Method, device and equipment for adjusting shape of additive manufacturing molten pool in real time and medium

Abstract

The invention belongs to the technical field of molten pool shape adjustment, and discloses a method, device, equipment and medium for adjusting the shape of an additive manufacturing molten pool in real time, and the method comprises the steps: obtaining a molten pool image of the additive manufacturing molten pool and a corresponding molten pool marking image, and constructing a molten pool image segmentation model according to the molten pool image and the corresponding molten pool marking image, periodically acquiring real-time molten pool images of the additive manufacturing molten pool, inputting the real-time molten pool images into the molten pool image segmentation model, extracting to obtain molten pool segmentation images only containing the additive manufacturing molten pool, calculating to obtain real-time molten pool flow velocity through molten pool approximate geometric centers of the molten pool segmentation images of adjacent frames, and adjusting the flow velocity of the molten pool through a laser adjusting formula. With the target molten pool shape as a target, the molten pool shape of the additive manufacturing molten pool is adjusted; the shape of the molten pool is adjusted through the laser adjusting formula, the real-time molten pool flow speed and the target molten pool shape, and the precision and stability of the additive manufacturing molten pool are improved.

Description

Technical Field

[0001] The present application relates to the technical field of adjusting the shape of a molten pool, and in particular to a method, device, equipment and medium for adjusting the shape of an additive manufacturing molten pool in real time. Background Art

[0002] With the rapid development of additive manufacturing technology, the shape of the additive manufacturing melt pool has become an important factor affecting the quality of the finished product and process stability. However, traditional control methods often cannot adapt to changes in process parameters in real time, resulting in an unsatisfactory shape of the melt pool (additive manufacturing melt pool), which in turn affects the performance and quality of the product.

[0003] At present, the traditional molten pool adjustment method mainly relies on experimental observation and analysis to obtain the width, height, area and flow rate of the molten pool, and then determine the shape of the molten pool according to the width, height, area and flow rate of the molten pool. However, this method is not only time-consuming and labor-intensive, but also has certain subjectivity and limitations.

[0004] Therefore, in order to solve the technical problems that the existing molten pool adjustment method is time-consuming and labor-intensive and has certain subjectivity and limitations, a method, device, equipment and medium for real-time adjustment of the shape of the additive manufacturing molten pool is urgently needed. Summary of the invention

[0005] The purpose of the present application is to provide a method, device, equipment and medium for real-time adjustment of the shape of the additive manufacturing molten pool. Through a preset laser adjustment formula, the shape of the molten pool is adjusted in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation image of adjacent frames and a preset flow rate calculation formula, so as to solve the problems that the existing molten pool adjustment methods are time-consuming and labor-intensive and have certain subjectivity and limitations. The method can monitor the additive manufacturing molten pool in real time and accurately and adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0006] In a first aspect, the present application provides a method for adjusting the shape of an additive manufacturing molten pool in real time, comprising: Obtain a melt pool image of an additive manufacturing melt pool and a corresponding melt pool annotation image; A melt pool image segmentation model is constructed according to the melt pool image and the corresponding melt pool annotated image; Periodically acquiring a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into the molten pool image segmentation model to extract a molten pool segmentation image that only includes the additive manufacturing molten pool; Determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculate the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula; Utilizing a preset laser adjustment formula, according to the real-time molten pool flow rate, combined with a preset PID controller, and taking a preset target molten pool shape as a target, the laser information for preparing the additive manufacturing molten pool is adjusted in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time.

[0007] The method for real-time adjustment of the shape of the additive manufacturing molten pool provided in the present application can realize the adjustment of the shape of the additive manufacturing molten pool. Through a preset laser adjustment formula, the shape of the molten pool is adjusted in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation image of adjacent frames and a preset flow rate calculation formula, thereby solving the problems of the existing molten pool adjustment methods being time-consuming, labor-intensive, and having certain subjectivity and limitations. The method can monitor the additive manufacturing molten pool in real time and accurately adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0008] Optionally, obtaining a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotated image includes: photographing the additive manufacturing molten pool to obtain an image of the molten pool; The contour position of the additive manufacturing molten pool is marked in the molten pool image to obtain the molten pool marked image.

[0009] Optionally, a melt pool image segmentation model is constructed according to the melt pool image and the corresponding melt pool annotated image, including: Construct a YOLOv8 model corresponding to the molten pool image to obtain a preliminary molten pool image segmentation model; According to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image, the preliminary melt pool image segmentation model is trained to obtain a trained preliminary melt pool image segmentation model; Based on the melt pool images that are not used for training and the corresponding melt pool annotated images in the melt pool images, the trained preliminary melt pool image segmentation model is verified to obtain the melt pool image segmentation model.

[0010] The method for real-time adjustment of the shape of the additive manufacturing molten pool provided in the present application can realize the adjustment of the shape of the additive manufacturing molten pool. Through the molten pool image and the corresponding molten pool annotated image, a YOLOv8 model is constructed and trained to obtain a molten pool image segmentation model, which can quickly identify the molten pool position of the additive manufacturing molten pool and extract image features outside the molten pool position to obtain an image containing only the molten pool, which is beneficial to improving the adjustment efficiency of the additive manufacturing molten pool.

[0011] Optionally, training the preliminary melt pool image segmentation model according to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image to obtain the trained preliminary melt pool image segmentation model includes: Inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain a corresponding image output; the image output is an image containing only the additive manufacturing molten pool; determining a training error according to a melt pool annotated image corresponding to the melt pool image used for training in the melt pool image and the corresponding image output; Based on the training error, the parameters of the preliminary melt pool image segmentation model are adjusted to obtain the optimal parameters, and the preliminary melt pool image segmentation model is optimized using the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

[0012] Optionally, before inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain the corresponding image output, the method further includes: Initialize the parameters of the preliminary melt pool image segmentation model.

[0013] Optionally, determining the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculating the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula, includes the steps of cyclic execution: Determining an approximate geometric center of the molten pool corresponding to the molten pool segmentation image according to a minimum circumscribed rectangle of the additive manufacturing molten pool corresponding to the molten pool segmentation image; After acquiring the first frame of the molten pool segmentation image, each time the molten pool segmentation image is acquired, the real-time molten pool flow rate of the additive manufacturing molten pool is calculated by using the preset flow rate calculation formula, combining the approximate geometric center of the molten pool of the molten pool segmentation image acquired this time with the approximate geometric center of the molten pool of the molten pool segmentation image acquired last time.

[0014] The method for real-time adjustment of the shape of the additive manufacturing molten pool provided in the present application can realize the adjustment of the shape of the additive manufacturing molten pool. Through a preset flow rate calculation formula, the real-time molten pool flow rate of the additive manufacturing molten pool is calculated by using the approximate geometric center of the molten pool of the molten pool segmentation image obtained this time and the approximate geometric center of the molten pool of the molten pool segmentation image obtained last time. The molten pool shape of the additive manufacturing molten pool can be adjusted through the real-time molten pool flow rate, which is beneficial to improving the adjustment efficiency of the additive manufacturing molten pool.

[0015] Optionally, the preset laser adjustment formula includes a preset laser power adjustment formula, a preset laser powder feed rate adjustment formula, a preset laser radius adjustment formula and a preset laser scanning speed adjustment formula.

[0016] In a second aspect, the present application provides a device for adjusting the shape of an additive manufacturing molten pool in real time, comprising: An acquisition module, used to acquire a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotated image; A construction module, used to construct a melt pool image segmentation model according to the melt pool image and the corresponding melt pool annotated image; An extraction module, used for periodically acquiring a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into the molten pool image segmentation model to extract a molten pool segmentation image containing only the additive manufacturing molten pool; a calculation module, used to determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculate the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula; The adjustment module is used to use a preset laser adjustment formula, according to the real-time molten pool flow rate, in combination with a preset PID controller, with a preset target molten pool shape as the target, to adjust the laser information for preparing the additive manufacturing molten pool in real time, so as to adjust the molten pool shape of the additive manufacturing molten pool in real time.

[0017] The device for real-time adjustment of the shape of the additive manufacturing molten pool adjusts the shape of the molten pool in real time through a preset laser adjustment formula according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation images of adjacent frames and a preset flow rate calculation formula, thereby solving the problems that the existing molten pool adjustment methods are time-consuming and labor-intensive and have certain subjectivity and limitations. The device can monitor the additive manufacturing molten pool in real time and accurately adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0018] In a third aspect, the present application provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the method for real-time adjustment of the shape of the additive manufacturing molten pool as described above.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, runs the steps of the method for real-time adjustment of the shape of the additive manufacturing molten pool as described above.

[0020] Beneficial effects: The method, device, equipment and medium for real-time adjustment of the shape of the additive manufacturing molten pool provided in the present application, through a preset laser adjustment formula, adjusts the shape of the molten pool in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation image of adjacent frames and a preset flow rate calculation formula, thereby solving the problems of the existing molten pool adjustment methods being time-consuming and labor-intensive and having certain subjectivity and limitations, and being able to monitor the additive manufacturing molten pool in real time and accurately adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flow chart of a method for real-time adjustment of the shape of an additive manufacturing molten pool provided in an embodiment of the present application.

[0022] Figure 2 A schematic diagram of the structure of a device for real-time adjustment of the shape of an additive manufacturing molten pool provided in an embodiment of the present application.

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0024] Explanation of reference numerals: 1. Acquisition module; 2. Construction module; 3. Extraction module; 4. Calculation module; 5. Adjustment module; 301. Processor; 302. Memory; 303. Communication bus. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] Please refer to Figure 1 , Figure 1A method for adjusting the shape of an additive manufacturing molten pool in real time in some embodiments of the present application is used to adjust the shape of an additive manufacturing molten pool, comprising the steps of: Step S101, obtaining a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotated image; Step S102, constructing a melt pool image segmentation model according to the melt pool image and the corresponding melt pool annotated image; Step S103, periodically acquiring a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into a molten pool image segmentation model to extract a molten pool segmentation image that only includes the additive manufacturing molten pool; Step S104, determining the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculating the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation images of adjacent frames in combination with a preset flow rate calculation formula; Step S105, using a preset laser adjustment formula, according to the real-time molten pool flow rate, combined with a preset PID controller, with a preset target molten pool shape as the target, the laser information for preparing the additive manufacturing molten pool is adjusted in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time.

[0028] The method for real-time adjustment of the shape of the additive manufacturing molten pool, through a preset laser adjustment formula, adjusts the shape of the molten pool in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation images of adjacent frames and a preset flow rate calculation formula, thereby solving the problems that the existing molten pool adjustment methods are time-consuming and labor-intensive and have certain subjectivity and limitations. The method can monitor the additive manufacturing molten pool in real time and accurately adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0029] Specifically, in step S101, a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotated image are obtained, including: Photographing the additive manufacturing molten pool to obtain a molten pool image; The contour position of the additive manufacturing molten pool is marked from the molten pool image to obtain a molten pool marked image.

[0030] In step S101, an additive manufacturing molten pool is prepared in advance by laser technology, and then an existing shooting technology (such as a camera or a video camera) is used to shoot the additive manufacturing molten pool from multiple angles with the additive manufacturing molten pool as the center to obtain a molten pool image of the additive manufacturing molten pool. The contour position of the additive manufacturing molten pool is marked in the molten pool image by a manual marking method or a mechanical marking method (such as using labelme software) to obtain a molten pool marked image; thereby, a large number of molten pool images and molten pool marked images are obtained for training the model, so that the trained model can identify the molten pool position to extract the molten pool features.

[0031] Specifically, in step S102, a melt pool image segmentation model is constructed based on the melt pool image and the corresponding melt pool annotated image, including: Build the YOLOv8 model corresponding to the melt pool image and obtain the preliminary melt pool image segmentation model; According to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image, a preliminary melt pool image segmentation model is trained to obtain a trained preliminary melt pool image segmentation model; Based on the melt pool images that are not used for training and the corresponding melt pool annotated images in the melt pool images, the trained preliminary melt pool image segmentation model is verified to obtain the melt pool image segmentation model.

[0032] In step S102, a YOLOv8 model is constructed using the melt pool image to obtain a preliminary melt pool image segmentation model. By inputting the melt pool image into the preliminary melt pool image segmentation model, irrelevant features such as the background or additive manufacturing equipment in the melt pool image can be eliminated (i.e., the location of the additive manufacturing melt pool is segmented from the melt pool image), and the additive manufacturing melt pool is used as the target feature for extraction to obtain an image containing only the additive manufacturing melt pool. The YOLOv8 model is a prior art and will not be described in detail herein.

[0033] Specifically, in step S102, a preliminary melt pool image segmentation model is trained according to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image to obtain a trained preliminary melt pool image segmentation model, including: Inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain a corresponding image output; the image output is an image containing only the additive manufacturing molten pool; determining a training error according to a melt pool annotation image corresponding to the melt pool image used for training in the melt pool image and a corresponding image output; Based on the training error, the parameters of the preliminary melt pool image segmentation model are adjusted to obtain the optimal parameters, and the preliminary melt pool image segmentation model is optimized using the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

[0034] In step S102, the melt pool annotated image corresponding to the melt pool image used for training is compared with the image output obtained by inputting the melt pool image into the preliminary melt pool image segmentation model to obtain a training error, such as the size deviation degree between the melt pool contour area marked in the melt pool annotated image and the corresponding melt pool in the image output (for example, the size of the melt pool corresponding to the image output is inconsistent with the melt pool contour area marked in the melt pool annotated image), or the deviation degree between the melt pool contour area marked in the melt pool annotated image and the corresponding melt pool in the image output (for example, the melt pool contour area marked in the melt pool annotated image and the melt pool corresponding to the image output are not the same area), etc. The training error is used to adjust the parameters of the preliminary melt pool image segmentation model. If the training error is the size deviation degree between the melt pool contour area marked in the melt pool annotated image and the corresponding melt pool in the image output, the corresponding model parameters are modified to make the corresponding melt pool in the image output more accurate, so as to obtain the optimal parameters. The preliminary melt pool image segmentation model is optimized through the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

[0035] In step S102, the melt pool image that is not used for training in the melt pool image is input into the trained preliminary melt pool image segmentation model to obtain a corresponding image output, and the image output is used as verification data. The verification data and the melt pool annotation image corresponding to the melt pool image that is not used for training are compared to determine whether the error is within an acceptable range (the acceptable error range is generally 0 to 3%, which can be modified according to actual needs), verify the accuracy of the trained preliminary melt pool image segmentation model, and obtain the melt pool image segmentation model.

[0036] Specifically, in step S102, before the molten pool image used for training in the molten pool image is input into the preliminary molten pool image segmentation model to obtain the corresponding image output, the method further includes: Initialize the parameters of the preliminary melt pool image segmentation model.

[0037] In step S102, before inputting data to train the model, the parameters of the preliminary melt pool image segmentation model are initialized to ensure that the model is in normal use.

[0038] Specifically, in step S103, the additive manufacturing molten pool is photographed at a fixed position directly above the additive manufacturing molten pool at a preset shooting time interval as a period, and a real-time molten pool image of the additive manufacturing molten pool is periodically obtained, and the real-time molten pool image is input into the molten pool image segmentation model, and after calculation by the molten pool image segmentation model, a molten pool segmentation image containing only the additive manufacturing molten pool is extracted. Among them, the preset shooting time can be set according to actual needs.

[0039] Specifically, in step S104, the approximate geometric center of the molten pool corresponding to the molten pool segmentation image is determined, and the real-time molten pool flow rate of the additive manufacturing molten pool is calculated based on the approximate geometric center of the molten pool segmentation image of the adjacent frames and the preset flow rate calculation formula, including the steps of cyclic execution: Determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image according to the minimum circumscribed rectangle of the additive manufacturing molten pool corresponding to the molten pool segmentation image; After acquiring the first frame of the melt pool segmentation image, each time the melt pool segmentation image is acquired, the real-time melt pool flow rate of the additive manufacturing melt pool is calculated by using a preset flow rate calculation formula, combining the approximate geometric center of the melt pool of the melt pool segmentation image acquired this time with the approximate geometric center of the melt pool of the last acquired melt pool segmentation image.

[0040] In step S104, each time the melt pool segmentation image is obtained (except for the first time the melt pool segmentation image is obtained), a minimum circumscribed rectangle is made with the additive manufacturing melt pool in the melt pool segmentation image as the center, the height and width of the minimum circumscribed rectangle are obtained, the height and width of the minimum circumscribed rectangle are determined as the height and width of the additive manufacturing melt pool, the midpoint of the minimum circumscribed rectangle is determined as the approximate center point of the additive manufacturing melt pool, and the approximate geometric center of the melt pool corresponding to the melt pool segmentation image is obtained.

[0041] After each determination of the approximate geometric center of the melt pool (except for determining the approximate geometric center of the melt pool of the first frame of the melt pool segmentation image), the preset flow rate calculation formula is used to calculate the real-time melt pool flow rate of the additive manufacturing melt pool based on the coordinate value of the approximate geometric center of the melt pool of the melt pool segmentation image acquired this time and the coordinate value of the approximate geometric center of the melt pool of the melt pool segmentation image acquired last time.

[0042] Among them, the preset flow rate calculation formula is specifically: ; in, is the real-time molten pool flow rate; is the horizontal coordinate of the approximate geometric center of the molten pool at time t (current time); is the horizontal coordinate of the approximate geometric center of the molten pool at time t-1 (the previous moment); is the ordinate of the approximate geometric center of the molten pool at time t; is the ordinate of the approximate geometric center of the molten pool at time t-1; The time interval between two frames of melt pool segmentation images, the unit is set to milliseconds; is the interference coefficient, Used to indicate the influence of external temperature, airflow and pressure on the flow rate of the molten pool; is the adjustment coefficient of the molten pool width and height on the molten pool flow rate; and are the width and height of the molten pool at time t (mm); and are the width and height of the molten pool at time t-1 (mm); is the environmental noise impact at time t. Among them, the interference coefficient , adjustment coefficient 、Ambient noise impact It can be set according to actual needs.

[0043] Specifically, in step 105, the preset laser adjustment formula includes a preset laser power adjustment formula, a preset laser powder feed rate adjustment formula, a preset laser radius adjustment formula and a preset laser scanning speed adjustment formula; using the preset laser adjustment formula, according to the real-time molten pool flow rate, combined with the preset PID controller, with the preset target molten pool shape as the target, the real-time adjusted laser data is calculated, that is, the real-time adjusted laser power, laser powder feed rate, laser radius and laser scanning speed are calculated. Among them, the preset target molten pool shape includes a target molten pool area, a target molten pool height and a target molten pool width; the laser power is adjusted based on the molten pool area, the laser powder feed rate is adjusted based on the molten pool area, the laser radius is adjusted based on the molten pool height, and the laser scanning speed is adjusted based on the molten pool width.

[0044] Among them, the preset laser power adjustment formula is specifically: ; in, is the adjusted laser power (in watts); is the current laser power; , , They are respectively the laser power adjustment proportional coefficient, the laser power adjustment integral coefficient and the laser power adjustment differential coefficient of the PID controller, which are used to adjust the laser power by feedback according to the real-time molten pool area; is the target molten pool area (in square millimeters); is the current molten pool area (segment the additive manufacturing molten pool in the molten pool segmentation image by pixels, such as segmenting the pixels in units of square millimeters, and determine the current molten pool area according to the pixel ratio of the corresponding pixels of the additive manufacturing molten pool in the corresponding minimum circumscribed rectangle. This calculation process can be set in the molten pool image segmentation model, so that the molten pool image segmentation model automatically outputs the height, width and area of ​​the additive manufacturing molten pool when extracting the molten pool segmentation image, that is, the height of the current molten pool, the width of the current molten pool and the current molten pool area); Indicates the adjustment coefficient of the current molten pool area and height to the laser power; Indicates the adjustment coefficient of the current molten pool flow rate and width to the laser power; is the width of the current molten pool (in millimeters); is the current height of the molten pool (in millimeters); is the current melt pool flow rate (i.e. the real-time melt pool flow rate, in mm / s); is the current melt pool temperature (in degrees Celsius); is the adjustment coefficient of the current molten pool temperature; is the adjustment coefficient of the current molten pool area; It is the exponential coefficient for adjusting the influence of the current molten pool flow rate on the power. Among them, the laser power adjustment proportional coefficient , Laser power adjustment integral coefficient , Laser power adjustment differential coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0045] The preset laser powder feeding rate adjustment formula is as follows: ; in, is the adjusted laser powder feeding rate (in grams per minute); is the current laser powder feeding rate (g / min); , , They are the proportional, integral and differential coefficients of the PID controller, which are used to provide feedback based on the real-time molten pool area to adjust the laser powder feed rate; Indicates the adjustment coefficient of the current molten pool area and width to the laser powder feeding rate; Indicates the adjustment coefficient of the current molten pool height and flow rate on the laser powder feeding rate; among them, the laser powder feeding rate adjustment proportional coefficient , Laser powder feeding rate adjustment integral coefficient , Laser powder feeding rate adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0046] The specific formula for adjusting the laser radius is: ; in, is the adjusted laser radius (in millimeters); is the current laser radius; is the target molten pool height; is the current height of the molten pool; , , They are respectively the laser radius adjustment proportional coefficient, the laser radius adjustment integral coefficient and the laser radius adjustment differential coefficient of the PID controller, which are used to adjust the laser radius by providing feedback according to the real-time molten pool height; Indicates the adjustment coefficient of the current molten pool width and area to the laser radius; Indicates the adjustment coefficient of the current molten pool height and flow rate to the laser radius; among them, the laser radius adjustment proportional coefficient , Laser radius adjustment integral coefficient , Laser radius adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0047] The specific formula for adjusting the laser scanning speed is: ; in, is the adjusted laser scanning speed (in mm / s); is the current laser scanning speed; is the target molten pool width; is the width of the current molten pool; , , They are respectively a laser scanning speed adjustment proportional coefficient, a laser scanning speed adjustment integral coefficient and a laser scanning speed adjustment differential coefficient of a PID controller, and are used to provide feedback according to the real-time molten pool width to adjust the laser scanning speed; Indicates the adjustment coefficient of the current molten pool height and area to the laser radius; Indicates the adjustment coefficient of the current molten pool flow rate and width to the laser radius; among them, the laser scanning speed adjustment proportional coefficient , Laser scanning speed adjustment integral coefficient , Laser scanning speed adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs. In practical applications, the laser scanning speed adjustment coefficient , Laser scanning speed adjustment integral coefficient and laser scanning speed adjustment differential coefficient Both can be set to negative values. When adjusting the laser scanning speed, the control output of the PID controller can be adjusted in reverse through the negative coefficient (i.e., the laser scanning speed is adjusted in reverse) to achieve a negative correlation between the laser scanning speed and the molten pool size. Therefore, according to the laser scanning speed adjustment formula, the molten pool width can be controlled by adjusting the laser scanning speed.

[0048] In summary, the real-time adjusted laser power, laser powder feeding rate, laser radius and laser scanning speed are calculated, and the laser information is adjusted using the real-time adjusted laser power, laser powder feeding rate, laser radius and laser scanning speed to adjust the molten pool shape of the additive manufacturing molten pool.

[0049] In some embodiments, the preset flow rate calculation formula can be set in the molten pool image segmentation model through existing technology to obtain a molten pool flow rate calculation model (when constructing a numerical calculation model of molten pool stability, the molten pool flow rate calculated by the flow rate calculation formula needs to be obtained as training data and verification data). The molten pool flow rate calculation model has the ability to calculate the molten pool flow rate, and can calculate the real-time molten pool flow rate of the additive manufacturing molten pool based on the approximate geometric center of the molten pool of two frames of real-time molten pool images obtained periodically. Then, through the PID controller, the molten pool shape of the additive manufacturing molten pool is adjusted in real time using the preset laser power adjustment formula and the preset laser powder feed rate adjustment formula.

[0050] As can be seen from the above, the method for real-time adjustment of the shape of the additive manufacturing molten pool obtains a molten pool image and a corresponding molten pool annotated image of the additive manufacturing molten pool, constructs a molten pool image segmentation model according to the molten pool image and the corresponding molten pool annotated image, periodically obtains a real-time molten pool image of the additive manufacturing molten pool, and inputs the real-time molten pool image into the molten pool image segmentation model, extracts a molten pool segmentation image containing only the additive manufacturing molten pool, determines the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculates the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of the adjacent frames in combination with a preset flow rate calculation formula, and uses a preset laser adjustment formula According to the real-time molten pool flow rate, combined with a preset PID controller, with the preset target molten pool shape as the target, the laser information for preparing the additive manufacturing molten pool is adjusted in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time; thereby, through a preset laser adjustment formula, the molten pool shape is adjusted in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation image of adjacent frames and a preset flow rate calculation formula, thereby solving the problems of the existing molten pool adjustment method being time-consuming, labor-intensive, and having certain subjectivity and limitations, and being able to monitor the additive manufacturing molten pool in real time and accurately and adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0051] refer to Figure 2 The present application provides a device for adjusting the shape of an additive manufacturing molten pool in real time, which is used to adjust the shape of an additive manufacturing molten pool, including: An acquisition module 1 is used to acquire a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotation image; Construction module 2, used to construct a melt pool image segmentation model according to the melt pool image and the corresponding melt pool annotated image; An extraction module 3 is used to periodically obtain a real-time molten pool image of the additive manufacturing molten pool, and input the real-time molten pool image into a molten pool image segmentation model to extract a molten pool segmentation image that only contains the additive manufacturing molten pool; The calculation module 4 is used to determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculate the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of the adjacent frames in combination with a preset flow rate calculation formula; The adjustment module 5 is used to use a preset laser adjustment formula, according to the real-time molten pool flow rate, combined with a preset PID controller, with a preset target molten pool shape as the target, to adjust the laser information for preparing the additive manufacturing molten pool in real time, so as to adjust the molten pool shape of the additive manufacturing molten pool in real time.

[0052] The device for real-time adjustment of the shape of the additive manufacturing molten pool adjusts the shape of the molten pool in real time through a preset laser adjustment formula according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation images of adjacent frames and a preset flow rate calculation formula, thereby solving the problems that the existing molten pool adjustment methods are time-consuming and labor-intensive and have certain subjectivity and limitations. The device can monitor the additive manufacturing molten pool in real time and accurately adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0053] Specifically, when acquiring the molten pool image of the additive manufacturing molten pool and the corresponding molten pool annotated image, the acquisition module 1 executes: Photographing the additive manufacturing molten pool to obtain a molten pool image; The contour position of the additive manufacturing molten pool is marked from the molten pool image to obtain a molten pool marked image.

[0054] When the acquisition module 1 is executed, the additive manufacturing molten pool is prepared in advance by laser technology, and then the existing shooting technology (such as a camera or a video camera) is used to shoot the additive manufacturing molten pool from multiple angles with the additive manufacturing molten pool as the center to obtain a molten pool image of the additive manufacturing molten pool, and the contour position of the additive manufacturing molten pool is marked in the molten pool image by a manual marking method or a mechanical marking method (such as using labelme software) to obtain a molten pool marked image; thereby, a large number of molten pool images and molten pool marked images are obtained for training the model, so that the trained model can identify the molten pool position to extract the molten pool features.

[0055] Specifically, when constructing the melt pool image segmentation model according to the melt pool image and the corresponding melt pool annotated image, the construction module 2 executes: Build the YOLOv8 model corresponding to the melt pool image and obtain the preliminary melt pool image segmentation model; According to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image, a preliminary melt pool image segmentation model is trained to obtain a trained preliminary melt pool image segmentation model; Based on the melt pool images that are not used for training and the corresponding melt pool annotated images in the melt pool images, the trained preliminary melt pool image segmentation model is verified to obtain the melt pool image segmentation model.

[0056] When construction module 2 is executed, the melt pool image is used to construct a YOLOv8 model to obtain a preliminary melt pool image segmentation model. By inputting the melt pool image into the preliminary melt pool image segmentation model, irrelevant features such as the background or additive manufacturing equipment in the melt pool image can be eliminated (i.e., the location of the additive manufacturing melt pool is segmented from the melt pool image), and the additive manufacturing melt pool is used as the target feature for extraction to obtain an image containing only the additive manufacturing melt pool. Among them, the YOLOv8 model is a prior art and will not be described in detail here.

[0057] Specifically, when the construction module 2 trains the preliminary melt pool image segmentation model according to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image to obtain the trained preliminary melt pool image segmentation model, the following is executed: Inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain a corresponding image output; the image output is an image containing only the additive manufacturing molten pool; determining a training error according to a melt pool annotation image corresponding to the melt pool image used for training in the melt pool image and a corresponding image output; Based on the training error, the parameters of the preliminary melt pool image segmentation model are adjusted to obtain the optimal parameters, and the preliminary melt pool image segmentation model is optimized using the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

[0058] When construction module 2 is executed, the melt pool annotation image corresponding to the melt pool image used for training is compared with the image output obtained by inputting the melt pool image into the preliminary melt pool image segmentation model to obtain a training error, such as the size deviation degree between the melt pool contour area marked in the melt pool annotation image and the corresponding melt pool in the image output (for example, the size of the melt pool corresponding to the image output is inconsistent with the melt pool contour area marked in the melt pool annotation image), or the deviation degree between the melt pool contour area marked in the melt pool annotation image and the corresponding melt pool in the image output (for example, the melt pool contour area marked in the melt pool annotation image and the melt pool corresponding to the image output are not the same area), etc. The training error is used to adjust the parameters of the preliminary melt pool image segmentation model. If the training error is the size deviation degree between the melt pool contour area marked in the melt pool annotation image and the corresponding melt pool in the image output, the corresponding model parameters are modified to make the corresponding melt pool in the image output more accurate, and the optimal parameters are obtained. The preliminary melt pool image segmentation model is optimized through the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

[0059] When construction module 2 is executed, the melt pool image that is not used for training in the melt pool image is input into the trained preliminary melt pool image segmentation model to obtain the corresponding image output, and the image output is used as verification data. The verification data and the melt pool annotated image corresponding to the melt pool image that is not used for training are compared to determine whether the error is within an acceptable range (the acceptable error range is generally 0 to 3%, which can be modified according to actual needs), verify the accuracy of the trained preliminary melt pool image segmentation model, and obtain the melt pool image segmentation model.

[0060] Specifically, before inputting the melt pool image used for training in the melt pool image into the preliminary melt pool image segmentation model to obtain the corresponding image output, the construction module 2 executes: Initialize the parameters of the preliminary melt pool image segmentation model.

[0061] When constructing module 2, before inputting data to train the model, the parameters of the preliminary melt pool image segmentation model should be initialized to ensure that the model is in normal use.

[0062] Specifically, when the extraction module 3 is executed, it takes a picture of the additive manufacturing molten pool at a fixed position directly above the additive manufacturing molten pool at a preset shooting time interval as a period, periodically obtains a real-time molten pool image of the additive manufacturing molten pool, and inputs the real-time molten pool image into the molten pool image segmentation model. After calculation by the molten pool image segmentation model, a molten pool segmentation image containing only the additive manufacturing molten pool is extracted. The preset shooting time can be set according to actual needs.

[0063] Specifically, the calculation module 4 determines the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculates the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of the adjacent frames and the preset flow rate calculation formula, and executes the following cycle: Determine the approximate geometric center of the melt pool corresponding to the melt pool segmentation image, and calculate the real-time melt pool flow rate of the additive manufacturing melt pool according to the approximate geometric center of the melt pool segmentation image of the adjacent frames and the preset flow rate calculation formula, including the steps of cyclic execution: Determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image according to the minimum circumscribed rectangle of the additive manufacturing molten pool corresponding to the molten pool segmentation image; After acquiring the first frame of the melt pool segmentation image, each time the melt pool segmentation image is acquired, the real-time melt pool flow rate of the additive manufacturing melt pool is calculated by using a preset flow rate calculation formula, combining the approximate geometric center of the melt pool of the melt pool segmentation image acquired this time with the approximate geometric center of the melt pool of the last acquired melt pool segmentation image.

[0064] When the calculation module 4 is executed, each time the melt pool segmentation image is obtained (except for the first time the melt pool segmentation image is obtained), a minimum circumscribed rectangle is made with the additive manufacturing melt pool in the melt pool segmentation image as the center, the height and width of the minimum circumscribed rectangle are obtained, the height and width of the minimum circumscribed rectangle are determined as the height and width of the additive manufacturing melt pool, the midpoint of the minimum circumscribed rectangle is determined as the approximate center point of the additive manufacturing melt pool, and the approximate geometric center of the melt pool corresponding to the melt pool segmentation image is obtained.

[0065] After each determination of the approximate geometric center of the melt pool (except for determining the approximate geometric center of the melt pool of the first frame of the melt pool segmentation image), the preset flow rate calculation formula is used to calculate the real-time melt pool flow rate of the additive manufacturing melt pool based on the coordinate value of the approximate geometric center of the melt pool of the melt pool segmentation image acquired this time and the coordinate value of the approximate geometric center of the melt pool of the melt pool segmentation image acquired last time.

[0066] Among them, the preset flow rate calculation formula is specifically: ; in, is the real-time molten pool flow rate; is the horizontal coordinate of the approximate geometric center of the molten pool at time t (current time); is the horizontal coordinate of the approximate geometric center of the molten pool at time t-1 (the previous moment); is the ordinate of the approximate geometric center of the molten pool at time t; is the ordinate of the approximate geometric center of the molten pool at time t-1; The time interval between two frames of melt pool segmentation images, the unit is set to milliseconds; is the interference coefficient, Used to indicate the influence of external temperature, airflow and pressure on the flow rate of the molten pool; is the adjustment coefficient of the molten pool width and height on the molten pool flow rate; and are the width and height of the molten pool at time t (mm); and are the width and height of the molten pool at time t-1 (mm); is the environmental noise impact at time t. Among them, the interference coefficient , adjustment coefficient 、Ambient noise impact It can be set according to actual needs.

[0067] Specifically, when the adjustment module 5 is executed, the preset laser adjustment formula includes a preset laser power adjustment formula, a preset laser powder feed rate adjustment formula, a preset laser radius adjustment formula and a preset laser scanning speed adjustment formula; using the preset laser adjustment formula, according to the real-time molten pool flow rate, combined with the preset PID controller, with the preset target molten pool shape as the target, the real-time adjusted laser data is calculated, that is, the real-time adjusted laser power, laser powder feed rate, laser radius and laser scanning speed are calculated. Among them, the preset target molten pool shape includes a target molten pool area, a target molten pool height and a target molten pool width; the laser power is adjusted based on the molten pool area, the laser powder feed rate is adjusted based on the molten pool area, the laser radius is adjusted based on the molten pool height, and the laser scanning speed is adjusted based on the molten pool width.

[0068] Among them, the preset laser power adjustment formula is specifically: ; in, is the adjusted laser power (in watts); is the current laser power; , , They are respectively the laser power adjustment proportional coefficient, the laser power adjustment integral coefficient and the laser power adjustment differential coefficient of the PID controller, which are used to adjust the laser power by feedback according to the real-time molten pool area; is the target molten pool area (in square millimeters); is the current molten pool area (segment the additive manufacturing molten pool in the molten pool segmentation image by pixels, such as segmenting the pixels in units of square millimeters, and determine the current molten pool area according to the pixel ratio of the corresponding pixels of the additive manufacturing molten pool in the corresponding minimum circumscribed rectangle. This calculation process can be set in the molten pool image segmentation model, so that the molten pool image segmentation model automatically outputs the height, width and area of ​​the additive manufacturing molten pool when extracting the molten pool segmentation image, that is, the height of the current molten pool, the width of the current molten pool and the current molten pool area); Indicates the adjustment coefficient of the current molten pool area and height to the laser power; Indicates the adjustment coefficient of the current molten pool flow rate and width to the laser power; is the width of the current molten pool (in millimeters); is the current height of the molten pool (in millimeters); is the current melt pool flow rate (i.e. the real-time melt pool flow rate, in mm / s); is the current melt pool temperature (in degrees Celsius); is the adjustment coefficient of the current molten pool temperature; is the adjustment coefficient of the current molten pool area; It is the exponential coefficient for adjusting the influence of the current molten pool flow rate on the power. Among them, the laser power adjustment proportional coefficient , Laser power adjustment integral coefficient , Laser power adjustment differential coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0069] The preset laser powder feeding rate adjustment formula is as follows: ; in, is the adjusted laser powder feeding rate (in grams per minute); is the current laser powder feeding rate (g / min); , , They are the proportional, integral and differential coefficients of the PID controller, respectively, which control the feedback of the molten pool area in real time; Indicates the adjustment coefficient of the current molten pool area and width to the laser powder feeding rate; Indicates the adjustment coefficient of the current molten pool height and flow rate on the laser powder feeding rate; among them, the laser powder feeding rate adjustment proportional coefficient , Laser powder feeding rate adjustment integral coefficient , Laser powder feeding rate adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0070] The specific formula for adjusting the laser radius is: ; in, is the adjusted laser radius (in millimeters); is the current laser radius; is the target molten pool height; is the current height of the molten pool; , , They are respectively the laser radius adjustment proportional coefficient, the laser radius adjustment integral coefficient and the laser radius adjustment differential coefficient of the PID controller, which are used to adjust the laser radius by providing feedback according to the real-time molten pool height; Indicates the adjustment coefficient of the current molten pool width and area to the laser radius; Indicates the adjustment coefficient of the current molten pool height and flow rate to the laser radius; among them, the laser radius adjustment proportional coefficient , Laser radius adjustment integral coefficient , Laser radius adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs.

[0071] The specific formula for adjusting the laser scanning speed is: ; in, is the adjusted laser scanning speed (in mm / s); is the current laser scanning speed; is the target molten pool width; is the width of the current molten pool; , , They are respectively a laser scanning speed adjustment proportional coefficient, a laser scanning speed adjustment integral coefficient and a laser scanning speed adjustment differential coefficient of a PID controller, and are used to provide feedback according to the real-time molten pool width to adjust the laser scanning speed; Indicates the adjustment coefficient of the current molten pool height and area to the laser radius; Indicates the adjustment coefficient of the current molten pool flow rate and width to the laser radius; among them, the laser scanning speed adjustment proportional coefficient , Laser scanning speed adjustment integral coefficient , Laser scanning speed adjustment differential coefficient , adjustment coefficient , adjustment coefficient It can be set according to actual needs. In practical applications, the laser scanning speed adjustment coefficient , Laser scanning speed adjustment integral coefficient and laser scanning speed adjustment differential coefficient Both can be set to negative values. When adjusting the laser scanning speed, the control output of the PID controller can be adjusted in reverse through the negative coefficient (i.e., the laser scanning speed is adjusted in reverse) to achieve a negative correlation between the laser scanning speed and the molten pool size. Therefore, according to the laser scanning speed adjustment formula, the molten pool width can be controlled by adjusting the laser scanning speed.

[0072] In summary, the real-time adjusted laser power, laser powder feeding rate, laser radius and laser scanning speed are calculated, and the laser information is adjusted using the real-time adjusted laser power, laser powder feeding rate, laser radius and laser scanning speed to adjust the molten pool shape of the additive manufacturing molten pool.

[0073] In some embodiments, the preset flow rate calculation formula can be set in the molten pool image segmentation model through existing technology to obtain a molten pool flow rate calculation model (when constructing a numerical calculation model of molten pool stability, the molten pool flow rate calculated by the flow rate calculation formula needs to be obtained as training data and verification data). The molten pool flow rate calculation model has the ability to calculate the molten pool flow rate, and can calculate the real-time molten pool flow rate of the additive manufacturing molten pool based on the approximate geometric center of the molten pool of two frames of real-time molten pool images obtained periodically. Then, through the PID controller, the molten pool shape of the additive manufacturing molten pool is adjusted in real time using the preset laser power adjustment formula and the preset laser powder feed rate adjustment formula.

[0074] As can be seen from the above, the device for real-time adjustment of the shape of the additive manufacturing molten pool obtains a molten pool image and a corresponding molten pool annotated image of the additive manufacturing molten pool, constructs a molten pool image segmentation model according to the molten pool image and the corresponding molten pool annotated image, periodically obtains a real-time molten pool image of the additive manufacturing molten pool, and inputs the real-time molten pool image into the molten pool image segmentation model, extracts a molten pool segmentation image containing only the additive manufacturing molten pool, determines the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculates the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of the adjacent frames in combination with a preset flow rate calculation formula, and uses a preset laser adjustment formula According to the real-time molten pool flow rate, combined with a preset PID controller, with the preset target molten pool shape as the target, the laser information for preparing the additive manufacturing molten pool is adjusted in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time; thereby, through a preset laser adjustment formula, the molten pool shape is adjusted in real time according to the real-time molten pool flow rate calculated by the approximate geometric center of the molten pool of the molten pool segmentation image of adjacent frames and a preset flow rate calculation formula, thereby solving the problems of the existing molten pool adjustment method being time-consuming, labor-intensive, and having certain subjectivity and limitations, and being able to monitor the additive manufacturing molten pool in real time and accurately and adjust the molten pool shape of the additive manufacturing molten pool, thereby improving the adjustment efficiency of the additive manufacturing molten pool.

[0075] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The present application provides an electronic device, including: a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other through a communication bus 303 and / or other forms of connection mechanisms (not shown). The memory 302 stores a computer program executable by the processor 301. When the electronic device is running, the processor 301 executes the computer program to execute the method for real-time adjustment of the shape of the additive manufacturing molten pool in any optional implementation of the above embodiment to achieve the following functions: obtaining a molten pool image and a corresponding molten pool annotated image of the additive manufacturing molten pool, and according to the molten pool image and the corresponding molten pool annotated image, A melt pool image segmentation model is constructed, and real-time melt pool images of the additive manufacturing melt pool are periodically obtained. The real-time melt pool images are input into the melt pool image segmentation model, and a melt pool segmentation image containing only the additive manufacturing melt pool is extracted. The approximate geometric center of the melt pool corresponding to the melt pool segmentation image is determined, and the real-time melt pool flow rate of the additive manufacturing melt pool is calculated based on the approximate geometric center of the melt pool segmentation images of adjacent frames in combination with a preset flow rate calculation formula. A preset laser adjustment formula is used, and according to the real-time melt pool flow rate, combined with a preset PID controller, with a preset target melt pool shape as the target, the laser information for preparing the additive manufacturing melt pool is adjusted in real time, so as to adjust the melt pool shape of the additive manufacturing melt pool in real time.

[0076] The embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for real-time adjustment of the shape of an additive manufacturing molten pool in any optional implementation of the above-mentioned embodiment is executed to achieve the following functions: obtaining a molten pool image and a corresponding molten pool annotated image of the additive manufacturing molten pool, constructing a molten pool image segmentation model based on the molten pool image and the corresponding molten pool annotated image, periodically obtaining a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into the molten pool image segmentation model, extracting a molten pool segmentation image containing only the additive manufacturing molten pool, determining the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculating the real-time molten pool flow rate of the additive manufacturing molten pool based on the approximate geometric center of the molten pool segmentation images of adjacent frames in combination with a preset flow rate calculation formula, using a preset laser adjustment formula, based on the real-time molten pool flow rate, in combination with a preset PID controller, with a preset target molten pool shape as the target, adjusting the laser information for preparing the additive manufacturing molten pool in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0077] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0078] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0080] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0081] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for adjusting the shape of an additive manufacturing molten pool in real time, for adjusting the shape of an additive manufacturing molten pool, characterized in that: Includes steps: Obtain a melt pool image of an additive manufacturing melt pool and a corresponding melt pool annotation image; A melt pool image segmentation model is constructed according to the melt pool image and the corresponding melt pool annotated image; Periodically acquiring a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into the molten pool image segmentation model to extract a molten pool segmentation image that only includes the additive manufacturing molten pool; Determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculate the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula; Utilizing a preset laser adjustment formula, according to the real-time molten pool flow rate, combined with a preset PID controller, and taking a preset target molten pool shape as a target, the laser information for preparing the additive manufacturing molten pool is adjusted in real time to adjust the molten pool shape of the additive manufacturing molten pool in real time.

2. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 1, characterized in that: Obtain the melt pool image of the additive manufacturing melt pool and the corresponding melt pool annotation image, including: photographing the additive manufacturing molten pool to obtain an image of the molten pool; The contour position of the additive manufacturing molten pool is marked in the molten pool image to obtain the molten pool marked image.

3. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 1, characterized in that: According to the melt pool image and the corresponding melt pool annotated image, a melt pool image segmentation model is constructed, including: Construct a YOLOv8 model corresponding to the molten pool image to obtain a preliminary molten pool image segmentation model; According to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image, the preliminary melt pool image segmentation model is trained to obtain a trained preliminary melt pool image segmentation model; Based on the melt pool images that are not used for training and the corresponding melt pool annotated images in the melt pool images, the trained preliminary melt pool image segmentation model is verified to obtain the melt pool image segmentation model.

4. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 3, characterized in that: According to the melt pool image used for training and the corresponding melt pool annotated image in the melt pool image, the preliminary melt pool image segmentation model is trained to obtain the trained preliminary melt pool image segmentation model, including: Inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain a corresponding image output; the image output is an image containing only the additive manufacturing molten pool; determining a training error according to a melt pool annotated image corresponding to a melt pool image used for training in the melt pool image and the corresponding image output; Based on the training error, the parameters of the preliminary melt pool image segmentation model are adjusted to obtain the optimal parameters, and the preliminary melt pool image segmentation model is optimized using the optimal parameters to obtain the trained preliminary melt pool image segmentation model.

5. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 4, characterized in that: Before inputting the molten pool image used for training in the molten pool image into the preliminary molten pool image segmentation model to obtain the corresponding image output, the method further includes: Initialize the parameters of the preliminary melt pool image segmentation model.

6. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 1, characterized in that: Determining the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculating the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula, including the steps of cyclic execution: Determining an approximate geometric center of the molten pool corresponding to the molten pool segmentation image according to a minimum circumscribed rectangle of the additive manufacturing molten pool corresponding to the molten pool segmentation image; After acquiring the first frame of the molten pool segmentation image, each time the molten pool segmentation image is acquired, the real-time molten pool flow rate of the additive manufacturing molten pool is calculated by using the preset flow rate calculation formula, combining the approximate geometric center of the molten pool of the molten pool segmentation image acquired this time with the approximate geometric center of the molten pool of the molten pool segmentation image acquired last time.

7. The method for real-time adjustment of the shape of the additive manufacturing molten pool according to claim 1, characterized in that: The preset laser adjustment formula includes a preset laser power adjustment formula, a preset laser powder feed rate adjustment formula, a preset laser radius adjustment formula and a preset laser scanning speed adjustment formula.

8. A device for adjusting the shape of an additive manufacturing molten pool in real time, used to adjust the shape of an additive manufacturing molten pool, characterized in that: include: An acquisition module, used to acquire a molten pool image of an additive manufacturing molten pool and a corresponding molten pool annotated image; A construction module, used to construct a melt pool image segmentation model according to the melt pool image and the corresponding melt pool annotated image; An extraction module, used for periodically acquiring a real-time molten pool image of the additive manufacturing molten pool, and inputting the real-time molten pool image into the molten pool image segmentation model to extract a molten pool segmentation image containing only the additive manufacturing molten pool; a calculation module, used to determine the approximate geometric center of the molten pool corresponding to the molten pool segmentation image, and calculate the real-time molten pool flow rate of the additive manufacturing molten pool according to the approximate geometric center of the molten pool segmentation image of adjacent frames in combination with a preset flow rate calculation formula; The adjustment module is used to use a preset laser adjustment formula, according to the real-time molten pool flow rate, in combination with a preset PID controller, with a preset target molten pool shape as the target, to adjust the laser information for preparing the additive manufacturing molten pool in real time, so as to adjust the molten pool shape of the additive manufacturing molten pool in real time.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, the method runs the steps of the method for real-time adjustment of the shape of the additive manufacturing molten pool as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for adjusting the shape of an additive manufacturing molten pool in real time as claimed in any one of claims 1 to 7 are executed.

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