Artificial intelligence (AI) controlled material extrusion type 3D printing system and control method thereof

Abstract

The present invention relates to an artificial intelligence (AI)-based control material extrusion type 3D printing system for extruding high viscosity material and a control method thereof, and more particularly, to an artificial intelligence (AI)-based control material extrusion type 3D printing system capable of determining whether a printing platform and a nozzle are horizontal or not by a line width of extruded material, and preventing a defect of a printed object by correcting a line width of a layer when the printing platform and the nozzle are not horizontal, and a control method thereof.

Description

Technical Field

[0001] This invention relates to an artificial intelligence (AI)-controlled material extrusion 3D printing system and its control method for extruding high-viscosity materials. Background Technology

[0002] 3D printing technology is a manufacturing technology that uses 3D drawings as a basis to print objects in 3D space.

[0003] In the past, as mentioned above, 3D printing technology was used for very limited purposes due to factors such as the high price of 3D printers. However, recently, with the decrease in the price of 3D printers, they have become more accessible to the general public, and their materials are no longer limited to plastics, but have expanded to include materials such as nylon and metals, thus enabling their application in all industrial sectors.

[0004] 3D printing methods include, for example, stereolithography (SLA), which uses the principle that the part of a photocurable resin is cured when a laser is irradiated; selective laser sintering (SLS), which uses a functional polymer to lift the photocurable resin in a stereolithography (SLA) apparatus and sinters it by irradiating it with a laser beam; laminated object manufacturing (LOM), which uses a laser beam to cut paper coated with adhesive along the desired cross section and stack it layer by layer; ballistic particle manufacturing (BPM), which uses inkjet printer technology; binder jet, which uses an adhesive to bond powder to the desired area of ​​the powder coated on the build platform and stacks it layer by layer to form a model; and direct ink writing (DIW), which prints by using compressed gas, a piston, or a screw to eject material.

[0005] 3D printers using the Direct Ink Writing (DIW) method described above are suitable for using materials in a liquid state with high concentration and high viscosity.

[0006] Direct Ink Writing (DIW) 3D printers eject material onto a printing platform for layering, and the layered material forms a 3D shape, thus creating a 3D printed object.

[0007] As mentioned above, since 3D printed objects are generated by layering the ejected material, if the printing platform is tilted or the feeder is not level with the printing platform, the material will not be able to be layered horizontally on the printing platform. Consequently, if the material cannot be layered horizontally, the error will increase with each layering, resulting in defective 3D printed objects.

[0008] Therefore, a technology is needed to correct the misalignment of the printing platform and nozzle when the material is being ejected.

[0009] Prior technology documents

[0010] Patent documents

[0011] (Patent Document 1) Korean Patent No. 10-2239029 Summary of the Invention

[0012] The present invention aims to solve the problems described above, and its purpose is to provide a material extrusion 3D printing system and control method based on artificial intelligence (AI) control, which can determine whether the printing platform and nozzle are level by means of the linewidth of the extruded material, and prevent defects in the printed material by correcting the linewidth of the layer when the printing platform and nozzle are not level.

[0013] According to one feature of the present invention, a material extrusion 3D printing system based on artificial intelligence (AI) control includes: a feeder for extruding material into a nozzle; a printing platform disposed below the nozzle for stacking multiple layers of material extruded from the nozzle; a linewidth measuring device for measuring the linewidth of the layers stacked on the printing platform; and a control unit that, when the linewidth of the layer measured by the linewidth measuring device is above a preset reference linewidth, controls the feeder to reduce the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area, and when the linewidth of the layer measured by the linewidth measuring device is below the reference linewidth, controls the feeder to increase the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area.

[0014] Furthermore, after generating an imaginary circle with the center of the nozzle orifice as the center point, the control unit measures the number of pixels between two contact points where the imaginary circle intersects with the linewidth of the layer extruded from the nozzle, and calculates the linewidth of the layer by calculating the distance value of each pixel preset in the control unit and the number of pixels.

[0015] A control method for an artificial intelligence (AI)-based material extrusion 3D printing system according to one feature of the present invention includes: a measurement step, wherein the linewidth of a layer stacked on a printing platform is measured by a linewidth measuring device; and a correction step, wherein if the linewidth of the layer measured by the linewidth measuring device is greater than or equal to a pre-set reference linewidth, the control unit controls the feeder to reduce the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area, and if the linewidth of the layer measured by the linewidth measuring device is less than the reference linewidth, the control unit controls the feeder to increase the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area.

[0016] Furthermore, the measurement steps include: a reference point selection step, selecting the center of the nozzle orifice of the feeder nozzle as a reference point; an imaginary circle generation step, generating an imaginary circle with the reference point as the center point; a contact point selection step, selecting two contact points where the imaginary circle intersects with the linewidth of the layer extruded from the nozzle; and a calculation step, measuring the number of pixels between the two contact points and calculating the linewidth of the layer by substituting the measured number of pixels into a distance value for each pixel preset in the control unit.

[0017] The artificial intelligence (AI)-based material extrusion 3D printing system and its control method of the present invention, as described above, can achieve the following effects.

[0018] Even when the printing platform and the feeder are not level, the control unit can correct this by adjusting the amount of material ejected from the feeder while simultaneously stacking the layers. This allows for easy correction of unevenness in the level of the stacked layers and prevents defects in the printed material.

[0019] Even when the printing platform is not tilted, and the feeder moves up and down, causing only a portion of the layer to be horizontally disrupted, the unevenness in material extrusion caused by the disruption of the horizontality can be corrected.

[0020] By using the two points of contact between the imaginary circle and the line width, the length of the line width can be easily calculated using the number of pixels and the distance between each pixel. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the material extrusion 3D printing system based on artificial intelligence (AI) control of the present invention.

[0022] Figure 2 This is a sequence diagram of the control method for a material extrusion 3D printing system based on artificial intelligence (AI).

[0023] Figure 3 This is a schematic diagram illustrating a method for measuring the linewidth of material ejected from a nozzle in an artificial intelligence (AI)-controlled material extrusion 3D printing system of the present invention.

[0024] Figures 4 to 6 This is a schematic diagram illustrating the process of correcting the level of layers using a control method in an artificial intelligence (AI)-based material extrusion 3D printing system.

[0025] [Symbol Explanation]

[0026] 10: Artificial Intelligence (AI) Controlled Material Extrusion 3D Printing System

[0027] 100: Feeder

[0028] 110: Chamber

[0029] 130: Gas supply pipeline

[0030] 140: Control valve

[0031] 160: Nozzle

[0032] 161: Nozzle orifice

[0033] 190: Heater

[0034] 200: Printing Platform

[0035] 300: Line width measuring device

[0036] 400: Control Department Detailed Implementation

[0037] The following content is merely an illustration of the principles of the invention. Therefore, those skilled in the art can invent various devices that, while not explicitly described or illustrated in this specification, achieve the principles of the invention and are included within the concept and scope of the invention. Furthermore, in principle, all conditional terms and embodiments listed in this specification are merely for the purpose of clarifying the concept of the invention and should be understood as not being limited to the embodiments and states specifically listed above.

[0038] The objectives, features, and advantages described above will become even clearer from the following detailed description with reference to the accompanying drawings, and those skilled in the art to which this invention pertains will be able to readily implement the technical concept of this invention based thereon.

[0039] The embodiments described in this specification will now be described with reference to the ideal illustrative drawings of the invention, namely cross-sectional views and / or oblique views. The technical terms used in this specification are for illustrative purposes only and are not intended to limit the invention. Singular statements also have plural meanings unless the context clearly indicates otherwise. Terms such as "comprising" or "having" in this specification are used only to indicate the presence of features, numbers, steps, actions, constituent elements, components, or combinations thereof described in this specification, and should not be construed as excluding the possibility of one or more other features, numbers, steps, actions, constituent elements, components, or combinations thereof being present or added.

[0040] Next, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description of various embodiments, for ease of explanation, constituent elements that perform the same function are assigned the same names and reference numerals even in different embodiments. Furthermore, for ease of explanation, configurations and operations already described in other embodiments will be omitted.

[0041] Next, please refer to Figures 1 to 6 The material extrusion 3D printing system 10 based on artificial intelligence (AI) control and the control method of the material extrusion 3D printing system based on artificial intelligence (AI) control are described.

[0042] Figure 1 This is a schematic diagram of the material extrusion 3D printing system based on artificial intelligence (AI) control according to the present invention. Figure 2 This is a sequence diagram of the control method for a material extrusion 3D printing system based on artificial intelligence (AI). Figure 3 This is a schematic diagram illustrating a method for measuring the linewidth of material ejected from a nozzle in an artificial intelligence (AI)-controlled material extrusion 3D printing system of the present invention. Figures 4 to 6 This is a schematic diagram illustrating the process of correcting the level of layers using a control method in an artificial intelligence (AI)-based material extrusion 3D printing system.

[0043] First, the material extrusion 3D printing system based on artificial intelligence (AI) control of the present invention will be described.

[0044] like Figure 1 As shown, the artificial intelligence (AI)-controlled material extrusion 3D printing system (10) of the present invention may include:

[0045] The feeder 100 extrudes material into the nozzle 160; the gas supply line 130 supplies gas to the feeder 100; the control valve 140 opens and closes the gas supply line 130; the heater 190 heats the feeder 100; the printing platform 200 is disposed below the nozzle 160 and allows the material extruded from the nozzle 160 to be stacked into multiple layers L; the line width measuring device 300 measures the line width W of the layers L stacked on the printing platform 200; and the control unit 400 drives the control valve 140 to operate.

[0046] The feeder 100 is equipped with a chamber 110.

[0047] Chamber 110 is connected to gas supply line 130. Hereby, gas can be selectively supplied to chamber 110 by means of operation of control valve 140.

[0048] The interior of chamber 110 is filled with material.

[0049] The material is composed of a high-viscosity fluid and can be composed of fine solid molecules within a high-viscosity fluid.

[0050] A nozzle 160 is provided in the lower part of the chamber 110.

[0051] The nozzle 160 is equipped with a nozzle hole 161 that communicates with the lower chamber 112.

[0052] The material extruded through nozzle orifice 161 will be ejected to the outside of nozzle 160. As described above, nozzle orifice 161 has a fine size.

[0053] The material supplied and filled into the chamber 110 can be pressurized by gas supplied from the gas supply line 130 and extruded through the nozzle 160, thereby being ejected to the outside of the feeder 100.

[0054] The control valve 140 functions to open or close the gas supply line 130 under the control of the control unit 400, or to control the flow rate of the gas supplied through the gas supply line 130.

[0055] The heater 190 functions to heat the feeder 100 by generating heat, thereby heating the material filled into the lower chamber 112 of the feeder 100.

[0056] By heating the material using heater 190, the viscosity of the high-viscosity material can be reduced, thereby allowing the high-viscosity material to be precisely and smoothly ejected through the smaller nozzle orifice 161.

[0057] The printing platform 200 is located below the feeder 100 and the nozzle 160.

[0058] The printing platform 200 provides space for printing objects made of the material as the extruded material is ejected from the nozzle 160.

[0059] The feeder 100 is suspended above the printing platform 200 by means of a feeder transfer mechanism (not shown).

[0060] The feeder transfer mechanism can transfer the feeder 100 in the upward, downward, left, right, front, and rear directions (i.e., the X-axis, Y-axis, and Z-axis directions).

[0061] The feeder 100 can move in 3D according to the shape of the printed object and eject the material in multiple layers on the printing platform 200 to generate the printed object.

[0062] The line width measuring device 300 is used to measure the line width W of the layer L stacked on the printing platform 200.

[0063] The line width measuring device 300 can be composed of devices such as cameras, laser scanners, and laser sensors.

[0064] The control unit 400 measures the line width W of layer L by connecting to the line width measuring device 300 and determines whether the feeder 100 and the printing platform 200 are horizontally aligned. If the feeder 100 and the printing platform 200 are not horizontally aligned, it corrects the printed material by adjusting the amount of material dispensed.

[0065] A baseline width SW is preset in the control unit 400. The baseline width is the width of the material normally ejected from the nozzle 160 when the feeder 100 and the printing platform 200 are arranged horizontally.

[0066] When the line width W of layer L measured by the line width measuring device 300 is greater than or equal to the preset baseline line width SW, the control unit 400 reduces the material extrusion amount of the corresponding area of ​​the layer L above the area of ​​layer L where the line width W is measured by controlling the feeder 100.

[0067] Furthermore, if the line width W of layer L measured by the line width measuring device 300 is less than the reference line width SW, the control unit 400 increases the material extrusion amount of the corresponding area of ​​the layer L above the area of ​​layer L where the line width W is measured by controlling the feeder 100.

[0068] The distance value for each pixel is preset in the control unit 400.

[0069] The control unit 400 can calculate the line width W of layer L by connecting to the line width measuring device 400.

[0070] After generating an imaginary circle VC with the center of the nozzle orifice of the nozzle 160 as a reference point RP, the control unit 400 measures the number of pixels between two contact points CP where the imaginary circle VC intersects with the linewidth W of the layer L extruded from the nozzle 160, and calculates the linewidth W of the layer L by calculating the distance and number of pixels of each pixel preset in the control unit 400.

[0071] Next, please refer to Figures 2 to 6 The control method of the material extrusion 3D printing system 10 based on artificial intelligence (AI) control of the present invention will be described.

[0072] like Figure 2 As shown, the control method of the material extrusion 3D printing system 10 based on artificial intelligence (AI) control of the present invention may include: a measurement step S10, measuring the line width W of layer L stacked on the printing platform 200 by means of a line width measuring device 300; and a correction step S20, in which, if the line width W of layer L measured by the line width measuring device 300 is greater than or equal to a preset reference line width SW, the control unit 400 controls the feeder 100 to reduce the material extrusion amount of the corresponding area of ​​the layer K above the area of ​​layer L where the line width W is measured, and if the line width W of layer L measured by the line width measuring device 300 is less than the reference line width SW, the control unit 400 controls the feeder 100 to increase the material extrusion amount of the corresponding area of ​​the layer L above the area of ​​layer L where the line width W is measured.

[0073] In measurement step S10, the process of measuring the line width W of layer L stacked on printing platform 200 by line width measuring device 300 can be performed.

[0074] The measurement step S10 may include: a reference point selection step S11, selecting the center of the nozzle hole 161 of the nozzle 160 of the feeder 100 as a reference point RP; an imaginary circle generation step S12, generating an imaginary circle VC with the reference point RP as the center point; a contact point selection step S13, selecting two contact points CP that intersect the imaginary circle VC with the line width W of the layer L extruded from the nozzle 160; and a calculation step S14, measuring the number of pixels between the two contact points CP, and calculating the line width W of the layer L by substituting the measured number of pixels into the distance value of each pixel preset in the control unit 400.

[0075] First, in the reference point selection step S11, as follows: Figure 3 As shown, after the line width measuring device 300 takes a picture of the end of the nozzle 160, the control unit 400 selects the center of the nozzle hole 161 at the end of the nozzle 160 as the reference point RP.

[0076] Next, in the imaginary circle generation step S12, an imaginary circle VC is generated with the reference point RP as its center point. As described above, the imaginary circle VC is formed with a diameter that can form two contact points CP with the linewidth W of layer L when the material ejected from the nozzle orifice 161 forms layer L.

[0077] Next, in the contact point selection step S13, two contact points CP are selected where the imaginary circle VC intersects with the line width W of the layer L extruded from the nozzle 160.

[0078] Next, in calculation step S14, the number of pixels between the two contact points CP is measured by the line width measuring device 300, and the line width W of layer L is calculated by substituting the measured number of pixels into the distance value of each pixel preset in the control unit 400.

[0079] For example, if the distance value of each pixel is preset to "20μm" in the control unit 400 and the number of pixels measured is "1,000", then the line width W of layer L is "20,000μm", or "2cm".

[0080] As described above, after the control unit 400 calculates the line width W of layer L using the elements measured in the line width measuring device 300, the measurement step S10 is completed.

[0081] In measurement step S10, when detecting straight lines from the image captured by the line width measuring device 300, the Hough transform algorithm can be used.

[0082] The Hough transform algorithm converts the equation of a straight line into a parameter space in 2D image coordinates, thereby finding and detecting the straight line.

[0083] Furthermore, when detecting pixels in measurement step S10, the probabilistic Hough transform algorithm can be used.

[0084] The probabilistic Hough transform algorithm can perform the Hough transform on randomly selected pixels to reduce computational load, and set the minimum length to be identified as a line and the spacing between lines as reference values. Furthermore, it can return the two endpoints of the detected lines in coordinate form.

[0085] Furthermore, in measurement step S10, when detecting lines, pixels, and points from the image, a region of interest (ROI) setting method can be used to specify a region in the image in order to reduce computational load.

[0086] Furthermore, in the reference point selection step S11, when identifying the end of the nozzle 160 and setting the reference point RP, if two straight lines of a certain length or more are detected from the region of interest (ROI) using the probabilistic Hough transform algorithm, the center point of the two line endpoints can be selected as the reference point RP.

[0087] After completing measurement step S10, perform correction step S20.

[0088] In the correction step S20, if the control unit 400 compares the line width W of layer L with the preset baseline line width SW and the result exceeds the baseline line width SW, a correction process is performed.

[0089] In other words, when the linewidth W of layer L measured by the linewidth measuring device 300 is greater than or equal to the preset baseline linewidth SW, the control unit 400 controls the feeder 100 to reduce the material extrusion amount of the corresponding area of ​​the layer K above the layer L area where the linewidth W is measured; and when the linewidth W of layer L measured by the linewidth measuring device 300 is less than the baseline linewidth SW, the control unit 400 controls the feeder 100 to increase the material extrusion amount of the corresponding area of ​​the layer L above the layer L area where the linewidth W is measured.

[0090] In the material extrusion 3D printing system 10 based on artificial intelligence (AI) control, the control unit 400 needs to stably control the flow rate of gas supplied from the air supply line 130 to the piston 120.

[0091] Therefore, when the material quantity is stable and the printing platform 200 and the feeder 100 are level, the same thickness can be measured when the line width W of layer L is measured after printing a layer L.

[0092] When the material quantity is stable but the printing platform 200 and the nozzle 160 are not level, if layer L is below the level, a smaller line width W will be measured, while if layer L is above the level, a larger line width W will be measured.

[0093] Whether the printing platform 200 and the nozzle 160 are level is determined by whether the vertical distance (or Z-direction distance) between the end of the nozzle 160 that dispenses material and the upper side of the printing platform 200 is the same.

[0094] For example, if the printing platform 200 is tilted, the feeder 100 moves horizontally in the tilted direction, or the printing platform 200 or the feeder 100 moves up or down due to an unexpected external force (such as vibration), it can be determined that the horizontal position has not been achieved because the distance between the printing platform 200 and the nozzle 160 is not the same.

[0095] The control unit 400 can measure the line width W of the layer L generated by the extruded material using the line width measuring device 300, thereby determining whether the printing platform 200 and the nozzle 160 are level.

[0096] Next, if a larger linewidth W is measured because layer L is located at a higher position, the problem of horizontal disruption can be corrected by generating layer L with a reduced material extrusion amount in the next layer L. If a smaller linewidth W is measured because layer L is located at a lower position, the problem of horizontal disruption can be corrected by generating layer L with an increased material extrusion amount in the next layer L.

[0097] As described above, the control unit 400 can determine the linewidth W for generating the next layer L by comparing the linewidth W of layer L measured by the linewidth measuring device 300 with the reference linewidth SW, and then adjust the extrusion pressure (or discharge pressure) of the material based on this. The extrusion pressure (or discharge pressure) adjustment of the control unit 400 described above can be automatically completed by utilizing artificial intelligence (AI) learning.

[0098] Specifically, the present invention can use artificial intelligence (AI) based pattern recognition technology to analyze the line width W data of layer L collected by the line width measuring device 400, thereby accurately determining the horizontal state of the printing platform 200 and the nozzle 160.

[0099] The deep learning-based image analysis model can detect the uneven stacking pattern of the printed layer L in real time and predict the possibility of stacking defects.

[0100] In addition, the control unit 400 can use artificial intelligence (AI) algorithms to learn the changes in the thickness of layer L and line width W and calculate the optimal extrusion amount, thereby controlling the feeder 100.

[0101] Reinforcement learning algorithms can learn on their own in various printing environments and can generate high-quality prints while minimizing material usage.

[0102] Therefore, this invention can break away from the existing simple physical control and provide a data-based intelligent overlay correction technology.

[0103] Next, please refer to Figures 4 to 6 The process of correcting the level of layer L by means of the control method of the material extrusion 3D printing system 10 based on artificial intelligence (AI) control of the present invention will be described in detail.

[0104] exist Figures 4 to 6The example illustrates a situation where the horizontal alignment of the print platform 200 and the nozzle 160 is disrupted due to the print platform 200 being configured at an angle.

[0105] like Figure 4 As shown, when the printing platform 200 is tilted and not horizontally aligned, the linewidth W of the layer L generated on the upper side of the printing platform 200 will be unstable due to the difference in distance between the printing platform 200 and the end of the nozzle 160.

[0106] Therefore, as Figure 5 As shown, when layers L are stacked, the measured line width W1 of the uppermost layer L, which is located at a relatively high position, i.e., the left side region of layer L, will be greater than the baseline line width SW.

[0107] Furthermore, the measured line width W2, located at a relatively low position, i.e., the right side region of layer L, will be smaller than the baseline line width SW.

[0108] like Figure 6 As shown, in order to correct the measured linewidth of layer L, the control unit 400 increases the material extrusion amount in the layer above the linewidth W1 (i.e., the left side region of the fourth layer L). This causes the linewidth W3 in the layer above the linewidth W1 (i.e., the left side region of the fourth layer L) to be smaller than the reference linewidth SW, thereby correcting the material extrusion amount.

[0109] Furthermore, the material extrusion amount in the upper region of linewidth W2 (i.e., the right region of the fourth layer L) will be reduced. As a result, the linewidth W4 of the layer above linewidth W2 (i.e., the right region of the fourth layer L) will be greater than the baseline linewidth SW, thereby allowing for correction of the material extrusion amount.

[0110] As described above, the control unit 400 can use the line width measuring device 300 to measure the line width W of layer L, thereby identifying materials with more foundations in areas where the line width W is less than the reference line width SW, and materials with fewer foundations in areas where the line width W is greater than the reference line width SW, thus correcting the situation where the horizontality is disrupted.

[0111] The control unit 400 can adjust the amount of air supplied through the air supply line 130 by controlling the control valve 140, thereby adjusting the discharge pressure from the nozzle 160 and thus adjusting the amount of material extruded.

[0112] Furthermore, the control unit 400 can adjust the amount of material protruding from the nozzle 160 by increasing or decreasing the temperature of the heat generated in the heater 190, thereby adjusting the extrusion amount of the material.

[0113] As described above, correction step S20 will be completed when the horizontal correction of layer L is completed.

[0114] The artificial intelligence (AI)-based material extrusion 3D printing system and its control method of the present invention, as described above, can achieve the following effects.

[0115] Even if the printing platform 200 and the feeder 100 are not level, the control unit 400 corrects it by adjusting the amount of material ejected from the feeder 100 while stacking the layers L. This makes it easy to correct unevenness in the level of the stacked layers L and prevents defects in the printed matter.

[0116] In this invention, unlike existing 3D printing systems that adjust the level by correcting the tilt of the printing platform, the material extrusion amount is adjusted. This allows for the correction of uneven material extrusion caused by the disruption of the level, even when the printing platform 200 is not tilted and the feeder 100 moves up and down, resulting in the disruption of the level in only a portion of layer L.

[0117] By using the two contact points CP between the imaginary circle VC and the line width W, the length of the line width W can be easily calculated using the number of pixels and the distance between each pixel.

[0118] The present invention has been described with reference to the embodiments illustrated in the accompanying drawings, but these are merely exemplary. Those skilled in the art should understand that various modifications and other embodiments can be implemented based on this. Therefore, the true scope of protection of the present invention should be determined according to the spirit of the appended claims.

Claims

1. A material extrusion 3D printing system based on artificial intelligence (AI) control, comprising: The feeder forces the material into the nozzle; A printing platform, configured below the nozzle, allows material layers extruded from the nozzle to be stacked into multiple layers; A linewidth measuring device for measuring the linewidth of layers stacked on the printing platform; and, The control unit controls the feeder to reduce the material extrusion amount in the corresponding area of ​​the layer above the layer area whose linewidth is measured when the linewidth of the layer measured by the linewidth measuring device is greater than or equal to a preset reference linewidth. Conversely, if the linewidth of the layer measured by the linewidth measuring device is less than the reference linewidth, the control unit controls the feeder to increase the material extrusion amount in the corresponding area of ​​the layer above the layer area whose linewidth is measured.

2. The material extrusion 3D printing system based on artificial intelligence (AI) control according to claim 1, After generating an imaginary circle with the center of the nozzle orifice as the center point, the control unit measures the number of pixels between two contact points where the imaginary circle intersects with the linewidth of the layer extruded from the nozzle, and calculates the linewidth of the layer by calculating the distance value of each pixel preset in the control unit and the number of pixels.

3. A control method for a material extrusion 3D printing system based on artificial intelligence (AI) control, comprising: The measurement step involves measuring the line width of the layers stacked on the printing platform using a line width measuring device. as well as, The correction step involves the following steps: if the linewidth of the layer measured by the linewidth measuring device is above the preset baseline linewidth, the control unit controls the feeder to reduce the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area; conversely, if the linewidth of the layer measured by the linewidth measuring device is below the baseline linewidth, the control unit controls the feeder to increase the material extrusion amount in the corresponding area of ​​the layer above the measured linewidth layer area.

4. The control method for the material extrusion 3D printing system based on artificial intelligence (AI) control according to claim 3. The measurement steps include: The reference point selection step involves selecting the center of the nozzle orifice of the feeder's nozzle as the reference point. The imaginary circle generation step involves using the reference point as the center point to generate an imaginary circle. The contact point selection step involves selecting two contact points where the imaginary circle intersects with the linewidth of the layer extruded from the nozzle; and... The calculation step involves measuring the number of pixels between the two contact points and calculating the linewidth of the layer by substituting the measured number of pixels into the distance value of each pixel preset in the control unit.

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