A method for reducing porosity defects in a multi-laser overlap area based on scan trajectory optimization

Abstract

The application discloses a method for reducing porosity defects in a multi-laser overlap area based on an optimized scanning track, comprising the following steps: obtaining optimized process parameters by calculating the density based on a set of laser process parameters through the Archimedes drainage method and porosity test; calculating the laser power threshold of the keyhole mode based on the normalized enthalpy theory, and determining that the molten pool is in the conduction mode if the actual laser power in the optimized process parameters is less than the laser power threshold; obtaining the porosity defect formation mechanism by online monitoring of high-speed cameras, SEM characterization based on the overlap area forming data under the optimized process parameters; constructing the overlap area porosity model based on the dynamic response law of a galvanometer, single-channel molten pool morphology data and a Gaussian heat source model; and analyzing the heat accumulation distribution of different scanning tracks according to the overlap area porosity model and in-situ thermal imaging monitoring results, and determining that the parallel-to-overlap scanning strategy of the multi-laser is the optimized scanning track to reduce the porosity defects.

Description

Technical Field

[0001] This invention belongs to the field of mechanical engineering, and in particular relates to a method for reducing porosity defects in multi-laser overlap areas based on scanning trajectory optimization. Background Technology

[0002] Laser bed fusion molding (LBD) technology, through CAD slicing and layer-by-layer printing, significantly improves design freedom and solves the problem of achieving high-quality forming of complex parts that is difficult to achieve using traditional casting and forging methods. Multi-laser LBD technology, while maintaining the high printing accuracy of traditional single-laser LBD systems, breaks through the limitations of forming size and significantly improves the forming efficiency of printed parts, further promoting the practical application of LBD technology in aerospace, defense, automotive engineering, and biomedicine. Currently, commercially available multi-laser LBD equipment can achieve up to 64 lasers working collaboratively. While improving processing efficiency, multi-laser LBD technology inevitably creates laser overlap areas. The more complex thermal history of these overlap areas results in differences in microstructure and mechanical properties compared to the independently scanned areas of a single laser, affecting the overall performance of the formed part. Therefore, studying the influence of the scanning trajectory on the thermal history of the laser overlap areas is of great significance for evaluating and analyzing the forming quality of these areas.

[0003] Existing research on multi-laser powder bed fusion forming technology, both domestically and internationally, largely focuses on thermal stress control and the impact of the overlap region on the mechanical properties of the formed specimens. Thermal stress control is based on optimized scanning strategies, altering the laser trajectory to avoid heat concentration. For example, the residual stress on the surface of specimens formed using bidirectional reciprocating scanning and checkerboard scanning strategies is significantly higher than that formed using 67° rotating scanning or orthogonal scanning strategies. Mechanical property studies focus on the microstructural differences between the overlap region and independent regions, revealing the relationship between thermal history, microstructure, and mechanical properties. However, there are few reports on the porosity defects caused by laser overlap. Due to the porosity defects in the overlap region, the fatigue life of laser-overlap formed specimens is significantly lower than that of single-laser formed specimens. Therefore, researching an optimized scanning trajectory is of great significance for suppressing porosity defects in multi-laser overlap regions and improving the quality of multi-laser overlap formed specimens.

[0004] Therefore, this invention proposes a method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization to address current problems. Ti-6Al-4V alloy, as a high-strength alloy, possesses excellent corrosion resistance and fatigue resistance, and is widely used in aerospace, defense, and other fields, making it an extremely important alloy system. This invention uses Ti-6Al-4V alloy as an example for research. Furthermore, this invention can also be extended to defect suppression in other alloy systems such as nickel-based alloys, 316L, copper alloys, aluminum alloys, and high-entropy alloys during multi-laser overlap forming processes in multi-laser powder bed melting technology.

[0005] This invention obtains optimized process parameters for laser powder bed fusion forming based on orthogonal experiments. It investigates the effects of scanning trajectory variations on the thermal history, porosity formation, and defect distribution of the formed part using thermal imaging, transmission electron microscopy, and CT imaging techniques. This invention enriches the research on the porosity defect formation mechanism in the overlapping region of multi-laser powder bed fusion forming technology, filling the current theoretical and technological gap regarding the defect formation mechanism and defect suppression in multi-laser overlapping regions. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization. Through orthogonal experiments, optimized process parameters are obtained, conduction modes are determined, the three major porosity mechanisms are revealed, and a porosity prediction model is constructed. Based on thermal imaging and CT comparison verification, a scanning strategy parallel to the overlap direction is determined as the optimized trajectory, reducing the number of defects to single digits and the defect diameter by 43%. This method can be widely applied to multi-laser powder bed melting forming systems such as nickel-based alloys, 316L, copper alloys, aluminum alloys, and high-entropy alloys, filling the theoretical and technological gap in defect suppression in multi-laser overlap regions.

[0007] A first aspect of the present invention provides a method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization, comprising: Based on the laser process parameter set, the density is calculated by Archimedes' drainage method and porosity test to obtain optimized process parameters; The laser power threshold for the keyhole mode is calculated based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. Based on the forming data of the overlapping area under optimized process parameters, the formation mechanism of pore defects was obtained by online monitoring with a high-speed camera and SEM characterization. A porosity model for the overlapping region was constructed based on the dynamic response law of the galvanometer, the morphology data of a single-channel molten pool, and the Gaussian heat source model. Based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, the heat accumulation distribution of different scanning trajectories was analyzed, and the multi-laser scanning strategy parallel to the overlapping direction was determined as the optimized scanning trajectory to reduce porosity defects.

[0008] Preferably, it further includes: using a 67° rotational scanning strategy as a comparison benchmark, driving the forming of the overlapping area sample using either a 67° rotational scanning strategy or a multi-laser parallel-overlapping-direction scanning strategy, and comparing the porosity defects of the 67° rotational scanning strategy and the parallel-overlapping-direction scanning strategy through X-CT imaging and surface observation.

[0009] Preferably, the step of obtaining the formation mechanism of pore defects through online monitoring with a high-speed camera and SEM characterization further includes: Optimized process parameters were adopted, and the monitoring results of the overlapping area forming process were monitored online by a high-speed camera. The characterization results after forming were observed by SEM characterization. The monitoring results included the dynamic behavior of the molten pool and the galvanometer response state, and the characterization results included the microstructure and trajectory misalignment phenomenon. Based on the monitoring and characterization results, the feature information of the overlapping area is obtained by identification. The feature information includes the overlapping area of ​​the molten pool, the shrinkage porosity at the laser start and stop position, and the instability characteristics of the molten pool at the overlapping step. Based on the aforementioned feature information, the formation mechanism of pore defects is determined by induction. The formation mechanism of pore defects includes laser overlap, shrinkage pores, and overlapping step effect as the formation mechanism of regional pore defects.

[0010] Preferably, the step of constructing the porosity model of the overlapping region further includes: The actual energy density is calculated based on the actual scanning speed, laser power, scanning spacing, and printing layer thickness. In the formula, The laser power, For scanning speed, For printing layer thickness, This refers to the scanning spacing; Based on the dynamic response law of the galvanometer, laser acceleration / deceleration correction coefficients and inflection point correction coefficients are constructed, and the actual scanning speed is calculated and obtained; Based on the actual energy density, the laser acceleration / deceleration correction coefficient, and the inflection point correction coefficient, the corrected actual energy density is obtained through deduction, and the calculation expression is as follows: In the formula, This refers to the actual scanning speed. For short vector weight coefficients, The weighting coefficients accumulated for the inflection point heat. For the actual turning point, This is the actual scan length. This is the critical scan length; Based on single-pass molten pool morphology data and actual energy density, the molten pool width and depth are obtained by power function fitting, and the porosity of a single laser molten pool is calculated. Based on the Gaussian heat source model and the dimensions of a single laser and an overlapping molten pool, the width enhancement coefficient and depth enhancement coefficient are obtained by calculating the width ratio and depth ratio of the equivalent single laser and the overlapping molten pool. A porosity prediction model for the overlapping region is constructed based on the porosity of the single-laser molten pool, the width enhancement coefficient, and the depth enhancement coefficient.

[0011] Preferably, the calculation expression for the laser acceleration / deceleration correction coefficient is: ; The formula for calculating the inflection point correction coefficient is as follows: In the formula, For the actual turning point, The weighting coefficients are used to indicate the impact of turning points. The expression for calculating the actual scanning speed is: .

[0012] Preferably, the expression for calculating the molten pool width is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool width, respectively; The formula for calculating the depth of the molten pool is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool depth, respectively. The formula for calculating the porosity of the single laser molten pool is as follows: In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. This represents the critical energy density value for the transition from conduction mode to keyhole mode. This is the weighting coefficient for heat accumulation.

[0013] Preferably, the expression for calculating the width enhancement factor is: In the formula, For the overlap position parameters, The width of the molten pool in the overlapping area. To enhance the width adjustment coefficient, For overlap rate or position parameters, This is the length normalization factor; The expression for calculating the depth enhancement coefficient is as follows: In the formula, , These are the depth attenuation factor and the depth enhancement amplitude coefficient, respectively. In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. , , These are the conduction mode index parameters, keyhole mode index parameters, and transition mode index parameters, respectively. For width enhancement index, For depth enhancement index, This represents the inflection point effect coefficient.

[0014] Preferably, the step of analyzing the heat accumulation distribution of different scanning trajectories further includes: Based on the porosity model of the overlapping area, the theoretical porosity of different scanning trajectories is calculated. The different scanning trajectories are formed by single-laser H-scanning strategy, dual-laser overlapping H-scanning strategy, 67° rotation scanning strategy or multi-laser scanning strategy parallel to the overlapping direction, and have different numbers of short vectors and inflection points. Based on the positive correlation between the number of short vectors and the number of inflection points and thermal accumulation, regions in the scanning center region, inflection point region, and laser overlap region where the theoretical porosity exceeds a preset threshold are identified as pore defect formation regions. In-situ thermal imaging monitoring was carried out to obtain actual heat accumulation distribution images under different scanning strategies, and the images were compared and verified with the theoretical porosity distribution. Based on the comparative verification results, the multi-laser scanning strategy parallel to the overlapping direction with the lowest heat accumulation and the lowest probability of pore formation was determined to be the optimal scanning strategy.

[0015] Preferably, the expression for calculating the laser power threshold in the keyhole mode is: In the formula, The diameter of the laser spot. For laser scanning speed, For printing layer thickness, Thermal conductivity, The boiling point temperature of the material. Where is the thermal diffusivity, denoted as the laser absorption coefficient.

[0016] A second aspect of the present invention provides a device for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization, comprising: The process parameter optimization module is used to obtain optimized process parameters based on the laser process parameter set by calculating the density through Archimedes' drainage method and porosity testing. The molten pool mode determination module is used to calculate the laser power threshold of the keyhole mode based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. The porosity mechanism acquisition module is used to acquire the porosity defect formation mechanism based on the overlapping area forming data under optimized process parameters through online monitoring with a high-speed camera and SEM characterization. The porosity modeling module is used to construct a porosity model of the overlapping region based on the dynamic response law of the galvanometer, the morphology data of a single melt pool, and the Gaussian heat source model. The scanning trajectory optimization module is used to analyze the heat accumulation distribution of different scanning trajectories based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, and determine the multi-laser scanning strategy parallel to the overlapping direction as the optimized scanning trajectory to reduce porosity defects.

[0017] Because of the above technical solutions, this invention has the following advantages and positive effects compared with the prior art: First, through online monitoring with a high-speed camera and SEM characterization, the formation mechanism of three major pore defects in multi-laser overlapping regions—laser overlap, shrinkage porosity, and overlapping step effect—was revealed for the first time, filling the theoretical gap in defect formation mechanism.

[0018] Second, based on the dynamic response law of the galvanometer, the morphology data of the single-channel molten pool and the Gaussian heat source model, a high-precision porosity prediction model for the overlapping area was established, which considers short vector correction, turning angle correction and geometric enhancement of the molten pool, thus realizing the quantitative prediction of porosity.

[0019] Third, based on the porosity model, the theoretical porosity of different scanning trajectories was calculated, and the heat accumulation distribution was verified by in-situ thermal imaging monitoring. The optimal scanning trajectory was determined to be parallel to the overlap direction, providing a clear principle for process optimization.

[0020] Fourth, through comparison and verification by X-CT imaging and surface observation, the scanning strategy parallel to the overlapping direction, compared with the traditional 67° rotation scanning strategy, reduced the number of defects in the overlapping area to single digits, and the average diameter of the defects decreased from about 35 μm to about 20 μm, a reduction of 43%, achieving near-pore-free forming.

[0021] Fifth, taking Ti-6Al-4V alloy as an example, this invention can be extended to multi-laser powder bed melting forming systems such as nickel-based alloys, 316L, copper alloys, aluminum alloys, and high-entropy alloys, filling the theoretical and technical gap in the suppression of defects in multi-laser overlapping areas. Attached Figure Description

[0022] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is the main flowchart of the method for reducing porosity defects in multi-laser overlap areas in this invention; Figure 2 This is a diagram illustrating the formation mechanism of pore defects in this invention. Figure 3 This is a diagram showing the distribution of pore defects in samples formed by single-laser and dual-laser overlap under different scanning trajectories in this invention. Figure 4 This is a diagram showing the distribution of pore defects in samples formed by single-laser and dual-laser overlap under different scanning trajectories in this invention. Figure 5 This refers to the number of defects and the average diameter of defects in the specimens formed by single-laser and dual-laser overlapping under different scanning trajectories in this invention. Detailed Implementation

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and use non-precise ratios, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0024] It should be noted that all directional indicators (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicator will also change accordingly.

[0025] See Figure 1 The first aspect of the present invention provides a method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization, comprising: S100: Based on the laser process parameter set, density is calculated using the Archimedes drainage method and porosity test to obtain optimized process parameters; S200: Calculate the laser power threshold of the keyhole mode based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. S300: Based on the forming data of the overlapping area under optimized process parameters, the formation mechanism of pore defects is obtained through online monitoring with a high-speed camera and SEM characterization. S400: A porosity model for the overlapping region is constructed based on the dynamic response law of the galvanometer, the morphology data of a single-channel molten pool, and the Gaussian heat source model. S500: Based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, analyze the heat accumulation distribution of different scanning trajectories, and determine the multi-laser scanning strategy parallel to the overlapping direction as the optimized scanning trajectory to reduce porosity defects.

[0026] S100: Determine the optimized process parameters for single-laser and laser-overlap forming of samples. This invention uses Ti-6Al-4V alloy as an example. Laser process parameters are closely related to forming quality: excessively high laser power and excessively low scanning speed can easily lead to over-melting, causing warping deformation and cracking; excessively low laser power and excessively high scanning speed can easily lead to under-fusion of powder, forming a large number of defects and reducing forming quality. Therefore, to achieve high-quality forming of multi-laser powder bed melting, it is necessary to first determine the optimized process parameters of the formed sample. The set of process parameters includes laser power, scanning speed, spot diameter, melt channel spacing, and printing layer thickness. Based on the dynamic performance and actual working conditions of the laser powder bed melting forming equipment, a suitable process window is selected through orthogonal experiments to optimize the process parameters. In this embodiment, by constructing process windows for two process parameters, laser power and scanning speed, a 10×10×10mm3 cube is printed. The density of the formed sample with different process parameters is determined based on Archimedes' drainage method and porosity. The process parameters used for the sample with the highest density are selected as the optimized process parameters. Other parameters can also be used; this embodiment does not impose any restrictions. S200: Determining the molten pool mode based on normalized enthalpy theory. This invention uses Ti-6Al-4V alloy as an example. Based on the optimized process parameters determined in step S100 and the inherent material properties of Ti-6Al-4V alloy, the laser power threshold required to form the keyhole mode is calculated using normalized enthalpy theory. The actual laser power in the optimized process parameters is compared with this threshold: if the actual laser power is less than the threshold, the molten pool is determined to be in conduction mode, and subsequent steps are continued; if the actual laser power is greater than or equal to the threshold, the molten pool is determined to be in keyhole mode, and step S100 is returned to redetermine the process window and a new round of process parameter optimization is carried out. S300: Determining the formation mechanism of porosity defects in the overlapping area. This invention uses Ti-6Al-4V alloy as an example. Under optimized process parameter conditions, a high-speed camera is used to monitor the forming process of the laser overlapping area online, and combined with scanning electron microscopy characterization, the formation mechanism of porosity defects in the overlapping area is determined. S400: Establish a porosity defect prediction model for single-laser and laser overlap processes. This invention uses Ti-6Al-4V alloy as an example. Based on the porosity defect formation mechanism in the laser overlap region determined in step S300, establish the correlation between laser start / stop and scanning transition and laser speed change, and then construct a porosity defect prediction model for single-laser and laser overlap processes. S500: Solve for the porosity defect formation probability of the scanning trajectory in the overlap region. This invention uses Ti-6Al-4V alloy as an example. Based on the porosity defect prediction model established in step S400, calculate the porosity defect formation probability of different scanning trajectories in the laser overlap region. S600: Determine the optimized scanning trajectory for multi-laser overlap regions. This invention uses Ti-6Al-4V alloy as an example.Based on the porosity comparison results obtained in step S500, the optimized scanning trajectory for the laser overlap region is determined. The combination of parameters to be tested is determined through orthogonal experiments. The actual density of the sample is measured using the Archimedes' displacement method, and the porosity is calculated and compared. The optimized process parameters with the lowest porosity are selected, laying the foundation for high-quality forming and avoiding over-melting or under-fusion defects caused by improper parameters. The keyhole mode threshold is calculated based on the normalized enthalpy theory, and it is verified that the actual laser power is less than this threshold, preventing the molten pool from entering the keyhole mode and suppressing the generation of porosity defects from the source. Through online monitoring with a high-speed camera and SEM characterization, the system identifies three porosity causes: laser overlap, shrinkage porosity, and overlap step effect, providing a theoretical basis for subsequent defect suppression. By integrating galvanometer dynamic response correction, single-pass molten pool morphology fitting, and the Gaussian heat source model, quantitative prediction of the porosity in the overlap region is achieved, providing computational support for scanning trajectory optimization. The theoretical porosity of different trajectories was calculated based on the porosity model, and the heat accumulation distribution was verified by in-situ thermal imaging. Finally, the scanning strategy parallel to the overlap direction was determined as the optimal trajectory, which effectively reduced porosity defects in the overlap area.

[0027] See Figure 4 and Figure 5 Preferably, S600 further includes: using a 67° rotation scanning strategy as a comparison benchmark, driving the forming of the overlapping area sample using either a 67° rotation scanning strategy or a multi-laser scanning strategy parallel to the overlapping direction, and comparing the porosity defects of the 67° rotation scanning strategy and the multi-laser scanning strategy parallel to the overlapping direction through X-CT imaging and surface observation.

[0028] Using the traditional 67° rotational scanning strategy (R strategy) as a benchmark, and based on the previously established model for the formation mechanism of porosity defects in the overlap region and the porosity prediction model, a multi-laser scanning strategy parallel to the overlap direction (Z strategy) is proposed, adhering to the core principle of reducing heat accumulation and molten pool oscillation in the overlap region. By forming samples in the overlap region using both the R and Z strategies, X-CT imaging and surface observation were used to quantitatively compare the distribution, number, and size of porosity defects under the two strategies, thus verifying the superiority of the Z strategy in suppressing porosity defects in the overlap region. Figure 4 As shown, there are significant differences in the distribution of pore defects under different scanning trajectories: the R strategy forms a large number of diffusely distributed pores in the overlapping area, while the Z strategy has very few pore defects. Figure 5Further verification confirmed that strategy R resulted in a large number of defects with an average diameter of approximately 35 μm, while strategy Z reduced the number of defects to single digits and the average diameter to approximately 20 μm. This comparative verification process not only confirmed the correctness of the porosity model and thermal accumulation analysis but also demonstrated the physical effectiveness of the multi-laser scanning strategy parallel to the overlap direction in reducing thermal accumulation and avoiding molten pool oscillation. X-CT imaging and surface observation provided a direct and visual experimental evidence for the "parallel to the overlap direction" optimization principle by visually comparing the porosity defect differences between strategies R and Z. After adopting strategy Z, the number of defects in the overlap area was reduced to single digits, achieving near-porosity-free forming; the average defect diameter decreased from approximately 35 μm to approximately 20 μm, a reduction of 43%, effectively suppressing the formation of large-sized pores. The experimental results highly matched the theoretical predictions in steps 4 and 5, proving the reliability of the porosity defect prediction model and thermal accumulation analysis method established in this invention. Using a 67° rotating scanning strategy as a benchmark, the shortcomings of the traditional strategy and the advantages of the optimized strategy are clearly demonstrated, providing a direct principle for the design of scanning paths parallel to the overlapping direction for multi-laser powder bed melting technology. The comparative verification process is simple and intuitive, and can be quickly extended to various material systems such as nickel-based alloys, 316L, copper alloys, aluminum alloys, and high-entropy alloys, as well as different models of multi-laser powder bed melting equipment.

[0029] See Figure 2 Preferably, the step of obtaining the formation mechanism of pore defects through online monitoring with a high-speed camera and SEM characterization further includes: Optimized process parameters were adopted, and the monitoring results of the overlapping area forming process were monitored online by a high-speed camera. The characterization results after forming were observed by SEM (Scanning Electron Microscope). The monitoring results included the dynamic behavior of the molten pool and the galvanometer response state, and the characterization results included the microstructure and trajectory misalignment phenomenon. Based on the monitoring and characterization results, the feature information of the overlapping area is obtained by identification. The feature information includes the overlapping area of ​​the molten pool, the shrinkage porosity at the laser start and stop position, and the instability characteristics of the molten pool at the overlapping step. Based on the aforementioned feature information, the formation mechanism of pore defects is determined by induction. The formation mechanism of pore defects includes laser overlap, shrinkage pores, and overlapping step effect as the formation mechanism of regional pore defects.

[0030] First, under optimized process parameters, a high-speed camera was used to monitor the dynamic behavior of the molten pool and the response state of the galvanometer during the forming process of the overlapping area. Simultaneously, SEM was used to observe the microstructure and trajectory misalignment phenomena after forming. The high-speed camera captured real-time changes in the molten pool, including pool overlap, oscillation, instability, and galvanometer start-stop and turning delays. SEM was used for high-resolution observation of the pore morphology and trajectory misalignment traces after solidification. Second, based on the above monitoring and characterization results, three types of characteristic information were identified: the molten pool overlap area was caused by galvanometer delay and random splicing; the shrinkage porosity at the laser start-stop position was formed by molten pool solidification shrinkage caused by laser start-stop; and the molten pool instability characteristics at the overlapping step were caused by the step effect in the overlapping area. Finally, through inductive reasoning, the above-mentioned characteristic information is respectively corresponding to three major porosity defect formation mechanisms: laser overlap mechanism, specifically: molten pool overlap, conduction mode to keyhole mode, and porosity; shrinkage porosity mechanism, specifically: laser start-stop, solidification shrinkage pre-defect, and porosity after remelting; and overlapping step effect mechanism, specifically: step structure, molten pool oscillation / instability, and defect formation. Figure 2 This is a schematic diagram illustrating the main causes of porosity defects in the overlapping area in an embodiment of the present invention. Figure 2 (a) in the figure illustrates the laser overlap mechanism, namely, the galvanometer delay and random splicing cause the molten pools of laser 1 and laser 2 to overlap, which drives the conduction mode to change to the keyhole mode; Figure 2 (b) demonstrates the shrinkage porosity mechanism, namely, the solidification shrinkage of the molten pool caused by laser start-stop to form pre-defects, which then form porosity during subsequent remelting; Figure 2 (c) demonstrates the lap step effect, where the step structure in the lap region leads to molten pool oscillation and instability, promoting the formation of pores or defects. Through collaborative monitoring and characterization using a high-speed camera and SEM, the three major pore defect formation mechanisms—laser overlap, shrinkage pores, and lap step effect—were accurately identified and summarized, providing a theoretical basis for porosity modeling and trajectory optimization, ultimately achieving near-pore-free forming of the lap region.

[0031] Preferably, the step of constructing the porosity model of the overlapping region further includes: The actual energy density is calculated based on the actual scanning speed, laser power, scanning spacing, and printing layer thickness. In the formula, The laser power, For scanning speed, For printing layer thickness, This refers to the scanning spacing; Based on the dynamic response law of the galvanometer, laser acceleration / deceleration correction coefficients and inflection point correction coefficients are constructed, and the actual scanning speed is calculated and obtained; Based on the actual energy density, the laser acceleration / deceleration correction coefficient, and the inflection point correction coefficient, the corrected actual energy density is obtained through deduction, and the calculation expression is as follows: In the formula, This refers to the actual scanning speed. For short vector weight coefficients, The weighting coefficients accumulated for the inflection point heat. For the actual turning point, This is the actual scan length. This is the critical scan length; Based on single-pass molten pool morphology data and actual energy density, the molten pool width and depth are obtained by power function fitting, and the porosity of a single laser molten pool is calculated. Based on the Gaussian heat source model and the dimensions of a single laser and an overlapping molten pool, the width enhancement coefficient and depth enhancement coefficient are obtained by calculating the width ratio and depth ratio of the equivalent single laser and the overlapping molten pool. A porosity prediction model for the overlapping region is constructed based on the porosity of the single-laser molten pool, the width enhancement coefficient, and the depth enhancement coefficient.

[0032] Considering the dynamic response of the galvanometer, a correction coefficient is established to obtain the actual scanning speed. Substituting the actual scanning speed into the energy density formula yields the corrected actual energy density, avoiding misjudgments of energy density caused by galvanometer acceleration and deceleration, making the model closer to the actual process. Single-pass molten pool experiments are used to fit the molten pool width and depth. Based on the molten pool mode, a single-laser porosity model is established. This model distinguishes between incomplete fusion defects and porosity defects and sets a critical energy density for mode switching. Based on the Gaussian heat source model and the material melting point, the molten pool width enhancement coefficient and depth enhancement coefficient of the overlapping region relative to the single-laser region are calculated. These two coefficients use the overlapping position parameter as the independent variable and employ a Gaussian function to describe the spatial distribution of the enhancement effect in the overlapping region. Multiplying the single-laser porosity model by the overlapping enhancement coefficient yields the porosity model of the overlapping region. This model comprehensively considers the galvanometer dynamic response, molten pool geometric nonlinear amplification, and overlapping position effects, enabling quantitative prediction of the porosity distribution of the overlapping region under different scanning trajectories. By introducing short vector correction coefficients and turning angle correction coefficients, the actual velocity changes during galvanometer start-up, shutdown, and turning were accurately quantified, significantly reducing the energy density calculation error and providing reliable input parameters for subsequent porosity prediction. A quantitative relationship between molten pool geometry and energy density was established. By fitting the relationship between molten pool width, depth, and actual energy density using a power function, process parameters were directly correlated with molten pool morphology, avoiding complex thermodynamic numerical simulations and achieving efficient and analytical molten pool size prediction. A quantitative characterization of the overlap effect was achieved. Width enhancement coefficients and depth enhancement coefficients were defined to describe the degree of molten pool geometry enhancement using the overlap position as a variable, revealing the spatial distribution law of heat accumulation in the overlap region and providing a mathematical tool for identifying high-probability porosity regions. The model decouples single-laser porosity from the overlap amplification effect, compatible with different porosity mechanisms in both conduction and keyhole modes, and reflecting the influence of the overlap position on porosity. The model showed good agreement with subsequent in-situ thermal imaging monitoring results, validating its prediction accuracy.

[0033] Preferably, the calculation expression for the laser acceleration / deceleration correction coefficient is: ; The formula for calculating the inflection point correction coefficient is as follows: In the formula, For the actual turning point, The weighting coefficients are used to indicate the impact of turning points. The expression for calculating the actual scanning speed is: .

[0034] Preferably, the expression for calculating the molten pool width is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool width, respectively; The formula for calculating the depth of the molten pool is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool depth, respectively. The formula for calculating the porosity of the single laser molten pool is as follows: In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. This represents the critical energy density value for the transition from conduction mode to keyhole mode. This is the weighting coefficient for heat accumulation.

[0035] By establishing short vector correction coefficients and turning angle correction coefficients, the velocity loss caused by galvanometer acceleration and deceleration when the scanning line segment is too short, and the deceleration effect caused by inertia when the scanning path turns, are quantified respectively. The actual scanning speed is obtained by multiplying the preset speed by these two correction coefficients, thus fully compensating for the velocity deviation caused by galvanometer start-up, shutdown, and turning. This correction improves the accuracy of the actual energy density calculation, making the porosity prediction closer to the actual process. Through power function fitting, the molten pool width and molten pool depth are correlated with the actual energy density. This relationship can be determined with only a few single-pass molten pool experiments, avoiding complex thermodynamic simulations, and can quickly and accurately predict the molten pool morphology under different process parameters, providing a reliable geometric input for subsequent porosity calculations. The single-laser molten pool porosity model adopts piecewise logic: when the actual energy density is lower than the critical value for the transition from the conduction mode to the keyhole mode, the contributions of unfused porosity and conduction mode porosity are mainly considered; when the energy density exceeds the critical value, the keyhole mode porosity contribution term is activated. This segmented model realistically reflects the physical laws governing insufficient energy leading to incomplete fusion, moderate energy resulting in dense microstructure, and excessive energy causing porosity. By adjusting the contribution of each mode through weighting coefficients and thermal accumulation coefficients, the porosity prediction possesses clear physical interpretability. Accurately correcting the scanning speed, actual energy density, molten pool geometry, and single-laser porosity is fundamental to calculating the overlap enhancement coefficient and final overlap porosity. The aforementioned calculation formulas ensure the accuracy of the underlying parameters, thereby guaranteeing the reliability and prediction accuracy of the porosity prediction model for the entire overlap region. All coefficients in the formulas can be obtained through standard experimental fitting, without relying on specific equipment models or dedicated software. This method can be rapidly deployed on various types of multi-laser powder bed melting equipment and can be widely applied to various material systems such as titanium alloys, nickel-based alloys, stainless steel, aluminum alloys, copper alloys, and high-entropy alloys.

[0036] Preferably, the expression for calculating the width enhancement factor is: In the formula, For the overlap position parameters, The width of the molten pool in the overlapping area. To enhance the width adjustment coefficient, For overlap rate or position parameters, This is the length normalization factor; The expression for calculating the depth enhancement coefficient is as follows: In the formula, , These are the depth attenuation factor and the depth enhancement amplitude coefficient, respectively. In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. , , These are the conduction mode index parameters, keyhole mode index parameters, and transition mode index parameters, respectively. For width enhancement index, For depth enhancement index, This represents the inflection point effect coefficient.

[0037] Both the width enhancement coefficient and the depth enhancement coefficient are used with the overlap position as the variable, and a Gaussian function is used to describe the spatial distribution of the enhancement effect in the overlap region. This is the first time that the precise quantification of the molten pool widening and deepening caused by the overlap has been achieved. The model allocates the porosity contributions of three modes—unfused, conduction mode, and keyhole mode—through weighting coefficients, and controls the nonlinear evolution law of each mode through independent exponential parameters. It can accurately predict the porosity changes from the insufficient energy to the moderate energy conduction mode, and then to the excessive energy keyhole mode and transition mode. The porosity contribution in the transition mode is corrected by the turning point influence coefficient, reflecting the physical fact that the increased heat accumulation at the turning point of the scanning path leads to an increase in the porosity probability, which significantly improves the prediction accuracy of the model for complex scanning trajectories. Based on this model, the theoretical porosity distribution under different scanning strategies can be quantitatively calculated, thereby selecting the optimized trajectory with the lowest heat accumulation and the lowest porosity probability. Experimental verification shows that by using a scanning strategy parallel to the overlap direction, the number of defects is reduced to single digits, the average defect diameter is reduced by 43%, and near-porosity-free forming is achieved.

[0038] See Figure 3 Preferably, the step of analyzing the heat accumulation distribution of different scanning trajectories further includes: Based on the porosity model of the overlapping area, the theoretical porosity of different scanning trajectories is calculated. The different scanning trajectories are formed by single-laser H-scanning strategy, dual-laser overlapping H-scanning strategy, 67° rotation scanning strategy or multi-laser scanning strategy parallel to the overlapping direction, and have different numbers of short vectors and inflection points. Based on the positive correlation between the number of short vectors and the number of inflection points and thermal accumulation, regions in the scanning center region, inflection point region, and laser overlap region where the theoretical porosity exceeds a preset threshold are identified as pore defect formation regions. In-situ thermal imaging monitoring was carried out to obtain actual heat accumulation distribution images under different scanning strategies, and the images were compared and verified with the theoretical porosity distribution. Based on the comparative verification results, the multi-laser scanning strategy parallel to the overlapping direction with the lowest heat accumulation and the lowest probability of pore formation was determined to be the optimal scanning strategy.

[0039] The established porosity model for the overlapping region shows that different scanning trajectories (single-laser H-scan, dual-laser overlapping H-scan, 67° rotation scan, and scan parallel to the overlapping direction) have different numbers of short vectors and inflection points. More short vectors and more inflection points result in higher acceleration and deceleration frequencies during laser start-up, stopping, and turning, leading to increased local heat accumulation. The theoretical porosity model can calculate the theoretical porosity value at each location in the overlapping region for each trajectory and identify areas exceeding a preset threshold as high-probability porosity defect formation areas. In-situ thermal imaging monitoring was conducted to record the temperature field distribution of the overlapping region in real time under different scanning strategies, obtaining images of the actual heat accumulation distribution. The actual heat accumulation distribution was compared with the theoretical porosity distribution to verify the accuracy of the model prediction. The comparison results show that areas with higher heat accumulation have a higher probability of porosity formation. Among several candidate scanning strategies, the scanning strategy parallel to the overlapping direction has the fewest short vectors and inflection points, resulting in the lowest heat accumulation and the lowest theoretical porosity; therefore, it was determined as the optimized scanning trajectory. See [link to relevant documentation] Figure 3 Taking single-laser and laser-overlapping H-scanning strategies as examples, the heat accumulation in the central region, inflection point region, and laser-overlapping region is significantly higher. In these regions, the molten pool mode is more likely to change from conduction mode to keyhole mode, significantly increasing the probability of porosity formation. Based on the porosity model, theoretical porosity is calculated and combined with preset thresholds to accurately locate high-risk positions in the scanning center, inflection points, and laser-overlapping region, providing clear spatial guidance for subsequent process adjustments. In-situ thermal imaging monitoring is used to obtain the actual heat accumulation distribution, which is then compared with the theoretical porosity distribution. This verifies the accuracy of the porosity model and enhances the credibility of the optimization conclusions. It is clearly pointed out that the more short vectors and inflection points there are, the greater the heat accumulation and the higher the probability of porosity. This provides a direct physical principle for scanning trajectory design: short vectors and inflection points should be minimized as much as possible. Based on the comparison results of the lowest heat accumulation and the lowest probability of porosity formation, a scanning strategy parallel to the overlap direction was finally selected. Experiments show that this strategy reduces the number of defects in the overlap region to single digits, and the average defect diameter decreases from approximately 35 μm to approximately 20 μm, a reduction of 43%, achieving near-porosity-free forming. It does not rely on specific equipment and can be quickly applied to multi-laser powder bed melting equipment of different material systems and different models by combining theoretical calculations with thermal imaging monitoring.

[0040] Preferably, the expression for calculating the laser power threshold in the keyhole mode is: In the formula, The diameter of the laser spot. For laser scanning speed, For printing layer thickness, Thermal conductivity, The boiling point temperature of the material. Where is the thermal diffusivity, denoted as the laser absorption coefficient.

[0041] S200 of this application determines the optimized process parameters based on step S100 as follows: powder layer thickness 30 μm, scanning spacing 70 μm, spot diameter 50 μm, laser power 175 W, and scanning speed 1050 mm / s. The laser power in the keyhole mode is in W, the laser spot diameter is in μm, the laser scanning speed is in mm / s, the thermal conductivity is in W / m / K, the boiling point temperature of the material is in K, and the thermal diffusivity is in m³ / s. 2 / s. This embodiment uses the above parameters, but other parameters can also be used; this embodiment is not limited. The laser power Pt in the keyhole mode is calculated to be 220W using this calculation expression, which is higher than the instantaneous incident laser power of 175W for a single laser. Therefore, the optimized process parameter molten pool mode is determined to be the conduction mode.

[0042] A second aspect of the present invention provides a device for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization, comprising: The process parameter optimization module is used to obtain optimized process parameters based on the laser process parameter set by calculating the density through Archimedes' drainage method and porosity testing. The molten pool mode determination module is used to calculate the laser power threshold of the keyhole mode based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. The porosity mechanism acquisition module is used to acquire the porosity defect formation mechanism based on the overlapping area forming data under optimized process parameters through online monitoring with a high-speed camera and SEM characterization. The porosity modeling module is used to construct a porosity model of the overlapping region based on the dynamic response law of the galvanometer, the morphology data of a single melt pool, and the Gaussian heat source model. The scanning trajectory optimization module is used to analyze the heat accumulation distribution of different scanning trajectories based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, and determine the multi-laser scanning strategy parallel to the overlapping direction as the optimized scanning trajectory to reduce porosity defects.

[0043] Through the collaborative work of the process parameter optimization module, molten pool mode determination module, porosity acquisition module, porosity modeling module, and scanning trajectory optimization module, a systematic end-to-end porosity defect control system, from parameter selection to trajectory decision-making, is achieved. This device can quantitatively predict the porosity distribution in the overlap region and, combined with in-situ thermal imaging verification results, accurately identify high-probability porosity formation areas. Ultimately, a scanning trajectory parallel to the overlap direction is determined as the optimized trajectory, reducing the number of defects in the overlap region to single digits and the average defect diameter to 43%, achieving near-porosity-free forming.

[0044] In the description of this application, it should be noted that the terms "inner" and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing this application and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0045] It should also be noted that, unless otherwise explicitly specified and limited, the terms "setup" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0046] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific identification content executed by the system and device described above can be referred to the corresponding process in the foregoing method embodiments.

[0047] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, if these changes fall within the scope of the claims of the present invention and their equivalents, they shall still fall within the protection scope of the present invention.

Claims

1. A method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization, characterized in that, include: Based on the laser process parameter set, the density is calculated by Archimedes' drainage method and porosity test to obtain optimized process parameters; The laser power threshold for the keyhole mode is calculated based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. Based on the forming data of the overlapping area under optimized process parameters, the formation mechanism of pore defects was obtained by online monitoring with a high-speed camera and SEM characterization. A porosity model for the overlapping region was constructed based on the dynamic response law of the galvanometer, the morphology data of a single-channel molten pool, and the Gaussian heat source model. Based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, the heat accumulation distribution of different scanning trajectories was analyzed, and the multi-laser scanning strategy parallel to the overlapping direction was determined as the optimized scanning trajectory to reduce porosity defects.

2. The method of claim 1, wherein, Also includes: Using a 67° rotational scanning strategy as a benchmark, samples of the overlapping area were shaped by either a 67° rotational scanning strategy or a multi-laser scanning strategy parallel to the overlapping direction. The porosity defects of the 67° rotational scanning strategy and the scanning strategy parallel to the overlapping direction were compared by X-CT imaging and surface observation.

3. The method of claim 1, wherein the method is based on a scan trajectory optimization to reduce porosity defects in a multi-laser overlap area. The steps of obtaining the formation mechanism of porosity defects through online monitoring with a high-speed camera and SEM characterization further include: Optimized process parameters were adopted, and the monitoring results of the overlapping area forming process were monitored online by a high-speed camera. The characterization results after forming were observed by SEM characterization. The monitoring results included the dynamic behavior of the molten pool and the galvanometer response state, and the characterization results included the microstructure and trajectory misalignment phenomenon. Based on the monitoring and characterization results, the feature information of the overlapping area is obtained by identification. The feature information includes the overlapping area of ​​the molten pool, the shrinkage porosity at the laser start and stop position, and the instability characteristics of the molten pool at the overlapping step. Based on the aforementioned feature information, the formation mechanism of pore defects is determined by induction. The formation mechanism of pore defects includes laser overlap, shrinkage pores, and overlapping step effect as the formation mechanism of regional pore defects.

4. The method of claim 1, wherein, The steps for constructing a porosity model for the overlap region further include: The actual energy density is calculated based on the actual scanning speed, laser power, scanning spacing, and printing layer thickness. In the formula, The laser power, For scanning speed, For printing layer thickness, This refers to the scanning spacing; Based on the dynamic response law of the galvanometer, laser acceleration / deceleration correction coefficients and inflection point correction coefficients are constructed, and the actual scanning speed is calculated and obtained; Based on the actual energy density, the laser acceleration / deceleration correction coefficient, and the inflection point correction coefficient, the corrected actual energy density is obtained through deduction, and the calculation expression is as follows: In the formula, This refers to the actual scanning speed. For short vector weight coefficients, The weighting coefficients accumulated for the inflection point heat. For the actual turning point, This is the actual scan length. This is the critical scan length; Based on single-pass molten pool morphology data and actual energy density, the molten pool width and depth are obtained by power function fitting, and the porosity of a single laser molten pool is calculated. Based on the Gaussian heat source model and the dimensions of a single laser and an overlapping molten pool, the width enhancement coefficient and depth enhancement coefficient are obtained by calculating the width ratio and depth ratio of the equivalent single laser and the overlapping molten pool. A porosity prediction model for the overlapping region is constructed based on the porosity of the single-laser molten pool, the width enhancement coefficient, and the depth enhancement coefficient.

5. The method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization according to claim 4, characterized in that, The calculation expression for the laser acceleration / deceleration correction coefficient is as follows: ； The formula for calculating the inflection point correction coefficient is as follows: In the formula, For the actual turning point, The weighting coefficients are used to indicate the impact of turning points. The expression for calculating the actual scanning speed is: 。 6. The method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization according to claim 4, characterized in that, The formula for calculating the width of the molten pool is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool width, respectively; The formula for calculating the depth of the molten pool is: In the formula, , These are the fitting coefficient and the exponential coefficient of the molten pool depth, respectively. The formula for calculating the porosity of the single laser molten pool is as follows: In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. This represents the critical energy density value for the transition from conduction mode to keyhole mode. This is the weighting coefficient for heat accumulation.

7. The method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization according to claim 4, characterized in that, The expression for calculating the width enhancement factor is as follows: In the formula, For the overlap position parameters, The width of the molten pool in the overlapping area. To enhance the width adjustment coefficient, For overlap rate or position parameters, This is the length normalization factor; The expression for calculating the depth enhancement coefficient is as follows: In the formula, , These are the depth attenuation factor and the depth enhancement amplitude coefficient, respectively. In the formula, , , These represent the weighting coefficients for unfused porosity, conduction mode porosity, and keyhole mode porosity, respectively. , , These are the conduction mode index parameters, keyhole mode index parameters, and transition mode index parameters, respectively. For width enhancement index, For depth enhancement index, This represents the inflection point effect coefficient.

8. The method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization according to claim 1, characterized in that, The steps for analyzing the heat accumulation distribution of different scan trajectories further include: Based on the porosity model of the overlapping area, the theoretical porosity of different scanning trajectories is calculated. The different scanning trajectories are formed by single-laser H-scanning strategy, dual-laser overlapping H-scanning strategy, 67° rotation scanning strategy or multi-laser scanning strategy parallel to the overlapping direction, and have different numbers of short vectors and inflection points. Based on the positive correlation between the number of short vectors and the number of inflection points and thermal accumulation, regions in the scanning center region, inflection point region, and laser overlap region where the theoretical porosity exceeds a preset threshold are identified as pore defect formation regions. In-situ thermal imaging monitoring was carried out to obtain actual heat accumulation distribution images under different scanning strategies, and the images were compared and verified with the theoretical porosity distribution. Based on the comparative verification results, the multi-laser scanning strategy parallel to the overlapping direction with the lowest heat accumulation and the lowest probability of pore formation was determined to be the optimal scanning strategy.

9. The method for reducing porosity defects in multi-laser overlap regions based on scanning trajectory optimization according to claim 1, characterized in that, The expression for calculating the laser power threshold in the keyhole mode is: In the formula, The diameter of the laser spot. For laser scanning speed, For printing layer thickness, Thermal conductivity, The boiling point temperature of the material. Where is the thermal diffusivity, denoted as the laser absorption coefficient.

10. A device for reducing porosity defects in multi-laser overlap areas based on scanning trajectory optimization, characterized in that, include: The process parameter optimization module is used to obtain optimized process parameters based on the laser process parameter set by calculating the density through Archimedes' drainage method and porosity testing. The molten pool mode determination module is used to calculate the laser power threshold of the keyhole mode based on the normalized enthalpy theory. If the actual laser power in the optimized process parameters is less than the laser power threshold, the molten pool is determined to be in the conduction mode. The porosity mechanism acquisition module is used to acquire the porosity defect formation mechanism based on the overlapping area forming data under optimized process parameters through online monitoring with a high-speed camera and SEM characterization. The porosity modeling module is used to construct a porosity model of the overlapping region based on the dynamic response law of the galvanometer, the morphology data of a single melt pool, and the Gaussian heat source model. The scanning trajectory optimization module is used to analyze the heat accumulation distribution of different scanning trajectories based on the porosity model of the overlapping area and the in-situ thermal imaging monitoring results, and determine the multi-laser scanning strategy parallel to the overlapping direction as the optimized scanning trajectory to reduce porosity defects.

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