A method and system for additive manufacturing of a curved metal component

Abstract

The application relates to the technical field of metal additive manufacturing, in particular to a curved surface metal component additive manufacturing method and system. A simulation model of multiple physical field mutual coupling of a curved surface metal component is constructed; a plurality of target partitions of each layer are identified based on a simulation result, the maximum principal stress direction of each partition is determined, the evolution curve of the molten pool temperature and time of each partition is predicted, and the electromagnetic vibration time window after laser scanning cladding is determined accordingly; the corresponding preheating temperature, laser power, scanning speed and electromagnetic vibration frequency are determined according to the structure characteristics of the target partition; the to-be-cladded area is preheated based on the preheating temperature; the to-be-cladded area after preheating is laser scanned and cladded based on the laser power and the scanning speed; and the to-be-cladded area is directionally electromagnetically vibrated at the electromagnetic vibration frequency within the electromagnetic vibration time window, and the vibration direction is the vertical direction of the maximum principal stress direction. The temperature gradient and solidification shrinkage of each area are coordinately controlled, and the component forming precision and structural integrity are ensured.

Description

Technical Field

[0001] This invention relates to the field of metal additive manufacturing technology, and in particular to a method and system for additive manufacturing curved metal components. Background Technology

[0002] Curved metal components are widely used in radar antennas, communication antennas, and aerospace fields. Their additive manufacturing process typically employs selective laser melting to deposit materials layer by layer. However, curved metal components have different geometric characteristics and heat dissipation conditions in different regions, including differences in wall thickness, curvature, and internal structure. This causes the temperature field distribution, solidification shrinkage rate, and residual stress accumulation rate in each region to change asynchronously during the forming process.

[0003] In existing additive manufacturing processes, uniform process parameters are used for forming each region, without distinguishing the differences in geometric features and heat dissipation conditions between regions. Due to the differences in wall thickness, curvature, and internal structure in different regions of curved metal components, the temperature field distribution, solidification shrinkage rate, and residual stress accumulation rate vary in each region during the forming process. Uniform process parameters cannot adapt to these differences, easily leading to continuous asynchronous changes in temperature gradient and solidification shrinkage in each region during the forming process. This results in differences in temperature gradient and solidification shrinkage, manifesting as defects such as surface warping, thin-wall collapse, and interlayer porosity. Uneven distribution of residual stress after component forming further reduces dimensional stability, and the continuous release of residual stress under temperature alternation and vibration conditions exacerbates component deformation.

[0004] Therefore, the contradiction between the asynchronous dynamic changes in temperature gradient and solidification shrinkage in different regions during the additive manufacturing process of curved metal components and the overall structural integrity of the components restricts the forming accuracy and long-term service reliability of curved metal components in additive manufacturing, making it difficult to meet the engineering requirements of high-precision assembly and long-term working stability. Summary of the Invention

[0005] This application provides a method and system for additive manufacturing of curved metal components, which enables coordinated control of temperature gradient and solidification shrinkage in different regions of the curved metal components during the additive manufacturing process.

[0006] Specifically, this is achieved through the following technical solutions: In a first aspect, this application provides an additive manufacturing method for curved metal components, comprising: Construct a simulation model of multi-physics coupling for curved metal components; Based on the simulation results of the simulation model, multiple target partitions of each layer of the curved metal component are identified, the direction of the maximum principal stress corresponding to each target partition is determined, and the evolution curve of the molten pool temperature and time of each target partition in each layer is predicted. Based on the evolution curve, the electromagnetic vibration time window of each target partition in each layer after laser scanning cladding is determined. The target process parameters are determined based on the structural characteristics of the target partition; wherein, the target process parameters include preheating temperature, laser power, scanning speed and electromagnetic vibration frequency; The target zone's cladding area is preheated based on the preheating temperature; Laser scanning cladding is performed on the preheated area to be clad based on the laser power and the scanning speed. Within the electromagnetic vibration time window, the area to be clad is subjected to directional electromagnetic vibration at the electromagnetic vibration frequency. The direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress.

[0007] Secondly, this application provides an additive manufacturing system for curved metal components, comprising: The simulation module is used to construct a simulation model of the multi-physics coupling of curved metal components. Based on the simulation results of the simulation model, multiple target partitions of each layer of the curved metal component are identified, the direction of the maximum principal stress corresponding to each target partition is determined, and the evolution curve of the molten pool temperature versus time for each target partition in each layer is predicted. Based on the evolution curve, the electromagnetic vibration time window of each target partition after laser scanning cladding is determined. The corresponding target process parameters are determined based on the structural characteristics of the target partitions. The target process parameters include preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency. A preheating module is used to preheat the target cladding area of ​​the target partition based on the preheating temperature; A laser scanning cladding module is used to perform laser scanning cladding on the preheated area to be clad based on the laser power and the scanning speed. An electromagnetic vibration module is used to perform directional electromagnetic vibration on the area to be clad at the electromagnetic vibration frequency within the electromagnetic vibration time window; wherein the direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress. The simulation module outputs the preheating temperature to the preheating module, the laser power and the scanning speed to the laser scanning cladding module, and the electromagnetic vibration time window, the electromagnetic vibration frequency and the direction of the maximum principal stress to the electromagnetic vibration module.

[0008] As can be seen from the above, compared with the prior art, this application has the following beneficial technical effects: This application constructs a simulation model of multi-physics coupling of curved metal components. Based on the simulation results, it identifies multiple target partitions in each layer and determines the direction of the maximum principal stress corresponding to each target partition. It predicts the evolution curve of the molten pool temperature versus time for each target partition and determines the corresponding preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency according to the structural characteristics of each target partition. Based on the preheating temperature, the area to be clad in the target partition is preheated. Based on the laser power and scanning speed, the area to be clad is laser-scanned and clad. Within the electromagnetic vibration time window determined according to the evolution curve, the area to be clad is subjected to directional electromagnetic vibration at the electromagnetic vibration frequency, with the vibration direction perpendicular to the direction of the maximum principal stress. This ensures that the process parameters of each target partition in each stage of preheating, cladding, and electromagnetic vibration are matched with the temperature gradient and solidification shrinkage characteristics of that partition. The differences in temperature gradient and solidification shrinkage between regions are coordinated and controlled during the forming process, ensuring the forming accuracy and structural integrity of the component. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart illustrating an additive manufacturing method for curved metal components provided in this application embodiment; Figure 2 This is a schematic diagram illustrating the interrelationship of multiphysics coupling paths in the simulation model provided in the embodiments of this application; Figure 3 A schematic diagram illustrating the mapping relationship between target partition structure features and process parameters provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of an additive manufacturing system for curved metal components provided in an embodiment of this application. Detailed Implementation

[0011] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0012] Example 1 This application addresses the contradiction between the asynchronous dynamic changes in temperature gradients and solidification shrinkage in different regions and the overall structural integrity of the component during the additive manufacturing of curved metal components. It constructs a multi-physics coupled simulation model, configures differentiated process parameters for each region of the curved metal component based on the simulation results, and applies directional electromagnetic vibration within the liquid-solid coexistence time window after laser scanning cladding. This achieves coordinated control of temperature gradients and solidification shrinkage in each region, ensuring the forming accuracy and structural integrity of the component. It is primarily applicable to the additive manufacturing of curved metal components with differences in wall thickness, curvature, and internal structure in radar antennas, communication antennas, and aerospace applications.

[0013] like Figure 1 As shown in the figure, this application provides an additive manufacturing method for curved metal components, including the following steps: S1. Construct a simulation model of the multi-physics coupling of curved metal components.

[0014] S2. Based on the simulation results of the simulation model, identify multiple target partitions for each layer of the curved metal component.

[0015] S3. Determine the direction of the maximum principal stress for each target partition.

[0016] S4. Predict the evolution curve of the molten pool temperature and time for each target zone in each layer.

[0017] S5. Determine the electromagnetic vibration time window of each target partition in each layer after laser scanning cladding based on the evolution curve.

[0018] S6. Determine the corresponding target process parameters based on the structural characteristics of the target partition. The target process parameters include preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency.

[0019] S7. Preheat the target partition's cladding area based on the preheating temperature.

[0020] S8. Perform laser scanning cladding on the preheated area to be clad based on the laser power and the scanning speed.

[0021] S9. Within the electromagnetic vibration time window, perform directional electromagnetic vibration on the area to be clad at the electromagnetic vibration frequency. The direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress.

[0022] like Figure 1As shown, the execution order of steps S3, S4, and S6 can be sequential, such as S3-S4-S6, or they can be executed in parallel and synchronously; no limitation is made here. It should be noted that after step S9, when the area to be clad after laser scanning cladding undergoes directional electromagnetic vibration and the molten metal in the molten pool completely solidifies into a solid phase, that is, when the current component layer of the curved metal component has been additively formed, the additive manufacturing of the next component layer of the curved metal component is cyclically entered according to the pre-set 3D printing path. Step S2 is then returned, and the step of identifying multiple target partitions of each layer of the curved metal component based on the simulation results of the simulation model is re-executed until all component layers of the curved metal component have been additively formed. To determine how to determine if the molten metal in the molten pool has completely solidified into a solid phase, this embodiment of the application uses the end time after laser scanning cladding of each target zone in each layer as the starting point, and calculates the evolution curve of the center temperature of the molten pool of the target zone over time after laser scanning cladding. By determining the moment when the center temperature of the molten pool drops to the solidus temperature on the evolution curve, this moment is taken as the marker moment when the molten metal in the target zone completely solidifies into a solid phase after directional electromagnetic vibration following laser scanning cladding, i.e., the current component layer of the curved metal component has been additively formed. That is, if it is determined that the curved metal component has not yet been fully formed, additive manufacturing of the next component layer of the curved metal component begins from this moment, and the process returns to step S2. Here, the solidus temperature is the lower limit of the temperature at which the molten metal solution in the molten pool completely solidifies into solid metal after laser scanning cladding.

[0023] In this embodiment, step S1 is implemented as follows: First, a high-precision three-dimensional geometric model of the curved metal component is constructed using three-dimensional modeling software. The three-dimensional geometric model includes geometric information such as the wall thickness distribution, curvature distribution, location of hollow areas, and location of precision assembly features of the curved metal component. Then, the three-dimensional geometric model is meshed using finite element methods. The mesh size is 0.05–0.2 mm in thin-walled regions and 0.2–0.5 mm in thick-walled regions. Mesh refinement in thin-walled regions ensures simulation accuracy, while sparse meshing in thick-walled regions balances computational efficiency. Then, the governing equations for the temperature field, stress field, and solidification structure field, as well as their coupling terms, are defined. The three-dimensional geometric model is imported into a metal additive manufacturing simulation system to establish a multi-physics simulation model that includes the temperature field model, stress field model, and solidification structure field model. The temperature field model uses a transient heat conduction equation with a moving laser heat source, which is applied to the current cladding layer in the form of a Gaussian heat source. The stress field model employs a mechanical equilibrium equation containing thermal strain and solidification shrinkage strain terms. Thermal strain is calculated by multiplying the coefficient of thermal expansion by the temperature change. The solidification microstructure model uses a solidification kinetic equation describing the change in solid fraction with temperature. The solid fraction increases from 0 to 1 as the temperature decreases from the liquidus temperature to the solidus temperature.

[0024] The three physical field models mentioned above are not solved independently, but rather have a bidirectional interaction; a change in one physical field will, in turn, affect the other physical fields. In the embodiments of this application, the three physical field models are interconnected through four coupling paths. For example... Figure 2 As shown in the figure, the arrows connect the coupling paths, and the direction of the arrows indicates the coupling direction. The temperature field model provides thermal strain to the stress field model. This thermal strain is obtained by multiplying the coefficient of thermal expansion by the temperature change within the current time step. ;in, The coefficient of thermal expansion is... This is the change in temperature. This thermal strain The strain term in the mechanical equilibrium equations participates in stress calculations. The temperature field model provides the cooling rate to the solidification structure field model; the cooling rate is obtained by differentiating the temperature at the current time step with respect to time. The cooling rate R The solidification kinetics equations serve as inputs driving the evolution of the solidification fraction. The solidification microstructure model provides the latent heat of crystallization to the temperature field model. This latent heat is obtained by multiplying the latent heat of crystallization per unit mass by the rate of change of the solidification fraction, i.e. ;in, L The latent heat of crystallization per unit mass, The solid fraction; the latent heat of crystallization The term is superimposed as a heat source term into the transient heat conduction equation, allowing the latent heat released during solidification to be fed back into the temperature field model calculation, thus slowing down the local cooling rate. The solidification microstructure field model provides solidification shrinkage strain to the stress field model. Solidification shrinkage strain is obtained by multiplying the solidification shrinkage coefficient by the change in solid fraction, i.e. ;in, The solidification shrinkage coefficient is... This represents the change in solid fraction; the solidification shrinkage strain. The terms are superimposed into the mechanical equilibrium equations, so that the contribution of the volume contraction caused by the liquid-solid phase transition to the stress field can be reflected.

[0025] Among the four coupling paths mentioned above, the temperature field and the solidification structure field form a two-way coupling. That is, the temperature field drives the evolution of the solidification structure field, and the evolution of the solidification structure field releases the latent heat of crystallization, which is fed back to the temperature field. This two-way coupling is the core mechanism of the mutual coupling of multiple physical fields. If only the temperature field is considered to drive the solidification structure field in a one-way manner and the feedback of the latent heat of crystallization is ignored, the cooling rate of the thin-walled region will be overestimated, the temperature recovery effect will be omitted, and the electromagnetic vibration time window determined by simulation prediction for the coexistence of liquid and solid states in the molten pool will be too short, resulting in the electromagnetic vibration being applied too early, which will reduce the densification effect on the molten pool. For example, in the radar transceiver surface region with a curvature radius of 4 mm, when the laser scans this ultra-thin-walled region with a large curvature, the laser heat source input causes the local temperature to rise instantaneously above the melting point (above 600°C). However, the wall thickness of this region is only 0.5 mm, and the heat is quickly conducted to the surrounding thin walls, resulting in extremely fast heat dissipation. On the other hand, the adjacent thick-walled solid region dissipates heat slowly, and the temperature gradient can reach hundreds of°C / mm. The aforementioned temperature gradient causes the thin-walled region to cool and contract rapidly, while the adjacent thick-walled region remains in a state of high-temperature expansion. This generates significant tensile stress between the two, which is the direct cause of warping and cracking in the thin-walled region. Rapid cooling of the thin-walled region implies a rapid cooling rate... R Large, temperature gradient G It is also very large, tending to grow into coarse columnar crystals; while the thick-walled regions cool slowly. G / R Different ratios may result in the formation of equiaxed crystals. The solidification structure varies across different regions of the same component. The latent heat of crystallization released during solidification causes a temporary temperature rise in localized areas, slowing the cooling rate. This effect is particularly pronounced in thin-walled regions because their heat capacity is small, resulting in a relatively larger proportion of latent heat. During cooling and solidification, the volume contraction from liquid to solid generates additional shrinkage stress in thin-walled regions, which, superimposed on thermal stress, makes these areas sensitive to solidification shrinkage.

[0026] Finally, within the same time step, the three equations are solved simultaneously. The simulation model integrates all the coupling effects and outputs the temperature field distribution, stress field distribution, and solid fraction distribution of each region at each time step. The output of the previous time step is used as the input of the next time step, progressing layer by layer, until the complete evolution history of the temperature field, stress field, and solidification structure field of each target zone in each layer of the entire curved metal component during the forming process is obtained. In the embodiments of this application, the time step length can be 0.1~1ms.

[0027] By solving the temperature field, stress field, and solidification microstructure field in a two-way coupled manner, the temperature gradient, solidification shrinkage rate, and residual stress distribution of each region of a curved metal component during the forming process can be accurately predicted. This provides a data foundation for the subsequent identification of target zones and the determination of process parameters. Existing additive manufacturing processes typically employ single-temperature field simulation or thermo-mechanical unidirectional coupling simulation, which does not incorporate the latent heat feedback between the solidification microstructure field and the temperature field, nor the shrinkage strain coupling between the solidification microstructure field and the stress field. This results in the simulated temperature gradient, solidification shrinkage rate, and residual stress distribution deviating from the actual forming state, failing to provide a reliable basis for configuring differentiated process parameters.

[0028] Based on the temperature field distribution, stress field distribution, and solidification microstructure field distribution output by the above simulation model, physical field indices for each region of each layer are extracted, including temperature gradient, solidification shrinkage rate, and residual stress. The temperature gradient is calculated from the partial derivative of the temperature field model in the spatial direction, taking the maximum temperature change rate within the region, with units of ℃ / mm; the solidification shrinkage rate is calculated by multiplying the solid fraction change rate of the solidification microstructure field model by the solidification shrinkage coefficient, i.e. The unit is s -1 The residual stress is directly output from the stress field model, taking the equivalent stress value within the region, with units of MPa.

[0029] Then, the extracted physical field indices are judged for differences: whether the temperature gradient difference between adjacent regions exceeds the preset temperature gradient difference threshold, or whether the solidification shrinkage rate difference exceeds the preset solidification shrinkage rate difference threshold, or whether the residual stress difference exceeds the preset residual stress difference threshold.

[0030] If the above judgment is true, that is, if at least one of the differences in temperature gradient, solidification shrinkage rate, and residual stress between adjacent regions exceeds the corresponding preset difference threshold (preset temperature gradient difference threshold, preset solidification shrinkage rate difference threshold, or preset residual stress difference threshold), then the two adjacent regions are divided into different target partitions. It should be noted that the region mentioned in this embodiment refers to the region sequentially scanned and contacted by the 3D printer during laser scanning along the printing path. This is different from the target partitioning in step S2. By traversing all layers and all regions of the component, extracting the physical field indicators of each region, and then sequentially judging the differences in all regions, the target partitions of all layers of the component are obtained. For example, it can be denoted as q. 1-1 This indicates the first-level, first-class target partition of the component. Continuous physical field data is transformed into discrete partition labels.

[0031] For example, in this embodiment of the application, each layer of the component can be divided into three target zones: a high-curvature ultra-thin-walled zone, a structural stress concentration zone, and a solidification shrinkage sensitive zone. These three target zones may overlap, and the same location may belong to two or three zones simultaneously. For instance, the root of a high-curvature thin-walled area may be a high-curvature thin-walled zone, a stress concentration zone, and a solidification sensitive zone, but their respective identification dimensions are different. The specific identification criteria are as follows: 1. High-curvature ultrathin-walled region: Due to its small heat capacity, this type of region experiences a more dramatic temperature rise and faster cooling when the same amount of heat is applied by laser, making it prone to warping and cracking. Therefore, it needs to be identified and classified as a separate target zone. Geometrically, this zone has a wall thickness of 0.3–1 mm and a radius of curvature ≤ 5 mm. Thermally, this zone exhibits a large temperature gradient and a high cooling rate due to its thin wall structure.

[0032] 2. Structural Stress Concentration Zones: These areas are where residual stress peaks are located, making them high-risk zones for subsequent cracking and deformation. In simulations, the direction of the maximum principal stress in the target zone can be determined based on the residual stress distribution. In the stress field output from the simulation, the equivalent stress or maximum principal stress is significantly higher than the surrounding areas. Typical locations include areas of geometric abrupt changes such as wall thickness transition zones, the root of hollow edges, and around holes and slots.

[0033] 3. Solidification Shrinkage Sensitive Region: This region experiences the most severe volume shrinkage during solidification, which, combined with thermal stress, makes it a high-risk area for micropores and shrinkage defects. It is the region in the phase variable field output by the simulation that exhibits a solidification shrinkage strain rate exceeding a critical value. (Solidification rate) R A large region with a short liquid-solid window means that the solidification process is rapid and the shrinkage stress does not have time to relax.

[0034] Additionally, it should be noted that the aforementioned preset temperature gradient difference thresholds can be taken as the 75th percentile of the simulated global temperature gradient distribution output by the simulation model, the preset solidification shrinkage rate difference thresholds can be taken as the 75th percentile of the simulated global solidification shrinkage rate distribution, and the preset residual stress difference thresholds can be taken as the 75th percentile of the simulated global residual stress distribution. The physical field distribution in different regions of curved metal components is continuous. Using percentiles as dividing points can adapt to the physical field distribution patterns under different component geometric characteristics, avoiding the problem of fixed thresholds being inapplicable to different components. For example, for the outer shell of a curved aluminum alloy antenna for a meteorological phased array radar, the temperature gradient in the large curvature ultrathin wall region with a wall thickness of 0.3–1 mm is typically 500–1500 °C / mm, and the solidification shrinkage rate is 0.05–0.15 s. -1 The residual stress is 150~350MPa; while the temperature gradient in the flat, thick-walled region is typically 50~200℃ / mm, and the solidification shrinkage rate is 0.01~0.03s. -1The residual stress is 50~120MPa. The physical field indicators of the two types of regions differ significantly. By setting the difference thresholds for each physical field indicator using percentiles as the dividing point, the differences can be more effectively distinguished.

[0035] After completing the target partition identification, the stress tensor of each target partition is extracted from the stress field model; the stress tensor is a 3×3 symmetric matrix containing six independent components. , , , , , The stress tensor is decomposed into eigenvalues ​​to obtain three eigenvalues ​​and their corresponding eigenvector directions. The eigenvector direction corresponding to the largest eigenvalue is determined as the direction of the maximum principal stress corresponding to the target partition.

[0036] After identifying the target zones, the evolution curves of the molten pool temperature versus time for each target zone in each layer can be further predicted, and the electromagnetic vibration time window can be determined based on the evolution curves. Specifically, starting from the end time of laser scanning cladding for each target zone in each layer, the evolution curve of the molten pool center temperature of the target zone over time after laser scanning cladding is calculated. The calculation of the evolution curve is based on the transient heat conduction equation of the temperature field model, using the temperature field at the end of laser scanning cladding as the initial condition, and environmental convection and radiation as boundary conditions. The time step is 0.1~1ms, and the calculation duration is 5~10s. Then, the first time t1 when the molten pool center temperature drops to the liquidus temperature and the second time t2 when it drops to the solidus temperature are determined on the evolution curve. Here, the liquidus temperature is the upper limit of the temperature at which the metal is completely liquid, and the solidus temperature is the lower limit of the temperature at which the metal is completely solid. Taking aluminum alloy as an example, the liquidus temperature is approximately 635℃ and the solidus temperature is approximately 580℃. The first moment is typically 0.5–2 seconds after the laser scanning ends, and the second moment is typically 2–5 seconds after the laser scanning ends. The time interval between the first moment t1 and the second moment t2 is defined as the electromagnetic vibration time window [t1, t2] of the target zone after laser scanning cladding. This time window corresponds to the stage where the molten pool is in a liquid-solid coexistence state. At this time, the metal still has some fluidity, and applying electromagnetic vibration can effectively drive the flow of molten metal, avoiding excessive fluctuations in the molten pool and the generation of surface defects.

[0037] Optionally, the third time t3 corresponding to the temperature of the molten pool center dropping to 50°C below the liquidus temperature and the second time t2 corresponding to the temperature dropping to the solidus temperature are determined on the evolution curve. The time interval between the third time t3 and the second time t2 is defined as the electromagnetic vibration time window [t3, t2] of the target partition after laser scanning cladding. The supercooling effect near the liquidus line is considered, making the starting point of the electromagnetic vibration time window closer to the actual solidification start time of the metal in the molten pool.

[0038] The two methods for determining the electromagnetic vibration time window are as follows: the first method uses the first moment t1 corresponding to the liquidus temperature as the starting point, which is suitable for pure metals or alloys with a narrow solidification range; the second method uses the third moment t3 corresponding to 50°C below the liquidus temperature as the starting point, which is suitable for alloys with a wider solidification range. The appropriate method can be selected based on the material properties.

[0039] After target partition identification is completed, each identified target partition corresponds to a set of structural feature descriptions. Based on the structural features of each target partition in each layer of the component, the corresponding target process parameters are determined. The structural features of the target partition include wall thickness, curvature, temperature gradient, and solidification shrinkage rate. Specifically, the temperature gradient corresponding to the first target partition is greater than the temperature gradient corresponding to the second target partition, and the solidification shrinkage rate corresponding to the first target partition is greater than the solidification shrinkage rate corresponding to the second target partition; the wall thickness corresponding to the first target partition is less than a preset wall thickness threshold, and the wall thickness corresponding to the second target partition is greater than or equal to the preset wall thickness threshold; the laser power corresponding to the third target partition is less than the laser power corresponding to the fourth target partition, and the scanning speed corresponding to the third target partition is greater than the scanning speed corresponding to the fourth target partition; the temperature gradient corresponding to the third target partition is greater than a preset temperature gradient threshold. The temperature gradient corresponding to the fourth target zone is less than or equal to the preset temperature gradient threshold; wherein the preheating temperature corresponding to the fifth target zone is higher than the preheating temperature corresponding to the sixth target zone; wherein the solidification shrinkage rate corresponding to the fifth target zone is greater than the preset solidification shrinkage rate threshold, and the solidification shrinkage rate corresponding to the sixth target zone is less than or equal to the preset solidification shrinkage rate threshold; wherein the preheating and holding time corresponding to the seventh target zone is longer than the preheating and holding time corresponding to the eighth target zone; wherein the curvature corresponding to the seventh target zone is greater than the preset curvature threshold, and the curvature corresponding to the eighth target zone is less than or equal to the preset curvature threshold; the preheating and holding time is the duration for which the area to be clad maintains the preheating temperature after preheating.

[0040] The mapping relationship between specific structural features and process parameters is as follows: Figure 3 As shown in the figure, the left side represents the structural feature input, including wall thickness, curvature, temperature gradient, and solidification shrinkage rate; the middle side represents the mapping rules; and the right side represents the process parameter output, including laser power, scanning speed, preheating temperature, and preheating holding time. The arrows indicate the mapping direction. Wall thickness and curvature are geometric features, directly obtained from the 3D geometric model; temperature gradient and solidification shrinkage rate are physical features, extracted from the simulation results of the aforementioned simulation model.

[0041] The first set of mapping rules reflects the transmission relationship between geometric features and physical field features. The temperature gradient corresponding to a target region with a wall thickness less than a preset wall thickness threshold is greater than that of a target region with a wall thickness greater than or equal to the preset wall thickness threshold, and the corresponding solidification shrinkage rate is also greater than that of a target region with a wall thickness greater than or equal to the preset wall thickness threshold. The preset wall thickness threshold is 1 mm. Due to the small heat capacity of thin-walled regions, the temperature rise is more dramatic and the heat dissipation is faster when the same amount of heat is input by the laser, resulting in a larger temperature gradient, a higher cooling rate, and a greater solidification shrinkage rate. Taking the aluminum alloy curved antenna shell of a meteorological phased array radar as an example, the temperature gradient of a large-curvature ultra-thin-walled region with a wall thickness of 0.5 mm is 800~1500℃ / mm, and the solidification shrinkage rate is 0.08~0.15s. -1 The temperature gradient in the straight, thick-walled region with a wall thickness of 3 mm is 50~200℃ / mm, and the solidification shrinkage rate is 0.01~0.03s. -1 .

[0042] The second set of mapping rules reflects the mapping relationship between temperature gradient, laser power, and scanning speed. For target areas with temperature gradients greater than a preset temperature gradient threshold, the corresponding laser power is less than that of target areas with temperature gradients less than or equal to the preset temperature gradient threshold, and the corresponding scanning speed is greater than that of target areas with temperature gradients less than or equal to the preset temperature gradient threshold. The preset temperature gradient threshold is 300℃ / mm. Areas with large temperature gradients have a high risk of heat accumulation, requiring a reduction in heat input per unit length to suppress local overheating, heat accumulation, and grain coarsening. Heat input is determined by the ratio of laser power to scanning speed; reducing power and increasing speed can simultaneously reduce heat input from two directions. Taking an aluminum alloy curved antenna shell as an example, the laser power for ultra-thin-walled areas with large curvature is 135–187W, and the scanning speed is 1050–1200mm / s; for flat, thick-walled areas, the laser power uses a standard value of 180–220W, and the scanning speed uses a conventional value of 800–1000mm / s. Optionally, the power reduction ratio for the hollowed-out edge area is 15% to 25%, that is, a reduction of 15% to 25% from the standard power. This ratio can be selected within the range according to the geometric complexity of the hollowed-out edge.

[0043] The third set of mapping rules reflects the mapping relationship between solidification shrinkage rate and preheating temperature. Target zones with a solidification shrinkage rate greater than a preset solidification shrinkage rate threshold correspond to target zones with a preheating temperature higher than target zones with a solidification shrinkage rate less than or equal to the preset solidification shrinkage rate threshold. The preset solidification shrinkage rate threshold is set to 0.05s. -1A high solidification shrinkage rate means a rapid solidification process, leaving insufficient time for shrinkage stress to relax. Therefore, it's necessary to increase the preheating temperature to slow the cooling rate and extend the solidification window, allowing sufficient time for stress relaxation. Taking an aluminum alloy curved antenna shell as an example, the preheating temperature for the high-curvature, ultra-thin-walled region is 280~320℃; while the preheating temperature for the flat, thick-walled region is 150~200℃. The specific preheating temperature value is adjusted within a range based on the material's thermal conductivity and the component's wall thickness: the upper limit is used for materials with high thermal conductivity to compensate for rapid heat dissipation, such as aluminum alloy (approximately 167 W / (m·K); the lower limit is used for materials with low thermal conductivity, such as titanium alloy (approximately 7 W / (m·K)).

[0044] The fourth set of mapping rules reflects the mapping relationship between curvature and preheating and holding time. Target areas with curvature greater than a preset curvature threshold require longer preheating and holding times than target areas with curvature less than or equal to the preset curvature threshold. The preset curvature threshold is a curvature radius of 5mm. Preheating and holding time is the duration for which the area to be clad maintains its preheated temperature after preheating. Large curvature areas have short heat dissipation paths and rapid heat loss, requiring extended holding times to ensure sufficient heat penetration into the substrate, preventing preheating from only affecting the surface while the interior remains at a low temperature. For example, in a radar transceiver surface area with a curvature radius of 4mm, the preheating and holding time is extended by 0.2–0.5 seconds from the standard value (0.5–1s). This means maintaining the preheated temperature for 0.7–1.5 seconds after reaching the set value before initiating laser scanning cladding to enhance the stress buffering effect in thin-walled areas. For a flat, gently curved surface area with a curvature radius of 20mm, the preheating and holding time is taken from the standard value of 0.5–1s. It should be noted that the preheating mechanism moves synchronously with the laser printhead along the trajectory, preheating the area to be clad. This linkage method can be achieved using infrared heating, induction heating, or laser preheating. Infrared heating uses an infrared radiation heater with a wavelength of 1~10μm and a heating power density of 5~20W / cm²; induction heating uses a medium-frequency induction coil with a frequency of 20~100kHz, suitable for ferromagnetic materials; laser preheating uses a coaxial semiconductor laser with a power of 10~30W, coaxial with the main laser beam but with independently controlled power.

[0045] It should be noted that the mapping rules described in this application embodiment are not corresponding formulas, but a set of correspondence rules. Given a set of structural feature quantities, a set of process parameter quantities can be determined. A correspondence table between structural features and process parameters can be established in advance. The target partition and its corresponding structural features are identified through the above simulation model, and then the process parameters corresponding to the structural features of the partition are directly matched by looking up the table. Each target partition outputs a set of target process parameters (laser power, scanning speed, preheating temperature, and preheating holding time), and the target process parameters of all target partitions are summarized into the global process parameter set of the curved metal component.

[0046] In determining the electromagnetic vibration frequency, the frequency can be determined based on the slope of the evolution curve as temperature decreases within the electromagnetic vibration time window; wherein the electromagnetic vibration frequency is negatively correlated with the slope. The slope is calculated as the ratio of the temperature difference to the time difference between the start and end times of the electromagnetic vibration time window, expressed in °C / s. The electromagnetic vibration frequency decreases as the slope increases. A large slope indicates a fast solidification rate and a large solidification shrinkage rate, resulting in more intense solidification shrinkage. This region is a solidification shrinkage sensitive zone, where a lower frequency electromagnetic vibration is used to prolong the vibration duration and drive the molten metal in the pool to flow fully, filling the micropores created by shrinkage in this region. A small slope indicates a slow solidification rate and a small solidification shrinkage rate, indicating a slower solidification process. A higher frequency electromagnetic vibration is used to enhance dendrite fragmentation and refine the grains. Taking the curved aluminum alloy antenna shell as an example, the slope of the high-curvature ultrathin wall region is 200~500℃ / s, and the electromagnetic vibration frequency is 15~18Hz (lower limit of the 15~25Hz window); the slope of the flat thick wall region is 20~80℃ / s, and the electromagnetic vibration frequency is 20~25Hz (upper limit of the 15~25Hz window). The electromagnetic vibration amplitude is controlled within 0.05~0.1mm. This amplitude range, combined with the 15~25Hz frequency, ensures that the attenuation rate of the Lorentz force in the depth direction of the molten pool does not exceed 15%, ensuring uniform dendrite fragmentation across the entire thickness of the thin-walled region. The 15~25Hz frequency range can be determined through the aforementioned three-physics coupling simulation combined with the material's conductivity, permeability, and viscosity coupling characteristics within the liquid-solid window. At this frequency, the Lorentz force can penetrate deep into the molten pool to drive dendrite fragmentation, while avoiding standing wave disturbances on the molten pool surface above 25Hz and insufficient driving force below 15Hz.

[0047] This application's embodiments transform the output of the simulation model into a process parameter configuration scheme for executable 3D printing. This allows each identified target region to obtain preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency that match its temperature gradient and solidification shrinkage characteristics, eliminating differences in temperature gradient and solidification shrinkage between target regions at the parameter configuration level. Existing additive manufacturing processes use uniform process parameters for all regions, failing to differentiate between regions' geometric features and heat dissipation conditions. Uniform process parameters cannot adapt to these regional differences. This application's embodiments, through simulation-driven differentiated parameter configuration, match the process parameters of each region at each stage of preheating, cladding, and electromagnetic vibration with the region's temperature gradient and solidification shrinkage characteristics. Differences in temperature gradient and solidification shrinkage between regions are coordinated and controlled during the molding process, ensuring the molding accuracy and structural integrity of the component.

[0048] In this embodiment of the application, during the laser selective melting process, the laser is a localized, instantaneous heat source; that is, the area swept by the laser spot melts instantly, but cools rapidly after the laser moves away. For areas with large curvature and ultra-thin walls (as mentioned above, wall thickness is 0.3–1 mm), the heat capacity is extremely small, and the cooling rate is extremely high. However, for adjacent thick-walled areas, heat dissipation is slow. Thus, a huge temperature gradient forms between the thin-walled and thick-walled areas. The thin-walled area contracts rapidly, while the thick-walled area continues to expand, generating significant tensile stress between them. This is the direct cause of warping and cracking in the thin-walled area. Therefore, this embodiment of the application employs a dynamic preheating module linked to the laser printhead. The preheating module moves synchronously with the laser printhead along the curved printing trajectory, preheating the area to be melted before the laser scanning and melting. The preheating temperature is determined based on the process parameters corresponding to each target zone. As mentioned above, for areas with a large solidification shrinkage rate, the preheating temperature is controlled at 280–320°C; for areas with a small solidification shrinkage rate, the preheating temperature is 150–200°C. For areas with curvature greater than a preset curvature threshold, the preheating and holding time is extended by 0.2 to 0.5 seconds based on the standard value (0.5 to 1 s). Preheating can be achieved through infrared heating, induction heating, or laser preheating, or a combination thereof. Infrared heating uses halogen lamps or semiconductor infrared heaters with a heating power density of 5 to 20 W / cm²; induction heating uses medium-frequency induction coils with a frequency of 20 to 100 kHz, suitable for ferromagnetic metals; laser preheating uses a low-power coaxial laser pre-scan with a power of 10 to 30 W. This embodiment uses infrared heating as an example. The preheating module is installed in front of the laser printhead, maintaining a distance of 5 to 15 mm from the printhead, and moves synchronously with the printing trajectory. Preheating increases the base temperature of the area to be clad, reduces the temperature gradient during laser scanning cladding, slows down the cooling rate, thereby reducing the solidification shrinkage rate and buffering the shrinkage thermal stress generated by rapid cooling. For thin-walled areas, preheating can significantly reduce the temperature difference with adjacent thick-walled areas, effectively suppressing warping and cracking in thin-walled areas from the source. This method solves the problem of uneven thermal field distribution caused by differences in wall thickness in different regions. By conformal preheating, different thermal energy reserves are matched to regions with different heat dissipation capacities, compensating for the differences in heat dissipation. This makes the temperature curves of regions with different wall thicknesses tend to be similar during the cooling process after laser preheating, reducing the temperature difference from the source and making the overall thermal field distribution more balanced. It can be understood that laser selective melting is a layer-by-layer process. In a certain layer, the laser does not scan the entire layer at once, but scans one path at a time. The area to be melted refers to the part in front of the current position of the laser that is about to be scanned and melted but has not yet been melted. The forming process of each layer includes powder laying, laser scanning and melting, solidification, and then laying the next layer of powder, and so on. This is a conventional technology in existing 3D printing processes and will not be elaborated here.

[0049] Laser scanning cladding is performed on the preheated area to be clad based on the laser power and the scanning speed. Specifically, laser selective melting is performed according to the determined partitioning process parameters, with different combinations of laser power and scanning speed used for different target partitions. For areas with a temperature gradient greater than a preset temperature gradient threshold, the laser power is set to 135–187 W, and the scanning speed to 1050–1200 mm / s to reduce heat input per unit length and suppress heat accumulation and grain coarsening. For areas with a temperature gradient less than or equal to the preset temperature gradient threshold, the laser power is set to 180–220 W, and the scanning speed to 800–1000 mm / s to ensure forming efficiency and structural strength. The laser spot diameter is set to 50–100 μm, and the layer thickness to 20–50 μm.

[0050] After each layer of laser scanning cladding is completed, within the aforementioned defined electromagnetic vibration time window, the electromagnetic vibration module is activated to apply directional electromagnetic vibration to the current cladding area at the electromagnetic vibration frequency determined for the current target partition. Electromagnetic vibration is achieved through an electromagnetic exciter, whose magnetic field direction is adjusted according to the maximum principal stress direction corresponding to the current target partition, ensuring that the direction of the directional electromagnetic vibration is perpendicular to the maximum principal stress direction. The vibration amplitude is controlled between 0.05 and 0.1 mm. For example, taking the large curvature ultrathin wall region of an aluminum alloy curved antenna shell as an example, the maximum principal stress direction is along the tangential direction of the curved surface, and the electromagnetic vibration direction is perpendicular to the tangential direction of the curved surface, i.e., vibration is applied along the thin wall normal. Under vibration in this direction, the Lorentz force drives the molten pool metal to spread uniformly along the direction perpendicular to the maximum principal stress, promoting dendrite breakage and equiaxed crystal transformation, expelling internal microbubbles, and filling interlayer micropores. The electromagnetic vibration frequency is set at 15–25 Hz. For regions with a high solidification shrinkage rate (i.e., a steeper temperature drop), the lower limit of 15–18 Hz is used to prolong the vibration duration. For regions with a low solidification shrinkage rate (i.e., a steeper temperature drop), the upper limit of 20–25 Hz is used to enhance dendrite fragmentation. Electromagnetic vibration can be applied using either pulsed or alternating electromagnetic fields. Pulsed electromagnetic fields generate intermittent Lorentz forces through periodically switching the electromagnetic coil on and off, suitable for scenarios requiring controlled vibration duration. Alternating electromagnetic fields generate periodic Lorentz forces through continuous alternating current, suitable for scenarios requiring a stable vibration frequency. This embodiment uses an alternating electromagnetic field as an example. A 15–25 Hz alternating current is applied to the electromagnetic vibrator coil, generating an alternating Lorentz force perpendicular to the direction of maximum principal stress in the molten pool region. By applying directional electromagnetic vibration within the time window when the molten pool is in a liquid-solid coexistence state, the Lorentz force drives the molten pool metal flow, achieving dendrite fragmentation, equiaxed crystal transformation, and micropore filling, thereby refining the grains and increasing density. The vibration direction is perpendicular to the direction of maximum principal stress, making the direction of the vibration force orthogonal to the direction of residual stress concentration, which can alleviate stress concentration to the greatest extent. Existing technologies typically use cold mechanical vibration after printing, which cannot drive the flow of molten metal during solidification, resulting in limited densification effects. However, the embodiments of this application seize the time window when the molten pool is not completely solidified to apply electromagnetic vibration, achieving microstructure densification while the metal is still fluid, thus overcoming the limitation of existing technologies where cold vibration cannot intervene in the solidified structure.

[0051] In summary, the additive manufacturing method for curved metal components provided in this application addresses the contradiction between the asynchronous dynamic changes in temperature gradients and solidification shrinkage in different regions during the additive manufacturing process of curved metal components and the overall structural integrity of the component. It accurately predicts the temperature gradient, solidification shrinkage rate, and residual stress distribution in each region through multi-physics field coupling simulation, solving the problem that existing simulation methods cannot accurately predict asynchronous dynamic changes. Based on the simulation output, the component is divided into multiple target zones, and differentiated process parameters are configured for each zone, solving the problem that existing uniform process parameters cannot adapt to the differences in each region. Differentiated preheating reduces the temperature difference between regions, lowering the temperature gradient from the source. Differentiated laser power and scanning speed match the heat input and heat dissipation capacity of each region, controlling the solidification rate difference. Finally, directional electromagnetic vibration is applied within the liquid-solid coexistence window to eliminate microporosity and refine grains during solidification, suppressing the accumulation of residual stress. The technical solutions in this application constitute a complete technical chain of simulation prediction, zoning configuration, preheating buffer, differentiated cladding, and vibration densification, which enables the temperature gradient and solidification shrinkage of each region to be coordinated and controlled during the molding process, ensuring the molding accuracy and structural integrity of the components.

[0052] In one feasible implementation, the process parameters predicted by the simulation model are theoretical values. In actual printing, factors such as uneven powder distribution and fluctuations in protective airflow may cause the molten pool state to deviate from the predicted values. Therefore, this embodiment monitors the thermal radiation signal of the molten pool in real time during the laser scanning cladding process. When the fluctuation of the thermal radiation signal exceeds a preset fluctuation threshold, the preheating temperature and laser power of the area to be clad are adjusted. The thermal radiation signal is collected by a high-temperature colorimeter or infrared detector installed coaxially at the laser printhead, with a sampling frequency of 1000–5000 Hz. The fluctuation of the thermal radiation signal is characterized by calculating the standard deviation of the thermal radiation intensity within the monitoring window, with a monitoring window length of 0.1–0.5 s. When the standard deviation of the thermal radiation intensity exceeds ±5% of the average value within the monitoring window, it is determined that the thermal fluctuation exceeds the preset fluctuation threshold, triggering parameter fine-tuning. The fine-tuning range is ±3% to ±8% of the initial value: if the preheating temperature is fine-tuned by increasing, it can compensate for insufficient heat dissipation; if the laser power is fine-tuned by decreasing, it can reduce heat input. The specific fine-tuning range is selected within the range according to the degree of fluctuation. As can be seen from the above, by combining laser power and scanning speed differently for each region, the heat input per unit length in each region is matched with its heat dissipation capacity, avoiding overheating, grain coarsening, and surface warping caused by heat accumulation in thin-walled areas, while ensuring the forming efficiency of thick-walled areas. The purpose of the closed-loop feedback mechanism in this application embodiment is to dynamically adapt process parameters to the actual molten pool state through real-time monitoring and closed-loop fine-tuning, further ensuring the consistency of forming quality and the stability of the forming process.

[0053] In one feasible implementation, if the process parameters of adjacent zones change abruptly, new temperature gradient differences and solidification shrinkage differences will occur at the boundary. Therefore, embodiments of this application provide an overlap region at the boundary between two adjacent target zones. The width of the overlap region is determined based on the difference in preheating temperature and scanning speed between the two adjacent target zones; the greater the difference in preheating temperature and scanning speed, the wider the overlap region. For example, at the boundary between a high-curvature ultrathin-walled region (preheating temperature of 300°C, scanning speed of 1100 mm / s) and a flat thick-walled region (preheating temperature of 180°C, scanning speed of 900 mm / s), the preheating temperature difference is 120°C, the scanning speed difference is 200 mm / s, and the overlap region width is 3–5 mm. As another example, at the boundary between two adjacent flat thick-walled regions (preheating temperature difference < 20°C, scanning speed difference < 50 mm / s), the overlap region width is 0.5–1 mm. Within the overlap area, the preheating temperature and scanning speed are linearly transitioned from the process parameters of the target area where laser scanning cladding is performed first to the process parameters of the target area where laser scanning cladding is performed later.

[0054] The specific implementation of linear transition can be as follows: the overlapping area is divided into N segments along the scanning direction, where N takes the value [5~20]. The preheating temperature and scanning speed in each segment are calculated by linear interpolation, i.e. , .

[0055] in, , These are the process parameters for the target area where laser scanning cladding is performed first. , These are the process parameters for the target area to be clad using laser scanning, respectively. The sequence number of the sub-segment.

[0056] This application embodiment sets an overlapping area at the boundary of two adjacent target partitions. The overlapping area transitions through parameter gradual change, so that the temperature gradient and solidification shrinkage rate change continuously at the boundary, avoiding defects caused by new temperature gradient differences and solidification shrinkage differences due to parameter abrupt changes.

[0057] In one feasible implementation, the initial prediction of the simulation model is based on ideal conditions. However, due to factors such as interlayer heat accumulation and powder spreading deviation during actual forming, the actual state deviates from the predicted value. Therefore, in this embodiment, after each layer of laser scanning cladding and directional electromagnetic vibration is completed, the residual stress state and temperature field state of the simulation model are updated to the actual state of the currently formed component layer. Specifically, the actual temperature field distribution and residual stress distribution after the current layer is formed are used as the initial conditions for the calculation of the next layer in the simulation model, replacing the predicted value of that layer in the original simulation model. The actual state can be obtained as follows: the temperature field state is acquired in real time by an infrared thermal imager to collect the surface temperature field of the component and invert the internal temperature distribution; the residual stress state is measured online by X-ray diffraction or ultrasonic critical refraction longitudinal wave method to measure the residual stress on the component surface, and combined with the simulation model to invert the internal stress distribution. The updated simulation model is used to re-identify multiple target partitions of the next layer and redetermine the maximum principal stress direction, evolution curve, and electromagnetic vibration time window of each target partition in the next layer. That is, return to step S2 above, and identify multiple target partitions of each layer of the curved metal component based on the simulation results of the simulation model, such as... Figure 1 As shown. The layer-by-layer update mechanism in this embodiment keeps the simulation model synchronized with the actual forming state, ensuring the accuracy of target partition identification and process parameter configuration during the multi-layer stacking process of the component.

[0058] In one preferred embodiment, the densification effect evaluation data of electromagnetic vibration, including interlayer porosity and grain size, is fed back to the simulation model to update the process parameter set for subsequent layers, forming a closed-loop adaptive control throughout the entire process. In engineering, interlayer porosity and grain size data can be obtained through online metallographic testing or ultrasonic testing, and the simulation model parameters are corrected after comparison with the simulation prediction values.

[0059] Example 2 The above combination Figures 1-3 This application provides a detailed description of an additive manufacturing method for curved metal components, based on embodiments of the present application. The following, in conjunction with... Figure 4 This document describes in detail a curved metal component additive manufacturing system for implementing a curved metal component additive manufacturing method provided in the embodiments of this application. Figure 4 A schematic diagram of a curved metal component additive manufacturing system provided in this application embodiment; see reference Figure 4 The system includes: The simulation module 100 is used to construct a simulation model of the multi-physics coupling of curved metal components; based on the simulation results of the simulation model, it identifies multiple target partitions of each layer of the curved metal component, determines the direction of the maximum principal stress corresponding to each target partition, and predicts the evolution curve of the molten pool temperature versus time for each target partition in each layer; based on the evolution curve, it determines the electromagnetic vibration time window of each target partition after laser scanning cladding; and determines the corresponding target process parameters based on the structural characteristics of the target partitions; wherein, the target process parameters include preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency. The preheating module 200 is used to preheat the target partition's cladding area based on the preheating temperature; The laser scanning cladding module 300 is used to perform laser scanning cladding on the preheated area to be clad based on the laser power and the scanning speed. The electromagnetic vibration module 400 is used to perform directional electromagnetic vibration on the area to be clad at the electromagnetic vibration frequency within the electromagnetic vibration time window; wherein the direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress. The simulation module 100 outputs the preheating temperature to the preheating module 200, the laser power and the scanning speed to the laser scanning cladding module 300, and the electromagnetic vibration time window, the electromagnetic vibration frequency and the direction of the maximum principal stress to the electromagnetic vibration module 400.

[0060] The specific implementation method and technical effects of the additive manufacturing system for curved metal components are the same as those described above for an additive manufacturing method for curved metal components, and will not be repeated here.

[0061] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A method for additive manufacturing of curved metal components, characterized in that, include: Construct a simulation model of multi-physics coupling for curved metal components; Based on the simulation results of the simulation model, multiple target partitions of each layer of the curved metal component are identified, the direction of the maximum principal stress corresponding to each target partition is determined, and the evolution curve of the molten pool temperature versus time for each target partition in each layer is predicted. Based on the evolution curve, the electromagnetic vibration time window of each target partition after laser scanning cladding is determined. The corresponding target process parameters are determined based on the structural characteristics of the target partition. The target process parameters include preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency. The target zone's cladding area is preheated based on the preheating temperature; Laser scanning cladding is performed on the preheated area to be clad based on the laser power and the scanning speed. Within the electromagnetic vibration time window, the area to be clad is subjected to directional electromagnetic vibration at the electromagnetic vibration frequency; wherein, the direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress.

2. The additive manufacturing method for curved metal components according to claim 1, characterized in that, The simulation model includes a temperature field model, a stress field model, and a solidification structure field model; wherein, the temperature field model provides thermal strain and cooling rate to the stress field model and the solidification structure field model, respectively, and the solidification structure field model provides latent heat of crystallization and solidification shrinkage strain to the temperature field model and the stress field model, respectively.

3. The additive manufacturing method for curved metal components according to claim 2, characterized in that, The simulation results based on the simulation model identify multiple target partitions in each layer of the curved metal component, and determine the direction of the maximum principal stress corresponding to each target partition, including: Based on the simulation results of the simulation model, the temperature gradient, solidification shrinkage rate, and residual stress of each region in each layer of the curved metal component are extracted; adjacent regions where at least one of the differences in temperature gradient, solidification shrinkage rate, and residual stress exceeds a corresponding preset threshold are divided into different target partitions, resulting in multiple target partitions for each layer of the curved metal component; the stress tensor of each target partition is extracted from the stress field model; the stress tensor is decomposed into eigenvalues, and the direction of the eigenvector corresponding to the largest eigenvalue is determined as the direction of the largest principal stress corresponding to the target partition.

4. The additive manufacturing method for curved metal components according to claim 3, characterized in that, The method of predicting the evolution curve of the molten pool temperature and time for each target zone in each layer, and determining the electromagnetic vibration time window of each target zone after laser scanning cladding based on the evolution curve, includes: Starting from the end time of laser scanning cladding of each target zone in each layer, calculate the evolution curve of the center temperature of the molten pool of the target zone over time after laser scanning cladding; determine the first moment when the center temperature of the molten pool drops to the liquidus temperature and the second moment when it drops to the solidus temperature on the evolution curve; and determine the time interval between the first moment and the second moment as the electromagnetic vibration time window of the target zone after laser scanning cladding.

5. The additive manufacturing method for curved metal components according to claim 3, characterized in that, The structural features of the target partition include wall thickness, curvature, temperature gradient, and solidification shrinkage rate; Wherein, the temperature gradient corresponding to the first target partition is greater than the temperature gradient corresponding to the second target partition, and the solidification shrinkage rate corresponding to the first target partition is greater than the solidification shrinkage rate corresponding to the second target partition; wherein, the wall thickness corresponding to the first target partition is less than a preset wall thickness threshold, and the wall thickness corresponding to the second target partition is greater than or equal to the preset wall thickness threshold. Wherein, the laser power corresponding to the third target partition is less than the laser power corresponding to the fourth target partition, and the scanning speed corresponding to the third target partition is greater than the scanning speed corresponding to the fourth target partition; wherein, the temperature gradient corresponding to the third target partition is greater than a preset temperature gradient threshold, and the temperature gradient corresponding to the fourth target partition is less than or equal to the preset temperature gradient threshold; Wherein, the preheating temperature corresponding to the fifth target zone is higher than the preheating temperature corresponding to the sixth target zone; wherein, the solidification shrinkage rate corresponding to the fifth target zone is greater than a preset solidification shrinkage rate threshold, and the solidification shrinkage rate corresponding to the sixth target zone is less than or equal to the preset solidification shrinkage rate threshold. Wherein, the preheating and heat preservation time corresponding to the seventh target partition is longer than the preheating and heat preservation time corresponding to the eighth target partition; wherein, the curvature corresponding to the seventh target partition is greater than a preset curvature threshold, and the curvature corresponding to the eighth target partition is less than or equal to the preset curvature threshold; the preheating and heat preservation time is the duration for which the area to be clad maintains the preheating temperature after preheating.

6. The additive manufacturing method for curved metal components according to claim 1, characterized in that, Also includes: The electromagnetic vibration frequency is determined based on the slope of the decrease in temperature within the electromagnetic vibration time window of the evolution curve; wherein the electromagnetic vibration frequency is negatively correlated with the slope of decrease.

7. The additive manufacturing method for curved metal components according to claim 1, characterized in that, Also includes: During the laser scanning cladding process, the thermal radiation signal of the molten pool is monitored in real time. When the fluctuation of the thermal radiation signal exceeds a preset fluctuation threshold, the preheating temperature and the laser power of the area to be clad are adjusted.

8. The additive manufacturing method for curved metal components according to claim 1, characterized in that, Also includes: An overlap area is provided at the boundary of two adjacent target partitions; wherein, the width of the overlap area is determined according to the difference between the preheating temperature and the scanning speed of the two adjacent target partitions, and the greater the difference between the preheating temperature and the scanning speed, the greater the width of the overlap area; within the overlap area, the preheating temperature and the scanning speed linearly transition from the target partition where the laser scanning cladding is performed first to the target partition where the laser scanning cladding is performed later.

9. A method for additive manufacturing of curved metal components according to any one of claims 1 to 8, characterized in that, Also includes: After each layer of the curved metal component is formed, the residual stress state and temperature field state of the simulation model are updated to the actual state of the currently formed component layer, and the process returns to the step of identifying multiple target partitions of each layer of the curved metal component based on the simulation results of the simulation model.

10. An additive manufacturing system for curved metal components, characterized in that, include: The simulation module is used to build simulation models of multi-physics coupling of curved metal components; Based on the simulation results of the simulation model, multiple target partitions of each layer of the curved metal component are identified, the direction of the maximum principal stress corresponding to each target partition is determined, and the evolution curve of the molten pool temperature versus time for each target partition in each layer is predicted. Based on the evolution curve, the electromagnetic vibration time window of each target partition after laser scanning cladding is determined. The corresponding target process parameters are determined based on the structural characteristics of the target partition. The target process parameters include preheating temperature, laser power, scanning speed, and electromagnetic vibration frequency. A preheating module is used to preheat the target cladding area of ​​the target partition based on the preheating temperature; A laser scanning cladding module is used to perform laser scanning cladding on the preheated area to be clad based on the laser power and the scanning speed. An electromagnetic vibration module is used to perform directional electromagnetic vibration on the area to be clad at the electromagnetic vibration frequency within the electromagnetic vibration time window; wherein the direction of the directional electromagnetic vibration is perpendicular to the direction of the maximum principal stress. The simulation module outputs the preheating temperature to the preheating module, the laser power and the scanning speed to the laser scanning cladding module, and the electromagnetic vibration time window, the electromagnetic vibration frequency and the direction of the maximum principal stress to the electromagnetic vibration module.

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