A selective laser melting powder laying quality in-situ monitoring and real-time feedback system

Abstract

The utility model provides a kind of area selection laser melting powder laying quality in situ monitoring and real-time feedback system, it is related to metal additive manufacturing quality monitoring technical field, including doctor blade, multi-source information acquisition module, defect identification module and powder laying control module;Multi-source information acquisition module includes vibration sensor, camera, infrared thermal imager and triangulation instrument.The utility model is through the layout multiple sensors of different types, vibration signal in powder laying process, powder surface image, temperature field distribution diagram and three-dimensional cloud picture are collected, to carry out comprehensive monitoring to powder laying quality, overcome the limitation that a variety of defect forms cannot be covered in powder laying process due to the single information type of single sensor, simultaneously, by in situ monitoring mode, multiple defects possibly existing can be found in real time in powder laying process by the multi-source information of collection, and after discovering defect, control doctor blade to realize defect elimination, avoid defect accumulation, to improve powder laying quality.

Description

Technical Field

[0001] This utility model relates to the field of quality monitoring technology in metal additive manufacturing, and more specifically, to a selective laser melting powder spreading quality in-situ monitoring and real-time feedback system. Background Technology

[0002] Selective laser melting (SLM) is an additive manufacturing technology that uses a high-energy laser beam to selectively melt metal powder layer by layer based on three-dimensional model data, directly producing precision metal parts with near-100% density and complex geometries. Powder layering is a crucial step in the SLM process, and its quality directly affects the final performance of the formed part. Because SLM technology is costly to produce individual parts, real-time quality monitoring of each powder layer is essential during the manufacturing process to ensure part quality.

[0003] The quality of powder spreading directly affects the density, dimensional accuracy, and mechanical properties of the formed parts. However, during the powder spreading process, inspection methods are limited. Traditional methods mainly rely on visual inspection based on the operator's experience, which is inefficient and inaccurate, and cannot achieve quantitative evaluation and real-time monitoring.

[0004] While existing powder spreading monitoring devices employ vision-based defect detection, they fail to consider the impact of vibration and temperature on powder spreading quality. Furthermore, they rely on a single data type for defect identification, while defects generated during powder spreading are diverse, including scratches, powder agglomeration, and uneven spreading. A single sensor is insufficient for accurate and comprehensive detection of powder spreading quality. This results in inaccurate monitoring and control of the scraper, ultimately affecting the final powder spreading quality. Utility Model Content

[0005] The purpose of this invention is to provide an in-situ monitoring and real-time feedback system for the quality of selective laser melting powder spreading, in order to improve the aforementioned problems. To achieve this objective, the technical solution adopted by this invention is as follows: In a first aspect, this application provides an in-situ monitoring and real-time feedback system for the quality of selective laser melting powder spreading, characterized in that it includes: scraper; The multi-source information acquisition module includes: A vibration sensor, located inside the scraper, is used to generate vibration signals when the scraper spreads powder; a camera, located at the back end of the scraper, is used to acquire images of the powder surface; an infrared thermal imager, located at the end of the camera furthest from the scraper, is used to acquire temperature field distribution maps of the powder surface; and a triangulation device, located at the end of the infrared imager furthest from the scraper, is used to acquire three-dimensional cloud maps of the powder surface. A defect identification module, connected to the multi-source information acquisition module, is used to identify powder defects based on the information acquired by the multi-source information acquisition module; The powder spreading control module is connected to the defect identification module and is used to control the travel speed of the scraper based on the identification result of the defect identification module.

[0006] Furthermore, the vibration sensor is fixedly installed inside the scraper near the scraper blade.

[0007] Furthermore, the vibration sensor is a triaxial accelerometer with a frequency response range of 0.5-10kHz and a dynamic range of ±50g.

[0008] Furthermore, a selective laser melting powder spreading quality in-situ monitoring and real-time feedback system also includes a forming chamber, in which a substrate is disposed, and a powder bed is fixedly disposed on the substrate. A scraper is disposed at one end of the substrate near the powder bed and moves on the powder bed.

[0009] Furthermore, the camera is fixedly mounted on the back end of the scraper, at a 30° angle to the side of the scraper near the powder bed.

[0010] Furthermore, the camera is a linear CCD camera equipped with a ring LED light source and a resolution of 5μm.

[0011] Furthermore, the triangulation measuring instrument is fixedly and vertically installed on the plane where the molding chamber is located on the top of the substrate.

[0012] Furthermore, the measurement range of the infrared thermal imager is set to 0-400℃, and the spatial resolution is set to 1mrad.

[0013] Furthermore, a selective laser melting powder spreading quality in-situ monitoring and real-time feedback system also includes an early warning module, which is connected to the defect identification module and is used to generate an alarm signal based on the identification result of the defect identification module.

[0014] The beneficial effects of this utility model are as follows: This invention utilizes multiple sensors of different types to collect vibration signals, powder surface images, temperature field distribution maps, and 3D cloud maps during the powder spreading process. This allows for comprehensive monitoring of powder spreading quality, overcoming the limitations of single sensors that cannot cover the various defect types that may occur during powder spreading due to their limited information collection. Furthermore, by employing in-situ monitoring, the multi-source information collected enables real-time detection of potential defects during powder spreading. Upon detection, the scraper is controlled to eliminate defects, preventing their accumulation and thus improving powder spreading quality.

[0015] Other features and advantages of this invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of this invention. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this utility model, the drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this utility model and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the structure of a selective laser melting powder spreading quality in-situ monitoring and real-time feedback system as described in an embodiment of this utility model; Figure 2 This is a schematic diagram of the scraper structure of a selective laser melting powder spreading quality in-situ monitoring and real-time feedback system as described in an embodiment of this utility model.

[0018] The following are labeled in the diagram: 1. Camera; 2. Triangulator; 3. Vibration sensor; 4. Infrared thermal imager; 5. Scraper; 6. Powder bed; 7. Forming substrate; 8. Defect identification module; 9. Powder spreading control module; 10. Early warning module; 11. Human-machine interface module. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this utility model clearer, the technical solutions of the embodiments of this utility model will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this utility model. The components of the embodiments of this utility model described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this utility model provided in the accompanying drawings is not intended to limit the scope of the claimed utility model, but merely to illustrate selected embodiments of the utility model. All other embodiments obtained by those skilled in the art based on the embodiments of this utility model without inventive effort are within the scope of protection of this utility model.

[0020] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this utility model, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] Most existing powder spreading monitoring devices are vision-based powder spreading defect detection devices, which rely solely on real-time images during the powder spreading process for defect detection. However, the defects generated during the powder spreading process are diverse, including scratches, powder agglomeration, and uneven powder spreading. Relying solely on images captured by a camera to detect defects that occur during the powder spreading process results in insufficient detection accuracy.

[0022] Vibration and temperature also have a certain impact on the quality of powder spreading, and a single sensor is insufficient to accurately and comprehensively detect the quality of powder spreading. Furthermore, the lack of a feedback system that integrates multi-source data acquisition makes it impossible to monitor and adjust the powder spreading process in real time, making it difficult to overcome various defects that may occur during the powder spreading process and further improve the quality of powder spreading.

[0023] To address the above problems, this utility model provides an in-situ monitoring and real-time feedback system for the quality of selective laser melting powder spreading. This system enables the collection of multi-source data during the powder spreading process, thereby conducting comprehensive defect detection and monitoring. Based on the defect detection results, the system can promptly eliminate defects by adjusting the scraper speed in real time, thus improving the powder spreading quality.

[0024] Please see Figure 1 and Figure 2 This embodiment provides an in-situ monitoring and real-time feedback system for the quality of selective laser melting powder spreading, including: Scraper 5; The multi-source information acquisition module includes: Vibration sensor 3 is installed inside scraper 5 to generate vibration signals when scraper 5 spreads powder; camera 1 is installed on the back of scraper 5 to collect images of the powder surface; infrared thermal imager 4 is installed at the end of camera 1 away from scraper 5 to collect temperature field distribution map of powder surface; triangulation instrument 2 is installed at the end of infrared imager away from scraper 5 to collect three-dimensional cloud map of powder surface. The defect identification module 8 is connected to the multi-source information acquisition module and is used to identify powder defects based on the information acquired by the multi-source information acquisition module. The powder spreading control module 9 is connected to the defect identification module 8 and is used to control the rotation speed of the motor of the scraper 5 based on the identification result of the defect identification module 8. The early warning module 10 is connected to the defect identification module 8 and is used to generate an alarm signal based on the identification result of the defect identification module 8.

[0025] In practical implementation: While a selective laser melting device is printing a metal part, the system starts controlling the scraper 5 to spread a new layer of powder. Driven by a motor, the scraper 5 moves smoothly on the powder bed 6, evenly spreading a thin layer of metal powder on top of the already printed part. During the powder spreading process, the multi-source information acquisition module installed on the scraper 5 works synchronously, collecting multi-source information about the powder spreading process in real time and sending the collected information to the defect identification module 8, which identifies defects. Furthermore, after completing the identification, the defect identification module 8 simultaneously sends the identification results to the powder spreading control module 9 and the early warning module 10. The identification results include the location, type, and severity of the defect. Further, upon receiving the identification results, if the defect is not severe, the powder spreading control module 9, based on the type and location of the defect, adjusts the rotation speed of the scraper 5 motor at different times (e.g., slightly accelerating or decelerating) during the next powder spreading to overcome the powder spreading defect. Furthermore, after receiving the identification result, if the early warning module 10 finds a serious defect, it will issue an alarm signal, stop the powder spreading action, and notify on-site personnel to make adjustments.

[0026] Furthermore, the vibration sensor 3 monitors the vibration of the scraper 5 in real time and transmits the vibration signal to the defect identification module 8. The defect identification module 8 identifies defects based on the vibration signal. Under normal circumstances, the scraper 5 slides across the flat powder, and the collected vibration signal is stable. If it encounters large powder particles or splashes from the previous layer, abnormal vibration peak signals will be collected. By recording the location of the abnormal vibration peak signal and transmitting it to the powder spreading control module 9 (this part about the defect identification module 8's identification process of abnormal vibration peak signals is based on existing vibration signal identification technology and will not be elaborated further here), the powder spreading control module 9 can decelerate the motor of the scraper 5 at that location when spreading the next layer of powder, thereby overcoming the defect at that location.

[0027] Furthermore, camera 1 captures an image of the freshly laid powder surface from behind scraper 5 and transmits the image to defect recognition module 8. Defect recognition module 8 performs image recognition on the powder surface image to determine whether there are obvious scratches, voids, or foreign objects, marks the location of the defects, and sends the defect type and corresponding location information to powder spreading control module 9 (this part regarding the recognition process of scratches, voids, or foreign objects by defect recognition module 8 is based on existing image recognition technology and will not be elaborated further here). When spreading the next layer of powder, powder spreading control module 9 can decelerate the motor of scraper 5 at the defect location to overcome the defect at that location. Preferably, after receiving the image recognition result from defect recognition module 8, early warning module 10 can determine whether the area of ​​the identified scratch, void, or foreign object exceeds a preset threshold. If it exceeds the preset threshold, it indicates a serious defect, and an early warning signal will be sent to stop the movement of scraper 5 and notify on-site personnel to intervene and make adjustments.

[0028] Furthermore, the infrared thermal imager 4 measures the temperature distribution on the powder surface and sends the data to the defect identification module 8. The defect identification module 8 can identify localized high-temperature points or areas of uneven temperature distribution. Localized high-temperature points may be caused by uneven spheroidization due to insufficient melting of the previous layer, while large-area temperature unevenness may be due to a malfunction in the substrate 7 heater or insufficient preheating. The defect identification module 8 records the type and location of defects and sends the data to the powder spreading control module 9 (this part regarding the identification process of localized high-temperature points or areas of uneven temperature distribution by the defect identification module 8 is based on existing infrared thermal imaging identification technology and will not be elaborated further here). If a localized high-temperature point occurs, the powder spreading control module 9 will slow down the scraper 5 at that location to avoid violent interaction between the scraper 5 and potentially adhering high-temperature spheroidized particles, and to allow more powder to cover the area to help dissipate heat and achieve uniform temperature. If a large-area temperature unevenness occurs, because the friction and flow characteristics of the powder are inconsistent on the unevenly temperatured powder bed 6, uniform powder spreading is prone to defects. The powder spreading control module 9 will adjust the overall speed of the scraper 5 to achieve uniform powder spreading. Preferably, after receiving the identification result, if a large area of ​​temperature unevenness occurs, the early warning module 10 can issue an early warning to remind the operator to check the thermal field system.

[0029] Furthermore, the triangulation measuring instrument 2 uses laser triangulation to quickly scan the powder surface and generate a high-precision three-dimensional cloud map. The defect identification module 8 can quantify the uniformity of the powder layer thickness through the three-dimensional cloud map. If a large area of ​​depression appears, it may be due to insufficient powder supply, wear of the scraper 5, or excessive warping of the previous layer. This defect type is sent to the powder spreading control module 9 (the identification process of the defect identification module 8 in quantifying the uniformity of the powder layer thickness through the three-dimensional cloud map is based on existing three-dimensional cloud map identification technology and will not be elaborated further here). When spreading the next layer of powder, the powder spreading control module 9 will globally decelerate the scraper 5, allowing more powder to accumulate in front of the scraper 5, providing more time to fill the depressed area and increasing the local powder spreading thickness. If a local protrusion is identified, it may be due to powder agglomeration or the presence of unsweeped spherical particles. This defect type and location are sent to the powder spreading control module 9. The powder spreading control module 9 can control the scraper 5 to accelerate at the defect location, reducing the amount of powder accumulated in front of the protrusion area, allowing the scraper 5 to flatten the protrusion.

[0030] Preferably, camera 1 is a linear CCD camera 1, which is fixedly mounted on the back of the scraper 5 at a 30° angle to the scraper 5. The linear CCD camera 1 is equipped with a ring LED light source with a resolution of 5μm. The tilted mounting avoids specular reflection from directly entering the lens. Combined with the ring light source, it highlights the texture and micro-undulations of the powder surface, resulting in higher contrast in the image for defects such as scratches, pits, and adhered spherical particles, making them easier for the algorithm to identify. The 5μm high resolution allows for clear differentiation of the distribution of individual powder particles (typically with a particle size of 15-60μm), enabling the detection of very small defects such as tiny scratches, powder agglomerations, or small voids.

[0031] Preferably, the vibration sensor 3 is a triaxial accelerometer with a frequency response range of 0.5-10kHz and a dynamic range of ±50g. The vibration sensor 3 is fixedly embedded inside the scraper 5 near the blade edge. Since the interaction between the scraper 5 and the powder is complex, involving not only vertical collisions but also frictional forces in the direction of travel, this embodiment uses a triaxial sensor to capture omnidirectional vibration information and provide richer diagnostic data. Embedding the vibration sensor 3 inside the scraper 5 near the blade edge minimizes signal attenuation and distortion during structural transmission, obtaining the most original and sensitive vibration signal expressing the interaction between the scraper 5 and the powder. The 0.5-10kHz frequency response covers mid-to-high frequency vibrations generated by powder flow, particle collisions (low frequency), and instantaneous impacts between the scraper 5 and hard defects (such as spheroidized particles), ensuring the capture of characteristic frequencies of various faults. The ±50g dynamic range ensures that even in the event of a very severe collision (such as the scraper 5 scraping a large spheroidized particle), the sensor will not saturate due to insufficient range, and the impact event can be fully recorded.

[0032] Preferably, the infrared thermal imager 4 has a measurement range of 0-400℃ and a high spatial resolution of 1 mrad. The 0-400℃ temperature range fully covers the residual heat of the previous printed layer, the temperature of the substrate 7 heater, and the temperature of the powder itself during the SLM process, ensuring no data loss due to exceeding the measurement range. The high spatial resolution of 1 mrad ensures that, at typical installation heights, the infrared thermal imager 4 can distinguish temperature differences in very small areas of the powder bed 6, providing a high-quality temperature distribution map.

[0033] Preferably, the laser triangulation gauge 2 is vertically mounted on the top of the forming chamber, with a measurement accuracy of ±2μm and a measurement range covering the entire width of the powder bed 6. Vertical mounting of the laser triangulation gauge 2 allows for the most accurate acquisition of the height of each point on the powder bed 6 surface relative to the reference plane, thereby constructing a precise three-dimensional topography. Since the thickness of the SLM auxiliary powder layer is typically 20-50μm, setting the accuracy range of the laser triangulation gauge 2 to ±2μm allows for precise detection of minute changes in layer thickness at the 10% level. This enables reliable identification of minute depressions or protrusions caused by wear of the scraper 5, spheroidization of the previous layer, or warping, generating a high-quality three-dimensional cloud map.

[0034] Preferably, the warning module 10 can use an existing buzzer to implement its warning function.

[0035] It should also be noted that in this application, the data preprocessing and defect identification of the powder surface image, three-dimensional cloud map, vibration signal and temperature field distribution map collected by the multi-source information acquisition module 8 are all based on existing technologies, and this application has not improved them, so they will not be described in detail here.

[0036] Preferably, the multi-source information acquisition module, defect identification module 8, and early warning module 10 are all connected to the human-machine interface module 11. The human-machine interface module 11 is used to set the operating parameters of the sensors in the multi-source information acquisition module, and to display the data collected by the multi-source information acquisition module and the identification results of the defect identification module 8. This interface can dynamically display real-time images, 3D cloud maps, vibration signals, and temperature field distribution maps of the powder-coated surface transmitted by each sensor in the multi-source information acquisition module. Operators can easily set the sampling frequency of each sensor and the threshold for early warning by the early warning module 10 through this interface. The human-machine interface displays the status and results of the entire process for operators to monitor and intervene.

[0037] The above description is merely a preferred embodiment of this utility model and is not intended to limit the utility model. Various modifications and variations can be made to this utility model by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this utility model should be included within the protection scope of this utility model.

[0038] The above description is only a specific embodiment of this utility model, but the protection scope of this utility model is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this utility model should be included within the protection scope of this utility model.

Claims

1. A selective laser melting powder spreading quality in-situ monitoring and real-time feedback system, characterized in that, include: scraper; The multi-source information acquisition module includes: A vibration sensor, located inside the scraper, is used to generate vibration signals when the scraper spreads powder; a camera, located at the back end of the scraper, is used to acquire images of the powder surface; an infrared thermal imager, located at the end of the camera furthest from the scraper, is used to acquire temperature field distribution maps of the powder surface; and a triangulation device, located at the end of the infrared imager furthest from the scraper, is used to acquire three-dimensional cloud maps of the powder surface. A defect identification module, connected to the multi-source information acquisition module, is used to identify powder defects based on the information acquired by the multi-source information acquisition module; The powder spreading control module is connected to the defect identification module and is used to control the travel speed of the scraper based on the identification result of the defect identification module.

2. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that, The vibration sensor is fixedly installed inside the scraper near the scraper blade.

3. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that, The vibration sensor is a triaxial accelerometer with a frequency response range of 0.5-10kHz and a dynamic range of ±50g.

4. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that, It also includes a molding chamber, in which a substrate is disposed, and a powder bed is fixedly disposed on the substrate. The scraper is disposed at one end of the substrate near the powder bed and moves on the powder bed.

5. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 4, characterized in that... The camera is fixedly mounted on the back end of the scraper, at a 30° angle to the side of the scraper near the powder bed.

6. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that... The camera is a linear CCD camera equipped with a ring LED light source and a resolution of 5μm.

7. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 4, characterized in that... The triangulation measuring instrument is fixedly and vertically installed on the plane of the molding chamber on the top of the substrate.

8. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that... The infrared thermal imager has a measurement range of 0-400℃ and a spatial resolution of 1mrad.

9. The selective laser melting powder spreading quality in-situ monitoring and real-time feedback system according to claim 1, characterized in that... It also includes an early warning module, which is connected to the defect identification module and is used to generate an alarm signal based on the identification result of the defect identification module.

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