Intelligent grafting printing system and method based on selective laser melting equipment

Abstract

The application discloses an intelligent grafting printing system and method based on a laser selective melting device. The intelligent grafting printing method based on the laser selective melting device comprises the following steps: installing and fixing a grafting base on a printing substrate; starting the laser selective melting device, taking the grafting base plane as a reference surface, and adjusting to a printing focal plane; turning on a light source device and an industrial camera, and the industrial camera collects images at a laser printing area; an image processing device processes the images collected by the industrial camera by using a deep learning algorithm, calculates coordinates and angles of the grafting base; the laser selective melting device converts the coordinates and angles of the grafting base calculated by the image processing device into coordinates and angles of a grafting part, and performs printing processing according to the coordinates and angles of the grafting part. The application not only improves the accuracy of part positioning, thereby improving the accuracy of processing, but also greatly reduces the time required for part positioning, and improves the processing efficiency.

Description

Technical Field

[0001] This invention relates to the field of metal additive manufacturing technology, and in particular to an intelligent grafting printing system and method based on laser selective melting equipment. Background Technology

[0002] Metal mold grafting printing is a process that transcends traditional mold manufacturing. It uses additive manufacturing technology to create metal molds and then grafts them onto forming equipment to create more complex metal molds. The advantage of this technology lies in its ability to produce more complex shapes, and it has been widely used in the automotive, motorcycle, electronics, machinery, new energy, and medical fields, particularly in the production of automotive parts and mold manufacturing. With the continuous development of this technology, it will be applied to an even wider range of manufacturing sectors.

[0003] Accurate positioning is the biggest technical challenge in additive manufacturing. The working area of ​​the additive manufacturing process must be perfectly aligned with the substrate; otherwise, misalignment will occur. Generally, a misalignment tolerance of less than 0.1mm is considered an effective grafting. Traditional mold grafting relies on visual positioning, which is slow and prone to errors. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an intelligent grafting printing system and method based on laser selective melting equipment, which can improve the accuracy and efficiency of part positioning.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A smart grafting printing system based on a laser selective melting (SLM) device includes a SLM device, a light source device, an industrial camera, and an image processing device. The SLM device has a laser printing area with a printing substrate, on which a grafting base is fixedly mounted. The light source device is installed on both sides of the SLM device to provide light to the laser printing area. The industrial camera is installed on the top of the SLM device to capture images of the laser printing area. The image processing device uses deep learning algorithms to process the images captured by the industrial camera and calculate the coordinates and angles of the grafting base. The SLM device converts the coordinates and angles of the grafting base calculated by the image processing device into the coordinates and angles of the grafted part, and performs printing processing based on the coordinates and angles of the grafted part.

[0007] A smart grafting printing method based on a laser selective melting (SDM) device is disclosed, which is applied to the aforementioned smart grafting printing system based on a laser selective melting device. The smart grafting printing method based on a laser selective melting device includes the following steps: mounting and fixing the grafting base onto the printing substrate; starting the laser selective melting device and adjusting it to the printing focal plane with the plane of the grafting base as the reference plane; turning on the light source device and the industrial camera, with the industrial camera acquiring images of the laser printing area; the image processing device using a deep learning algorithm to process the images acquired by the industrial camera and calculate the coordinates and angles of the grafting base; the laser selective melting device converting the coordinates and angles of the grafting base calculated by the image processing device into the coordinates and angles of the grafted part, and performing printing processing according to the coordinates and angles of the grafted part.

[0008] The beneficial technical effects of this invention are as follows: This invention uses an industrial camera to capture images of the laser printing area containing the grafting base, and then transmits the captured images to an image processing device for rapid and accurate analysis and calculation to obtain the printing position of the part. Compared with the existing technology of human eye positioning judgment, this invention not only improves the accuracy of part positioning, thereby improving the accuracy of processing, but also greatly reduces the time required for part positioning and improves processing efficiency. Attached Figure Description

[0009] Figure 1 A flowchart illustrating an intelligent grafting printing method based on a laser selective melting device, provided as an embodiment of the present invention;

[0010] Figure 2 This is a schematic diagram of a sub-process of an intelligent grafting printing method based on a laser selective melting device, provided in an embodiment of the present invention. Detailed Implementation

[0011] To enable those skilled in the art to more clearly understand the purpose, technical solution, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0012] This invention provides an intelligent grafting printing system based on a laser selective melting (SLM) device, comprising a laser selective melting device, a light source, an industrial camera, and an image processing device. The laser selective melting device has a laser printing area, on which a printing substrate is mounted. A grafting base is fixedly installed on the printing substrate to ensure stable installation without shaking. The industrial camera is mounted on top of the laser selective melting device to capture images of the laser printing area, ensuring the camera's field of view encompasses the entire laser printing area. Adjusting the camera's aperture and focal length ensures image clarity. The light source is mounted on both sides of the galvanometer of the laser selective melting device to provide light to the laser printing area, ensuring uniform image brightness. The image processing device is communicatively connected to both the industrial camera and the laser selective melting device.

[0013] When performing grafting printing, first start the laser selective melting equipment, using the grafting base plane as the reference plane, and adjust it to the printing focal plane; then turn on the light source device and industrial camera, and the industrial camera captures an image of the laser printing area including the grafting base; the image processing device uses deep learning algorithms to process the image captured by the industrial camera and calculate the coordinates and angles of the grafting base; the laser selective melting equipment converts the coordinates and angles of the grafting base calculated by the image processing device into the coordinates and angles of the grafted part, and finally performs printing processing based on the coordinates and angles of the grafted part.

[0014] The intelligent grafting printing system based on laser selective melting equipment of the present invention uses an industrial camera to acquire images of the laser printing area containing the grafting base, and then transmits the acquired images to an image processing device for rapid and accurate analysis and calculation to obtain the printing position of the part. Compared with the existing technology of human eye positioning judgment, it not only improves the accuracy of part positioning, thereby improving the accuracy of processing, but also greatly reduces the time required for part positioning and improves processing efficiency.

[0015] Based on the above-mentioned intelligent grafting printing system based on laser selective melting equipment, the present invention provides an intelligent grafting printing method based on laser selective melting equipment.

[0016] like Figure 1 As shown, in one embodiment of the present invention, the intelligent grafting printing method based on a laser selective melting device includes the following steps:

[0017] S10. Install and fix the grafting base onto the printing substrate;

[0018] S20. Start the laser selective melting equipment and adjust it to the printing focal plane, using the base plane as the reference plane.

[0019] S30. Turn on the light source device and industrial camera. The industrial camera acquires an image of the laser-printed area, including the grafting base.

[0020] S40. The image processing device uses deep learning algorithms to process the images captured by the industrial camera and calculates the coordinates and angles of the grafting base.

[0021] The S50 laser selective melting equipment converts the coordinates and angles of the grafting base calculated by the image processing device into the coordinates and angles of the grafting parts. Based on the coordinates and angles of the grafting parts, it performs printing processing, ultimately achieving intelligent grafting printing.

[0022] like Figure 2 As shown, step S40 further includes the following steps:

[0023] S41. Take the lower left corner of the image as the origin of the coordinate system;

[0024] S42. Use deep learning edge detection algorithms to extract the grafting base contour in the image;

[0025] S43. Obtain the coordinates (x, y) of all points in the grafting base outline. c y c );

[0026] S44, Obtain x c minimum value x cmin y c The minimum value of y cmin x c The maximum value x cmax ,y c The maximum value of y cmax ;

[0027] S45. Calculate the center coordinates (X,Y) of the grafting base outline. These center coordinates (X,Y) are the coordinates of the grafting base, where X = (x... cmin +x cmax ) / 2, Y=(y cmin +y cmax ) / 2;

[0028] S46. Using a deep learning edge detection algorithm, extract the contour of the internal flow channel of the grafting base in the image;

[0029] S47. Obtain the coordinates (x, y) of all points in the internal flow channel contour of the grafting base. r y r );

[0030] S48, Obtain x r minimum value x rmin y r The minimum value of y rmin x r The maximum value x rmax ,y r The maximum value of y rmax ;

[0031] S49. Calculate the center coordinates (x0, y0) of the internal flow channel profile of the grafting base, where x0 = (x rmin +x rmax ) / 2,y0=(y rmin +y rmax ) / 2;

[0032] S410. According to the Bressenham line algorithm, generate a straight line between the center coordinate point (X,Y) and the center coordinate point (x0,y0);

[0033] S411. Calculate the angle θ between the straight line generated in step S410 and the x-axis of the coordinate system. This angle θ is the angle of the grafting base.

[0034] In step S50, the coordinates (X,Y) of the grafting base are multiplied by R to obtain the coordinates (X',Y') of the grafting part, i.e., X'=X*R, Y'=Y*R, where R=printing substrate width / image width; the included angle θ calculated in step S411 is the angle of the grafting part.

[0035] The intelligent grafting printing system based on laser selective melting equipment of the present invention uses an industrial camera to acquire images of the laser printing area containing the grafting base, and then transmits the acquired images to an image processing device for rapid and accurate analysis and calculation to obtain the printing position of the part. Compared with the existing technology of human eye positioning judgment, it not only improves the accuracy of part positioning, thereby improving the accuracy of processing, but also greatly reduces the time required for part positioning and improves processing efficiency.

[0036] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any way. Those skilled in the art can make various equivalent changes and improvements based on the above embodiments, and all equivalent variations or modifications made within the scope of the claims should fall within the protection scope of the present invention.

Claims

1. A method for intelligent grafting printing based on a selective laser melting device, applied to an intelligent grafting printing system based on a selective laser melting device, characterized in that, The intelligent grafting printing system based on the laser selective melting equipment comprises a laser selective melting equipment, a light source device, an industrial camera and an image processing device; the laser selective melting equipment is provided with a laser printing area, the laser printing area is provided with a printing substrate, and the printing substrate is fixedly installed with a grafting base; the light source device is installed on both sides of the laser selective melting equipment and is used for providing light source for the laser printing area; the industrial camera is installed on the top of the laser selective melting equipment and is used for collecting images at the laser printing area; The intelligent grafting printing method based on the laser selective melting equipment comprises the following steps: S10, the grafting base is installed and fixed on the printing substrate; S20, the laser selective melting equipment is started, and the grafting base plane is taken as a reference surface, and the printing focal plane is adjusted; S30, the light source device and the industrial camera are turned on, and the industrial camera collects images at the laser printing area; S40, the image processing device processes the images collected by the industrial camera by using a deep learning algorithm, and calculates the coordinates and angle of the grafting base; S50, the laser selective melting equipment converts the coordinates and angle of the grafting base calculated by the image processing device into the coordinates and angle of the grafting part, and performs printing processing according to the coordinates and angle of the grafting part; The step S40 further comprises the following steps: S41, taking the lower left corner of the image as the origin of the coordinate system; S42, using a deep learning edge detection algorithm to extract the grafting base profile in the image; S43, obtain all point coordinates (x c , y c ) in the contour of the grafting base; S44, obtaining x c the minimum value x of x cmin , y c the minimum value y of y cmin , x c the maximum value x of x cmax , y c the maximum value y of y cmax ; S45, calculate the center coordinate point (X, Y) of the grafting base contour, which is the coordinate of the grafting base, wherein X=(x cmin +x cmax ) / 2, Y =(y cmin +y cmax ) / 2; S46, using a deep learning edge detection algorithm to extract the internal flow channel profile of the grafting base in the image; S47, obtain all point coordinates (x r , y r ) in the internal flow channel profile of the grafting base; r , y r ) in the internal flow channel profile of the grafting base; S48, get x r minimum x of x rmin , y r minimum y of y rmin , x r maximum x of x rmax , y r maximum y of y rmax ; S49, calculate the center coordinate point (x0, y0) of the profile of the flow channel inside the grafting base, wherein x0 = (x rmin +x rmax ) / 2, y0 = (y rmin +y rmax ) / 2; S410, according to the Brezenham straight line algorithm, a straight line is generated from the center coordinate point (X, Y) and the center coordinate point (x0, y0); S411, the included angle θ of the straight line generated in step S410 and the x-axis of the coordinate system is calculated, and the included angle θ is the angle of the grafting base.

2. The method of claim 1, wherein the laser-based selective melting apparatus is a selective laser melting apparatus. In step S50, converting the coordinates and angle of the grafting base into the coordinates and angle of the grafting part further comprises the following steps: The coordinates (X, Y) of the grafting base are multiplied by R to obtain the coordinates (X', Y') of the grafting part, wherein X'=X*R, Y'=Y*R, and R=printing substrate width / image width; The included angle θ calculated in step S411 is taken as the angle of the grafting part.

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