A method and device for metal additive manufacturing control based on multi-dimensional molten pool characteristics

Abstract

The present application relates to the technical field of metal additive manufacturing, and particularly relates to a metal additive manufacturing control method and device based on multi-dimensional molten pool characteristics, comprising: acquiring morphological characteristic data of a molten pool in real time in a metal additive manufacturing process; obtaining target molten pool state parameters corresponding to current working condition parameters based on the current working condition parameters of the molten pool, wherein the current working condition parameters include a current printing layer number, a thermal history accumulation index and a preset scanning strategy; comparing the morphological characteristic data with the target molten pool state parameters dimension by dimension to obtain a comprehensive deviation index and a deviation trend index of the molten pool; obtaining a current deviation mode of the molten pool based on the comprehensive deviation index and the deviation trend index; and based on the deviation mode and the comprehensive deviation index, adjusting at least two different process parameters in linkage to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process. The above technical solution can improve the regulation effect and regulation accuracy of the molten pool state.

Description

Technical Field

[0001] This invention relates to the field of metal additive manufacturing technology, and in particular to a metal additive manufacturing control method and apparatus based on multi-dimensional molten pool characteristics. Background Technology

[0002] Metal additive manufacturing is an advanced manufacturing technology that shapes parts by melting metal powder or wire layer by layer. During the forming process, the molten pool is the core area for energy input and material melting, and its shape directly determines the quality and performance of the final part.

[0003] In existing technologies, fixed molten pool width, area, or temperature thresholds are typically used as target values ​​to adjust the state of the molten pool in real time. However, fixed target values ​​cannot adapt to changes in operating conditions under different layers, different structural regions, and different thermal histories. Feedback control based solely on a single indicator such as molten pool width or temperature peak cannot fully reflect the comprehensive stability of the molten pool, resulting in a rather one-sided state monitoring result. Consequently, the control effect and accuracy of state regulation based on this monitoring result are poor.

[0004] Therefore, those skilled in the art urgently need to develop a new technical solution to address the above problems. Summary of the Invention

[0005] This invention provides a metal additive manufacturing control method and apparatus based on multi-dimensional molten pool characteristics, which can improve the control effect and accuracy of molten pool state.

[0006] In a first aspect, embodiments of the present invention provide a metal additive manufacturing control method based on multi-dimensional molten pool characteristics, comprising: In the process of metal additive manufacturing, the morphological feature data of the molten pool is acquired in real time. The morphological feature data includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation and molten pool center offset. Based on the current operating parameters of the molten pool, target molten pool state parameters adapted to the current operating parameters are obtained. The current operating parameters include the current number of printing layers, thermal history accumulation index, and preset scanning strategy. The morphological feature data is compared with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool. Based on the comprehensive deviation index and the deviation trend index, the current deviation pattern of the molten pool is obtained; Based on the deviation mode and the comprehensive deviation index, at least two different process parameters are adjusted in a coordinated manner to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

[0007] Secondly, embodiments of the present invention provide a metal additive manufacturing control device based on multi-dimensional molten pool characteristics, comprising: The morphological data acquisition module acquires morphological feature data of the molten pool in real time during the metal additive manufacturing process. The morphological feature data includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset. The state parameter acquisition module is connected to the morphology data acquisition module. Based on the current operating condition parameters of the molten pool, it obtains the target molten pool state parameters that are adapted to the current operating condition parameters. The current operating condition parameters include the current number of printing layers, thermal history accumulation index, and preset scanning strategy. The comprehensive deviation acquisition module is connected to the state parameter acquisition module. It compares the morphological feature data with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool. The deviation pattern acquisition module is connected to the comprehensive deviation acquisition module, and obtains the current deviation pattern of the molten pool based on the comprehensive deviation index and the deviation trend index. The molten pool state adjustment module is connected to the deviation mode acquisition module. Based on the deviation mode and the comprehensive deviation index, it performs linkage adjustment on at least two different process parameters to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

[0008] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect of the present invention.

[0009] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method described in the first aspect of the present invention.

[0010] The present invention provides a metal additive manufacturing control method and apparatus based on multi-dimensional molten pool characteristics. This method dynamically generates target molten pool state parameters according to the current number of printing layers, accumulated thermal history, and scanning strategy. This allows the target molten pool state parameters to flexibly adapt to different working conditions, generating more accurate and reasonable target values ​​for the current working condition. By acquiring morphological feature data in four dimensions, the method overcomes the incompleteness of feedback from a single indicator. Furthermore, by comprehensively calculating the overall deviation based on the morphological data from the four dimensions, it comprehensively reflects the overall stability of the molten pool, improving the accuracy and comprehensiveness of the detection results. Specific molten pool deviation patterns are identified based on the combination of deviations in each dimension, and at least two process parameters are adjusted in a linked manner based on these deviation patterns. This adjustment method is more flexible and targeted, improving the control effect and accuracy of the molten pool state. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart of a metal additive manufacturing control method based on multi-dimensional molten pool characteristics provided in an embodiment of the present invention; Figure 2 This is a structural diagram of a metal additive manufacturing control device based on multi-dimensional molten pool characteristics, provided by an embodiment of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0014] Please refer to Figure 1 This invention provides a metal additive manufacturing control method based on multi-dimensional molten pool characteristics, the method comprising: Step 100: Acquire morphological feature data of the molten pool in real time during the metal additive manufacturing process; The morphological characteristics data include: molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset; Step 102: Based on the current operating parameters of the molten pool, obtain the target molten pool state parameters that are adapted to the current operating parameters; The current operating parameters include the current number of printed layers, thermal history accumulation index, and preset scanning strategy; Step 104: Compare the morphological feature data with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool; Step 106: Based on the comprehensive deviation index and the deviation trend index, obtain the current deviation pattern of the molten pool; Step 108: Based on the deviation mode and the comprehensive deviation index, at least two different process parameters are adjusted in a coordinated manner to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

[0015] In this embodiment, during the metal additive manufacturing process, at least one sensor is used to collect molten pool state data in real time. These sensors include, but are not limited to, coaxial vision cameras, side-axis high-speed cameras, infrared thermal imagers, photodetectors, laser reflection signal collectors, molten pool radiation sensors, and temperature field acquisition devices. The collected molten pool state data undergoes image processing, signal processing, and multi-source fusion processing to extract molten pool morphological features. These features include molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset. The current number of printed layers, thermal history accumulation index, and a preset scanning strategy are obtained as operating parameters. The current number of printed layers refers to the number of layers being printed. The thermal history accumulation index is calculated by weighted summation of the molten pool temperatures from the previous several layers. The scanning strategy code is determined based on the current printing area (different code values ​​correspond to contour boundary areas, solid filling areas, or island scanning areas). Based on these operating parameters, the current target molten pool state parameters are dynamically generated to characterize the standard values ​​of the molten pool state at the current number of printed layers. The molten pool width, peak temperature, fluctuation, and center offset are compared with the molten pool state parameters to obtain the relative deviation of the molten pool morphology in each dimension. The relative deviations in each dimension are weighted and summed to obtain a comprehensive deviation index, and a deviation trend index is derived from this comprehensive deviation index. Based on the combination of relative deviations in each dimension, the magnitude of the comprehensive deviation index, and the direction and duration of the deviation trend index, the current deviation mode is identified. Deviation modes include insufficient energy deviation, over-melting deviation, and boundary instability deviation. According to the identified deviation mode, the corresponding coordinated adjustment rules are invoked: if it is determined to be an insufficient energy deviation, the laser scanning power is increased and the scanning speed is decreased; if it is determined to be an over-melting deviation, the laser scanning power is decreased and the scanning speed is increased; if it is determined to be a boundary instability deviation, the laser scanning power is decreased and the powder feed is reduced. After adjustment, the molten pool state is monitored, and the above steps are repeated until the relative deviation between the measured molten pool morphology characteristics and the target molten pool state parameters is less than a threshold. This achieves closed-loop control of the metal additive manufacturing process, maintains molten pool stability, and reduces the probability of defects such as incomplete fusion, over-melting, and morphological instability.

[0016] In one embodiment of the present invention, morphological feature data is compared dimension-by-dimensionally with the target molten pool state parameters to obtain a comprehensive deviation index and a deviation trend index for the molten pool, including: The real-time molten pool state vector is compared with the target molten pool state vector dimension by dimension to obtain the relative deviation of each dimension. The relative deviation of each dimension is expressed by the following formula:

[0017] This represents the relative deviation of each dimension. Data representing the morphological characteristics of the molten pool. Indicates the target molten pool state parameters; Based on the relative deviation of each dimension, the comprehensive deviation index of the molten pool is obtained, which is expressed by the following formula:

[0018] Indicates the overall deviation index, Indicates the relative deviation of the molten pool width. This indicates the relative deviation of the peak temperature of the molten pool. This indicates the relative deviation of the fluctuation at the edge of the molten pool. This indicates the relative deviation of the molten pool center offset. The weighting coefficient representing the width of the molten pool. The weighting coefficient represents the peak temperature of the molten pool. The weighting coefficients representing the volatility at the edge of the molten pool. The weighting coefficient represents the offset of the molten pool center. ; Based on the comprehensive deviation index of the molten pool, a deviation trend index is obtained, which is expressed by the following formula:

[0019] Indicators representing deviation trends This indicates the preset time window.

[0020] In this embodiment, the real-time molten pool state vector and the target molten pool state vector are compared dimension by dimension to obtain the relative deviation of each dimension. The real-time molten pool state vector includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset; the target molten pool state vector includes the corresponding target molten pool width, target molten pool peak temperature, target molten pool edge fluctuation, and target center offset. Based on the relative deviation of each dimension, a comprehensive deviation index of the molten pool is obtained, which characterizes the degree to which the molten pool deviates from the target state. In the formula for calculating the comprehensive deviation index, the weighting coefficients of the molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset are added together to equal 1. The magnitude of the weighting coefficients is predetermined according to the degree of influence of the corresponding feature on the stability of the molten pool; features with greater influence are assigned higher weights.

[0021] Based on the comprehensive deviation index of the molten pool, a deviation trend index is obtained to characterize the trend of the molten pool state over time. When the deviation trend index is positive, it indicates that the molten pool state is gradually deviating from the target state parameter; when the deviation trend index is negative, it indicates that the molten pool state is gradually returning to the target state parameter; when the deviation trend index is zero or close to zero, it indicates that the molten pool state is currently stable.

[0022] In one embodiment of the present invention, the current deviation pattern of the molten pool is obtained based on a comprehensive deviation index and a deviation trend index, including: When the relative deviation of the molten pool width is negative and the absolute value is greater than the first preset threshold, and the relative deviation of the peak molten pool temperature is negative and the absolute value is greater than the second preset threshold, the current deviation mode of the molten pool is determined to be an energy-deficient deviation. When the relative deviation of the molten pool width is positive and greater than the third preset threshold, the relative deviation of the peak temperature of the molten pool is positive and greater than the fourth preset threshold, and the relative deviation of the fluctuation of the molten pool edge is positive and greater than the fifth preset threshold, the current deviation mode of the molten pool is determined to be an over-melting deviation. When the relative deviation of the molten pool edge fluctuation is positive and greater than the sixth preset threshold, the absolute value of the relative deviation of the molten pool temperature peak is less than the seventh preset threshold, and the absolute value of the relative deviation of the molten pool center offset is less than the eighth preset threshold, the current deviation mode of the molten pool is determined to be boundary instability type deviation.

[0023] In this embodiment, the current deviation pattern of the molten pool is obtained based on the comprehensive deviation index and the deviation trend index. When the relative deviation of the molten pool width is negative and the absolute value is greater than the first preset threshold, and the relative deviation of the peak temperature of the molten pool is negative and the absolute value is greater than the second preset threshold, it indicates that the width and temperature of the molten pool are significantly smaller than the target values, and the current energy input is insufficient to fully melt the metal powder or metal wire, requiring an increase in energy input.

[0024] When the relative deviation of the molten pool width is positive and greater than the third preset threshold, the relative deviation of the peak temperature of the molten pool is positive and greater than the fourth preset threshold, and the relative deviation of the edge fluctuation of the molten pool is positive and greater than the fifth preset threshold, it indicates that the current input energy is too much, the molten pool is over-expanded and the boundary is unstable, which can easily lead to defects such as splashing, collapse and spheroidization, and the energy input needs to be reduced.

[0025] When the relative deviation of the molten pool edge fluctuation is positive and greater than the sixth preset threshold, the absolute value of the relative deviation of the molten pool temperature peak is less than the seventh preset threshold, and the absolute value of the relative deviation of the molten pool center offset is less than the eighth preset threshold, it indicates that the current molten pool edge fluctuation is severe, but the width, temperature and center offset are basically normal. The current state of the molten pool is unstable, and it is necessary to reduce the fluidity of the molten pool to restore boundary stability and reduce surface quality degradation, porosity defects, etc.

[0026] In one embodiment of the present invention, based on deviation patterns and comprehensive deviation indices, at least two different process parameters are adjusted in a coordinated manner, including: When the current deviation mode of the molten pool is determined to be an energy-deficient deviation, the laser scanning power in the metal additive manufacturing process is increased and the laser scanning speed is decreased. The increase in laser scanning power is proportional to the value of the comprehensive deviation index, and the decrease in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be over-melting deviation, the laser scanning power in the metal additive manufacturing process is reduced and the laser scanning speed is increased. The magnitude of the reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the magnitude of the increase in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be boundary instability type deviation, the laser scanning power and powder feed amount in the metal additive manufacturing process are reduced. The magnitude of the reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the magnitude of the reduction in powder feed amount is positively correlated with the absolute value of the relative deviation of the molten pool edge fluctuation.

[0027] In this embodiment, based on the identified deviation pattern, corresponding collaborative adjustment rules are invoked to adjust at least two different process parameters in a coordinated manner, so that the molten pool state approaches the target state. When the current deviation pattern of the molten pool is an energy deficiency type, the laser scanning power is increased and the scanning speed is decreased simultaneously, increasing the energy input and extending the energy application time, so that the molten pool width and temperature return to near the target values. When the current deviation pattern of the molten pool is an overmelting type, the laser scanning power is decreased and the laser scanning speed is increased simultaneously, decreasing the energy input and shortening the energy application time, so that the molten pool width and temperature fall back to near the target values. When the current deviation pattern of the molten pool is a boundary instability type, the laser scanning power is decreased and the powder feed is reduced simultaneously, reducing the fluidity and volume of the molten pool, so that the edge of the molten pool recovers stability and the fluctuation decreases. The above-adjusted parameters are used to control the subsequent printing process, and the molten pool state is continuously monitored during the subsequent printing process. When the real-time monitored molten pool state characteristic data approaches the target molten pool state parameters, the adjustment is stopped or reverse fine-tuning is performed to maintain the stability of the molten pool.

[0028] In one embodiment of the present invention, the target molten pool state parameters include: target molten pool width, target molten pool peak temperature, target molten pool edge fluctuation, and target center offset. The target molten pool width is expressed by the following formula:

[0029] For the target molten pool width, The reference width of the contour boundary region, The reference width of the solid fill area. The reference width of the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number is a characteristic constant. As an indicator for accumulating historical heat, This is the characteristic constant for thermal accumulation; The target peak molten pool temperature is expressed by the following formula:

[0030] The target molten pool temperature peak value, The reference temperature for the contour boundary region. The reference temperature for the solid filling region. The reference temperature for the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The characteristic constant of the number of layers at the temperature peak is... This is the characteristic constant for heat accumulation at the temperature peak. The target molten pool edge fluctuation is expressed by the following formula:

[0031] The target is the edge fluctuation of the molten pool. The baseline fluctuation of the contour boundary region, This serves as the baseline volatility for the solid fill region. This serves as the baseline fluctuation for the island-shaped scan area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number characteristic constant of volatility, As an indicator for accumulating historical heat, This is the thermal accumulation characteristic constant of the fluctuation.

[0032] In this embodiment, the target melt pool width is equal to the reference width multiplied by the layer number correction factor and the heat accumulation correction factor, where the reference width is determined by the scanning strategy. When the scanning area is a contour boundary region, the reference width of the contour boundary region is used; when the scanning area is a solid fill region, the reference width of the solid fill region is used; when the scanning area is an island scan region, the reference width of the island scan region is used. The layer number correction factor decreases with increasing printed layers, and the heat accumulation correction factor decreases with increasing historical heat accumulation indices. Furthermore, the reference width of the contour boundary region is smaller than the reference width of the solid fill region, and the reference width of the solid fill region is smaller than the reference width of the island scan region. Similarly, the target melt pool temperature peak is calculated based on the same principle, correcting the reference temperature value (determined by the scanning strategy) using the layer number correction factor and the heat accumulation correction factor. The layer number correction factor decreases with increasing current printed layers, and the heat accumulation correction factor decreases with increasing historical heat accumulation indices. In the reference values, the reference temperature of the contour boundary region is smaller than the reference temperature of the solid fill region, and the reference temperature of the solid fill region is smaller than the reference temperature of the island scan region.

[0033] In calculating the target molten pool edge fluctuation, the layer increment factor increases with the current number of printed layers, and the heat accumulation increment factor increases with the increase of historical heat accumulation indicators. Unlike the target width and target temperature, the target fluctuation increases with the number of layers and heat accumulation. This is because as the number of printed layers increases and heat accumulation intensifies, the edge fluctuation of the molten pool itself increases. Therefore, the target value of fluctuation should be appropriately relaxed within a certain range when calculating the target value.

[0034] In one embodiment of the present invention, the target center offset is expressed by the following formula:

[0035] This is the target center offset. As the reference offset, The layer number characteristic constant of the offset, The characteristic constant for thermal accumulation of the offset is denoted as .

[0036] In this embodiment, the target center offset is also calculated from the reference offset, the layer number correction factor, and the heat accumulation correction factor. The layer number correction factor increases with the current number of printed layers. As the number of printed layers increases, the overall heat accumulation of the part intensifies, which leads to a decrease in the stability of the molten pool. Therefore, the target center offset is appropriately widened within a certain range. Similarly, when the historical heat accumulation is high, the target center offset should also be appropriately widened within a certain range.

[0037] In one embodiment of the present invention, the method further includes: When the deviation trend index is greater than the ninth preset threshold and the duration exceeds the preset duration, and the comprehensive deviation index of the molten pool is less than the preset deviation value, a step is triggered to adjust at least two different process parameters in a coordinated manner based on the deviation pattern and the comprehensive deviation index.

[0038] In this embodiment, the deviation trend index of the molten pool is continuously calculated during the printing process. If the deviation trend index is greater than the ninth preset threshold and the duration of this state exceeds a preset time, while the overall deviation index of the molten pool is still less than the preset deviation value (i.e., the current molten pool state has not exceeded the allowable target range), it is determined that the molten pool is about to deteriorate. At this time, before the molten pool state seriously exceeds the target range, the linkage adjustment step can be triggered in advance. If the deviation pattern can be identified, at least two different process parameters are linkedly adjusted according to the identified deviation pattern and the preset collaborative adjustment rules to prevent the molten pool state from further deteriorating. Through the above trend prevention and control, early intervention can be carried out before the deviation exceeds the standard, effectively suppressing the molten pool instability trend and improving the stability of the forming quality.

[0039] In one specific embodiment, Inconel 625 parts (200 layers in total, with a 90° inward corner between layers 80 and 120) were manufactured on a laser powder bed fusion (L-PBF) apparatus. Reference parameters: laser power 250W, scanning speed 960mm / s, scanning spacing 110μm, powder layer thickness 30μm, powder feed ratio 100%. Sensors: coaxial high-speed camera and dual-color infrared thermometer.

[0040] Real-time acquisition of molten pool width, peak temperature, edge fluctuation, and center offset. At the corner of layer 90, the measured data are as follows: molten pool width is 92 μm, peak temperature is 1420℃, edge fluctuation is 0.14 mm, and center offset is 12 μm.

[0041] The target state parameters of the molten pool are generated based on the current operating conditions. Among these parameters, the target molten pool width calculation formula includes the reference width of the contour boundary. Reference width of solid fill area Island scanning area reference width Currently, this is a solid filling region, with layer feature constants. Thermal accumulation characteristic constant The target molten pool width is calculated. Reference temperature of solid filling region ℃, characteristic constant of the number of layers of temperature peak Thermal accumulation characteristic constant of temperature peak The peak value of the target temperature of the molten pool was calculated. ℃. Reference fluctuation of the solid filling area. The characteristic constant of the number of layers of volatility Thermal accumulation characteristic constant of fluctuation The fluctuation degree at the edge of the target molten pool was calculated. Reference offset Offset layer characteristic constant Offset heat accumulation characteristic constant The target center offset is calculated. .

[0042] Based on the target state parameters in various dimensions, the relative deviation of the molten pool width is calculated. (i.e., 250%), relative deviation of peak molten pool temperature (i.e., 260%), the relative deviation of the fluctuation at the edge of the molten pool The relative deviation of the molten pool center offset Among them, the weighting coefficient for the molten pool width Weighting coefficient of peak molten pool temperature Weighting coefficients for the volatility at the edge of the molten pool Weighting coefficient of molten pool center offset The comprehensive deviation index was calculated. The relative deviation in width is positive and far exceeds the third preset threshold of 0.12, and the relative deviation in temperature is positive and far exceeds the fourth preset threshold of 0.05. These conditions meet the core criteria for over-melting deviation, and therefore the deviation is determined to be over-melting.

[0043] The current deviation mode is determined to be over-melting deviation. Simultaneously, the laser scanning power is reduced and the scanning speed is increased. The power adjustment coefficient is 0.5, and the speed adjustment coefficient is 1. The power reduction is 0.5 x 1.9386 = 0.9693, and the speed increase is 1.9386 (it should be noted that the speed adjustment range calculated in this embodiment is a theoretical value. In actual applications, to prevent over-adjustment, an upper limit for the adjustment range may be set. For example, the upper limit for the power adjustment range is 30%, but the actual power is only reduced by 30%, and the state correction is achieved through multiple consecutive adjustments). After the above adjustments, the molten pool state is continuously monitored. 20 consecutive frames of data after adjustment show that the molten pool width has recovered to near the target value, the temperature peak has recovered to near the target value, the edge fluctuation has significantly decreased, and the center offset has significantly decreased. The comprehensive deviation index is recalculated and reduced to below 50%, and the molten pool state approaches the target value. Compared with traditional single-parameter control (only power adjustment), this invention reduces the standard deviation of the molten pool width from... The peak boundary fluctuation decreased from 0.23 to 0.11, the internal porosity decreased from 0.42% to 0.08%, and there were no unfused or over-melted defects in the corners and thin-walled areas.

[0044] According to another embodiment, the present invention provides a metal additive manufacturing control device based on multi-dimensional molten pool characteristics. Figure 2 A schematic block diagram of a metal additive manufacturing control apparatus based on multi-dimensional molten pool characteristics is shown. It is understood that this apparatus can be implemented using any device, equipment, platform, or cluster of devices with computing and processing capabilities. Figure 2 As shown, the device includes: The morphological data acquisition module 200 acquires the morphological feature data of the molten pool in real time during the metal additive manufacturing process. The morphological feature data includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset. The state parameter acquisition module 202 is connected to the morphology data acquisition module. Based on the current working condition parameters of the molten pool, it obtains target molten pool state parameters that are adapted to the current working condition parameters. The current working condition parameters include the current number of printing layers, thermal history accumulation index, and preset scanning strategy. The comprehensive deviation acquisition module 204 is connected to the state parameter acquisition module. It compares the morphological feature data with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool. Deviation pattern acquisition module 206 is connected to the comprehensive deviation acquisition module, and obtains the current deviation pattern of the molten pool based on the comprehensive deviation index and the deviation trend index. The molten pool state adjustment module 208 is connected to the deviation mode acquisition module. Based on the deviation mode and the comprehensive deviation index, it performs linkage adjustment on at least two different process parameters to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

[0045] In this embodiment of the invention, the morphological data acquisition module 200 can be used to execute step 100 in the above method embodiment, the state parameter acquisition module 202 can be used to execute step 102 in the above method embodiment, the comprehensive deviation acquisition module 204 can be used to execute step 104 in the above method embodiment, the deviation mode acquisition module 206 can be used to execute step 106 in the above method embodiment, and the melt pool state adjustment module 208 can be used to execute step 108 in the above method embodiment.

[0046] In one embodiment of the present invention, the comprehensive deviation acquisition module is configured to perform the following operations: The real-time molten pool state vector is compared with the target molten pool state vector dimension by dimension to obtain the relative deviation of each dimension. The relative deviation of each dimension is expressed by the following formula:

[0047] This represents the relative deviation of each dimension. Data representing the morphological characteristics of the molten pool. Indicates the target molten pool state parameters; Based on the relative deviation of each dimension, the comprehensive deviation index of the molten pool is obtained, and the comprehensive deviation index is expressed by the following formula:

[0048] Indicates the overall deviation index, Indicates the relative deviation of the molten pool width. This indicates the relative deviation of the peak temperature of the molten pool. This indicates the relative deviation of the fluctuation at the edge of the molten pool. This indicates the relative deviation of the molten pool center offset. The weighting coefficient representing the width of the molten pool. The weighting coefficient represents the peak temperature of the molten pool. The weighting coefficients representing the volatility at the edge of the molten pool. The weighting coefficient represents the offset of the molten pool center. ; Based on the comprehensive deviation index of the molten pool, the deviation trend index is obtained, and the deviation trend index is expressed by the following formula:

[0049] Indicators representing deviation trends This indicates the preset time window.

[0050] In one embodiment of the present invention, the deviation pattern acquisition module is configured to perform the following operations: When the relative deviation of the molten pool width is negative and the absolute value is greater than the first preset threshold, and the relative deviation of the peak temperature of the molten pool is negative and the absolute value is greater than the second preset threshold, the current deviation mode of the molten pool is determined to be an energy-deficient deviation. When the relative deviation of the molten pool width is positive and greater than the third preset threshold, the relative deviation of the peak temperature of the molten pool is positive and greater than the fourth preset threshold, and the relative deviation of the edge fluctuation of the molten pool is positive and greater than the fifth preset threshold, the current deviation mode of the molten pool is determined to be an over-melting deviation. When the relative deviation of the edge fluctuation of the molten pool is positive and greater than the sixth preset threshold, the absolute value of the relative deviation of the peak temperature of the molten pool is less than the seventh preset threshold, and the absolute value of the relative deviation of the center offset of the molten pool is less than the eighth preset threshold, the current deviation mode of the molten pool is determined to be a boundary instability type deviation.

[0051] In one embodiment of the present invention, the molten pool state adjustment module is configured to perform the following operations: When the current deviation mode of the molten pool is determined to be an energy-deficient deviation, the laser scanning power in the metal additive manufacturing process is increased and the laser scanning speed is decreased. The increase in laser scanning power is proportional to the value of the comprehensive deviation index, and the decrease in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be over-melting deviation, the laser scanning power in the metal additive manufacturing process is reduced and the laser scanning speed is increased. The reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the increase in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be boundary instability type deviation, the laser scanning power in the metal additive manufacturing process is reduced and the powder feeding amount is reduced. The magnitude of the reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the magnitude of the reduction in powder feeding amount is positively correlated with the absolute value of the relative deviation of the molten pool edge fluctuation.

[0052] In one embodiment of the present invention, the target molten pool state parameters include: target molten pool width, target molten pool peak temperature, target molten pool edge fluctuation, and target center offset; The target molten pool width is expressed by the following formula:

[0053] For the target molten pool width, The reference width of the contour boundary region, The reference width of the solid fill area. The reference width of the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number is a characteristic constant. As an indicator for accumulating historical heat, This is the characteristic constant for thermal accumulation; The target peak temperature of the molten pool is expressed by the following formula:

[0054] The target molten pool temperature peak value, The reference temperature for the contour boundary region. The reference temperature for the solid filling region. The reference temperature for the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The characteristic constant of the number of layers at the temperature peak is... This is the characteristic constant for heat accumulation at the temperature peak. The target molten pool edge fluctuation is expressed by the following formula:

[0055] The target is the edge fluctuation of the molten pool. The baseline fluctuation of the contour boundary region, This serves as the baseline volatility for the solid fill region. This serves as the baseline fluctuation for the island-shaped scan area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number characteristic constant of volatility, As an indicator for accumulating historical heat, This is the thermal accumulation characteristic constant of the fluctuation.

[0056] In one embodiment of the present invention, the target center offset is expressed by the following formula:

[0057] This is the target center offset. As the reference offset, The layer number characteristic constant of the offset, The characteristic constant for thermal accumulation of the offset is denoted as .

[0058] In one embodiment of the present invention, it is also used to perform the following operations: When the deviation trend index is greater than the ninth preset threshold and the duration exceeds the preset duration, and the comprehensive deviation index of the molten pool is less than the preset deviation value, at least two different process parameters are adjusted in a coordinated manner based on the deviation pattern and the comprehensive deviation index.

[0059] According to another embodiment, an electronic device is also provided, including a memory and a processor, wherein executable code is stored in the memory, and when the processor executes the executable code, it implements a combination... Figure 1 The method.

[0060] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0061] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium.

[0062] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling metal additive manufacturing based on multi-dimensional molten pool characteristics, characterized in that, include: In the process of metal additive manufacturing, the morphological feature data of the molten pool is acquired in real time. The morphological feature data includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation and molten pool center offset. Based on the current operating parameters of the molten pool, target molten pool state parameters adapted to the current operating parameters are obtained. The current operating parameters include the current number of printing layers, thermal history accumulation index, and preset scanning strategy. The morphological feature data is compared with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool. Based on the comprehensive deviation index and the deviation trend index, the current deviation pattern of the molten pool is obtained; Based on the deviation mode and the comprehensive deviation index, at least two different process parameters are adjusted in a coordinated manner to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

2. The method according to claim 1, characterized in that, The step of comparing the morphological feature data with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool includes: The real-time molten pool state vector is compared with the target molten pool state vector dimension by dimension to obtain the relative deviation of each dimension. The relative deviation of each dimension is expressed by the following formula: This represents the relative deviation of each dimension. Data representing the morphological characteristics of the molten pool. Indicates the target molten pool state parameters; Based on the relative deviation of each dimension, the comprehensive deviation index of the molten pool is obtained, and the comprehensive deviation index is expressed by the following formula: Indicates the overall deviation index, Indicates the relative deviation of the molten pool width. This indicates the relative deviation of the peak temperature of the molten pool. This indicates the relative deviation of the fluctuation at the edge of the molten pool. This indicates the relative deviation of the molten pool center offset. The weighting coefficient representing the width of the molten pool. The weighting coefficient represents the peak temperature of the molten pool. The weighting coefficients representing the volatility at the edge of the molten pool. The weighting coefficient represents the offset of the molten pool center. ; Based on the comprehensive deviation index of the molten pool, the deviation trend index is obtained, and the deviation trend index is expressed by the following formula: Indicators representing deviation trends This indicates the preset time window.

3. The method according to claim 2, characterized in that, The process of obtaining the current deviation pattern of the molten pool based on the comprehensive deviation index and the deviation trend index includes: When the relative deviation of the molten pool width is negative and the absolute value is greater than the first preset threshold, and the relative deviation of the peak temperature of the molten pool is negative and the absolute value is greater than the second preset threshold, the current deviation mode of the molten pool is determined to be an energy-deficient deviation. When the relative deviation of the molten pool width is positive and greater than the third preset threshold, the relative deviation of the peak temperature of the molten pool is positive and greater than the fourth preset threshold, and the relative deviation of the edge fluctuation of the molten pool is positive and greater than the fifth preset threshold, the current deviation mode of the molten pool is determined to be an over-melting deviation. When the relative deviation of the edge fluctuation of the molten pool is positive and greater than the sixth preset threshold, the absolute value of the relative deviation of the peak temperature of the molten pool is less than the seventh preset threshold, and the absolute value of the relative deviation of the center offset of the molten pool is less than the eighth preset threshold, the current deviation mode of the molten pool is determined to be a boundary instability type deviation.

4. The method according to claim 3, characterized in that, The method of adjusting at least two different process parameters in a coordinated manner based on the deviation pattern and the comprehensive deviation index includes: When the current deviation mode of the molten pool is determined to be an energy-deficient deviation, the laser scanning power in the metal additive manufacturing process is increased and the laser scanning speed is decreased. The increase in laser scanning power is proportional to the value of the comprehensive deviation index, and the decrease in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be over-melting deviation, the laser scanning power in the metal additive manufacturing process is reduced and the laser scanning speed is increased. The reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the increase in scanning speed is proportional to the value of the comprehensive deviation index. When the current deviation mode of the molten pool is determined to be boundary instability type deviation, the laser scanning power in the metal additive manufacturing process is reduced and the powder feeding amount is reduced. The magnitude of the reduction in laser scanning power is proportional to the value of the comprehensive deviation index, and the magnitude of the reduction in powder feeding amount is positively correlated with the absolute value of the relative deviation of the molten pool edge fluctuation.

5. The method according to claim 2, characterized in that, The target molten pool state parameters include: target molten pool width, target molten pool peak temperature, target molten pool edge fluctuation, and target center offset; The target molten pool width is expressed by the following formula: For the target molten pool width, The reference width of the contour boundary region, The reference width of the solid fill area. The reference width of the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number is a characteristic constant. As an indicator for accumulating historical heat, This is the characteristic constant for thermal accumulation; The target peak temperature of the molten pool is expressed by the following formula: The target molten pool temperature peak value, The reference temperature for the contour boundary region. The reference temperature for the solid filling region. The reference temperature for the island-shaped scanning area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The number of layers is a characteristic constant for the temperature peak. This is the characteristic constant for heat accumulation at the temperature peak. The target molten pool edge fluctuation is expressed by the following formula: The target is the edge fluctuation of the molten pool. The baseline fluctuation of the contour boundary region, This serves as the baseline volatility for the solid fill region. This serves as the baseline fluctuation for the island-shaped scan area. This is an indicator function, which takes the value 1 if the current scanned layer is a contour boundary region, and 0 otherwise. This is an indicator function, which takes the value 1 if the currently scanned layer is a solid filling region, and 0 otherwise. This is an indicator function, which takes the value 1 if the current scan layer is an island-shaped scan region, and 0 otherwise. This is the current number of printing layers. The layer number characteristic constant of volatility, As an indicator for accumulating historical heat, This is the thermal accumulation characteristic constant of the fluctuation.

6. The method according to claim 5, characterized in that, The target center offset is expressed by the following formula: This is the target center offset. As the reference offset, The layer number characteristic constant of the offset, The characteristic constant for thermal accumulation of the offset is denoted as .

7. The method according to claim 1, characterized in that, The method further includes: When the deviation trend index is greater than the ninth preset threshold and the duration exceeds the preset duration, and the comprehensive deviation index of the molten pool is less than the preset deviation value, the step of adjusting at least two different process parameters in a coordinated manner based on the deviation pattern and the comprehensive deviation index is triggered.

8. A metal additive manufacturing control device based on multi-dimensional molten pool characteristics, characterized in that, include: The morphological data acquisition module acquires morphological feature data of the molten pool in real time during the metal additive manufacturing process. The morphological feature data includes: molten pool width, peak molten pool temperature, molten pool edge fluctuation, and molten pool center offset. The state parameter acquisition module is connected to the morphology data acquisition module. Based on the current operating condition parameters of the molten pool, it obtains the target molten pool state parameters that are adapted to the current operating condition parameters. The current operating condition parameters include the current number of printing layers, thermal history accumulation index, and preset scanning strategy. The comprehensive deviation acquisition module is connected to the state parameter acquisition module. It compares the morphological feature data with the target molten pool state parameters dimension by dimension to obtain the comprehensive deviation index and deviation trend index of the molten pool. The deviation pattern acquisition module is connected to the comprehensive deviation acquisition module, and obtains the current deviation pattern of the molten pool based on the comprehensive deviation index and the deviation trend index. The molten pool state adjustment module is connected to the deviation mode acquisition module. Based on the deviation mode and the comprehensive deviation index, it performs linkage adjustment on at least two different process parameters to make the molten pool state approach the target molten pool state, thereby controlling the metal additive manufacturing process.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in any one of claims 1-7.

Images