ultimately, the printing system error is reduced to between 0-50µm, ensuring the error is within one pixel.

Description

Technical Field

[0001] The invention belongs to the technical field of 3D printer optical system correction, and in particular relates to a 3D printer optical system distortion measurement and correction method. Background Art

[0002] The surface exposure stereolithography 3D printer is a rapid prototyping device that uses photocuring technology. Its working principle is that the printer is filled with liquid or powdered printing materials. After being connected to a computer, the printing materials are superimposed layer by layer on the printing platform through computer control. At the same time, the layered images of the printed model are projected onto the material surface layer by layer to solidify the material, and finally the model is printed as a physical object.

[0003] Among them, photocuring technology refers to a photoprocessing process that uses ultraviolet light of a certain wavelength to polymerize liquid photosensitive resin into a solid state at high speed. The photocuring reaction is essentially a polymerization and cross-linking reaction initiated by light. In summary, it can be seen that the ultraviolet light irradiation link is crucial to the printing result. A slight angle deviation will lead to a loss of precision and even cause printing failure.

[0004] Since ultraviolet light is emitted by the optical system, the calibration technology of the optical system is crucial. Usually before 3D printing begins, the optical system must be calibrated, that is, the position of the optical system must be fine-tuned so that the projection format of the optical system coincides with the size of the calibration plate of the 3D printer, which is similar to position zeroing. The calibration adjustment of the optical system mainly includes two aspects, one is the horizontal adjustment of the projection surface of the optical system, and the other is the adjustment of the focal length of the optical system. At this stage, the general 3D printing system only adjusts the horizontality of the projection surface of the optical system and the focal length of the optical system by manually adjusting the bolts by visual inspection. The error is relatively large. Even with the help of tools such as spirit levels and vernier calipers, it can only be accurate to the millimeter level. Therefore, the current adjustment method leaves a great hidden danger in the printing process, which seriously affects the accuracy of 3D printing. Summary of the invention

[0005] To solve the above technical problems, the present invention provides a method for measuring and correcting the distortion of a 3D printer optical system. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0006] The present invention adopts the following technical solution:

[0007] In some optional embodiments, a method for measuring and correcting the distortion of a 3D printer optical system is provided, comprising: generating a projection original image and driving the optical system to project; obtaining the coordinates of the intersection points of each cross figure in the projection photo taken by the area array camera; obtaining the distortion equation coefficients of the function model, and obtaining the coordinates of the intersection points of each cross figure after transformation according to the function model, and repeating the projection until the error is less than a preset threshold.

[0008] Furthermore, the process of generating the projection original image and driving the optical system to project includes: S1: generating the projection original image of the optical system; S2: driving the optical system to a predetermined coordinate for projection.

[0009] Furthermore, the process of obtaining the coordinates of the intersection points of each cross figure in the projection photo taken by the area array camera includes: S3: driving the area array camera to shoot the figure projected by the optical system to obtain a projection photo; S4: processing the projection photo and obtaining the coordinates of the intersection points of each cross figure in the projection photo.

[0010] Furthermore, the process of obtaining the distortion equation coefficients of the function model, obtaining the coordinates of the intersection points of each cross figure after transformation according to the function model, and repeating the projection until the error is less than the preset threshold value includes: S5: bringing the coordinate values ​​of the intersection points of each cross figure in the projected photo and the coordinate values ​​of the intersection points of each cross figure in the original projection photo into the function model to obtain the distortion equation coefficients of the function model; S6: obtaining the coordinates of the intersection points of each cross figure after transformation according to the function model with known coefficients;

[0011] S7: driving the optical system to project the transformed image, and repeating steps S2-S6 until the error is less than a preset threshold.

[0012] Furthermore, the projection original image includes a central point and multiple cross figures, and the cross figures are distributed in the form of four concentric circles; the radii of the four concentric circles are 150, 300, 450, and 600 optical system pixel units, respectively, and the length of the two cross lines of each cross figure is 20 optical system pixel units.

[0013] Furthermore, the function model is as follows:

[0014] x=a 00 +a 01 u+a 02 u 2 +a 03 u 3 +a 10 v+a 11 vu+a 12 v 2 +a20 v 2 +a 21 uv 2 +a 30 v 3 ;

[0015] y=b 00 +b 01 u+b 02 u 2 +b 03 u 3 +b 10 v+b 11 vu+b 12 v 2 +b 20 v 2 +b 21 uv 2 +b 30 v 3 ;

[0016] Wherein, (x, y) is the coordinate of the intersection of each cross figure in the projection original image, and (u, v) is the coordinate of the intersection of each cross figure in the projection photo taken by the area array camera.

[0017] Furthermore, the process of obtaining the coordinates of the intersection points of each cross figure in the projection photo includes: preprocessing the projection photo; extracting the skeleton of the cross figure in the preprocessed projection photo; using the circumscribed rectangle algorithm to obtain the center point of the skeleton figure; dividing the points on the skeleton into two parts according to the center point obtained by the circumscribed rectangle algorithm and fitting the points of the two parts into two straight lines, and the two straight lines intersect to obtain the coordinates of the intersection points of the final cross figure.

[0018] Furthermore, the process of preprocessing the projection photo includes: one image binarization; one image erosion; and five image dilations.

[0019] The beneficial effects brought by the present invention are as follows: the present invention performs calibration through operation steps such as image generation projection, cyclic search for the cross center point and function model approximation. On the basis of measuring the error of the optical system itself, the original projection figure is corrected so that the figure projected on the exposure plane is consistent with the theoretical figure, thereby ensuring the accuracy of the printing system, and finally reducing the error of the printing system to between 0-50um, thereby ensuring that the error is within one pixel grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a method for measuring and correcting distortion of an optical system of a 3D printer according to the present invention;

[0021] Figure 2It is a schematic diagram of the positions of the instruments and equipment used in the present invention;

[0022] Figure 3 is a schematic diagram of a projection original image used in an embodiment of the present invention;

[0023] Figure 4 is the original image of the cross figure collected by the present invention;

[0024] Figure 5 is a cross figure after the preprocessing operation of the present invention;

[0025] Figure 6 is a skeleton diagram of the cross figure extracted by the present invention;

[0026] Figure 7 It is a morphological refinement effect diagram of the present invention. DETAILED DESCRIPTION

[0027] The following description and accompanying drawings fully demonstrate specific embodiments of the present invention so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent possible variations only. Unless clearly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments.

[0028] like Figure 1 As shown, in some illustrative embodiments, the present invention provides a method for measuring and correcting the distortion of a 3D printer optical system, and the main instruments and equipment used are as follows: Figure 2 As shown, it includes: a mechanical frame, a translation stage, an area array camera and an optical system of a 3D printer. The mechanical frame is used to support the translation stage. The area array camera is set on the translation stage. The translation stage is driven to move, thereby driving the area array camera to move, and then shooting the projection image projected by the optical system below.

[0029] The distortion measurement correction method of the present invention mainly includes three parts:

[0030] First, image generation projection: generate the original projection image and drive the optical system for projection.

[0031] Second, find points in a loop: drive the area array camera to take pictures, and find points in the cross, that is, obtain the coordinates of the intersection points of each cross figure in the projection photo taken by the area array camera.

[0032] Third, function model approximation: the function model is obtained by using the intersection point coordinates of each cross figure in the projection photo and the intersection point coordinates of each cross figure in the projection original image, and the transformed intersection point coordinates of each cross figure are obtained according to the obtained function model, and the optical system is driven to repeatedly project the adjusted projection image until the error is less than the preset threshold.

[0033] Among them, the original projection image is as follows Figure 3 As shown, the original projection image contains a central point and multiple cross graphics, and the cross graphics are distributed in four layers of concentric circles. The radii of the four layers of concentric circles are 150, 300, 450, and 600 optical system pixel units, respectively, and the length of the two cross lines of each cross graphic is 20 optical system pixel units, which is convenient for subsequent data processing.

[0034] The present invention specifically comprises the following steps:

[0035] S1: Generate the projection original image of the optical system. The projection original image is generated by the system, so the center point is used as the origin of the coordinate system, and the coordinates of the intersection points of each cross figure in the projection original image are known.

[0036] S2: Drive the optical system to the predetermined coordinates for projection. In the initial state, that is, the optical system first projects the original projection image generated in step S1, but the horizontality and position of the optical system itself may be deviated. Therefore, there is a difference between the image projected on the printing platform and the original projection image. And as the data is processed and adjusted, the optical system subsequently projects the transformed projection image to gradually approach the most accurate projection angle and position.

[0037] S3: Drive the translation stage to move, thereby driving the area array camera to move, and shoot the image projected by the optical system to obtain a projection photo. Due to the deviation of the optical system itself, the projection photo obtained each time is different from the image prepared for projection by the optical system.

[0038] S4: Processing the projection photo and obtaining the intersection coordinates of each cross figure in the projection photo.

[0039] Step S4 includes the following steps:

[0040] First, before obtaining the intersection of the cross pattern, the projection photo needs to be preprocessed. Figure 4 As shown, the preprocessing process includes: one image binarization; one image erosion; and five image dilations.

[0041] The thresholds for image binarization are set to 20 and 50. Image binarization is the process of setting the grayscale value of the pixels on the image to 0 or 255, that is, making the entire image appear in obvious black and white. In digital image processing, image binarization greatly reduces the amount of data in the image, thereby highlighting the outline of the target. Image erosion is mainly used in morphology to remove certain parts of the image. The present invention mainly removes scattered light spots near the cross figure. Image dilation refers to adding pixels to the boundaries of objects in the image. In the present invention, since there are many breaks in the middle of the cross figure, only multiple dilations can connect them all. The image after preprocessing is as follows Figure 5 shown.

[0042] After the preprocessing is completed, the skeleton of the cross figure in the preprocessed projection photo is extracted.

[0043] The present invention specifically uses a morphological thinning method to extract the skeleton of the image, with almost no burrs remaining, and the effect is as follows Figure 6 The refinement of image morphology in digital image processing is mainly for binary images. To extract the skeleton of a binary image is to delete unnecessary contour points and only keep its skeleton points.

[0044] Then, the center point of the skeleton figure is obtained by using the bounding rectangle algorithm. The bounding rectangle algorithm is to find the rectangle with the smallest area that circumscribes the figure given the vertices of an irregular figure. After finding the rectangle, the center point of the skeleton figure is obtained according to the centroid.

[0045] Finally, the points on the skeleton are divided into two parts according to the center point obtained by the circumscribed rectangle algorithm, and the points of the two parts are fitted into two straight lines. The two straight lines intersect to obtain the coordinates of the intersection point of the final cross figure. The morphological refinement effect is shown in the figure below. Figure 7 shown.

[0046] The above method of obtaining the coordinates of the intersection of the cross figure has the advantages of being accurate and fitting to the actual coordinate data, and the data processing method is simple and fast.

[0047] S5: Substitute the coordinate values ​​of the intersection points of each cross figure in the projected photo and the coordinate values ​​of the intersection points of each cross figure in the original projection image into the function model to obtain the distortion equation coefficient of the function model. The coordinate system in the projected photo also takes the center point as the origin of the coordinate system, and the coordinates of the intersection points of each cross figure are obtained by the method of step S4.

[0048] The function model is a cubic equation, and the function model is as follows:

[0049] x=a 00 +a 01 u+a 02 u 2 +a03 u 3 +a 10 v+a 11 vu+a 12 v 2 +a 20 v 2 +a 21 uv 2 +a 30 v 3 ;

[0050] y=b 00 +b 01 u+b 02 u 2 +b 03 u 3 +b 10 v+b 11 vu+b 12 v 2 +b 20 v 2 +b 21 uv 2 +b 30 v 3 ;

[0051] Among them, (x, y) is the coordinate of the intersection of each cross figure in the projection original image, and (u, v) is the coordinate of the intersection of each cross figure in the projection photo taken by the area array camera.

[0052] There are 20 unknown coefficients in the function model that need to be solved, namely a 00 、a 01 、a 02 、a 03 、a 10 、a 11 、a 12 、a 20 、a 21 、a 30 、b 00 、b 01 、b 02 、b 03 、b 10 、b 11 、b 12 、b 20 、b 21 、b 30 There are 26 cross figures in the original projection image, so 26 pairs of coordinates of corresponding distortion points can be calculated and substituted into the solution to obtain the distortion equation coefficients of the function model.

[0053] S6: Obtain the coordinates of the intersection points of each cross figure after transformation according to the function model with known coefficients. First, use the 11 points on the coordinate axis to calculate the degree of inclination of the coordinate axis, and then rotate the coordinates of all points. Because the motion coordinates of the translation stage and the projection coordinates of the optical system are not necessarily consistent, after the inclination correction, they are basically consistent with the projection coordinate system of the optical system. At this point, the coefficients of the function model are known. After substituting the preset correct position coordinates into the calibration equation, that is, the function model, the coordinates of the intersection points of each cross figure after transformation can be calculated, thereby obtaining the adjusted projection diagram, that is, the transformed image.

[0054] S7: Drive the optical system to project the transformed image, and repeat steps S2-S6 until the error is less than a preset threshold.

[0055] Since the coordinates of each intersection point in each projection map prepared for the optical system are known, and the coordinates of each intersection point in the photo taken after the projection is completed are also known, when the distance between two points at the same position after multiple adjustments to the projection is less than 0-50um, it can be determined that the error is less than the preset threshold, thereby completing the calibration process. 0-50um is within an optical system pixel grid.

[0056] The present invention proposes a method of generating image projection, driving the translation stage to cyclically find the center point of a cross figure, then taking pictures with an area array camera, extracting the skeleton after processing the image, and finally using the coordinates of each point to approximate a function model to measure and correct the distortion of the optical system.

[0057] The present invention combines the algorithm of refinement + straight line fitting to complete the distortion measurement and correction of the optical system of the surface exposure stereolithography 3D printer, which can reduce the error to between 0 and 50um, which is completely within one pixel grid.

[0058] The present invention corrects the original projection image on the basis of measuring the error of the optical system itself, so that the image projected on the exposure plane is consistent with the theoretical image, thereby ensuring the accuracy of the system.

[0059] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments herein can all be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above around their functions. Whether such functions are implemented as hardware or software depends on specific applications and the design constraints imposed on the entire system. A skilled person can implement the described functions in an alternative manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of the present disclosure.

Claims

1. A method for measuring and correcting distortion of a 3D printer optical system, characterized in that: include: Generate the original projection image and drive the optical system projection; Obtain the coordinates of the intersection points of each cross figure in the projection photo taken by the area array camera; Obtaining the distortion equation coefficients of the function model, and obtaining the coordinates of the intersection points of each cross figure after transformation according to the function model, and repeating the projection until the error is less than a preset threshold; The function model is as follows: x=a 00 +a 01 u+a 02 u 2 +a 03 u 3 +a 10 v+a 11 vu+a 12 vu 2 +a 20 v 2 +a 21 uv 2 +a 30 v 3 ; y=b 00 +b 01 u+b 02 u 2 +b 03 u 3 +b 10 v+b 11 vu+b 12 vu 2 +b 20 v 2 +b 21 uv 2 +b 30 v 3 ; Among them, (x, y) is the coordinate of the intersection of each cross figure in the projection original image, and (u, v) is the coordinate of the intersection of each cross figure in the projection photo taken by the array camera. There are 20 unknown coefficients in the function model that need to be solved, namely, a 00 、a 01 、a 02 、a 03 、a 10 、a 11 、a 12 、a 20 、a 21 、a 30 、b 00 、b 01 、b 02 、b 03 、b 10 、b 11 、b 12 、b 20 、b 21 、b 30 ; There are 26 cross figures in the original projection image, so 26 pairs of coordinates of corresponding distortion points can be calculated, and the distortion equation coefficients of the function model can be obtained by substituting them into the solution.

2. A 3D printer optical system distortion measurement and correction method according to claim 1, characterized in that: The process of generating the projection original image and driving the optical system to project includes: S1: Generate an original projection image of the optical system; S2: driving the optical system to a predetermined coordinate for projection.

3. A 3D printer optical system distortion measurement and correction method according to claim 2, characterized in that: The process of obtaining the coordinates of the intersection points of each cross figure in the projection photo taken by the area array camera includes: S3: driving the area array camera to shoot the image projected by the optical system to obtain a projection photo; S4: Processing the projection photo and obtaining the intersection coordinates of each cross figure in the projection photo.

4. A 3D printer optical system distortion measurement and correction method according to claim 3, characterized in that: The process of obtaining the distortion equation coefficients of the function model, obtaining the coordinates of the intersection points of each cross figure after transformation according to the function model, and repeating the projection until the error is less than a preset threshold comprises: S5: Substitute the coordinate values ​​of the intersection points of each cross figure in the projection photo and the coordinate values ​​of the intersection points of each cross figure in the projection original image into the function model to obtain the distortion equation coefficients of the function model; S6: Obtain the coordinates of the intersection points of each cross figure after transformation according to the function model with known coefficients; S7: driving the optical system to project the transformed image, and repeating steps S2-S6 until the error is less than a preset threshold.

5. A 3D printer optical system distortion measurement and correction method according to claim 4, characterized in that: The projection original image includes a central point and multiple cross figures, and the cross figures are distributed in the form of four concentric circles; the radii of the four concentric circles are 150, 300, 450, and 600 optical system pixel units, respectively, and the length of the two cross lines of each cross figure is 20 optical system pixel units.

6. A 3D printer optical system distortion measurement and correction method according to claim 5, characterized in that: The process of obtaining the coordinates of the intersection points of each cross figure in the projection photo includes: Preprocessing the projected photo; Extracting the skeleton of the cross figure in the preprocessed projection photo; Use the circumscribed rectangle algorithm to find the center point of the skeleton figure; The points on the skeleton are divided into two parts according to the center point obtained by the circumscribed rectangle algorithm, and the points of the two parts are fitted into two straight lines. The two straight lines intersect to obtain the coordinates of the intersection point of the final cross figure.

7. A 3D printer optical system distortion measurement and correction method according to claim 6, characterized in that: The process of preprocessing the projection photo includes: one image binarization; one image erosion; and five image dilations.

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