Additive manufacturing forming device and method for large-size macro-mesoscopic integrated structural part

Abstract

The invention discloses a large-size macro-mesoscopic integrated structural part additive manufacturing forming device and method. The large-size macro-mesoscopic integrated structural part additive manufacturing forming device comprises a multi-laser cooperative machining system, an intelligent area recognition and control module, a laser mode switching unit, a high-precision motion platform and a powder laying and conveying system. The method comprises the following steps: S1, preprocessing and slicing a three-dimensional model; s2, intelligently identifying macro and mesoscopic areas; s3, multi-laser collaborative layered processing is carried out; s4, powder spreading and conveying and motion control; s5, layer-by-layer stacking is conducted till forming is completed; through cooperation of at least three paths of laser, mesoscopic precision and macroscopic efficiency are both considered, and the problem that traditional equipment is large in size and low in precision is solved; on the basis of a multi-parameter automatic identification algorithm, macro and mesoscopic areas are accurately divided, manual intervention errors are avoided, and the machining reliability of a complex structure is improved; and a synergistic process of small light spot forming and large light spot annealing is adopted, so that the thermal stress is remarkably reduced, the interface bonding strength is improved, and integrated efficient and high-precision manufacturing of a macroscopic structure and a mesoscopic fine structure is realized.

Description

Technical Field

[0001] The present invention relates to the technical field related to additive manufacturing, and in particular to a device and method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts. Background Art

[0002] The selective laser melting forming process occupies an important position in the field of additive manufacturing. Its core principle is to slice the three-dimensional structure into two dimensions and then process it layer by layer with the help of a high-energy laser beam. During the actual printing process, the laser completes the construction of the part by filling and scanning vector by vector according to the path pre-planned by the process software. At present, this process has a strong part forming capability, and the internal structure of the manufactured parts is rich and diverse, including not only common macroscopic solid structures such as sheets, plates, blocks and rods, but also mesoscopic structures such as thin walls, hollows, thin rods, porous and lattices, especially the manufacture of supporting functional structures.

[0003] In actual application scenarios, in order to meet the specific needs of different industries, such as dentistry, 3C consumer electronics, shoe molds and other industries with high requirements for precision, small spots are usually used for printing to achieve precise manufacturing of mesoscopic fine structures; and in large-scale selective melting forming equipment, in order to improve printing efficiency, more and more laser sources and larger-sized spots are used; however, as the forming size of the equipment continues to increase, in order to meet the scanning requirements of a larger range, the laser focusing focal length has to be increased accordingly. This change directly leads to an increase in the size of the focused spot; in this case, the manufacture of large-scale components containing mesoscopic fine structures faces huge challenges, and it is difficult to ensure the accuracy and quality of the structure; at the same time, with the continuous expansion of the application field of selective laser melting forming process, the demand for the forming of complex functional integrated structures is increasing, and the existing technical means can no longer meet this urgent demand, and innovative breakthroughs are urgently needed. Summary of the Invention

[0004] The purpose of the present invention is to provide a device and method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts, which is committed to overcoming the forming difficulties of large-scale macro- and mesoscopic integrated structural parts, thereby realizing the integrated, efficient and high-precision manufacturing of macroscopic structures and mesoscopic fine structures in large-scale components.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A large-scale macro-mesoscopic integrated structural parts additive manufacturing device, including a multi-laser collaborative processing system, an intelligent area recognition and control module, a laser mode switching unit, a high-precision motion platform and a powder delivery system;

[0007] The multi-laser collaborative processing system is equipped with at least three laser emitting devices, the scanning range of each laser emitting device completely covers the forming area, and includes at least two laser beams with different focused spot sizes, wherein the laser beams of at least two laser emitting devices are small-spot lasers with a focused spot diameter of ≤60μm, and the laser beam of at least one laser emitting device can be switched to a large-spot laser;

[0008] The intelligent region recognition and control module automatically recognizes the macroscopic region, mesoscopic feature region and macro-mesoscopic interface region of the part based on the slice data through the equipment control software;

[0009] The laser mode switching unit controls at least one laser emitting device to operate in a discontinuous mode for controlling heat input during mesostructure processing, and the laser mode switching unit independently controls the scanning speed, energy density, and pulse frequency of each laser emitting device;

[0010] The high-precision motion platform is used to carry the forming material, with a positioning accuracy of ≤±5μm, and supports coordinate coordination during synchronous scanning of multiple laser emission devices;

[0011] The powder spreading system is equipped with a multi-level powder screen (mesh size ≥ 200 mesh) for achieving a powder layer thickness of ≤ 50 μm in the mesoscopic feature area.

[0012] A preferred solution is that in the multi-laser collaborative processing system:

[0013] The wavelength of the small spot laser is 1030-1070nm, and the power range is 50-500W, which is used for high-precision melting of mesoscopic structures;

[0014] The wavelength of the large spot laser is 1000-1100nm, the power range is 200-1500W, and the spot diameter is

[0015] ≥100μm, used for rapid scanning of macroscopic solid structures.

[0016] In a preferred solution, the specific identification method of the intelligent area identification and control module includes:

[0017] (1) Identification of mesoscopic feature regions: For the isolated island region Ai generated after slicing the 3D model, its minimum wall thickness Ti and area Si (i = 1, 2, ... m) are calculated. When Ti ≤ the preset wall thickness threshold P and Si ≤ the preset area threshold Q, it is determined to be a mesoscopic feature region;

[0018] (2) Definition of macro-mesoscopic interface region: Calculate the minimum distance Dij between the mesoscopic island region Ai and the non-mesoscopic island region Bj (j = 1, 2...n). When Dij ≤ the preset distance threshold M, the two are locked as the interface region. For the non-mesoscopic island region whose area exceeds the preset area threshold N, the range with the same thickness H (H ≥ 0) inward from its contour as the boundary is defined as the interface region.

[0019] In a preferred embodiment, the definition rules of the macro-mesoscopic interface region further include:

[0020] When the minimum distance Dij between the mesoscopic island region Ai and multiple non-mesoscopic island regions Bj is less than or equal to the preset distance threshold M, all associated regions together constitute the interface region;

[0021] The constant thickness H ranges from 50 to 500 μm and is adaptively adjusted according to the thermophysical properties of the material and the precision requirements of the parts.

[0022] In a preferred embodiment, the intelligent area identification and control module further includes a visualization algorithm unit;

[0023] The visualization algorithm unit displays the identified mesoscopic feature areas, macro-mesoscopic interface areas, and macroscopic areas in layers with different colors or labels, and supports users to manually adjust the thresholds P, Q, M, N, and equal thickness H.

[0024] In a preferred solution, the intelligent region recognition and control module has a built-in machine learning model, which optimizes the threshold parameters P, Q, M, and N through historical processing data to achieve self-calibration of the mesoscopic feature region recognition accuracy.

[0025] In addition, the present application also proposes a method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts, which is characterized by comprising the following steps:

[0026] S1, 3D model preprocessing and slicing: import the 3D model of the part to be formed into the equipment control software, perform layered slicing processing, and generate 2D contour slice data;

[0027] S2, macro-mesoscopic region intelligent identification: using the intelligent region identification and control module, based on the island region characteristics in the slice data, identify the mesoscopic feature region, macro-mesoscopic interface region and conventional macroscopic region:

[0028] (1) Calculate the minimum wall thickness Ti and area Si of each island region. When Ti≤P and Si≤Q, it is determined to be a mesoscopic characteristic region.

[0029] (2) Calculate the minimum distance Dij between the mesoscopic island region and the non-mesoscopic island region. When Dij≤M, it is locked as the interface region. For the non-mesoscopic island region with an area greater than N, define the interface region with an equal thickness H inward with the contour as the boundary.

[0030] S3, multi-laser collaborative layered processing: based on the recognition results, different laser modes are used for layer-by-layer processing;

[0031] (1) Contour forming: Use a small spot laser (≤60μm) to globally scan the part contour and determine the layer shape;

[0032] (2) Mesoscopic fine feature processing: For the mesoscopic feature area, a small spot laser is used to perform fine scanning in continuous or discontinuous mode;

[0033] (3) Macro feature processing: For conventional macro areas, switch to large spot laser (≥100μm) for high-speed filling scanning;

[0034] (4) Interface area collaborative processing: In the macro-mesoscopic interface area, a small spot laser is used to form the mesoscopic structure.

[0035] Synchronously trigger large spot laser to perform conformal annealing to eliminate interface stress;

[0036] S4, powder paving and motion control: using the powder paving system to lay metal powder with a thickness of ≤50 μm in the mesoscopic feature area, and using a high-precision motion platform to achieve coordinate coordination of multiple laser scanning paths;

[0037] S5, stacking layer by layer until the forming is completed: repeat the above-mentioned slicing recognition, laser processing and powder spreading steps until the three-dimensional solid forming of the part is completed.

[0038] A preferred solution is that in the mesoscopic fine feature processing:

[0039] For thin-walled, hollow, and dot-matrix structures with high continuity requirements, a small spot continuous mode is used with a scanning speed of 500-2000mm / s and an energy density of 50-150J / mm 3 ;

[0040] For heat-sensitive thin rods and curved beam structures, a small spot discontinuous mode is used with a pulse frequency of 50-100kHz, a duty cycle of 30%-60%, and a single pulse energy of 1-5mJ.

[0041] In the macro feature processing, the scanning speed of the large spot laser is 1000-5000mm / s, and the energy density is 80-200J / mm 3 , using bidirectional parallel scanning or contour offset scanning strategies;

[0042] In the conformal annealing step of the macro-mesoscopic interface region:

[0043] The scanning path of the large spot laser is geometrically synchronized with the small spot forming path, and the annealing temperature is 60%-80% of the material melting point;

[0044] The annealing scan speed is 20%-50% faster than the forming scan speed, ensuring uniform heat input without melting the formed mesostructure.

[0045] In a preferred embodiment, the threshold parameters P (0<P≤100μm), Q (0<Q≤10mm 2 ), M(0<M≤500μm), N(10mm 2 <N≤1000mm 2 ) and equal thickness H (50μm≤H≤500μm), determined by the following method:

[0046] The initial value is preset according to the material type and part accuracy requirements;

[0047] Subsequently, the machine learning model of the intelligent area recognition and control module is used to adaptively optimize based on the defect data of historical processing.

[0048] In a preferred embodiment, the powder spreading system adopts vibration-type powder spreading or scraper-type powder spreading in the mesoscopic feature area, and the thickness of the powder spreading layer is precisely controlled by a multi-level powder screen (mesh size ≥ 200 mesh) to ensure that the powder particle size is ≤ 50 μm.

[0049] Due to the application of the above technical solution, the beneficial effects of this application compared with the prior art are:

[0050] The present application provides a device and method for additive manufacturing of large-scale macro-mesoscopic integrated structural parts. By coordinating at least three lasers (≥2 spot sizes), it takes into account both mesoscopic precision (≤60μm spot) and macroscopic efficiency (large spot fast scanning), thereby solving the "large size and low precision" problem of traditional equipment. An automatic recognition algorithm based on multiple parameters such as wall thickness, area, and distance accurately divides macro-mesoscopic areas to avoid manual intervention errors and improve the reliability of complex structure processing. The interface area adopts a "small spot forming + large spot annealing" collaborative process to significantly reduce thermal stress and improve interface bonding strength. The machine learning model self-calibrates threshold parameters, is compatible with a variety of materials such as titanium alloys and aluminum alloys, and supports multiple scenarios such as complex load-bearing components in aerospace and medical implants. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 A schematic diagram of an additive manufacturing device for large-scale macro- and mesoscopic integrated structural parts according to the present invention;

[0053] Figure 2 is a schematic diagram of a pattern of a mesoscopic feature region of the present invention;

[0054] Figure 3 is a schematic diagram of the macro-mesoscopic interface region of the present invention;

[0055] Figure 4 This is a flow chart of a method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts according to the present invention;

[0056] Among them, 1. Multi-laser collaborative processing system; 2. Intelligent area recognition and control module; 3. Laser mode switching unit; 4. High-precision motion platform; 5. Powder spreading system; 6. Laser emission device; 7. Visualization algorithm unit. DETAILED DESCRIPTION

[0057] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0058] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0059] In this application, terms such as "upper," "lower," "left," "right," "front," "back," "top," "bottom," "inner," "outer," "center," "vertical," "horizontal," "transverse," and "longitudinal" indicate positions or locations based on the positions or locations shown in the accompanying drawings. These terms are primarily intended to better describe the present invention and its embodiments and are not intended to limit the devices, elements, or components indicated to having a specific orientation, or to being constructed or operated in a specific orientation.

[0060] Furthermore, some of the above terms may be used to express other meanings besides indicating a position or location. For example, the term "on" may also be used to indicate a dependency or connection in certain circumstances. Those skilled in the art will understand the specific meanings of these terms in the present invention based on the specific circumstances.

[0061] Furthermore, the terms "installed," "disposed," "provided with," "connected," "connected," and "socketed" should be interpreted broadly. For example, they can refer to fixed connections, removable connections, or integral structures; mechanical connections or electrical connections; direct connections or indirect connections through an intermediary; or internal communication between two devices, elements, or components. Those skilled in the art will understand the specific meanings of these terms in the present invention based on specific circumstances.

[0062] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0063] Example 1

[0064] See Figure 1-3 , the present application provides a large-scale macro-mesoscopic integrated structural parts additive manufacturing forming device, including a multi-laser collaborative processing system 1, an intelligent area recognition and control module 2, a laser mode switching unit 3, a high-precision motion platform 4 and a powder spreading system 5;

[0065] The multi-laser collaborative processing system 1 is equipped with at least three laser emitting devices 6. The scanning range of each laser emitting device 6 completely covers the forming area and includes at least two laser beams with different focused spot sizes. Among them, the laser beams of at least two laser emitting devices 6 are small-spot lasers with a focused spot diameter of ≤60μm, and the laser beam of at least one laser emitting device 6 can be switched to a large-spot laser.

[0066] In the multi-laser collaborative processing system 1:

[0067] The wavelength of the small spot laser is 1030-1070nm, and the power range is 50-500W, which is used for high-precision melting of mesoscopic structures;

[0068] The wavelength of the large spot laser is 1000-1100nm, the power range is 200-1500W, and the spot diameter is

[0069] ≥100μm, used for rapid scanning of macroscopic solid structures;

[0070] The intelligent region recognition and control module 2 automatically recognizes the macroscopic region, mesoscopic feature region and macro-mesoscopic interface region of the part based on the slice data through the equipment control software;

[0071] The specific identification method of the intelligent area identification and control module 2 includes:

[0072] (1) Identification of mesoscopic feature regions: For the isolated island region Ai generated after slicing the 3D model, its minimum wall thickness Ti and area Si (i = 1, 2, ... m) are calculated. When Ti ≤ the preset wall thickness threshold P and Si ≤ the preset area threshold Q, it is determined to be a mesoscopic feature region;

[0073] (2) Definition of macro-mesoscopic interface region: Calculate the minimum distance Dij between the mesoscopic island region Ai and the non-mesoscopic island region Bj (j = 1, 2, ... n). When Dij ≤ the preset distance threshold M, the two are locked as the interface region. For non-mesoscopic island regions with an area exceeding the preset area threshold N, the range with the same thickness H (H ≥ 0) inward from its outline is defined as the interface region.

[0074] The definition rules of the macro-mesoscopic interface region also include:

[0075] When the minimum distance Dij between the mesoscopic island region Ai and multiple non-mesoscopic island regions Bj is less than or equal to the preset distance threshold M, all associated regions together constitute the interface region;

[0076] The constant thickness H ranges from 50 to 500 μm and is adaptively adjusted according to the thermophysical properties of the material and the precision requirements of the parts;

[0077] The intelligent area recognition and control module 2 further includes a visualization algorithm unit 7;

[0078] The visualization algorithm unit 7 displays the identified mesoscopic feature area, macro-mesoscopic interface area and macroscopic area in different colors or labels in layers, and supports the user to manually adjust the thresholds P, Q, M, N and equal thickness H;

[0079] The intelligent region recognition and control module 2 has a built-in machine learning model that optimizes the threshold parameters P, Q, M, and N through historical processing data to achieve self-calibration of the mesoscopic feature region recognition accuracy;

[0080] The laser mode switching unit 3 controls at least one laser emitting device 6 to operate in a discontinuous mode for controlling heat input during mesostructure processing, and the laser mode switching unit 3 independently controls the scanning speed, energy density, and pulse frequency of each laser emitting device 6;

[0081] The high-precision motion platform 4 is used to carry the forming material, with a positioning accuracy of ≤±5μm, and supports coordinate coordination during synchronous scanning of multiple laser emission devices 6;

[0082] The powder spreading system 5 is equipped with a multi-level powder screen (mesh size ≥ 200 mesh) for achieving a powder layer thickness of ≤ 50 μm in the mesoscopic feature area.

[0083] Example 2

[0084] See Figure 4 The present application also proposes a method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts, which is characterized by comprising the following steps:

[0085] S1, 3D model preprocessing and slicing: import the 3D model of the part to be formed into the equipment control software, perform layered slicing processing, and generate 2D contour slice data;

[0086] S2, intelligent identification of macro-mesoscopic regions: using the intelligent region identification and control module 2, based on the island region features in the slice data, identify the mesoscopic feature region, macro-mesoscopic interface region and conventional macroscopic region:

[0087] (1) Calculate the minimum wall thickness Ti and area Si of each island region. When Ti≤P and Si≤Q, it is determined to be a mesoscopic characteristic region.

[0088] (2) Calculate the minimum distance Dij between the mesoscopic island region and the non-mesoscopic island region. When Dij≤M, it is locked as the interface region. For the non-mesoscopic island region with an area greater than N, define the interface region with an equal thickness H inward with the contour as the boundary.

[0089] The threshold parameters P (0<P≤100μm), Q (0<Q≤10mm 2 ), M(0<M≤500μm), N(10mm 2 <N≤1000mm 2 ) and equal thickness H (50μm≤H≤500μm), determined by the following method:

[0090] The initial value is preset according to the material type and part accuracy requirements;

[0091] Subsequently, the machine learning model of the intelligent area recognition and control module 2 is used to adaptively optimize based on the defect data of historical processing;

[0092] S3, multi-laser collaborative layered processing: based on the recognition results, different laser modes are used for layer-by-layer processing;

[0093] (1) Contour forming: Use a small spot laser (≤60μm) to globally scan the part contour and determine the layer shape;

[0094] (2) Mesoscopic fine feature processing: For the mesoscopic feature area, a small spot laser is used to perform fine scanning in continuous or discontinuous mode;

[0095] In the mesoscopic fine feature processing:

[0096] For thin-walled, hollow, and dot-matrix structures with high continuity requirements, a small spot continuous mode is used with a scanning speed of 500-2000mm / s and an energy density of 50-150J / mm 3 ;

[0097] For heat-sensitive thin rods and curved beam structures, a small spot discontinuous mode is used, and the pulse frequency

[0098] 50-100kHz, duty cycle 30%-60%, single pulse energy 1-5mJ;

[0099] (3) Macro feature processing: For conventional macro areas, switch to large spot laser (≥100μm) for high-speed filling scanning;

[0100] In the macro feature processing, the scanning speed of the large spot laser is 1000-5000mm / s, and the energy density is 80-200J / mm 3 , using bidirectional parallel scanning or contour offset scanning strategies;

[0101] (4) Interface area collaborative processing: In the macro-mesoscopic interface area, a small spot laser is used to form the mesoscopic structure.

[0102] Synchronously trigger large spot laser to perform conformal annealing to eliminate interface stress;

[0103] In the conformal annealing step of the macro-mesoscopic interface region:

[0104] The scanning path of the large spot laser is geometrically synchronized with the small spot forming path, and the annealing temperature is 60%-80% of the material melting point;

[0105] The annealing scan speed is 20%-50% faster than the forming scan speed, ensuring uniform heat input without melting the formed mesostructure;

[0106] S4, powder paving and motion control: using the powder paving system 5 to lay metal powder with a thickness of ≤50 μm in the mesoscopic feature area, and using the high-precision motion platform 4 to achieve coordinate coordination of multiple laser scanning paths;

[0107] The powder spreading system 5 adopts vibration spreading or scraper spreading in the mesoscopic feature area, and the thickness of the powder layer is precisely controlled by multi-level powder screen (mesh size ≥ 200 mesh) to ensure the powder particle size

[0108] ≤50μm;

[0109] S5, stacking layer by layer until the forming is completed: repeat the above-mentioned slicing recognition, laser processing and powder spreading steps until the three-dimensional solid forming of the part is completed.

[0110] Example 3

[0111] The specific processing is carried out using a large-scale macro-mesoscopic integrated structural part additive manufacturing forming device and method of the present application;

[0112] Titanium alloy aviation bracket forming

[0113] Equipment parameters:

[0114] Small spot laser: 2 channels, wavelength 1064nm, spot size 50μm, power 200W (continuous mode) / 150W (discontinuous mode);

[0115] Large spot laser: 1 channel, wavelength 1070nm, spot size 150μm, power 800W;

[0116] Threshold setting: P = 60 μm, Q = 5 mm 2 , M = 200 μm, N = 100 mm 2 , H = 100 μm.

[0117] Processing process:

[0118] The mesoscopic feature area (porous lattice, wall thickness 40 μm) adopts a small spot discontinuous mode (pulse frequency 60 kHz, duty cycle 50%) to avoid thermal deformation;

[0119] The macro area (solid support column) adopts large spot continuous scanning at a speed of 3000mm / s, which is 60% more efficient than the traditional single laser;

[0120] The interface area (lattice and solid connection part) is synchronously annealed at an annealing temperature of about 800°C (48% of the melting point of titanium alloy 1668°C) to eliminate connection defects.

[0121] result:

[0122] The dimensional accuracy of the mesostructure is ±20μm, the tensile strength of the interface area reaches 950MPa (an increase of 18% compared with traditional processes), and the overall forming time is shortened by 40%.

[0123] Example 4

[0124] The specific processing is carried out using a large-scale macro-mesoscopic integrated structural part additive manufacturing forming device and method of the present application;

[0125] Aluminum alloy automotive lightweight components

[0126] Equipment parameters:

[0127] Small spot laser: 2 channels, wavelength 1050nm, spot size 60μm, power 300W (continuous mode);

[0128] Large spot laser: 1 channel, wavelength 1080nm, spot size 200μm, power 1200W;

[0129] Threshold setting: P = 80 μm, Q = 10 mm 2 , M=300μm,N=500mm 2 , H = 200 μm.

[0130] Processing process:

[0131] The mesoscopic feature area (thin-walled ribbed plate, wall thickness 70 μm) adopts small spot continuous mode, speed 2000 mm / s, energy density 120 J / mm 3 , ensure surface roughness Ra≤5μm;

[0132] The macro area (main frame) adopts large spot bidirectional scanning, speed 4000mm / s, energy density 180J / mm 3 ;

[0133] The annealing temperature of the interface zone is about 500°C (76% of the melting point of aluminum alloy 660°C), and the scanning speed is 30% faster than the forming speed to ensure uniform heat input.

[0134] result:

[0135] The thin-wall structure has no fracture defects, the microstructure of the interface area is uniform, the overall weight of the part is reduced by 35% compared with traditional casting, and the mechanical properties meet the standards.

[0136] The present application provides a device and method for additive manufacturing of large-scale macro-mesoscopic integrated structural parts. By coordinating at least three lasers (≥2 spot sizes), it takes into account both mesoscopic precision (≤60μm spot) and macroscopic efficiency (large spot fast scanning), thereby solving the "large size and low precision" problem of traditional equipment. An automatic recognition algorithm based on multiple parameters such as wall thickness, area, and distance accurately divides macro-mesoscopic areas to avoid manual intervention errors and improve the reliability of complex structure processing. The interface area adopts a "small spot forming + large spot annealing" collaborative process to significantly reduce thermal stress and improve interface bonding strength. The machine learning model self-calibrates threshold parameters, is compatible with a variety of materials such as titanium alloys and aluminum alloys, and supports multiple scenarios such as complex load-bearing components in aerospace and medical implants.

[0137] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent replacements for some of the technical features therein. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A large-scale macro-mesoscopic integrated structural parts additive manufacturing forming device, characterized in that: It includes a multi-laser collaborative processing system, an intelligent area recognition and control module, a laser mode switching unit, a high-precision motion platform and a powder delivery system; The multi-laser collaborative processing system is equipped with at least three laser emitting devices, the scanning range of each laser emitting device completely covers the forming area, and includes at least two laser beams with different focused spot sizes, wherein the laser beams of at least two laser emitting devices are small-spot lasers with a focused spot diameter of ≤60μm, and the laser beam of at least one laser emitting device can be switched to a large-spot laser; The intelligent region recognition and control module automatically recognizes the macroscopic region, mesoscopic feature region and macro-mesoscopic interface region of the part based on the slice data through the equipment control software; The laser mode switching unit controls at least one laser emitting device to operate in a discontinuous mode for controlling heat input during mesostructure processing, and the laser mode switching unit independently controls the scanning speed, energy density, and pulse frequency of each laser emitting device; The high-precision motion platform is used to carry the forming material, with a positioning accuracy of ≤±5μm, and supports coordinate coordination during synchronous scanning of multiple laser emission devices; The powder spreading system is equipped with a multi-level powder screen (mesh size ≥ 200 mesh) for achieving a powder layer thickness of ≤ 50 μm in the mesoscopic feature area.

2. The large-scale macro- and mesoscopic integrated structural parts additive manufacturing forming device according to claim 1 is characterized in that: In the multi-laser collaborative processing system: The wavelength of the small spot laser is 1030-1070nm, and the power range is 50-500W, which is used for high-precision melting of mesoscopic structures; The wavelength of the large spot laser is 1000-1100nm, the power range is 200-1500W, and the spot diameter is ≥100μm, used for rapid scanning of macroscopic solid structures.

3. The large-scale macro- and mesoscopic integrated structural parts additive manufacturing forming device according to claim 1, characterized in that: The specific identification method of the intelligent area identification and control module includes: (1) Identification of mesoscopic feature regions: For the isolated island region Ai generated after slicing the 3D model, its minimum wall thickness Ti and area Si (i = 1, 2, ... m) are calculated. When Ti ≤ the preset wall thickness threshold P and Si ≤ the preset area threshold Q, it is determined to be a mesoscopic feature region; (2) Definition of macro-mesoscopic interface region: Calculate the minimum distance Dij between the mesoscopic island region Ai and the non-mesoscopic island region Bj (j = 1, 2...n). When Dij ≤ the preset distance threshold M, the two are locked as the interface region. For the non-mesoscopic island region whose area exceeds the preset area threshold N, the range with the same thickness H (H ≥ 0) inward from its contour as the boundary is defined as the interface region.

4. The large-scale macro- and mesoscopic integrated structural parts additive manufacturing forming device according to claim 3, characterized in that: The definition rules of the macro-mesoscopic interface region also include: When the minimum distance Dij between the mesoscopic island region Ai and multiple non-mesoscopic island regions Bj is less than or equal to the preset distance threshold M, all associated regions together constitute the interface region; The constant thickness H ranges from 50 to 500 μm and is adaptively adjusted according to the thermophysical properties of the material and the precision requirements of the parts.

5. The large-scale macro- and mesoscopic integrated structural parts additive manufacturing forming device according to claim 3, characterized in that: The intelligent area recognition and control module also includes a visualization algorithm unit; The visualization algorithm unit displays the identified mesoscopic feature areas, macro-mesoscopic interface areas, and macroscopic areas in layers with different colors or labels, and supports users to manually adjust the thresholds P, Q, M, N, and equal thickness H.

6. The large-scale macro- and mesoscopic integrated structural parts additive manufacturing forming device according to claim 3, characterized in that: The intelligent region recognition and control module has a built-in machine learning model that optimizes the threshold parameters P, Q, M, and N through historical processing data to achieve self-calibration of the mesoscopic feature region recognition accuracy.

7. A method for additive manufacturing of large-scale macro- and mesoscopic integrated structural parts based on the large-scale macro- and mesoscopic integrated structural part additive manufacturing device according to any one of claims 1 to 6, characterized in that: The following steps are involved: S1, 3D model preprocessing and slicing: import the 3D model of the part to be formed into the equipment control software, perform layered slicing processing, and generate 2D contour slice data; S2, macro-mesoscopic region intelligent identification: using the intelligent region identification and control module, based on the island region characteristics in the slice data, identify the mesoscopic feature region, macro-mesoscopic interface region and conventional macroscopic region: (1) Calculate the minimum wall thickness Ti and area Si of each island region. When Ti≤P and Si≤Q, it is determined to be a mesoscopic characteristic region. (2) Calculate the minimum distance Dij between the mesoscopic island region and the non-mesoscopic island region. When Dij≤M, it is locked as the interface region. For the non-mesoscopic island region with an area greater than N, define the interface region with an equal thickness H inward with the contour as the boundary. S3, multi-laser collaborative layered processing: based on the recognition results, different laser modes are used for layer-by-layer processing; (1) Contour forming: Use a small spot laser (≤60μm) to globally scan the part contour and determine the layer shape; (2) Mesoscopic fine feature processing: For the mesoscopic feature area, a small spot laser is used to perform fine scanning in continuous or discontinuous mode; (3) Macro feature processing: For conventional macro areas, switch to large spot laser (≥100μm) for high-speed filling scanning; (4) Cooperative processing of the interface area: In the macro-mesoscopic interface area, a small-spot laser is used to form the mesostructure, and a large-spot laser is synchronously triggered to perform conformal annealing to eliminate interface stress; S4, powder paving and motion control: using the powder paving system to lay metal powder with a thickness of ≤50 μm in the mesoscopic feature area, and using a high-precision motion platform to achieve coordinate coordination of multiple laser scanning paths; S5, stacking layer by layer until the forming is completed: repeat the above-mentioned slicing recognition, laser processing and powder spreading steps until the three-dimensional solid forming of the part is completed.

8. The additive manufacturing method for large-scale macro- and mesoscopic integrated structural parts according to claim 7, characterized in that: In the mesoscopic fine feature processing: For thin-walled, hollow, and dot-matrix structures with high continuity requirements, a small spot continuous mode is used with a scanning speed of 500-2000mm / s and an energy density of 50-150J / mm 3 ; For heat-sensitive thin rods and curved beam structures, a small spot discontinuous mode is used with a pulse frequency of 50-100kHz, a duty cycle of 30%-60%, and a single pulse energy of 1-5mJ. In the macro feature processing, the scanning speed of the large spot laser is 1000-5000mm / s, and the energy density is 80-200J / mm 3 , using bidirectional parallel scanning or contour offset scanning strategies; In the conformal annealing step of the macro-mesoscopic interface region: The scanning path of the large spot laser is geometrically synchronized with the small spot forming path, and the annealing temperature is 60%-80% of the material melting point; The annealing scan speed is 20%-50% faster than the forming scan speed, ensuring uniform heat input without melting the formed mesostructure.

9. The additive manufacturing method for large-scale macro- and mesoscopic integrated structural parts according to claim 7, characterized in that: The threshold parameters P (0<P≤100μm), Q (0<Q≤10mm 2 ), M(0<M≤500μm), N(10mm 2 <N≤1000mm 2 ) and equal thickness H (50μm≤H≤500μm), determined by the following method: The initial value is preset according to the material type and part accuracy requirements; Subsequently, the machine learning model of the intelligent area recognition and control module is used to adaptively optimize based on the defect data of historical processing.

10. The additive manufacturing method for large-scale macro- and mesoscopic integrated structural parts according to claim 7, characterized in that: The powder spreading system adopts vibration-type powder spreading or scraper-type powder spreading in the mesoscopic feature area, and the thickness of the powder spreading layer is precisely controlled by a multi-level powder screen (mesh size ≥ 200 mesh) to ensure that the powder particle size is ≤ 50 μm.

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