Nothing Special   »   [go: up one dir, main page]

CN113732308A - Detection and repair method and detection and repair device for 3D printing pore defects - Google Patents

Detection and repair method and detection and repair device for 3D printing pore defects Download PDF

Info

Publication number
CN113732308A
CN113732308A CN202110915359.1A CN202110915359A CN113732308A CN 113732308 A CN113732308 A CN 113732308A CN 202110915359 A CN202110915359 A CN 202110915359A CN 113732308 A CN113732308 A CN 113732308A
Authority
CN
China
Prior art keywords
defect
area
molten pool
repair
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110915359.1A
Other languages
Chinese (zh)
Other versions
CN113732308B (en
Inventor
杨洋
王成勇
文琢
陈孟
刘建业
戚文军
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangdong University of Technology
Original Assignee
Guangdong University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangdong University of Technology filed Critical Guangdong University of Technology
Priority to CN202110915359.1A priority Critical patent/CN113732308B/en
Publication of CN113732308A publication Critical patent/CN113732308A/en
Application granted granted Critical
Publication of CN113732308B publication Critical patent/CN113732308B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B22CASTING; POWDER METALLURGY
    • B22FWORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/20Direct sintering or melting
    • B22F10/28Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B22CASTING; POWDER METALLURGY
    • B22FWORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/50Treatment of workpieces or articles during build-up, e.g. treatments applied to fused layers during build-up
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B22CASTING; POWDER METALLURGY
    • B22FWORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/80Data acquisition or data processing
    • B22F10/85Data acquisition or data processing for controlling or regulating additive manufacturing processes
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B22CASTING; POWDER METALLURGY
    • B22FWORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/90Means for process control, e.g. cameras or sensors
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B33ADDITIVE MANUFACTURING TECHNOLOGY
    • B33YADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y10/00Processes of additive manufacturing
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B33ADDITIVE MANUFACTURING TECHNOLOGY
    • B33YADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y30/00Apparatus for additive manufacturing; Details thereof or accessories therefor
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B33ADDITIVE MANUFACTURING TECHNOLOGY
    • B33YADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00Data acquisition or data processing for additive manufacturing
    • B33Y50/02Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P10/00Technologies related to metal processing
    • Y02P10/25Process efficiency

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Materials Engineering (AREA)
  • Manufacturing & Machinery (AREA)
  • Analytical Chemistry (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • Plasma & Fusion (AREA)

Abstract

The application relates to a detection and repair method and a detection and repair device for 3D printing pore defects. The method comprises the following steps: (1) detecting the defects of the ith layer to determine a defective area; (2) determining the defect type of the defective area according to the image of the defective area of the ith layer; (3) determining a defect repairing mode according to the defect type, repairing the defect area and marking the defect area as a repairing area; (4) performing pore detection on the repair area of the ith layer; (5) determining the porosity of the repair area according to the pore volume and the repair area volume; (6) and determining whether pore defects exist or not according to the porosity of the repair area and repairing. Determining the defect type and the defect area layer by layer through image detection, detecting the pore defect of the repair area and repairing to realize qualified repair of the repair area and improve the mechanical property qualification rate of the casting.

Description

Detection and repair method and detection and repair device for 3D printing pore defects
Technical Field
The application relates to the technical field of computer vision and industrial automation detection, in particular to a 3D printing hole defect detection and repair method and a detection and repair device.
Background
In the prior art, selective laser melting (i.e., SLM) is widely used for 3D printing of metal castings. The SLM is used for manufacturing a three-dimensional casting by paving metal powder layer by layer according to the structural characteristics of the casting, melting the metal powder in a selected area by a laser beam, condensing and forming and stacking layer by layer. The SLM has the capability of integrally forming a complex and fine structure, and is widely applied to the fields of aerospace, medical instruments and implants thereof, molds, automobiles and the like.
At present, castings manufactured by the SLM technology have rough surfaces and abnormal internal pores and contours, and can cause adverse effects on the mechanical properties of the castings. In particular, the internal pores are located inside the casting, and it is difficult to identify the positions of the internal pores through simple machine vision, so that the internal pores cannot be repaired. And then, the areas with rough surfaces and abnormal outlines are subjected to mechanical milling or laser ablation to eliminate defects, and the connection area between the repaired defect area and the casting is subjected to massive internal pores due to the fact that the missing area is subjected to secondary printing after powder is spread again. The surface casting normally completes the printing process, but in practice, a casting with a large number of internal porosity defects is obtained, and the mechanical properties of the casting cannot be detected. The porosity defects are typically metallurgical pores and keyhole pores; the metallurgical pores are generated by element evaporation, gas escape and molten pool trapped gas generation under high laser energy density; the keyhole holes are caused by the rapid solidification of the metal powder without completely filling the gap, and the number thereof increases as the scanning speed increases
Therefore, how to detect the position of the void defect of the SLM casting and repair the void defect becomes an urgent problem to be solved.
Disclosure of Invention
In order to overcome the technical problems of the porosity defect of the SLM casting and repairing the porosity defect, the application provides in a first aspect a method for detecting and repairing a 3D printing porosity defect, including the steps of: (1) detecting the defects of the ith layer to determine a defective area; (2) determining the defect type of the defective area according to the image of the defective area of the ith layer; (3) determining a defect repairing mode according to the defect type, repairing the defect area and marking the defect area as a repairing area; (4) performing pore detection on the repair area of the ith layer; (5) determining the porosity of the repair area according to the pore volume and the repair area volume; (6) determining whether a pore defect exists according to the porosity of the repair area and repairing: if the porosity is larger than or equal to a first preset threshold value, adjusting printing parameters to repair the repair area again; and if the porosity is smaller than a first preset threshold value, printing the (i + 1) th layer.
In one embodiment, the performing the pore detection on the repair area of the ith layer specifically includes: acquiring a CT image of the repair area of the ith layer, and establishing a three-dimensional model of the repair area through a threshold segmentation algorithm; the three-dimensional model includes the repair area volume, pore center point coordinates, and pore volume.
In one embodiment, the determining the porosity of the repair area according to the pore volume and the repair area volume is specifically: determining the porosity of the repair area according to the pore volume, the repair area volume and a porosity calculation formula; the porosity calculation formula is as follows: p ═ v0-v)/v0100% of the total weight; p is a holeThe void fraction; the v0 is the repair area volume; the above-mentionedvIs the pore volume.
In an embodiment, if the porosity is greater than or equal to a first preset threshold, adjusting the printing parameter to repair the repair area again specifically includes: if the porosity is larger than or equal to a first preset threshold value, reducing the laser scanning speed of the molten pool, reducing the laser power and reducing the laser scanning interval; performing powder spreading and printing on the repair area; the first preset threshold range is as follows: 0.004% to 0.006%.
In an embodiment, the performing defect detection on the ith layer and determining the defect area specifically includes: acquiring a molten pool infrared image of an ith layer, a droplet splashing image of the ith layer and a surface image of the ith layer; the infrared image of the molten pool is the infrared image of the laser melting area of the ith layer; the droplet splash image is a high frame rate image of the ith layer; the surface image is the ith layer image after laser cladding is finished; determining whether the molten pool has abnormal size or abnormal temperature according to the molten pool size and the molten pool temperature, and marking the molten pool as the defect area; judging whether liquid drop splashing abnormity exists according to the high frame rate image of the ith layer and marking a liquid drop splashing area as the defect area; determining whether profile abnormality exists according to the profile characteristics of the surface image; and if the contour is abnormal, marking the abnormal contour region as the defect region.
In one embodiment, determining whether the molten pool has abnormal size or abnormal temperature according to the molten pool size and the molten pool temperature and marking the defect area specifically comprises: acquiring a maximum radius of a molten pool, an actual molten pool area, a theoretical molten pool area, a maximum length of the molten pool and a theoretical maximum length of the molten pool; calculating the abnormal value of the area of the molten pool according to a judgment formula for abnormal size of the molten pool: if VhcIf the number of the detected areas is larger than a third preset threshold, marking the detected areas as the defect areas; acquiring the average temperature of all printed layers, the highest temperature of the ith layer, the actual average temperature of the ith layer and the theoretical average temperature of the ith layer; calculating a molten pool temperature abnormal value according to a molten pool temperature abnormal judgment formula; if VicGreater than fourthIf a threshold value is preset, marking the defect area; the abnormal judgment calculation formula of the size of the molten pool is Vhc=α*Rmax+β*(Sf-St)2+ρ*(Lf-Lt)2(ii) a The V ishcAs a bath size anomaly value, said RmaxIs the maximum radius of the molten pool, SfFor the actual bath area, StIs the theoretical molten pool area, said LfFor the maximum length of the molten pool, said LtThe maximum length of the theoretical molten pool is defined, and the alpha, the beta and the rho are all adjustment coefficients; the judgment formula of the abnormal temperature of the molten pool is
Figure BDA0003205327860000031
Figure BDA0003205327860000032
The V isicAs a bath temperature anomaly value, said TavgIs the average temperature of all printed layers, the TmaxIs the ith layer highest temperature, said TfIs the actual average temperature of the i-th layer, TtIs the theoretical average temperature of the ith layer; and k, t and q are all adjustment coefficients.
In an embodiment, the determining the defect type of the defect area according to the defect area image of the ith layer is specifically: acquiring the defect area image of the ith layer; if the defect area has profile abnormality and the size of the profile abnormality is within a second preset threshold range, recording the defect area as a first type of defect; if the defect area has profile abnormality and the size of the profile abnormality is not within a second preset threshold range, recording the defect area as a second type of defect; and if the abnormal value of the size of the molten pool of the defect area is larger than a third preset threshold value, or the abnormal value of the temperature of the molten pool is larger than a fourth preset threshold value, recording the defect as a third type of defect.
In one embodiment, the second predetermined threshold is in a range of 27 mm to 113 mm.
In an embodiment, the selecting a defect repair method according to the defect type, and repairing the defect area and marking as a repair area specifically includes: if the defect type is the first type of defect, ablating the defect area by adopting pulse laser; if the defect type is the second type of defect, adopting pulse laser to remove the defect area, and performing powder spreading printing again and marking the defect area as a repair area; if the defect type is the third type of defect, the abnormal value of the size of the molten pool of the third type of defect is smaller than 120% of the third preset threshold, and the abnormal value of the temperature of the molten pool is smaller than 120% of the fourth preset threshold, re-cladding the defect area by adopting continuous laser and marking the defect area as a repair area; if the defect type is the third type of defect, and the abnormal value of the size of the molten pool of the third type of defect is larger than 120% of the third preset threshold, or the abnormal value of the temperature of the molten pool is larger than 120% of the fourth preset threshold, the defect area is removed by adopting pulse laser, and is printed and marked as a repair area by re-powder-spreading.
A second aspect of the present application provides a device for testing and repairing, based on the method of any one of claims 1 to 8, comprising: the system comprises a laser assembly, a printing platform, a high-speed camera, an infrared camera, a CT machine and a control system; the laser assembly, the high-speed camera, the infrared camera and the CT machine are assembled above the plane where the printing platform is located and are in communication connection with the control system; the laser assembly is used for melting a printing layer and ablating the defect area; the printing platform is used for erecting the printing piece; the high-speed camera is used for acquiring the liquid drop splashing image of the ith layer and the surface image of the ith layer; the infrared camera is used for acquiring the infrared image of the molten pool on the ith layer; the CT machine is used for acquiring a pore image of the repair area; the control system is used for processing the liquid drop splashing image, the surface image, the molten pool infrared image and the pore image and sending instructions.
The technical scheme provided by the application can comprise the following beneficial effects:
the detection and repair method for the 3D printing pore defects provided by the application performs layer-by-layer detection in the layer-by-layer printing process of the casting; during detection, acquiring image information when each layer is printed and image information after printing is completed, and judging and marking the defect area in each image information; determining the defect type of the defect area, determining a defect repair mode according to the defect type, and repairing the defect area; marking the repair area as a repair area after the repair is finished; and after all the third type defects and the repair areas are determined, carrying out internal appearance detection on the third type defects and the repair areas, calculating porosity, and eliminating the pore defects by adopting an effective repair mode.
In the first aspect of the application, the defect area containing potential pore defects is determined by detecting the size and temperature of a molten pool in the printing process, and is marked as the third type of defects; a second aspect is achieved by determining the repair area containing potential said pore defect; finally, detecting the internal appearance of the third type of defects and the repaired defects, and selecting a repairing mode according to the porosity of the third type of defects and the repaired defects; the method and the device can effectively detect the pore defects in the casting printing process and repair the pore defects, and improve the printing qualification rate of the casting.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application, as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.
Fig. 1 is a schematic flow chart of a method for detecting and repairing a 3D printing void defect according to an embodiment of the present application.
Detailed Description
Preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
Example one
In the process of printing a casting by using the SLM, in order to repair a pore defect of the casting printed by using the SLM, an embodiment of the present application provides a method for detecting and repairing a 3D printing pore defect, as shown in fig. 1, including the following steps:
s10, detecting the defects of the ith layer and determining the defect area;
further, acquiring a molten pool infrared image of the ith layer, a droplet splashing image of the ith layer and a surface image of the ith layer; the infrared image of the molten pool is the infrared image of the laser melting area of the ith layer; the droplet splash image is a high frame rate image of the ith layer; the surface image is the ith layer image after laser cladding is finished.
Further, determining whether the size of the molten pool is abnormal or the temperature of the molten pool is abnormal according to the abnormal molten pool size judgment calculation formula and the abnormal molten pool temperature judgment formula, and marking the abnormal molten pool as the defect area;
further, whether droplet splashing abnormity exists or not is judged according to the high frame rate image of the ith layer, and a droplet splashing area is marked as the defect area.
Further, determining whether profile abnormality exists according to the profile characteristics of the surface image; and if the contour is abnormal, marking the abnormal contour region as the defect region.
In the embodiment of the application, the layer-by-layer detection is carried out in the layer-by-layer printing process of the casting; during detection, acquiring the infrared image of the molten pool, the droplet splashing image and the surface image during printing of each layer; and comparing the acquired image information with the characteristics of the defect database, and identifying and marking the defect position of the ith layer.
S20, determining the defect type of the defect area according to the image of the defect area of the ith layer;
further, the maximum radius of the molten pool, the actual molten pool area, the theoretical molten pool area, the maximum length of the molten pool and the maximum length of the theoretical molten pool are obtained.
Further, calculating a molten pool area abnormal value according to the molten pool size abnormal judgment formula: if VhcAnd if the second preset threshold is larger than the third preset threshold, marking the defect area.
Further, the average temperature of all printed layers, the maximum temperature of the ith layer, the actual average temperature of the ith layer and the theoretical average temperature of the ith layer are obtained.
Further, calculating a molten pool temperature abnormal value according to a molten pool temperature abnormal judgment formula; if VicAnd if the second preset threshold is larger than the fourth preset threshold, marking the defect area.
Further, the abnormal size judgment calculation formula of the molten pool is Vhc=α*Rmax+β*(Sf-St)2+ρ*(Lf-Lt)2(ii) a The V ishcIs the size of the molten poolAbnormal value of said RmaxIs the maximum radius of the molten pool, SfFor the actual bath area, StIs the theoretical molten pool area, said LfFor the maximum length of the molten pool, said LtAnd the alpha, the beta and the rho are all adjustment coefficients for the maximum theoretical molten pool length.
Further, the abnormal judgment formula of the temperature of the molten pool is
Figure BDA0003205327860000061
Figure BDA0003205327860000062
The V isicAs a bath temperature anomaly value, said TavgIs the average temperature of all printed layers, the TmaxIs the ith layer highest temperature, said TfIs the actual average temperature of the i-th layer, TtIs the theoretical average temperature of the ith layer; and k, t and q are all adjustment coefficients.
Further, acquiring the defect area image of the ith layer;
if the defect area has profile abnormality and the size of the profile abnormality is within a second preset threshold range, recording the defect area as a first type of defect;
if the defect area has profile abnormality and the size of the profile abnormality is not within a second preset threshold range, recording the defect area as a second type of defect;
and if the abnormal value of the size of the molten pool of the defect area is larger than a third preset threshold value, or the abnormal value of the temperature of the molten pool is larger than a fourth preset threshold value, recording the defect as a third type of defect.
Further, the second preset threshold range is 27 mm square to 113 mm square.
In the embodiment of the application, the defect type of the defect area is determined by classifying according to the characteristics of the defect area. The first type of defect and the second type of defect are both apparent contour anomalies; the abnormal size of the first defect is small, and laser direct ablation can be adopted; the second type of defect has a large abnormal size and needs to be cut by laser; the third type of defect is a potential void defect, and different repair modes need to be further selected according to the abnormal condition of the third type of defect.
S30, determining a defect repair mode according to the defect type, repairing the defect area and marking the defect area as a repair area;
further, if the defect type is the first type of defect, the defect area is ablated by using a pulsed laser.
Further, if the defect type is the second type of defect, the pulse laser is adopted to remove the defect area, and the defect area is re-powdered and printed and marked as a repair area.
Further, if the defect type is the third type of defect, the weld pool size abnormal value of the third type of defect is less than 120% of the third preset threshold value, and the weld pool temperature abnormal value is less than 120% of the fourth preset threshold value, the defect area is rewelded by using continuous laser and marked as a repair area.
Further, the re-cladding is to heat the repair area by using continuous laser, so that the metal material in the repair area is re-melted and solidified, and the purpose of removing the third type of defects is achieved.
Furthermore, the power of the continuous laser to the repair area is reduced to 50%, the continuous laser scanning interval is reduced to 75%, and the continuous laser scanning speed is increased to 200%.
Further, if the defect type is the third type of defect, the abnormal value of the size of the molten pool of the third type of defect is greater than 120% of the third preset threshold, or the abnormal value of the temperature of the molten pool is greater than 120% of the fourth preset threshold, the defect area is removed and is printed with the pulse laser in a re-powder spreading mode, and the defect area is marked as a repair area.
Further, the third preset threshold is a molten pool size abnormity threshold, and the calculation formula of the molten pool size abnormity threshold is Qhc=Ravg+Savg+Lavg(ii) a The R isavgIs the average radius of the current layer molten pool, SavgThe average area of the current layer molten pool is LavgThe average length of the molten pool of the current layer.
Further, the fourth preset threshold is a molten pool temperature abnormal threshold, and the temperature abnormal threshold calculation formula is Qic=(Tavg+Tf) 2; the T isavgIs the average temperature of all layers printed.
Further, before repairing, the surface of the ith layer is subjected to preheating treatment by adopting continuous laser.
Further, the surface of the ith layer is cleaned before repairing.
S40, carrying out pore detection on the repair area of the ith layer;
further, acquiring a CT image of the repair area of the ith layer, and establishing a three-dimensional model of the repair area through a threshold segmentation algorithm; the three-dimensional model includes the repair area volume, pore center point coordinates, and pore volume.
S50, determining the porosity of the repair area according to the pore volume and the repair area volume;
further, determining the porosity of the repair area according to the pore volume, the repair area volume and a porosity calculation formula; the porosity calculation formula is as follows: p ═ v0-v)/v0100% of the total weight; p is porosity; the v0 is the repair area volume; and v is the pore volume.
S60, determining whether pore defects exist or not according to the porosity of the repair area and repairing: if the porosity is larger than or equal to a first preset threshold value, adjusting printing parameters to repair the repair area again; and if the porosity is smaller than a first preset threshold value, printing the (i + 1) th layer.
Further, if the porosity is larger than or equal to a first preset threshold, reducing the laser scanning speed of the molten pool, reducing the laser power and reducing the laser scanning interval; and performing powder spreading and printing on the repair area.
Further, the first preset threshold range is as follows: 0.004% to 0.006%.
The embodiment of the application performs layer-by-layer detection in the layer-by-layer printing process of the casting; during detection, acquiring image information when each layer is printed and image information after printing is completed, and judging and marking the defect area in each image information; determining the defect type of the defect area, determining a defect repair mode according to the defect type, and repairing the defect area; marking the repair area as a repair area after the repair is finished; and after all the third type defects and the repair areas are determined, carrying out internal appearance detection on the third type defects and the repair areas, calculating porosity, and eliminating the pore defects by adopting an effective repair mode.
In the first aspect of the application, the defect area containing potential pore defects is determined by detecting the size and temperature of a molten pool in the printing process, and is marked as the third type of defects; a second aspect is achieved by determining the repair area containing potential said pore defect; finally, detecting the internal appearance of the third type of defects and the repaired defects, and selecting a repairing mode according to the porosity of the third type of defects and the repaired defects; the method and the device can effectively detect the pore defects in the casting printing process and repair the pore defects, and improve the printing qualification rate of the casting.
Example two
Based on a method for detecting and repairing a 3D printing pore defect, the embodiment of the application provides a device for detecting and repairing a 3D printing defect, which comprises: the system comprises a laser assembly, a printing platform, a high-speed camera, an infrared camera, a CT machine and a control system; the laser assembly, the high-speed camera, the infrared camera and the CT machine are assembled above the plane where the printing platform is located and are in communication connection with the control system; the laser assembly is used for melting a printing layer and ablating the defect area; the printing platform is used for erecting the printing piece; the high-speed camera is used for acquiring the liquid drop splashing image of the ith layer and the surface image of the ith layer; the infrared camera is used for acquiring the infrared image of the molten pool on the ith layer; the CT machine is used for acquiring a pore image of the repair area; the control system is used for processing the liquid drop splashing image, the surface image, the molten pool infrared image and the pore image and sending instructions.
The 3D prints defect detection prosthetic devices that this application embodiment provided passes through high-speed camera, infrared camera and CT machine acquire every layer and print the image data on layer, through control system confirms every layer and prints the layer defect area, control print platform carries out the successive layer and restores, has improved the qualification rate of foundry goods, has avoided the waste of material.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The aspects of the present application have been described in detail hereinabove with reference to the accompanying drawings. In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments. Those skilled in the art should also appreciate that the acts and modules referred to in the specification are not necessarily required in the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application may be sequentially adjusted, combined, and deleted according to actual needs, and the modules in the device of the embodiment of the present application may be combined, divided, and deleted according to actual needs.
Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing some or all of the steps of the above-described method of the present application.
Alternatively, the present application may also be embodied as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or a computer program, or computer instruction code) which, when executed by a processor of an electronic device (or electronic device, server, etc.), causes the processor to perform part or all of the various steps of the above-described method according to the present application.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the applications disclosed herein may be implemented as electronic hardware, computer software, or combinations of both.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (10)

1. A3D printing pore defect detection and repair method is characterized by comprising the following steps:
detecting the defects of the ith layer to determine a defective area; i is an integer greater than or equal to 1;
determining the defect type of the defective area according to the image of the defective area of the ith layer;
determining a defect repairing mode according to the defect type, repairing the defect area and marking the defect area as a repairing area;
performing pore detection on the repair area of the ith layer;
determining the porosity of the repair area according to the pore volume and the repair area volume;
determining whether a pore defect exists according to the porosity of the repair area and repairing:
if the porosity is larger than or equal to a first preset threshold value, adjusting printing parameters to repair the repair area again;
and if the porosity is smaller than a first preset threshold value, printing the (i + 1) th layer.
2. The method for detecting and repairing the 3D printing pore defect according to claim 1, wherein the detecting the pore in the repaired area of the ith layer specifically comprises:
acquiring a CT image of the repair area of the ith layer, and establishing a three-dimensional model of the repair area through a threshold segmentation algorithm; the three-dimensional model includes the repair area volume, pore center point coordinates, and pore volume.
3. The method for detecting and repairing the 3D printing pore defect according to claim 2, wherein the determining the porosity of the repair area according to the pore volume and the repair area volume specifically comprises:
determining the porosity of the repair area according to the pore volume, the repair area volume and a porosity calculation formula; the porosity calculation formula is as follows: p ═ v0-v)/v0100% of the total weight; p is porosity; v is0Is the repair area volume; and v is the pore volume.
4. The method for detecting and repairing the 3D printed void defect according to claim 1, wherein if the porosity is greater than or equal to a first preset threshold, adjusting the printing parameters to repair the repaired area again specifically comprises:
if the porosity is larger than or equal to a first preset threshold value, reducing the laser scanning speed of the molten pool, reducing the laser power and reducing the laser scanning interval; performing powder spreading and printing on the repair area; the first preset threshold range is as follows: 0.004% to 0.006%.
5. The method for detecting and repairing the 3D printing pore defect according to claim 1, wherein the step of detecting the defect of the ith layer and the step of determining the defect area specifically comprises the steps of:
acquiring a molten pool infrared image of an ith layer, a droplet splashing image of the ith layer and a surface image of the ith layer; the infrared image of the molten pool is the infrared image of the laser melting area of the ith layer; the droplet splash image is a high frame rate image of the ith layer; the surface image is the ith layer image after laser cladding is finished;
determining whether the molten pool has abnormal size or abnormal temperature according to the molten pool size and the molten pool temperature, and marking the molten pool as the defect area;
judging whether liquid drop splashing abnormity exists according to the high frame rate image of the ith layer and marking a liquid drop splashing area as the defect area;
determining whether profile abnormality exists according to the profile characteristics of the surface image; and if the contour is abnormal, marking the abnormal contour region as the defect region.
6. The method for detecting and repairing the 3D printing pore defect according to the claim 5, wherein the step of determining whether the size or the temperature of the molten pool is abnormal or not according to the size and the temperature of the molten pool and marking the defect area comprises the following steps:
acquiring a maximum radius of a molten pool, an actual molten pool area, a theoretical molten pool area, a maximum length of the molten pool and a theoretical maximum length of the molten pool;
calculating the abnormal value of the area of the molten pool according to a judgment formula for abnormal size of the molten pool: if VhcIf the number of the detected areas is larger than a third preset threshold, marking the detected areas as the defect areas;
acquiring the average temperature of all printed layers, the highest temperature of the ith layer, the actual average temperature of the ith layer and the theoretical average temperature of the ith layer;
calculating a molten pool temperature abnormal value according to a molten pool temperature abnormal judgment formula; if VicIf the number of the detected areas is larger than a fourth preset threshold, marking the detected areas as the defect areas;
the abnormal judgment calculation formula of the size of the molten pool is Vhc=α*Rmax+β*(Sf-St)2+ρ*(Lf-Lt)2(ii) a The V ishcAs a bath size anomaly value, said RmaxIs the maximum radius of the molten pool, SfFor the actual bath area, StIs the theoretical molten pool area, said LfFor the maximum length of the molten pool, said LtThe maximum length of the theoretical molten pool is defined, and the alpha, the beta and the rho are all adjustment coefficients;
the judgment formula of the abnormal temperature of the molten pool is
Figure FDA0003205327850000021
Figure FDA0003205327850000022
The V isicAs a bath temperature anomaly value, said TavgIs the average temperature of all printed layers, the TmaxIs the ith layer highest temperature, said TfIs the actual average temperature of the i-th layer, TtIs the theoretical average temperature of the ith layer; and k, t and q are all adjustment coefficients.
7. The method for detecting and repairing the 3D printing pore defect according to claim 6, wherein the determining the defect type of the defect area according to the defect area image of the ith layer is specifically:
acquiring the defect area image of the ith layer;
if the defect area has profile abnormality and the size of the profile abnormality is within a second preset threshold range, recording the defect area as a first type of defect;
if the defect area has profile abnormality and the size of the profile abnormality is not within a second preset threshold range, recording the defect area as a second type of defect;
and if the abnormal value of the size of the molten pool of the defect area is larger than a third preset threshold value, or the abnormal value of the temperature of the molten pool is larger than a fourth preset threshold value, recording the defect as a third type of defect.
8. The method for detecting and repairing the 3D printing pore defect according to claim 7, wherein the second preset threshold value ranges from 27 square millimeters to 113 square millimeters.
9. The method for detecting and repairing 3D printed pore defects according to claim 7, wherein the selecting a defect repairing mode according to the defect type and the repairing the defect area and marking as the repaired area specifically comprises:
if the defect type is the first type of defect, ablating the defect area by adopting pulse laser;
if the defect type is the second type of defect, adopting pulse laser to remove the defect area, and performing powder spreading printing again and marking the defect area as a repair area;
if the defect type is the third type of defect, the abnormal value of the size of the molten pool of the third type of defect is smaller than 120% of the third preset threshold, and the abnormal value of the temperature of the molten pool is smaller than 120% of the fourth preset threshold, re-cladding the defect area by adopting continuous laser and marking the defect area as a repair area;
if the defect type is the third type of defect, and the abnormal value of the size of the molten pool of the third type of defect is larger than 120% of the third preset threshold, or the abnormal value of the temperature of the molten pool is larger than 120% of the fourth preset threshold, the defect area is removed by adopting pulse laser, and is printed and marked as a repair area by re-powder-spreading.
10. An inspection repair device based on the method of any one of claims 1 to 8, comprising: the system comprises a laser assembly, a printing platform, a high-speed camera, an infrared camera, a CT machine and a control system;
the laser assembly, the high-speed camera, the infrared camera and the CT machine are assembled above the plane where the printing platform is located and are in communication connection with the control system;
the laser assembly is used for melting a printing layer and ablating the defect area;
the printing platform is used for erecting the printing piece;
the high-speed camera is used for acquiring the liquid drop splashing image of the ith layer and the surface image of the ith layer;
the infrared camera is used for acquiring the infrared image of the molten pool on the ith layer;
the CT machine is used for acquiring a pore image of the repair area;
the control system is used for processing the liquid drop splashing image, the surface image, the molten pool infrared image and the pore image and sending instructions.
CN202110915359.1A 2021-08-10 2021-08-10 Detection and repair method for 3D printing pore defects Active CN113732308B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110915359.1A CN113732308B (en) 2021-08-10 2021-08-10 Detection and repair method for 3D printing pore defects

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110915359.1A CN113732308B (en) 2021-08-10 2021-08-10 Detection and repair method for 3D printing pore defects

Publications (2)

Publication Number Publication Date
CN113732308A true CN113732308A (en) 2021-12-03
CN113732308B CN113732308B (en) 2022-07-19

Family

ID=78730689

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110915359.1A Active CN113732308B (en) 2021-08-10 2021-08-10 Detection and repair method for 3D printing pore defects

Country Status (1)

Country Link
CN (1) CN113732308B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115386873A (en) * 2022-09-06 2022-11-25 北京航星机器制造有限公司 Defect repairing method for TA15 titanium alloy part formed by selective laser melting
CN116117169A (en) * 2023-01-29 2023-05-16 季华实验室 SLM technological process defect detection method and device
CN116883400A (en) * 2023-09-07 2023-10-13 山东大学 Powder spreading porosity prediction method and system in laser selective melting process
CN117372665A (en) * 2023-10-13 2024-01-09 山东创瑞激光科技有限公司 Online repair method for defect model data in additive manufacturing and forming process
CN117961089A (en) * 2024-04-01 2024-05-03 西安空天机电智能制造有限公司 Method, device, equipment and medium for manufacturing surface area laser powder bed additive

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104668553A (en) * 2015-01-30 2015-06-03 成都新柯力化工科技有限公司 Alloyed powder for directly printing metal parts in 3D (three-dimensional) manner and preparation method of alloyed powder
CN106141435A (en) * 2016-08-17 2016-11-23 广东工业大学 Laser-arc hybrid welding process 3D increases material repair apparatus and method for repairing and mending
CN106735224A (en) * 2016-12-17 2017-05-31 许昌学院 A kind of porous metal structure part hot melt drop printing deposition method for preparing and device
CN107708895A (en) * 2015-06-11 2018-02-16 瑞尼斯豪公司 Increasing material manufacturing apparatus and method
WO2019074827A1 (en) * 2017-10-09 2019-04-18 Sciaky, Inc. Electron beam additive manufacturing system and control components
CN109676135A (en) * 2018-11-28 2019-04-26 大连理工大学 A kind of laser gain material manufacture vision grey value difference on-line monitoring and bug repairing apparatus
WO2019172796A1 (en) * 2018-03-06 2019-09-12 Максим Львович ЧЕРНЫЙ Forming element of a mould for thermoforming articles made from foamed thermoplastic polymers and method for the manufacture thereof
CN110976861A (en) * 2019-11-29 2020-04-10 佛山科学技术学院 Metal 3D printing quality intelligent online monitoring system based on machine vision
CN111151751A (en) * 2020-01-02 2020-05-15 汕头大学 Three-laser-beam intelligent material-increasing and material-decreasing composite manufacturing system and method
CN111203538A (en) * 2020-04-22 2020-05-29 中国航发上海商用航空发动机制造有限责任公司 Prefabricated crack defect, preparation method of built-in crack defect and prefabricated part
WO2020167670A1 (en) * 2019-02-11 2020-08-20 The Regents Of The University Of Michigan Method of online stress measurement residual during laser additive manufacturing
CN112974803A (en) * 2019-12-17 2021-06-18 上海交通大学 Method for reducing porosity of laser selective melting forming component

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104668553A (en) * 2015-01-30 2015-06-03 成都新柯力化工科技有限公司 Alloyed powder for directly printing metal parts in 3D (three-dimensional) manner and preparation method of alloyed powder
CN107708895A (en) * 2015-06-11 2018-02-16 瑞尼斯豪公司 Increasing material manufacturing apparatus and method
CN106141435A (en) * 2016-08-17 2016-11-23 广东工业大学 Laser-arc hybrid welding process 3D increases material repair apparatus and method for repairing and mending
CN106735224A (en) * 2016-12-17 2017-05-31 许昌学院 A kind of porous metal structure part hot melt drop printing deposition method for preparing and device
WO2019074827A1 (en) * 2017-10-09 2019-04-18 Sciaky, Inc. Electron beam additive manufacturing system and control components
WO2019172796A1 (en) * 2018-03-06 2019-09-12 Максим Львович ЧЕРНЫЙ Forming element of a mould for thermoforming articles made from foamed thermoplastic polymers and method for the manufacture thereof
CN109676135A (en) * 2018-11-28 2019-04-26 大连理工大学 A kind of laser gain material manufacture vision grey value difference on-line monitoring and bug repairing apparatus
WO2020167670A1 (en) * 2019-02-11 2020-08-20 The Regents Of The University Of Michigan Method of online stress measurement residual during laser additive manufacturing
CN110976861A (en) * 2019-11-29 2020-04-10 佛山科学技术学院 Metal 3D printing quality intelligent online monitoring system based on machine vision
CN112974803A (en) * 2019-12-17 2021-06-18 上海交通大学 Method for reducing porosity of laser selective melting forming component
CN111151751A (en) * 2020-01-02 2020-05-15 汕头大学 Three-laser-beam intelligent material-increasing and material-decreasing composite manufacturing system and method
CN111203538A (en) * 2020-04-22 2020-05-29 中国航发上海商用航空发动机制造有限责任公司 Prefabricated crack defect, preparation method of built-in crack defect and prefabricated part

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
吴月梦等: "打印机驱动连接件开口处变形缺陷分析及优化", 《模具工业》 *
李莹等: "镁骨组织工程支架的打印制备及性能特征", 《中国组织工程研究》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115386873A (en) * 2022-09-06 2022-11-25 北京航星机器制造有限公司 Defect repairing method for TA15 titanium alloy part formed by selective laser melting
CN116117169A (en) * 2023-01-29 2023-05-16 季华实验室 SLM technological process defect detection method and device
CN116117169B (en) * 2023-01-29 2024-06-04 季华实验室 SLM technological process defect detection method and device
CN116883400A (en) * 2023-09-07 2023-10-13 山东大学 Powder spreading porosity prediction method and system in laser selective melting process
CN116883400B (en) * 2023-09-07 2023-11-21 山东大学 Powder spreading porosity prediction method and system in laser selective melting process
CN117372665A (en) * 2023-10-13 2024-01-09 山东创瑞激光科技有限公司 Online repair method for defect model data in additive manufacturing and forming process
CN117372665B (en) * 2023-10-13 2024-04-16 山东创瑞激光科技有限公司 Online repair method for defect model data in additive manufacturing and forming process
CN117961089A (en) * 2024-04-01 2024-05-03 西安空天机电智能制造有限公司 Method, device, equipment and medium for manufacturing surface area laser powder bed additive

Also Published As

Publication number Publication date
CN113732308B (en) 2022-07-19

Similar Documents

Publication Publication Date Title
CN113732308B (en) Detection and repair method for 3D printing pore defects
JP6723285B2 (en) Additive manufacturing and repair of metal components
EP3495077B1 (en) Powder spreading quality test method and additive manufacturing device
Chu et al. A vision-based system for post-welding quality measurement and defect detection
CN110508811B (en) Quality detection and automatic correction method in material increase and decrease composite manufacturing process
CN107727011B (en) Method for measuring flatness and profile on line in selective laser melting manufacturing process
Zhang et al. In situ monitoring of direct energy deposition via structured light system and its application in remanufacturing industry
CN113118465B (en) Method and apparatus for estimating puddle depth during 3D printing process, and 3D printing system
EP3659727A1 (en) Method for automatic identification of material deposition deficiencies during an additive manufacturing process and manufacturing device
EP3587006A1 (en) 3d-printing method and manufacturing device
Aminzadeh et al. Vision-based inspection system for dimensional accuracy in powder-bed additive manufacturing
CN115943431A (en) Computer-implemented, adaptive anomaly detection method for powder bed-based additive manufacturing
Yang et al. Analyzing Remelting Conditions based on In-Situ Melt Pool Data Fusion for Overhang Building in Powder Bed Fusion Process
CN116075381A (en) Computer-implemented correlation between monitoring data and corresponding inspection data in powder bed additive manufacturing
CN116664508A (en) Weld surface quality detection method and computer readable storage medium
Herzer et al. Detection of Defects in Solidified Layers within Laser-based Powder Bed Fusion using Active Thermography
CN113506267A (en) Metal manufacturing defect repairing method and system
Sen et al. In-situ surface roughness evaluation of laser powder bed fusion surfaces using optical tomography
Maass Demonstration of Closed-Loop Control for Laser Powder Bed Fusion (LPBF)
Dinh et al. Layering defects detection in laser powder bed fusion using embedded vision system
Nistler et al. Camera-based Process Monitoring for Powder Bed Additive Manufacturing in Construction
Yang et al. Enhancing Part Quality Management Using a Holistic Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing
CN118060558B (en) Unsupported forging printing method, system, device and medium
CN116117169B (en) SLM technological process defect detection method and device
Tocci et al. A preliminary study on the prediction of as-built surface quality in complex L-PBF parts using thermal imaging-based in-situ monitoring

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant