CN117067594A - Image information identification and analysis system and method of 3D printer - Google Patents
Image information identification and analysis system and method of 3D printer Download PDFInfo
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- CN117067594A CN117067594A CN202311105506.4A CN202311105506A CN117067594A CN 117067594 A CN117067594 A CN 117067594A CN 202311105506 A CN202311105506 A CN 202311105506A CN 117067594 A CN117067594 A CN 117067594A
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- 238000004458 analytical method Methods 0.000 title claims abstract description 26
- 238000000034 method Methods 0.000 title claims abstract description 23
- 239000000463 material Substances 0.000 claims abstract description 171
- 238000007639 printing Methods 0.000 claims abstract description 139
- 239000000701 coagulant Substances 0.000 claims abstract description 51
- 238000001035 drying Methods 0.000 claims abstract description 31
- 238000010276 construction Methods 0.000 claims abstract description 10
- 238000007711 solidification Methods 0.000 claims description 34
- 230000008023 solidification Effects 0.000 claims description 34
- 238000013507 mapping Methods 0.000 claims description 18
- 230000003287 optical effect Effects 0.000 claims description 14
- 238000002156 mixing Methods 0.000 claims description 12
- 230000001537 neural effect Effects 0.000 claims description 12
- 238000003756 stirring Methods 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 12
- 238000005520 cutting process Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- 238000005452 bending Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 230000004069 differentiation Effects 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 230000001678 irradiating effect Effects 0.000 claims description 5
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 239000003086 colorant Substances 0.000 claims 1
- 238000002360 preparation method Methods 0.000 claims 1
- 238000010146 3D printing Methods 0.000 abstract description 8
- 229910052602 gypsum Inorganic materials 0.000 description 8
- 239000010440 gypsum Substances 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 229920002401 polyacrylamide Polymers 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 229920003023 plastic Polymers 0.000 description 2
- 239000004033 plastic Substances 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003746 surface roughness Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
- B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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Abstract
The invention relates to the technical field of 3D printing, in particular to an image information identification and analysis system and method of a 3D printer, comprising the following steps: the invention discloses a three-dimensional printing device, which comprises an image recognition module, a model construction module, a workpiece printing module, a material analysis module and a printing adjustment module, wherein the image recognition module is used for distinguishing the outline of a workpiece according to the three-view of the workpiece, the model construction module is used for establishing a three-dimensional model of the workpiece and calculating the curvature of the outer surface of the model, the workpiece printing module is used for printing the workpiece and dynamically adjusting the diameter of a nozzle of a printer, the material conveying module is used for adjusting the proportion of coagulant aid in printing materials, and the printing adjustment module is used for further adjusting the moving speed of a nozzle of the printer according to the drying condition of the materials.
Description
Technical Field
The invention relates to the technical field of 3D printing, in particular to an image information identification and analysis system and method of a 3D printer.
Background
The 3D printing technology is also called additive manufacturing technology, and belongs to one of the rapid prototyping technologies. The 3D printing is based on a digital model file, and a workpiece is constructed by using materials such as metal, plastic or gypsum in a layer-by-layer printing mode, so that the manufacturing of the workpiece is realized. Today, with image segmentation and machine vision, 3D printing technology is already able to print solid workpieces in photos into the real world with several photos.
The workpiece on the picture often has a curved profile, however, the orifice aperture of the traditional 3D printer is fixed, the thickness of each layer is fixed during printing, and when a curved part of the workpiece is manufactured, obvious step effects exist on the boundary of the workpiece, and the dimensional accuracy and the surface roughness of the part are affected. In order to reduce the influence of the step effect, the thickness of each layer needs to be reduced during printing, but the reduction of the thickness can lead to the increase of the number of printing layers, so that the cost is increased, and the precision waste can be caused when the part without obvious bending is printed, so that the printing efficiency is reduced.
In addition, when materials such as gypsum and plastic are used for 3D printing, the drying time is long, and the undried materials cannot bear more than one layer of weight, and after the printer finishes printing one layer, if the last layer is not dried, collapse is easy to occur. The traditional method needs to add a certain amount of coagulant aid into the material to improve the drying speed, but the coagulant aid is expensive and is difficult to add in a large amount for use; even if coagulant aid is added, the drying of the material is affected by environmental factors, the specific drying time cannot be grasped, and the normal operation of the printer is affected.
Disclosure of Invention
The invention aims to provide an image information identification and analysis system and method of a 3D printer, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an image information recognition analysis system of a 3D printer, comprising: the device comprises an image recognition module, a model construction module, a workpiece printing module, a material conveying module and a printing adjustment module;
the image recognition module is used for receiving three views of the workpiece under the irradiation of the same light source, collecting characteristic information of each pixel point on the picture, carrying out Fourier transform on the picture according to the collected characteristic information, segmenting the picture by using a convolutional neural algorithm, collecting the pixel points at the edge of the segmented image, and distinguishing the contour of the workpiece;
the model construction module is used for establishing a three-dimensional coordinate system, calculating the space coordinates of each point in the picture according to the acquired contour in the three views, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece; acquiring contour information of a model, performing function fitting on the contour information, performing surface differentiation on the fitted function, and obtaining inclination characteristic values of the workpiece at different heights according to differentiation results;
The workpiece printing module is used for receiving the established model, dynamically layering the model according to the printing information, calculating the nozzle diameter of the printer when printing each layer, starting a printing program, and printing the model according to the calculated result;
the material conveying module is used for acquiring hardware parameters of the 3D printer, calculating the maximum drying time of each layer of material according to printing information and the hardware parameters, calculating the proportion of coagulant aid to be added into the material according to the maximum drying time, automatically mixing the material and the coagulant aid in corresponding proportions before starting printing of one layer, and sending the material to a nozzle for printing after stirring the material by a blade arranged at a feed inlet;
the printing adjustment module is used for irradiating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle finishes printing one layer, taking a picture of the section of the workpiece, judging the drying condition of the material according to the reflection intensity of the section of the workpiece on the light, and further adjusting the moving speed of the nozzle of the printer according to the drying condition of the material so as to improve the printing efficiency;
further, the image recognition module includes: an image conversion unit and a contour recognition unit;
the image conversion unit is used for receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on the picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
The contour recognition unit is used for combining low-level semantics and high-level semantics by utilizing a convolutional neural algorithm, cutting the picture, taking a region with the largest area after cutting as a region of a workpiece to be printed, and recording the edge of the region as the external contour of the workpiece to be printed;
further, the model building module includes: a model fitting unit and a curvature differentiating unit;
the model fitting unit is used for finding out pixel points containing the same characteristic information on other view contours according to the characteristic information of each pixel point on the main view contours, taking the two pixel points as the same part of the workpiece and establishing an association relation; establishing a three-dimensional coordinate system OXYZ in a computer space, and giving a ternary mapping relation table according to the association relation of each point on the contour in three views;
the curvature differentiating unit is used for fitting the outline of the outer surface of the workpiece into a curved surface function according to the established physical model, differentiating the curved surface function in the vertical direction, and calculating the inclined characteristic value of the outline of the model of the workpiece under different Z values, wherein the inclined characteristic value represents the bending degree of the surface of the workpiece;
further, the workpiece printing module includes: the device comprises a model input unit, a layer height calculation unit and a printing unit;
The model input unit is used for establishing a three-dimensional coordinate system OXYZ in the computer, calculating the space coordinate of each point in the picture according to the ternary mapping relation table, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece;
the layer height calculation unit is used for obtaining the inclination characteristic value of the model at each height and printing parameters, wherein the printing parameters comprise: calculating the layer height of each layer according to the inclination characteristic value and the printing parameter, wherein the maximum caliber of the nozzle, the minimum caliber of the nozzle and the workpiece manufacturing precision;
the printing unit is used for starting a printing program, acquiring the height coordinate of the current workpiece position, feeding back the height coordinate to the layer height calculating unit, and adjusting the caliber of the nozzle according to the layer height information sent by the layer height calculating unit to finish printing of one layer; moving the workpiece downwards by a layer height distance to prepare for printing of the next layer;
further, the material delivery module includes: the device comprises a data acquisition unit, a drying clock unit and a material mixing unit;
the data acquisition unit is used for acquiring the caliber of the nozzle, the moving distance of the nozzle and the material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
The drying clock unit is used for obtaining the default moving speed of the nozzle of the printer, calculating the printing time of the layer, and calculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the printing time;
the material mixing unit is used for calculating the total usage amount of materials before the printer is ready to print one layer, taking out the corresponding amount of materials and coagulant aids from the ink box according to the ratio of the total usage amount of the materials to the coagulant aids, stirring the materials by the blades arranged at the feed inlet, and sending the mixed materials to the nozzle for printing;
further, the print adjustment module includes: a light intensity analysis unit and a nozzle adjusting unit;
the light intensity analysis unit is used for irradiating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle is printed with a layer, the sensor receives light reflected on the section of the workpiece, the intensity of the reflected light is judged, and the solidification parameters of the material are deduced according to the relation between the historical solidification condition and the light intensity of the material in the database;
the nozzle adjusting unit is used for adjusting the speed of the nozzle when the next layer is printed according to the solidification parameters, so that the material of the upper layer is just solidified when the printer prints the next layer;
An image information recognition analysis method of a 3D printer includes the following steps:
s100, receiving three views of the workpiece under the irradiation of the same light source, carrying out Fourier transform on the picture according to the characteristic information of each pixel point on the picture, dividing the picture by using a convolutional neural algorithm, and dividing the workpiece from the background in the three views; collecting characteristic information of each pixel point in the workpiece picture, and corresponding the pixel points with the same characteristic information in the three views one by one to form a ternary mapping relation;
s200, establishing a three-dimensional coordinate system in a computer, and modeling a workpiece according to the ternary mapping relation constructed in the step S100; according to the established workpiece model, fitting the contour of the outer surface of the workpiece into a curved surface function by using a function fitting method, and calculating the normal curvature of each point on the outer surface of the model by using the vertical direction as a normal vector; acquiring the outer surface cross lines of the workpiece models at different heights, and marking the minimum value of the normal curvature of each point on the cross lines as the inclination characteristic value of the height;
the S300.3D printer receives the established model, layers the model according to the inclination characteristic value and the printing parameter of the model obtained in the step S200, and calculates the caliber of a nozzle when the printer prints each layer; after layering, starting a printing program, and printing the model according to the calculated result;
S400, in the printing process of the printer, calculating the use quantity and printing time of each layer of material according to the caliber information of the nozzle and the material information of the printer, calculating the proportion of coagulant aid to be added into the material according to the material information, automatically mixing the material and the coagulant aid in corresponding proportion before starting to print one layer, stirring by a blade arranged at a feed inlet, and then sending to the nozzle for printing;
s500, after the jet nozzle finishes printing a layer, illuminating a workpiece by using a light source arranged at the top end of the jet nozzle, judging the drying condition of a material according to the reflection intensity of the cross section of the workpiece on light, and further regulating the moving speed of the jet nozzle of the printer according to the drying condition of the material;
further, step S100 includes:
s101, receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on a picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
S102, combining low-level semantics and high-level semantics by using a convolutional neural algorithm, cutting a picture, separating an area containing a workpiece to be printed from the environment in the picture, and recording the edge of the area as the outer contour of the workpiece to be printed;
s103, according to the characteristic information of each pixel point in the area where the workpiece is located, finding out the pixel points containing the same characteristic information in the area of the workpiece on the three views, taking the three pixel points as the same part of the workpiece, and establishing an association relationship to form a ternary mapping relationship table;
further, step S200 includes:
step S201, a three-dimensional coordinate system OXYZ is established in a computer, the space coordinates of each point in the picture are calculated according to the ternary mapping relation table obtained in the step S103, the points are marked in the coordinate system, surface fitting is carried out, and a three-dimensional model of the workpiece is established;
s202, fitting the outline of the outer surface of a workpiece into a curved surface function by using a three-dimensional scattered point fitting function griddata in a Matlab program according to the established physical model, and calculating the normal curvature of each point on the outer surface of the model by taking a direction vector parallel to a Z axis as a normal vector;
s203, slicing the model by using a plane parallel to the X axis and the Y axis, marking the coordinates of the intersection point of the plane and the Z axis as (0, Z0), obtaining a closed plane graph of the obtained slice, and obtaining the normal curvature of each point on the contour of the outer edge of the slice, wherein the maximum value of the normal curvature is marked as an inclined characteristic value under the height Z0;
Further, step S300 includes:
step S301.3D the printer receives the model created in step S201, acquires the inclination feature values of the model at each height and print parameters including: the maximum caliber L of the nozzle, the minimum caliber S of the nozzle and the workpiece precision K of the workpiece are calculated according to the following formula:
wherein F (z) represents the layer height of the current printing layer when the height coordinate of the current printing layer is z, S is less than or equal to F (z) and less than or equal to L, r is an inclined characteristic value of a workpiece model when the height is z, K is the workpiece precision of the current workpiece, the value of K is equal to the maximum value of the inclined characteristic value of the workpiece at all heights, and K is more than 0;
step S302, a printing program is started, a height coordinate z of a current workpiece is obtained, the height coordinate is returned to the step S301, the layer height F (z) under the height coordinate is obtained, the caliber of a nozzle of a 3D printer is adjusted to be the same as the layer height F (z) in value, the distance of nozzle movement when the current layer is printed is predicted according to a model in a computer, the caliber of the nozzle and the distance information of nozzle movement are fed back to the step S400, and after waiting for a material to enter the nozzle, printing is started on the workpiece;
step S303.3D, after printing a layer, the printer moves the workpiece down by the distance of F (z), and repeats step S302 until all the workpieces are printed out;
Further, step S400 includes:
s401, before a 3D printer starts printing a layer, receiving caliber of a nozzle and distance information of nozzle movement in the step S300, and further obtaining material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
step S402, before the printer is ready to print a layer, calculating the total usage N of the material, wherein
S403, obtaining a default moving speed V of a printer nozzle, and calculating printing time T1 of the layer, wherein the default moving speed V is equal to or greater than a preset moving speed V of the printer nozzle, and the printing time T1 is equal to or greater than a preset moving speed V of the printer nozzleCalculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the time T1;
s404, taking out a corresponding amount of materials and coagulant aids from the ink box according to the total usage amount N calculated in the step S402 and the coagulant aid proportion obtained in the step S403, stirring the materials by a blade arranged at a feed inlet, and then delivering the mixed materials to a nozzle for printing;
further, in step S500, since the solidification speed of the material is also affected by environmental factors, the printer needs to further adjust the printing process based on step S400, after the spout prints one layer, the workpiece is irradiated by using a light source disposed at the top end of the spout, the sensor receives the light reflected on the cross section of the workpiece, the reflected light intensity I is determined, the solidification parameter of the material is deduced according to the relation between the historical solidification condition of the material in the database and the light intensity, and the speed of the spout when printing the next layer is adjusted according to the solidification parameter, so that the printer just solidifies the material of the previous layer after printing the next layer is completed;
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the picture of the solid workpiece can be intelligently segmented, the extracted contour information of the workpiece is converted into the model file which can be read by a machine, and a user only needs to shoot three views of the workpiece under the irradiation of the same light source, and the 3D printer can perform 3D printing on the workpiece in the picture.
2. According to the invention, the aperture of the nozzle of the 3D printer can be dynamically adjusted by calculating the bending amplitude of the contour of the workpiece, so that the printer can print with different precision when manufacturing different parts of the workpiece, the step effect generated on the outer side surface of the workpiece after printing due to the bending of the outer vertical surface of the workpiece can be effectively relieved, the roughness of the surface of the workpiece is reduced, and the surface strength of the workpiece is improved.
The invention can reduce the number of layers in the printing process as much as possible while meeting the precision requirement, thereby reducing the moving distance of the nozzle of the printer, saving the time of the workpiece and improving the printing efficiency of the 3D printer.
3. The invention can use big data, dynamically adjust the proportion of the coagulant aid in the material by analyzing the solidification time of each layer of material, avoid excessive use of the coagulant aid, ensure that the drying speed of the material can just meet the requirement of a printer under the condition of not influencing the printing efficiency, and save the cost of using the coagulant aid for users.
4. According to the invention, the drying condition of the material can be judged according to the section photo returned by the camera, and the moving speed of the nozzle of the printer is adaptively adjusted, so that the material of the upper layer is just solidified when the printer prints the next layer, the 3D printer can be prevented from collapsing due to the failure of solidification of the material of the upper layer in the process of preparing the 3D printer, and the speed of the 3D printed product can be improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic diagram of a structure of an image information recognition analysis system of a 3D printer according to the present invention;
FIG. 2 is a schematic diagram illustrating steps of an image information recognition analysis method of a 3D printer according to the present invention;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: an image information recognition analysis system of a 3D printer, comprising: the device comprises an image recognition module, a model construction module, a workpiece printing module, a material conveying module and a printing adjustment module;
the image recognition module is used for receiving three views of the workpiece under the irradiation of the same light source, collecting characteristic information of each pixel point on the picture, carrying out Fourier transform on the picture according to the collected characteristic information, segmenting the picture by using a convolutional neural algorithm, collecting the pixel points at the edge of the segmented image, and distinguishing the contour of the workpiece;
the image recognition module includes: an image conversion unit and a contour recognition unit;
the image conversion unit is used for receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on the picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
the contour recognition unit is used for combining low-level semantics and high-level semantics by utilizing a convolutional neural algorithm, cutting the picture, taking a region with the largest area after cutting as a region of a workpiece to be printed, and recording the edge of the region as the external contour of the workpiece to be printed;
The model construction module is used for establishing a three-dimensional coordinate system, calculating the space coordinates of each point in the picture according to the acquired contour in the three views, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece; acquiring contour information of a model, performing function fitting on the contour information, performing surface differentiation on the fitted function, and obtaining inclination characteristic values of the workpiece at different heights according to differentiation results;
the model construction module comprises: a model fitting unit and a curvature differentiating unit;
the model fitting unit is used for finding out pixel points containing the same characteristic information on other view contours according to the characteristic information of each pixel point on the main view contours, taking the two pixel points as the same part of the workpiece and establishing an association relation; establishing a three-dimensional coordinate system OXYZ in a computer space, and giving a ternary mapping relation table according to the association relation of each point on the contour in three views;
the curvature differentiating unit is used for fitting the outline of the outer surface of the workpiece into a curved surface function according to the established physical model, differentiating the curved surface function in the vertical direction, and calculating the inclined characteristic value of the outline of the model of the workpiece under different Z values, wherein the inclined characteristic value represents the bending degree of the surface of the workpiece;
The workpiece printing module is used for receiving the established model, dynamically layering the model according to the printing information, calculating the nozzle diameter of the printer when printing each layer, starting a printing program, and printing the model according to the calculated result;
the workpiece printing module includes: the device comprises a model input unit, a layer height calculation unit and a printing unit;
the model input unit is used for establishing a three-dimensional coordinate system OXYZ in the computer, calculating the space coordinate of each point in the picture according to the ternary mapping relation table, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece;
the layer height calculation unit is used for obtaining the inclination characteristic value of the model at each height and printing parameters, wherein the printing parameters comprise: calculating the layer height of each layer according to the inclination characteristic value and the printing parameter, wherein the maximum caliber of the nozzle, the minimum caliber of the nozzle and the workpiece manufacturing precision;
the printing unit is used for starting a printing program, acquiring the height coordinate of the current workpiece position, feeding back the height coordinate to the layer height calculating unit, and adjusting the caliber of the nozzle according to the layer height information sent by the layer height calculating unit to finish printing of one layer; moving the workpiece downwards by a layer height distance to prepare for printing of the next layer;
The material conveying module is used for acquiring hardware parameters of the 3D printer, calculating the maximum drying time of each layer of material according to printing information and the hardware parameters, calculating the proportion of coagulant aid to be added into the material according to the maximum drying time, automatically mixing the material and the coagulant aid in corresponding proportions before starting printing of one layer, and sending the material to a nozzle for printing after stirring the material by a blade arranged at a feed inlet;
the material delivery module includes: the device comprises a data acquisition unit, a drying clock unit and a material mixing unit;
the data acquisition unit is used for acquiring the caliber of the nozzle, the moving distance of the nozzle and the material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
the drying clock unit is used for obtaining the default moving speed of the nozzle of the printer, calculating the printing time of the layer, and calculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the printing time;
the material mixing unit is used for calculating the total usage amount of materials before the printer is ready to print one layer, taking out the corresponding amount of materials and coagulant aids from the ink box according to the ratio of the total usage amount of the materials to the coagulant aids, stirring the materials by the blades arranged at the feed inlet, and sending the mixed materials to the nozzle for printing;
The printing adjustment module is used for irradiating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle finishes printing one layer, taking a picture of the section of the workpiece, judging the drying condition of the material according to the reflection intensity of the section of the workpiece on the light, and further adjusting the moving speed of the nozzle of the printer according to the drying condition of the material so as to improve the printing efficiency;
the print adjustment module includes: a light intensity analysis unit and a nozzle adjusting unit;
the light intensity analysis unit is used for irradiating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle is printed with a layer, the sensor receives light reflected on the section of the workpiece, the intensity of the reflected light is judged, and the solidification parameters of the material are deduced according to the relation between the historical solidification condition and the light intensity of the material in the database;
the nozzle adjusting unit is used for adjusting the speed of the nozzle when the next layer is printed according to the solidification parameters, so that the material of the upper layer is just solidified when the printer prints the next layer;
as shown in fig. 2, a method for identifying and analyzing image information of a 3D printer includes the steps of:
s100, receiving three views of the workpiece under the irradiation of the same light source, carrying out Fourier transform on the picture according to the characteristic information of each pixel point on the picture, dividing the picture by using a convolutional neural algorithm, and dividing the workpiece from the background in the three views; collecting characteristic information of each pixel point in the workpiece picture, and corresponding the pixel points with the same characteristic information in the three views one by one to form a ternary mapping relation;
The step S100 includes:
s101, receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on a picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
s102, combining low-level semantics and high-level semantics by using a convolutional neural algorithm, cutting a picture, separating an area containing a workpiece to be printed from the environment in the picture, and recording the edge of the area as the outer contour of the workpiece to be printed;
s103, according to the characteristic information of each pixel point in the area where the workpiece is located, the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point; finding out pixel points containing the same characteristic information in a workpiece area on the three views, taking the three pixel points as the same part of the workpiece, and establishing an association relationship to form a ternary mapping relationship table;
s200, establishing a three-dimensional coordinate system in a computer, and modeling a workpiece according to the ternary mapping relation constructed in the step S100; fitting the outline of the outer surface of the workpiece into a curved surface function according to the established workpiece model, and calculating the normal curvature of each point on the outer surface of the model by taking the vertical direction as a normal vector; acquiring the outer surface cross lines of the workpiece models at different heights, and marking the minimum value of the normal curvature of each point on the cross lines as the inclination characteristic value of the height;
Step S200 includes:
step S201, a three-dimensional coordinate system OXYZ is established in a computer, the space coordinates of each point in the picture are calculated according to the ternary mapping relation table obtained in the step S103, the points are marked in the coordinate system, surface fitting is carried out, and a three-dimensional model of the workpiece is established;
s202, fitting the outline of the outer surface of a workpiece into a curved surface function by using a three-dimensional scattered point fitting function griddata in a Matlab program according to the established physical model, and calculating the normal curvature of each point on the outer surface of the model by taking a direction vector parallel to a Z axis as a normal vector;
s203, slicing the model by using a plane parallel to the X axis and the Y axis, marking the coordinates of the intersection point of the plane and the Z axis as (0, Z0), obtaining a closed plane graph of the obtained slice, and obtaining the normal curvature of each point on the contour of the outer edge of the slice, wherein the maximum value of the normal curvature is marked as an inclined characteristic value under the height Z0;
the S300.3D printer receives the established model, layers the model according to the inclination characteristic value and the printing parameter of the model obtained in the step S200, and calculates the caliber of a nozzle when the printer prints each layer; after layering, starting a printing program, and printing the model according to the calculated result;
Step S300 includes:
step S301.3D the printer receives the model created in step S201, acquires the inclination feature values of the model at each height and print parameters including: the maximum caliber L of the nozzle, the minimum caliber S of the nozzle and the workpiece precision K of the workpiece are calculated according to the following formula:
wherein F (z) represents the layer height of the current printing layer when the height coordinate of the current printing layer is z, S is less than or equal to F (z) and less than or equal to L, r is an inclined characteristic value of a workpiece model when the height is z, K is the workpiece precision of the current workpiece, the value of K is equal to the maximum value of the inclined characteristic value of the workpiece at all heights, and K is more than 0;
step S302, a printing program is started, a height coordinate z of a current workpiece is obtained, the height coordinate is returned to the step S301, the layer height F (z) under the height coordinate is obtained, the caliber of a nozzle of a 3D printer is adjusted to be the same as the layer height F (z) in value, the distance G of the nozzle moving when the current layer is printed is predicted according to a model in a computer, the caliber of the nozzle and the distance information of the nozzle moving are fed back to the step S400, and after materials enter the nozzle, printing is started on the workpiece;
step S303.3D, after printing a layer, the printer moves the workpiece down by the distance of F (z), and repeats step S302 until all the workpieces are printed out;
S400, in the printing process of the printer, calculating the use quantity and printing time of each layer of material according to the caliber information of the nozzle and the material information of the printer, calculating the proportion of coagulant aid to be added into the material according to the material information, automatically mixing the material and the coagulant aid in corresponding proportion before starting to print one layer, stirring by a blade arranged at a feed inlet, and then sending to the nozzle for printing;
step S400 includes:
s401, before a 3D printer starts printing a layer, receiving caliber of a nozzle and distance information of nozzle movement in the step S300, and further obtaining material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
step S402, before the printer is ready to print a layer, calculating the total usage N of the material, whereinG is the distance moved by the nozzle when printing the current layer;
s403, obtaining a default moving speed V of a printer nozzle, and calculating printing time T1 of the layer, wherein the default moving speed V is equal to or greater than a preset moving speed V of the printer nozzle, and the printing time T1 is equal to or greater than a preset moving speed V of the printer nozzleCalculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the time T1;
S404, taking out a corresponding amount of materials and coagulant aids from the ink box according to the total usage amount N calculated in the step S402 and the coagulant aid proportion obtained in the step S403, stirring the materials by a blade arranged at a feed inlet, and then delivering the mixed materials to a nozzle for printing;
s500, after the jet nozzle finishes printing a layer, illuminating a workpiece by using a light source arranged at the top end of the jet nozzle, judging the drying condition of a material according to the reflection intensity of the cross section of the workpiece on light, and further regulating the moving speed of the jet nozzle of the printer according to the drying condition of the material;
in step S500, since the solidification speed of the material is also affected by environmental factors, the printer needs to further adjust the printing process based on step S400, after the spout prints one layer, the light source disposed at the top end of the spout irradiates the workpiece, the sensor receives the light reflected on the cross section of the workpiece, determines the intensity I of the reflected light, deduces the solidification parameters of the material according to the relation between the historical solidification condition of the material in the database and the light intensity, and adjusts the speed of the spout when printing the next layer according to the solidification parameters, so that the printer just solidifies the material of the previous layer after printing the next layer.
Examples:
After receiving a picture sent by a user, the system models a model of a workpiece according to pixel points on the picture, reads model information of the workpiece, acquires an inclination characteristic value of the workpiece at each height, and sends a model file into a 3D printer, wherein in the embodiment, the printing material is gypsum, and the coagulant aid is polyacrylamide;
before the printer is ready to print, calculating the layer height of the first layer, acquiring an inclination characteristic value r=0.5 when z=0 according to the coordinate z=0 of the first layer, wherein the workpiece precision K=2 of the workpiece, and the adjusting range of the nozzle is 2mm to 10mm, wherein the layer height of the first layer is calculated When the first layer is printed, the caliber of the nozzle of the 3D printer is adjusted to be 8mm;
obtaining the distance g=100 mm that the nozzle moves when printing the first layer calculates the total usage of materialCalculating the printing time T1=10s of the layer according to the default moving speed V=10mm/s of the nozzle of the printer, searching the minimum coagulant aid proportion required by setting gypsum in 10s in a database, and extracting gypsum material and polyacrylamide solution from the ink box when the searching result is 0.5%, wherein the volume of the gypsum material and the polyacrylamide solution is 1600 pi mm 2 After stirring the materials by the blades arranged at the feed inlet, delivering the mixed materials to the nozzle for printing;
The printer starts to print, after the first layer is printed, a light source arranged at the top end of the nozzle irradiates the workpiece, the sensor receives light reflected on the section of the workpiece, the reflected light intensity I=5nt is judged, and as the reflected light intensity of the solidified gypsum is smaller than 2nt, the system judges that the gypsum is not solidified, the moving speed of the nozzle is slowed down when the next layer is printed, so that the first layer of material is just solidified after the printer finishes printing the next layer. Repeating the steps until the workpiece is printed;
it is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for identifying and analyzing image information of a 3D printer, the method comprising the steps of:
s100, receiving three views of the workpiece under the irradiation of the same light source, carrying out Fourier transform on the picture according to the characteristic information of each pixel point on the picture, dividing the picture by using a convolutional neural algorithm, and dividing the workpiece from the background in the three views; collecting characteristic information of each pixel point in the workpiece picture, and corresponding the pixel points with the same characteristic information in the three views one by one to form a ternary mapping relation;
s200, establishing a three-dimensional coordinate system in a computer, and modeling a workpiece according to the ternary mapping relation constructed in the step S100; according to the established workpiece model, fitting the contour of the outer surface of the workpiece into a curved surface function by using a function fitting method, and calculating the normal curvature of each point on the outer surface of the model by using the vertical direction as a normal vector; acquiring the outer surface cross lines of the workpiece models at different heights, and marking the minimum value of the normal curvature of each point on the cross lines as the inclination characteristic value of the height;
The S300.3D printer receives the established model, layers the model according to the inclination characteristic value and the printing parameter of the model obtained in the step S200, and calculates the caliber of a nozzle when the printer prints each layer; after layering, starting a printing program, and printing the model according to the calculated result;
s400, in the printing process of the printer, calculating the use quantity and printing time of each layer of material according to the caliber information of the nozzle and the material information of the printer, calculating the proportion of coagulant aid to be added into the material according to the material information, automatically mixing the material and the coagulant aid in corresponding proportion before starting to print one layer, stirring by a blade arranged at a feed inlet, and then sending to the nozzle for printing;
s500, after the jet nozzle finishes printing a layer, a light source arranged at the top end of the jet nozzle irradiates the workpiece, the drying condition of the material is judged according to the reflection intensity of the cross section of the workpiece on the light, and the moving speed of the jet nozzle of the printer is further regulated according to the drying condition of the material.
2. The image information recognition analysis method of a 3D printer according to claim 1, wherein: the step S100 includes:
S101, receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on a picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
s102, combining low-level semantics and high-level semantics by using a convolutional neural algorithm, cutting a picture, separating an area containing a workpiece to be printed from the environment in the picture, and recording the edge of the area as the outer contour of the workpiece to be printed;
s103, according to the characteristic information of each pixel point in the area where the workpiece is located, the characteristic information comprises: the method comprises the steps that the optical frequency of colors on pixel points and the gray value of the pixel points are found out, the pixel points containing the same characteristic information are found out in a workpiece area on a three-view, and three pixel points are used as the same part of a workpiece and are established with association relations to form a ternary mapping relation table;
step S200 includes:
step S201, a three-dimensional coordinate system OXYZ is established in a computer, the space coordinates of each point in the picture are calculated according to the ternary mapping relation table obtained in the step S103, the points are marked in the coordinate system, surface fitting is carried out, and a three-dimensional model of the workpiece is established;
S202, fitting the outline of the outer surface of a workpiece into a curved surface function by using a three-dimensional scattered point fitting function griddata in a Matlab program according to the established physical model, and calculating the normal curvature of each point on the outer surface of the model by taking a direction vector parallel to a Z axis as a normal vector;
s203, slicing the model by using a plane parallel to the X axis and the Y axis, marking the coordinates of the intersection point of the plane and the Z axis as (0, Z0), obtaining a closed plane graph of the obtained slice, and obtaining the normal curvature of each point on the contour of the outer edge of the slice, wherein the maximum value of the normal curvature is marked as an inclined characteristic value under the height Z0.
3. The image information recognition analysis method of a 3D printer according to claim 1, wherein: step S300 includes:
step S301.3D the printer receives the model created in step S201, acquires the inclination feature values of the model at each height and print parameters including: the maximum caliber L of the nozzle, the minimum caliber S of the nozzle and the workpiece precision K of the workpiece are calculated according to the following formula:
wherein F (z) represents the layer height of the current printing layer when the height coordinate of the current printing layer is z, S is less than or equal to F (z) and less than or equal to L, r is an inclined characteristic value of a workpiece model when the height is z, K is the workpiece precision of the current workpiece, the value of K is equal to the maximum value of the inclined characteristic value of the workpiece at all heights, and K is more than 0;
Step S302, a printing program is started, a height coordinate z of a current workpiece is obtained, the height coordinate is returned to the step S301, the layer height F (z) under the height coordinate is obtained, the caliber of a nozzle of a 3D printer is adjusted to be the same as the layer height F (z) in value, the distance of nozzle movement when the current layer is printed is predicted according to a model in a computer, the caliber of the nozzle and the distance information of nozzle movement are fed back to the step S400, and after waiting for a material to enter the nozzle, printing is started on the workpiece;
step S303.3D the printer moves the workpiece down by a distance F (z) after printing one layer, and repeats step S302 until the workpiece is completely printed.
4. The image information recognition analysis method of a 3D printer according to claim 1, wherein: step S400 includes:
s401, before a 3D printer starts printing a layer, receiving caliber of a nozzle and distance information of nozzle movement in the step S300, and further obtaining material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
step S402, before the printer is ready to print a layer, calculating the total usage N of the material, wherein
S403, obtaining a default moving speed V of a printer nozzle, and calculating printing time T1 of the layer, wherein the default moving speed V is equal to or greater than a preset moving speed V of the printer nozzle, and the printing time T1 is equal to or greater than a preset moving speed V of the printer nozzleCalculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the time T1;
s404, taking out a corresponding amount of materials and coagulant aids from the ink box according to the total usage amount N calculated in the step S402 and the coagulant aid proportion obtained in the step S403, stirring the materials by a blade arranged at a feed inlet, and delivering the mixed materials to a nozzle for printing.
5. The image information recognition analysis method of a 3D printer according to claim 1, wherein: in step S500, after the nozzle prints one layer, the workpiece is irradiated by using a light source disposed at the top end of the nozzle, the sensor receives the light reflected on the cross section of the workpiece, determines the intensity I of the reflected light, deduces the solidification parameters of the material according to the relation between the historical solidification condition of the material in the database and the light intensity, and adjusts the speed of the nozzle when printing the next layer according to the solidification parameters, so that the printer just solidifies the material of the previous layer after printing the next layer.
6. An image information recognition analysis system of a 3D printer, the system comprising: the device comprises an image recognition module, a model construction module, a workpiece printing module, a material conveying module and a printing adjustment module;
The image recognition module is used for receiving three views of the workpiece under the irradiation of the same light source, collecting characteristic information of each pixel point on the picture, carrying out Fourier transform on the picture according to the collected characteristic information, segmenting the picture by using a convolutional neural algorithm, collecting the pixel points at the edge of the segmented image, and distinguishing the contour of the workpiece;
the model construction module is used for establishing a three-dimensional coordinate system, calculating the space coordinates of each point in the picture according to the acquired contour in the three views, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece; acquiring contour information of a model, performing function fitting on the contour information, performing surface differentiation on the fitted function, and obtaining inclination characteristic values of the workpiece at different heights according to differentiation results;
the workpiece printing module is used for receiving the established model, dynamically layering the model according to the printing information, calculating the nozzle diameter of the printer when printing each layer, starting a printing program, and printing the model according to the calculated result;
the material conveying module is used for acquiring hardware parameters of the 3D printer, calculating the maximum drying time of each layer of material according to printing information and the hardware parameters, calculating the proportion of coagulant aid to be added into the material according to the maximum drying time, automatically mixing the material and the coagulant aid in corresponding proportions before starting printing of one layer, and sending the material to a nozzle for printing after stirring the material by a blade arranged at a feed inlet;
The printing adjustment module is used for illuminating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle is printed with one layer, taking a picture of the section of the workpiece, judging the drying condition of the material according to the reflection intensity of the section of the workpiece to light, and further adjusting the moving speed of the nozzle of the printer according to the drying condition of the material so as to improve the printing efficiency.
7. The image information recognition analysis system of a 3D printer of claim 6, wherein: the image recognition module includes: an image conversion unit and a contour recognition unit;
the image conversion unit is used for receiving three views of a workpiece to be printed under the irradiation of the same light source, and collecting characteristic information of each pixel point on the picture, wherein the characteristic information comprises: the optical frequency of the color on the pixel point and the gray value of the pixel point are subjected to Fourier transform on the whole picture according to the collected optical frequency, the pixel points in different frequency ranges are screened out through a screening device, and the picture is divided into a high-layer semantic part and a low-layer semantic part;
the contour recognition unit is used for combining low-level semantics and high-level semantics by utilizing a convolutional neural algorithm, cutting the picture, taking a region with the largest area after cutting as a region of a workpiece to be printed, and recording the edge of the region as the external contour of the workpiece to be printed;
The model construction module comprises: a model fitting unit and a curvature differentiating unit;
the model fitting unit is used for finding out pixel points containing the same characteristic information on other view contours according to the characteristic information of each pixel point on the main view contours, taking the two pixel points as the same part of the workpiece and establishing an association relation; establishing a three-dimensional coordinate system OXYZ in a computer space, and giving a ternary mapping relation table according to the association relation of each point on the contour in three views;
the curvature differentiating unit is used for fitting the outline of the outer surface of the workpiece into a curved surface function according to the established physical model, differentiating the curved surface function in the vertical direction, and calculating the inclination characteristic value of the outline of the model of the workpiece under different Z values, wherein the inclination characteristic value represents the bending degree of the surface of the workpiece.
8. The image information recognition analysis system of a 3D printer of claim 6, wherein: the workpiece printing module includes: the device comprises a model input unit, a layer height calculation unit and a printing unit;
the model input unit is used for establishing a three-dimensional coordinate system OXYZ in the computer, calculating the space coordinate of each point in the picture according to the ternary mapping relation table, marking the points in the coordinate system and performing surface fitting to establish a three-dimensional model of the workpiece;
The layer height calculation unit is used for obtaining the inclination characteristic value of the model at each height and printing parameters, wherein the printing parameters comprise: the maximum caliber of the nozzle, the minimum caliber of the nozzle and the workpiece precision of the workpiece, and calculating the layer height of each layer;
the printing unit is used for starting a printing program, acquiring the height coordinate of the current workpiece position, feeding back the height coordinate to the layer height calculating unit, and adjusting the caliber of the nozzle according to the layer height information sent by the layer height calculating unit to finish printing of one layer; the workpiece is moved down one level of distance in preparation for printing the next level.
9. The image information recognition analysis system of a 3D printer of claim 6, wherein: the material delivery module includes: the device comprises a data acquisition unit, a drying clock unit and a material mixing unit;
the data acquisition unit is used for acquiring the caliber of the nozzle, the moving distance of the nozzle and the material information of the printer, wherein the material information comprises: the storage amount of materials in the ink box, the storage amount of coagulant aids and the solidification time table of the materials after the coagulant aids are added in various proportions;
the drying clock unit is used for obtaining the default moving speed of the nozzle of the printer, calculating the printing time of the layer, and calculating the proportion of coagulant aid to be added into the material according to the usage amount and the solidification time table of the material, so that the material can be just solidified in the printing time;
The material mixing unit is used for calculating the total usage amount of the materials before the printer is ready to print one layer, taking out the corresponding amount of the materials and the coagulant aid from the ink box according to the ratio of the total usage amount of the materials to the coagulant aid, and sending the mixed materials to the nozzle for printing after the materials are stirred by the blades arranged at the feed inlet.
10. The image information recognition analysis system of a 3D printer of claim 6, wherein: the print adjustment module includes: a light intensity analysis unit and a nozzle adjusting unit;
the light intensity analysis unit is used for irradiating the workpiece by using a light source arranged at the top end of the nozzle after the nozzle is printed with a layer, the sensor receives light reflected on the section of the workpiece, the intensity of the reflected light is judged, and the solidification parameters of the material are deduced according to the relation between the historical solidification condition and the light intensity of the material in the database;
the nozzle adjusting unit is used for adjusting the speed of the nozzle when the next layer is printed according to the solidification parameters, so that the material of the upper layer is just solidified when the printer prints the next layer.
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| CN105112965A (en) * | 2015-09-16 | 2015-12-02 | 上海圣匡机电科技有限公司 | Printing head, printing device and printing method for rapid forming of metal piece |
| US20200055252A1 (en) * | 2018-08-20 | 2020-02-20 | James Lewicki | Optimal toolpath generation system and method for additively manufactured composite materials |
| WO2021228181A1 (en) * | 2020-05-13 | 2021-11-18 | 中国科学院福建物质结构研究所 | 3d printing method and device |
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| CN105112965A (en) * | 2015-09-16 | 2015-12-02 | 上海圣匡机电科技有限公司 | Printing head, printing device and printing method for rapid forming of metal piece |
| US20200055252A1 (en) * | 2018-08-20 | 2020-02-20 | James Lewicki | Optimal toolpath generation system and method for additively manufactured composite materials |
| WO2021228181A1 (en) * | 2020-05-13 | 2021-11-18 | 中国科学院福建物质结构研究所 | 3d printing method and device |
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