A laser selective melting energy regulation method and system based on simulated thermal history

Abstract

This invention belongs to the technical field of additive manufacturing and discloses a method and system for controlling laser selective melting energy based on simulated thermal history. The method includes the following steps: S1. Setting the laser power P for selective laser melting of different regions of the workpiece slice layer at the current iteration number N. N Laser selective melting simulation was performed according to the set laser power to obtain the temperature of different regions at different times; a thermal history feature vector H was constructed using the temperature of each region at different times. N S2 calculates the error function using the obtained thermal history feature vector and the preset expected value of the thermal history feature vector; S3 calculates the laser power P of N+1 laser selective melting simulations according to the preset relationship using the error function. N+1 S4 N=N+1, return to step S1, until P N+1 =P N Or it can reach the maximum number of iterations. This invention solves the problem of poor processing quality and efficiency caused by unreasonable energy distribution in laser selective melting.

Description

Technical Field

[0001] This invention belongs to the field of additive manufacturing technology, and more specifically, relates to a method and system for controlling laser selective melting energy based on simulated thermal history. Background Technology

[0002] In laser selective melting (LSM) forming of parts, slag on the lower surface refers to excess material formed on the lower surface due to overmelting or the adhesion of powder particles. Slag formation is often caused by localized overheating due to a combination of improper laser process parameters and poor heat dissipation. The main goal of mitigating slag pool defects is to prevent overmelting and control the shape and size of the molten pool. Warping of thin-walled parts and shrinkage of large-sized parts during forming result in uneven thermal and shrinkage stresses exceeding the material's yield strength, leading to plastic deformation. The formation of these defects is closely related to thermal history; therefore, predicting the thermal history during part manufacturing and optimizing additive manufacturing process parameters based on this history is a key problem to be solved.

[0003] To address the issue of optimizing process parameters for laser selective deposition modeling (SDM), researchers in the field have proposed several solutions. Riensche et al. developed a graph-based temperature field calculation method. By controlling the laser power and dwell time of each layer via feedforward, they obtained conical overhanging parts with finer grains, higher hardness, and more complete geometry. Patent CN119772196A, developed by Gu Dongdong's team, addresses existing laser directional energy deposition (laser energy deposition) technology by applying auxiliary thermal and gas flow fields from a process perspective. Through a control unit, they maintain the substrate's temperature by insulating, cooling, and heating, and by ensuring a suitable atmosphere, thereby improving the temperature distribution in the additive manufacturing process, reducing the molten pool temperature gradient, improving forming defects, and enhancing performance. Patent CN120790957A, developed by Li Miaoquan of Northwestern Polytechnical University, describes a laser additive manufacturing method for strengthening and toughening nickel-based superalloys based on power reduction. This method improves the strength and plasticity of nickel-based superalloys by dynamically adjusting the laser power and interlayer cooling time.

[0004] The above methods have the following problems: they tend to focus on adjusting uniform process parameters for a single layer, rather than fine-tuning the process to the level of precision. Furthermore, controlling substrate temperature, airflow, or cooling time adds extra processing time, leading to reduced processing efficiency. Therefore, a control method that can improve both processing quality and efficiency is needed. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a laser selective melting energy control method and system based on simulated thermal history, which solves the problems of poor processing quality and processing efficiency caused by unreasonable energy distribution in laser selective melting.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for controlling laser selective melting energy based on simulated thermal history is provided, the method comprising the following steps: S1 sets the laser power P for selective laser melting of different regions of all sliced ​​layers of the workpiece to be formed at the current iteration number N. N The laser selective melting and forming process was simulated according to the set laser power to obtain the temperature of different regions at different times; the thermal history feature vector H was constructed using the temperature of each region at different times. N ; S2 calculates the error function using the obtained thermal history feature vector and the preset expected value of the thermal history feature vector. ; S3 utilizes the error function The laser power P is calculated according to the preset formula for N+1 laser selective melting simulations. N+1 ; S4 N=N+1, return to step S1, until P N+1 =P N Or it may reach the maximum number of iterations.

[0007] More preferably, the thermal history feature vector is:

[0008] in, It is the highest temperature in each controlled zone during the overall processing. The temperature at the end of each control zone Each control region starts from the solidus temperature of the material. Cooled to zero strain reference temperature The integral of temperature over time, Temperature reached in each control zone At that moment, Temperature reached in each control zone At that moment, The temperature gradient at the end of processing for each control region.

[0009] More preferably, the temperature gradient at the end of processing in each control region The calculation formula is as follows:

[0010] in, These represent the temperature gradients at the end of processing for each layer in each control region along the x, y, and z directions. These are the weights in the x, y, and z directions, respectively. .

[0011] More preferably, the error function is calculated using the following formula:

[0012] Where n is the dimension of the thermal history feature vector H, The first component of H , The second component of the thermal history eigenvector H , The third component of the thermal history eigenvector H The fourth component of the thermal history eigenvector H, These are weighting coefficients. It is the expected value of the i-th dimension of the thermal history feature vector.

[0013] More preferably, when N>1, the laser power P in the N+1th laser selective melting simulation is... N+1 The calculation formula is as follows:

[0014] in, Where is the laser power iteration step size, and F is the error function value. Let F be the expected value of the objective function, and abs(F) be the absolute value of F.

[0015] More preferably, when N=1, the laser power P in the N+1th laser selective melting simulation is... N+1 The calculation formula is as follows:

[0016] Where a and b are the slope and intercept of the line, respectively. It is the upper limit of laser power at the maximum scanning speed. It is the upper limit of laser power at the maximum scanning speed. It is the temperature at the end of the printing layer for each region. It is a lower limit value for temperature control set according to the material properties. It represents the maximum temperature at the end of the printing process for all regions.

[0017] More preferably, the formulas for calculating a and b are as follows: a=

[0018] b=

[0019] in, It is the upper limit of laser power at the maximum scanning speed. It is the upper limit of laser power at the maximum scanning speed. It is the temperature at the end of the printing layer for each region. It is a lower limit value for temperature control set according to the material properties. It represents the maximum temperature at the end of the printing process for all regions.

[0020] According to another aspect of the present invention, a laser selective melting energy control system based on simulated thermal history is provided, which is used to execute the laser selective melting energy control method based on simulated thermal history described above.

[0021] According to another aspect of the present invention, a computer storage medium is provided having a computer program stored thereon, which, when executed, is used to implement the above-described laser selective melting energy control method based on simulated thermal history.

[0022] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art: 1. This invention employs a simulation-based thermal history iteration scheme. By constructing an accurate thermal simulation model, the laser power during the forming process is iteratively optimized repeatedly. This eliminates the need for any additional online monitoring components on the actual processing equipment, saving on the costs of purchasing, installing, debugging, and maintaining monitoring equipment. It also avoids problems such as decreased monitoring accuracy and rapid equipment wear caused by complex operating conditions (high temperature, dust, laser interference) in online monitoring equipment. Furthermore, it simplifies the process operation, lowers the professional threshold for operators, and provides accurate simulation results, thus improving the poor processing quality and efficiency caused by unreasonable energy distribution in laser selective melting.

[0023] 2. This invention avoids powder adhesion caused by excessively high local temperatures by optimizing the first component Tmax of the thermal history feature vector. If the simulation predicts that Tmax in certain areas during the part forming process exceeds a threshold value, the laser power in that area is reduced, thereby reducing the amount of slag adhering to the underside of the part; the second component of the thermal history feature vector... Significantly affects the size of the molten pool; optimization To ensure uniform molten pool size in all regions, a larger molten pool size results in a larger contact area between the powder and the high-temperature molten pool, leading to a greater tendency for powder to slag. The third eigenvector of the thermal history eigenvector... It has a guiding role, and under other conditions remaining unchanged, It has superior mechanical properties.

[0024] 3. This invention can optimize the laser power of simulation models for different material properties (such as differences in melting point, thermal conductivity, specific heat capacity, etc. of metal powders) and different geometric models (such as complex irregular parts, thin-walled parts, large structural parts, and overhanging structures, etc.), so as to achieve rapid adaptation of different materials and different geometric parts. The entire adaptation process does not require major modification of processing equipment or re-development of process algorithms, which significantly reduces the cost of process migration, improves the versatility of equipment and process flexibility, and can meet the production needs of multiple varieties and small batches.

[0025] 4. This invention, through thermal history iterative simulation optimization, effectively reduces the overall temperature fluctuation amplitude and local temperature gradient during the forming process, achieving accurate control of laser power. On the one hand, controlling the laser power indirectly achieves temperature control, which significantly optimizes the slag formation phenomenon on the overhanging parts, reduces the amount of slag generated, lowers the workload of subsequent grinding, polishing and other post-processing steps, and improves the surface forming accuracy of the parts. On the other hand, by controlling a suitable temperature gradient, it can promote the refinement and uniform distribution of grains in the internal structure of the parts, effectively improving problems such as coarse grains and structural segregation, and significantly improving the key mechanical properties of the parts such as tensile strength, hardness, and toughness, ensuring that the parts can meet the stringent requirements of high-end equipment, precision manufacturing and other fields.

[0026] 5. This invention overcomes this predicament by employing techniques such as thermal simulation optimization and precise parameter control. While ensuring that the forming density of the parts fully meets industry standards and usage requirements, it adopts the highest processing speed achievable under current process conditions. Compared with existing technologies, the processing speed of this invention is significantly improved, effectively shortening the single-piece processing cycle, increasing production efficiency, and reducing the manufacturing cost per unit part. It can better adapt to the needs of large-scale and batch production, further enhancing the market competitiveness of the technology. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating a laser selective melting energy control method based on simulated thermal history, constructed according to a preferred embodiment of the present invention.

[0028] Figure 2 This is a schematic diagram showing the determination of the process control range constructed according to a preferred embodiment of the present invention.

[0029] Figure 3 These are conventional energy regulation paths constructed according to preferred embodiments of the present invention and energy regulation paths of the present invention, wherein (a) is a schematic diagram of prior art energy regulation paths and (b) is a schematic diagram of the energy regulation paths of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0031] A method for controlling the energy of laser selective melting based on simulated thermal history, comprising the following steps: S1 determines the control range of process parameters.

[0032] Process parameters include: printed layer thickness d, hatch spacing Laser power limit Lower limit and scanning speed .

[0033] The printing layer thickness d is determined based on the average powder particle size to ensure powder flowability and uniformity. The hatch spacing is determined based on the wall thickness of a single print pass. This ensures the overlap rate between the melt channels.

[0034] Orthogonal experiments were conducted to set the variation range and amplitude of various process parameters, such as determining the variation of laser power to be 10W and the variation of laser power to be 100mm / s.

[0035] Define the quality evaluation indicators, such as density, yield strength, roughness, hardness, etc. Density is selected by default.

[0036] Obtain the results of orthogonal experiments. Taking density as a quality evaluation index as an example. Figure 2 Determine the material processing range, find the range where the material density can reach 99%, and determine the maximum scanning speed within that range. It was determined that the density reached 99% and the scanning speed was within the range. The maximum value of the laser power is the upper limit of the adjustable laser power. The density was determined to be above 98%, at a scanning speed Below, the minimum laser power is the lower limit of the adjustable power. .

[0037] In one embodiment of the present invention, the selection range of parameters is shown in Table 1 below:

[0038] like Figure 2As shown in the figure, with laser power as the vertical axis and scanning speed as the horizontal axis, the processing effect ranges corresponding to different parameter combinations are defined: the lower right is the failure area with insufficient melting, the upper right is the spheroidization defect area, the upper left is the keyhole defect area, blue is the traditional process range, red dashed line is the test range, and green is the variable parameter extended process range; it shows the difference between the parameter range of the present invention and the traditional fixed parameter printing parameter range, and widens the size of the traditional fixed parameter printing range, providing more options for laser power optimization of the present invention.

[0039] S2 obtains the thermal history feature vector H.

[0040] For the part to be processed, the part is first divided into multiple slice layers, and each slice layer is divided into multiple laser control regions. Given the laser power of each laser control region, the laser selective melting process is simulated using simulation software to obtain the temperature change of each laser control region in each slice layer over time, thereby obtaining the temperature multidimensional feature vector of each control region.

[0041] The multidimensional feature vector H of all control regions in three-dimensional space:

[0042] The highest temperature in each control zone during the entire processing is the maximum temperature. Under excessively large overhanging structures, the surface tends to accumulate slag. Too low a residual stress results in excessive residual stress, while too high a residual stress leads to an unstable molten pool. For each control region, from the solidus temperature of the material Cooled to zero strain reference temperature The integral of temperature over time, Temperature reached in each control zone At that moment, Temperature reached in each control zone At that moment, excessively high residual stress is essentially due to the cooling rate and heat accumulation. The temperature gradient at the end of processing for each layer in each control region. for .

[0043]

[0044] The temperature gradient at the end of processing for each layer in each control region along different directions (x, y, z) S3 Iterative optimization of laser power Define the error function F(P), and the expected value of each component of the thermal history eigenvector. The calculation relationship of the error function F(P) is as follows:

[0045] n: the dimension of vector H, here n=4. The first component of H , The second component of H , The third component of H , The fourth component of H , representing each control region.

[0046] The laser power of each control region after S3 optimization is used as the input for the next thermal history simulation.

[0047] The optimized laser power of each control region is considered as A new thermal history is generated through simulation iterations applied to the additive manufacturing process.

[0048] Set the laser power iteration step size Set the expected value of the objective function Set the number of iterations n, and calculate the error function for each control region. ,according to Calculate each control region .

[0049] S4 Based on Print Layer Temperature Minimum control region laser power optimization (1) When the number of iterations is 1, the lower limit of the control temperature is set in the thermal history feature vector based on the fixed laser power input. Calculate the laser power for each control region as follows: :

[0050] a= b=

[0051] The maximum temperature value in all controlled areas is a and b are the slope and intercept of the line, respectively. The simulation is performed again according to the calculated laser power.

[0052] (2) When the number of iterations is greater than or equal to 2,

[0053] Where F represents the error function value for each control region. Let abs(F) be the allowed value of the objective function, and let abs(F) represent the absolute value of F.

[0054] S4.4 The number of iterations N = N + 1, until the power of the minimum control region is reached ( () or exceeds the number of iterations N.

[0055] S5 generates processing tasks The maximum control scanning vector length is determined based on the laser power determined in the above steps. The length of ls should be less than or equal to the machining accuracy, and can usually be set to 0.1mm.

[0056] Select parameters such as fill strategy, contour strategy, and fill gap for path planning, such as... Figure 3 (a) Conventional path. In this path, the red scanning vectors are connected end to end to form the outline of the part in the forming layer, and the black parallel scanning vectors are spaced at equal intervals. Some scanning vectors are longer and span the edge and center areas of the part. If such longer scanning vectors are given laser power for direct processing, the different processing parameters required for different areas cannot be reflected.

[0057] Divide the scan vector length to ensure it is less than Give scanning speed The power value P corresponding to the minimum control region calculated by thermal history iteration is used to obtain multiple energy control scanning vectors, as shown in the figure for energy control paths. Figure 3 (b) In this context, the scanning vector with laser power covers all parts locally. The laser power is lower at the edge of the overhanging contour, appearing blue, which helps reduce slag buildup. In the central area, the laser power is higher, which helps improve the mechanical properties of the adhesion between different layers.

[0058] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling laser selective melting energy based on simulated thermal history, characterized in that, The method includes the following steps: S1 sets the laser power P for selective laser melting of different regions of all sliced ​​layers of the workpiece to be formed at the current iteration number N. N The laser selective melting and forming process was simulated according to the set laser power to obtain the temperature of different regions at different times; the thermal history feature vector H was constructed using the temperature of each region at different times. N ; S2 calculates the error function using the obtained thermal history feature vector and the preset expected value of the thermal history feature vector. ; S3 utilizes the error function The laser power P is calculated according to the preset formula for N+1 laser selective melting simulations. N+1 ; S4 N=N+1, return to step S1, until P N+1 =P N Or it may reach the maximum number of iterations.

2. The laser selective melting energy control method based on simulated thermal history as described in claim 1, characterized in that, The thermal history feature vector is: in, It is the highest temperature in each controlled zone during the entire processing. The temperature at the end of each control zone Each control region starts from the solidus temperature of the material. Cooled to zero strain reference temperature The integral of temperature over time, Temperature reached in each control zone At that moment, Temperature reached in each control zone At that moment, The temperature gradient at the end of processing for each control region.

3. The laser selective melting energy control method based on simulated thermal history as described in claim 2, characterized in that, The temperature gradient at the end of processing in each control region The calculation formula is as follows: in, These represent the temperature gradients at the end of processing for each layer in each control region along the x, y, and z directions. These are the weights in the x, y, and z directions, respectively. .

4. A laser selective melting energy control method based on simulated thermal history as described in claim 1 or 3, characterized in that, The formula for calculating the error function is as follows: Where n is the dimension of the thermal history feature vector H, The first component of H , The second component of the thermal history eigenvector H , The third component of the thermal history eigenvector H The fourth component of the thermal history eigenvector H, These are weighting coefficients. It is the expected value of the i-th dimension of the thermal history feature vector.

5. A laser selective melting energy control method based on simulated thermal history as described in claim 1 or 3, characterized in that, When N>1, the laser power P in the N+1th laser selective melting simulation is... N+1 The calculation formula is as follows: in, Where is the laser power iteration step size, and F is the error function value. Let F be the allowable value of the error function, and abs(F) be the absolute value of F.

6. The laser selective melting energy control method based on simulated thermal history as described in claim 5, characterized in that, When N=1, the laser power P in the N+1th laser selective melting simulation is... N+1 The calculation formula is as follows: Where a and b are the slope and intercept of the line, respectively. It is the upper limit of laser power at the maximum scanning speed. It is the upper limit of laser power at the maximum scanning speed. It is the temperature at the end of the printing layer for each region. It is a lower limit value for temperature control set according to the material properties. It represents the maximum temperature at the end of the printing process for all regions.

7. The laser selective melting energy control method based on simulated thermal history as described in claim 6, characterized in that, The formulas for calculating a and b are as follows: a= b= in, It is the upper limit of laser power at the maximum scanning speed. It is the upper limit of laser power at the maximum scanning speed. It is the temperature at the end of the printing layer for each region. It is a lower limit value for temperature control set according to the material properties. It represents the maximum temperature at the end of the printing process for all regions.

8. A laser selective melting energy control system based on simulated thermal history, characterized in that, The system is used to perform the laser selective melting energy control method based on simulated thermal history as described in any one of claims 1-7.

9. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it is used to implement the laser selective melting energy control method based on simulated thermal history as described in any one of claims 1-7.

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