A method, device and electronic equipment for determining parameters of additive manufacturing process

Abstract

The present disclosure discloses a parameter determination method, device and electronic equipment for an additive manufacturing process, which relates to the field of additive manufacturing technology, in order to solve the problem that existing research cannot reflect the complex physical process of additive manufacturing. The parameter determination method of the additive manufacturing process includes: searching for the target dimensionless process parameters of the target additive material from the process window of the dimensionless process diagram of the additive material. Determine a plurality of process parameters of the additive manufacturing process based on the target dimensionless process parameters and the material parameters of the target additive material. The dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter. The method is used to describe the thermal process of the additive manufacturing process, and to help researchers provide guidance on parameter selection in early experiments.

Description

Technical Field

[0001] The present disclosure relates to the field of additive manufacturing technology, and in particular to a method, device and electronic equipment for determining parameters of an additive manufacturing process. Background Art

[0002] Powder-fed laser melting deposition technology is the most commonly used additive manufacturing method. The molding quality of its parts is highly dependent on the parameters used. Researchers hope to obtain parts with high dimensional accuracy, good microstructure and mechanical properties by optimizing the process parameters.

[0003] However, current research mainly uses the laser volume energy density E (J / mm 3 ) explains the influence of process parameters on the microstructure or performance of materials, and optimizes the process parameters accordingly. The number of process parameters involved is relatively small, which cannot truly reflect the complex physical process of additive manufacturing. Moreover, the parameters are independent of each other and lack correlation. The reference significance and repeatability are poor, and they cannot provide guidance for researchers in the parameter selection of early experiments. Summary of the invention

[0004] The purpose of the present disclosure is to provide a method, device and electronic equipment for determining parameters of an additive manufacturing process to ensure that various process parameters of the additive manufacturing process are interrelated, thereby reflecting the complex physical process of additive manufacturing.

[0005] In order to achieve the above objectives, the present disclosure provides the following technical solutions:

[0006] A method for determining parameters of an additive manufacturing process, wherein the additive material of the additive manufacturing process is a target additive material, and the method for determining parameters of the additive manufacturing process comprises:

[0007] The target dimensionless process parameters of the target additive material are found from the process window of the dimensionless process map of the additive material.

[0008] A plurality of process parameters of the additive manufacturing process are determined based on the target dimensionless process parameters and material parameters of the target additive material.

[0009] The dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter. The first dimensionless process parameter is the dimensionless volume energy density, the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density, and the target dimensionless process parameter includes the first target dimensionless parameter and the second target dimensionless parameter located in the process window in the dimensionless process diagram of the additive material.

[0010] Compared with the prior art, in the parameter determination method of the additive manufacturing process provided by the present disclosure, the dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter, the first dimensionless process parameter is the dimensionless body energy density, and the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius. Therefore, the target dimensionless process parameters of the target additive material can be found from the process window of the dimensionless process diagram of the additive material, and then the target dimensionless process parameters and the material parameters of the target additive material are used to determine the various process parameters of the additive manufacturing process. It can be seen that when determining the parameters of the additive manufacturing process, the present disclosure can be determined through the process window of the dimensionless process diagram of the additive material, thereby narrowing the selection range of the optimal process parameters, so as to guide researchers to select process parameters, effectively reduce the amount of process parameters that need to be studied in the additive manufacturing process, and save the experimental cost and cycle of researchers in the early stage of determining the optimized process parameters.

[0011] In addition, the dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter, and the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density. Since the dimensionless equivalent energy density is determined by the material parameter and the process parameter, the interaction between the various process parameters in the additive manufacturing process can be understood through the dimensionless equivalent energy density, and the correlation between the various process parameters in the additive manufacturing process can be established, so that the process parameters of the additive manufacturing process determined by this method are highly referenceable and highly repeatable.

[0012] The present disclosure also provides a parameter determination device for an additive manufacturing process, wherein the additive material of the additive manufacturing process is a target additive material, and the parameter determination device for the additive manufacturing process comprises:

[0013] The search module is used to search for the target dimensionless process parameters of the target additive material from the process window of the dimensionless process map of the additive material.

[0014] A determination module is used to determine a plurality of process parameters of the additive manufacturing process based on the target dimensionless process parameter and a material parameter of the target additive material.

[0015] The dimensionless process diagram is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter. The first dimensionless process parameter is the dimensionless volume energy density, the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density, and the target dimensionless process parameter includes the first target dimensionless parameter and the second target dimensionless parameter located in the process window in the dimensionless process diagram of the additive material.

[0016] Compared with the prior art, the beneficial effects of the device for determining parameters of the additive manufacturing process provided by the present disclosure are the same as the beneficial effects of the method for determining parameters of the additive manufacturing process described in the above technical solution, and will not be elaborated here.

[0017] The present disclosure also provides an electronic device, the electronic device comprising:

[0018] processor. And,

[0019] Memory for storing programs.

[0020] The program includes instructions, which, when executed by the processor, cause the processor to execute the above-mentioned method for determining parameters of the additive manufacturing process.

[0021] Compared with the prior art, the beneficial effects of the electronic device provided by the present disclosure are the same as the beneficial effects of the parameter determination method of the additive manufacturing process described in the above technical solution, and will not be elaborated here.

[0022] The present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned parameter determination method for the additive manufacturing process.

[0023] Compared with the prior art, the beneficial effects of the non-transitory computer-readable storage medium provided by the present disclosure are the same as the beneficial effects of the parameter determination method of the additive manufacturing process described in the above technical solution, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings:

[0025] Figure 1 is a flowchart of a method for determining parameters of an additive manufacturing process in an embodiment of the present disclosure;

[0026] Figure 2 This is a method 1 for determining a dimensionless process diagram of an additive material in an embodiment of the present disclosure;

[0027] Figure 3 This is a second method for determining a dimensionless process diagram of an additive material in an embodiment of the present disclosure;

[0028] Figure 4 The third method for determining the dimensionless process diagram of the additive material in the embodiment of the present disclosure is as follows;

[0029] Figure 5is a schematic diagram of an additive manufacturing process in an embodiment of the present disclosure;

[0030] Figure 6 It is a dimensionless process diagram of additive materials of various alloy materials in the embodiments of the present disclosure;

[0031] Figure 7 A dimensionless process diagram of an additive material formed by orthogonal design of reference process parameters in the embodiment of the present disclosure;

[0032] Figure 8 A diagram showing the preparation process of a Ti6Al4V sample in an embodiment of the present disclosure;

[0033] Fig. 9 A size diagram of a Ti6Al4V sample in a uniaxial tensile test in an embodiment of the present disclosure;

[0034] Fig.10 This is a diagram showing the tensile results of a Ti6Al4V sample in an embodiment of the present disclosure;

[0035] Fig.11 A tensile performance diagram of Ti6Al4V prepared by an additive manufacturing process guided by a dimensionless process diagram of additive materials in an embodiment of the present disclosure and other technical methods;

[0036] Fig.12 It is a schematic block diagram of modules of a device for determining parameters of an additive manufacturing process in an embodiment of the present disclosure;

[0037] Fig.13 is a schematic block diagram of a chip in an embodiment of the present disclosure;

[0038] Fig.14 The figure is a structural block diagram of an electronic device that can be used to implement the embodiments of the present disclosure. DETAILED DESCRIPTION

[0039] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present disclosure more clearly understood, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and are not used to limit the present disclosure.

[0040] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element.

[0041] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure, "multiple" means two or more, unless otherwise clearly and specifically defined. "Several" means one or more, unless otherwise clearly and specifically defined.

[0042] In the description of the present disclosure, it is necessary to understand that the directions or positional relationships indicated by the terms "upper", "lower", "front", "back", "left", "right", etc. are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present disclosure.

[0043] In the description of the present disclosure, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0044] The American Society for Testing and Materials (ASTM) defines additive manufacturing (AM) as: "A process that, in contrast to subtractive manufacturing methods, generates a solid object from a three-dimensional model by depositing materials layer by layer." Powder-feeding laser melting deposition (LMD) technology is the most commonly used additive manufacturing method. It uses a laser heat source to melt the metal powder blown into the molten pool. The molten pool then solidifies and accumulates layer by layer, achieving rapid prototyping of complex shapes without a metal mold, breaking through unprecedented design freedom and manufacturing flexibility.

[0045] The thermal history experienced by metals during powder-fed laser melting deposition (LMD) technology is very different from that of traditional manufacturing. Due to the short laser action time and the local high input energy, the microstructure of powder-fed laser melting deposition (LMD) technology is formed after experiencing a high solidification rate, a large thermal gradient, and a significant thermal cycle caused by repeated melting and solidification processes across multiple deposition layers. This will lead to thermal stress and element segregation and non-equilibrium phase change caused by rapid solidification. The molding quality of parts in powder-fed laser melting deposition (LMD) technology is highly dependent on the parameters used, such as laser power, scanning speed, spot diameter, scanning spacing, layer thickness and other process parameters, as well as physical properties of different types of powder materials, wettability and other material parameters. All these parameters jointly affect the evolution of key organizational characteristics such as solidification morphology, segregation, grain structure, organizational stability, defects and inclusions.

[0046] Researchers are committed to revealing the relationship between process parameters, structure and performance using theoretical, experimental and numerical methods, hoping to obtain parts with high dimensional accuracy and good microstructure and mechanical properties by optimizing process parameters. This type of research or work mainly uses laser volume energy density E (J / mm 3 ) describes the effect of process parameters on material microstructure or performance, and optimizes process parameters based on this. Although it can provide guidance for parameter selection, the number of process parameters involved is small, which cannot truly reflect the complex physical process of AM, and does not consider the effect of powder physical parameters on material thermal processing. At the same time, E(J / mm 3 ) When describing the process window, each parameter is independent of each other and lacks correlation. The process parameter group of the material will vary depending on the equipment. The optimal processing parameters of a certain material cannot be bound to the equipment to form a unified standard, and the reference significance and repeatability are poor. Therefore, the application of scientific methods to describe the process parameters of powder-feeding laser melting deposition technology (LMD) has important guiding significance for a more comprehensive explanation of the thermal process of powder-feeding laser melting deposition technology (LMD), helping researchers to provide guidance on parameter selection in early experiments, preparing components with excellent mechanical properties and saving costs and time.

[0047] In order to overcome the defects of the above-mentioned existing methods, the present disclosure provides a method for determining parameters of an additive manufacturing process, wherein the additive material of the additive manufacturing process is a target additive material. The method for determining parameters of the additive manufacturing process provided by the present disclosure includes:

[0048] Step 101: Find the target dimensionless process parameters of the target additive material from the process window of the dimensionless process map of the additive material.

[0049] Exemplarily, the dimensionless process diagram of additive materials is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter, the first dimensionless process parameter is the dimensionless volume energy density, and the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius, therefore, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density. On this basis, the target dimensionless process parameter found from the process window in the dimensionless process diagram of additive materials may include the first target dimensionless parameter and the second target dimensionless parameter located in the process window in the dimensionless process diagram of additive materials, so that the first target dimensionless process parameter is located within the interval of the first dimensionless process parameter, and the second target dimensionless parameter is located within the interval of the second dimensionless process parameter.

[0050] Step 102: Determine multiple process parameters of the additive manufacturing process based on the target dimensionless process parameters and the material parameters of the target additive material. The material parameters of the additive material corresponding to the dimensionless process diagram of the additive material match the material parameters of the target additive material. The match here can be equal or the difference between the two can be within a preset threshold.

[0051] When the material parameters of the additive material corresponding to the dimensionless process diagram of the additive material are equal to the material parameters of the target additive material, the target additive material and the additive material corresponding to the dimensionless process diagram of the additive material are substantially the same material. When the difference between the material parameters of the additive material corresponding to the dimensionless process diagram of the additive material and the material parameters of the target additive material is within a preset threshold, the material properties of the target additive material and the additive material corresponding to the dimensionless process diagram of the additive material can be considered to be close. The preset threshold can be set according to actual conditions.

[0052] In practical applications, an additive material with similar performance to the additive material corresponding to the dimensionless process diagram of the additive material can be selected as the target additive material, and the target dimensionless process parameters of the target additive material can be found from the dimensionless process diagram of the additive material according to the process window of the dimensionless process diagram of the additive material corresponding to the dimensionless process diagram of the additive material, and multiple process parameters of the additive manufacturing process can be determined based on the target dimensionless process parameters and the material parameters of the target additive material. It can be seen that the dimensionless process diagram of the additive material of the embodiment of the present disclosure can not only determine the additive manufacturing process parameters of the additive material of the corresponding type, but also determine the additive manufacturing process parameters of the additive material with similar performance to the additive material of the corresponding type.

[0053] As can be seen from the above, in the parameter determination method of the additive manufacturing process provided in the embodiment of the present disclosure, the dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter, the first dimensionless process parameter is the dimensionless volume energy density, and the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius. Therefore, the target dimensionless process parameters of the target additive material can be found from the process window of the dimensionless process diagram of the additive material, and then the target dimensionless process parameters and the material parameters of the target additive material are used to determine the various process parameters of the additive manufacturing process. It can be seen that when determining the parameters of the additive manufacturing process, the present disclosure can be determined through the process window of the dimensionless process diagram of the additive material, thereby narrowing the selection range of the optimal process parameters, so as to guide researchers to select process parameters, effectively reduce the amount of process parameters that need to be studied in the additive manufacturing process, and save the experimental cost and cycle of researchers in the early stage of determining the optimized process parameters.

[0054] In addition, the dimensionless process diagram of the additive material is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter, and the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density. Since the dimensionless equivalent energy density is determined by the material parameter and the process parameter, the interaction between the various process parameters in the additive manufacturing process can be understood through the dimensionless equivalent energy density, and the correlation between the various process parameters in the additive manufacturing process can be established, so that the process parameters of the additive manufacturing process determined by this method are highly referenceable and highly repeatable.

[0055] As a possible implementation, the first dimensionless process parameter of the embodiment of the present disclosure can be determined by the dimensionless laser power, the dimensionless scanning speed and the dimensionless layer height. The second dimensionless process parameter can be determined by the dimensionless scanning spacing. For example: the first dimensionless process parameter is proportional to the dimensionless laser power, and the product of the dimensionless laser scanning speed and the dimensionless layer height is inversely proportional to the first dimensionless process parameter. At this time, the dimensionless volume energy density E=q * / (v * l * ).

[0056] The second dimensionless process parameter is inversely proportional to the laser scanning spacing. At this time, the second dimensionless process parameter can be expressed as 1 / h * .

[0057] It can be seen that the method for determining the dimensionless process diagram of the additive material of the exemplary embodiment of the present disclosure is essentially a process of solving the relationship between the dimensionless laser power, the dimensionless scanning speed, the dimensionless layer and the laser scanning spacing. The dimensionless process diagrams of one additive material or multiple additive materials can be represented in the same dimensionless process diagram. The following is a description of the dimensionless process diagram of one additive material as an example.

[0058] Figure 2 FIG. 1 shows a method for determining a dimensionless process diagram of an additive material according to an exemplary embodiment of the present disclosure. Figure 2 As shown, the method for determining the dimensionless process diagram of additive materials includes:

[0059] Step 201: Dimensionally transforming multiple sets of reference process parameters of additive materials in an additive manufacturing process to obtain multiple sets of dimensionless reference process parameters, each set of dimensionless reference process parameters including multiple dimensionless reference process parameters.

[0060] Exemplarily, each set of reference process parameters includes laser parameters, process variable parameters and material parameters. The material parameters may include material density (ρ), thermal diffusivity (α), thermal conductivity (λ), material melting point (T m ) and the initial material temperature (T0), the laser parameters include laser power (q), scanning speed (v), spot radius (r B ), the process variable parameters include layer height (l), scanning spacing (h) and powder feeding amount (ω).

[0061] Step 202: Determine a corresponding first dimensionless process parameter and a second dimensionless process parameter based on each set of dimensionless reference process parameters.

[0062] Step 203: Determine a dimensionless process diagram of the additive material based on the first dimensionless process parameter and the second dimensionless process parameter corresponding to different sets of dimensionless reference process parameters. The first dimensionless process parameter is used to determine the minimum dimensionless input energy required to lift the powder to the melting point, that is, the dimensionless volume energy density, and the second dimensionless process parameter is used to determine the ratio of the laser scanning spacing to the laser spot radius, which can also be considered as the reciprocal of the dimensionless scanning spacing.

[0063] In an alternative approach, Figure 3 FIG. 2 shows a second method for determining a dimensionless process diagram of an additive material according to an exemplary embodiment of the present disclosure. Figure 3 As shown, when each set of reference process parameters includes basic reference process parameters and non-basic reference process parameters, and the non-basic reference process parameters are determined by the basic reference process parameters, the multiple sets of reference process parameters of the additive material in the additive manufacturing process are dimensionless to obtain multiple sets of dimensionless reference process parameters, and each set of dimensionless reference process parameters includes multiple dimensionless process parameters including:

[0064] Step 2011: Determine the number of independent dimensions based on the dimensions of the same set of reference process parameters. The derivation of laser power (q) is used as an example to demonstrate how to determine its dimensions. The dimensions of the remaining reference process parameters are determined in the same manner and will not be described in detail here. According to the International System of Units, 1 watt is 1 joule / second, which is equivalent to 1 Newton·meter / second, so:

[0065] q=F×v (1)

[0066] F=m×a (2)

[0067] Combining (1) and (2) we can get

[0068] q=m×a×v (3)

[0069] in:

[0070] q——power, unit watt W;

[0071] F——force, unit: Newton N;

[0072] v——speed, in meters per second (m / s), dimension is LT -1 ;

[0073] m——mass, unit is kilogram, dimension is M;

[0074] a——acceleration, in meters per second squared (m / s) 2 , the dimension is LT -2 .

[0075] Therefore, the dimension of q can be expressed as [q] = [m] [a] [v] = M·LT -2 ·LT -1 =ML 2 T -3 .

[0076] Scanning speed v (m / s) dimension

[0077] Spot radius r B (m) Dimension [r B ] = L;

[0078] Layer thickness l (m) dimension [l] = L;

[0079] Overlap spacing h (m) dimension [h] = L;

[0080] Thermal diffusivity α(m 2 / s) dimension

[0081] Thermal conductivity λ (W / (m·K)), the denominator watt dimension is known, substitute it into

[0082] Material melting point T m and room temperature T0 to form the temperature difference T m -T0(K), dimension is [T m -T0] = θ;

[0083] Powder feeding amount ω(kg / s) dimension

[0084] Density ρ(kg / m 3 )dimension As shown in Table 1.

[0085] It can be seen from Table 1 that there are only 4 independent dimensions among the dimensions of the 10 reference process parameters in Table 1, namely M, L, T, and θ.

[0086] Table 1 Dimensions of variables

[0087]

[0088] Step 2012: Obtain basic reference process parameters from the same set of reference process parameters, where the number of basic reference process parameters is the same as the number of independent dimensions.

[0089] Step 2013: non-basic reference process parameters contained in each set of dimensionless reference process parameters are dimensionally transformed based on the basic reference process parameters to obtain corresponding dimensionless reference process parameters.

[0090] In practical applications, since there are only 4 independent dimensions among the 10 reference process parameters in Table 1, the number of basic reference process parameters is 4. m -T0, r B The remaining non-basic reference process parameters are dimensionless for the basic reference process parameters. The dimensions of the non-basic reference process parameters can be expressed as the power of the dimensions of the basic reference process parameters, thereby obtaining the corresponding dimensionless reference process parameters. Here, taking dimensionless power as an example, if [q * ]=1, and the exponents of the basic dimensions M, L, and T are all 0, then:

[0091]

[0092] therefore Obtain but A coefficient A is added here. A is the laser absorptivity of the material surface, which is a dimensionless number. Aq represents the power that the material can actually absorb.

[0093] akin Obtain the values ​​of a, b, c, and d, and the expressions of the remaining dimensionless reference process parameters can be obtained by analogy:

[0094]

[0095]

[0096]

[0097]

[0098]

[0099] As a possible implementation, Figure 2 As shown, when the above-mentioned multiple groups of reference process parameters are process parameters of multiple orthogonal test strategies determined by orthogonal test, and the orthogonal test method is a three-factor three-level orthogonal test method, wherein the three factors include dimensionless laser power, dimensionless scanning speed and dimensionless scanning spacing. The method for determining the dimensionless process map of the additive material also includes:

[0100] Step 204: Determine a process window of the dimensionless process diagram of the additive material based on the distribution density of the graphical representation of the mapping relationship in the dimensionless process diagram of the additive material.

[0101] Step 205: Determine process parameters of multiple orthogonal experimental strategies within the process window of the dimensionless process map of the additive material.

[0102] Step 206: Update multiple sets of reference process parameters using process parameters of multiple orthogonal experimental strategies.

[0103] In some embodiments, Figure 4 FIG. 3 shows a method for determining a dimensionless process diagram of an additive material according to an exemplary embodiment of the present disclosure. Figure 4 As shown, when different orthogonal test strategies for the same additive material contain some of the same process parameters, the method for determining the dimensionless process diagram of the additive material further includes:

[0104] Step 2051: Determine multiple experimental factors of the orthogonal experiment based on the first dimensionless process parameter and the second dimensionless process parameter.

[0105] Step 2052: Determine multiple levels corresponding to each experimental factor based on the process window of the dimensionless process map of the additive material.

[0106] Step 2053: Determine multiple orthogonal experimental strategies for additive materials based on each experimental factor and multiple levels corresponding to each experimental factor.

[0107] The parameter determination method of the additive manufacturing process in the embodiment of the present disclosure is further described below in conjunction with the embodiments and drawings.

[0108] Example 1

[0109] The metal powder material used in the additive manufacturing process of this embodiment is Ti6Al4V material. The parameter determination method of the additive manufacturing process of this embodiment includes the following steps:

[0110] In the first step, the dimensions of the reference process parameters of the additive manufacturing process are determined.

[0111] When the laser acts on the surface of the part, a thermal effect will be generated. This thermal effect mainly depends on the laser parameters, such as laser power (q), scanning speed (v), spot radius (r B ), as well as material parameters such as material density (ρ), thermal diffusivity (α), thermal conductivity (λ), material melting point (T m ), initial material temperature (T0), etc. In addition to the above parameters, there are also process variable parameters such as layer height (l), scanning spacing (h) and powder feeding amount (ω).

[0112] The second step is to determine the dimensionless process parameter group.

[0113] Based on the П theorem proposed by Buckingham, it can be concluded that the dimensions of the reference process parameters of the additive manufacturing process have only four independent dimensions according to the physical process of the additive manufacturing process. Therefore, the number of basic reference process parameters is determined to be four. m -T0, r B The remaining non-basic reference process parameters are dimensionless for the basic reference process parameters. The dimensions of the non-basic reference process parameters can be expressed as the power of the dimensions of the basic reference process parameters. The corresponding expressions of the non-basic reference process parameters are:

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120] Where q * is the dimensionless laser power, v * is the dimensionless laser scanning speed, l * is the dimensionless layer thickness, h * is the dimensionless scanning distance, ω * is the dimensionless powder mass flow rate, ρ *is the dimensionless material density, A is the laser absorptivity of the material surface, and η is the powder utilization rate. The thermophysical parameters used in the analysis are the average value between the initial temperature of the material and the melting point of the material, assuming that the physical properties of the material do not change when it melts.

[0121] Figure 5 This is the principle diagram of the additive manufacturing process. Figure 5 As shown in the figure, the laser melts and solidifies a powder material with a mass of ηω per unit time, and the laser energy density E per unit mass can be expressed as Aq / ηω. The minimum energy H required to melt a unit mass of powder material min for:

[0122] H min =C p (T m -T0)+L m =C p ΔT+L m (15)

[0123] Where L m is the latent heat of fusion, C p is the specific heat capacity of the powder. For metal materials, L m It can be approximately expressed as:

[0124] L m ≈0.5C p ΔT (16)

[0125] Therefore, H min It is expressed as:

[0126] H min =1.5C p ΔT (17)

[0127] Combining equations (1)-(9) we can obtain:

[0128]

[0129] In the formula It is the minimum dimensionless energy density required to melt a unit mass of powder material.

[0130] To simplify the analysis, Figure 5 As shown, the cross section of the single-channel printing track is approximated as a rectangle, and the cross-sectional area of ​​the laser moving heat source heating and melting in time t is 2r B l material, the powder flow rate ω of the additive manufacturing process and the quality of the forming have the following quantitative relationship:

[0131] ηωt=2r B lvtρ (19)

[0132] By non-dimensionalizing formula (19), we can obtain:

[0133]

[0134] Substituting formula (20) into formula (18) yields:

[0135]

[0136] Where E * is the dimensionless volume energy density.

[0137] The third step is to establish a dimensionless process map for additive materials.

[0138] Figure 6 It is a dimensionless process diagram of additive materials for various alloy materials. Figure 6 As shown in the figure, the reference process parameters of various alloys prepared by additive manufacturing processes in the literature are summarized and compared. According to the reference process parameters provided in the literature, the dimensionless reference process parameters of various alloys are calculated, and the q with log10 as the scale is * / (v * l * ) is the horizontal axis, 1 / h * As the vertical axis, establish Figure 6 Dimensionless process diagram of additive materials for various alloy materials shown.

[0139] The horizontal axis is the dimensionless number E * =q * / (v * l * ) represents the minimum dimensionless energy input required to raise the powder to the melting point, that is, to ensure that the continuous deposition layers are fully fused and the generation of holes is minimized. The dimensionless number of the ordinate is 1 / h * Indicates the size of the scanning interval relative to the laser spot radius, h * >1 means the scanning pitch is larger than the spot radius, otherwise it means the scanning pitch is smaller than the spot radius. Defined as E * and 1 / h * The product of , which represents the ratio of the dimensionless volumetric heat input to the dimensionless scanning spacing:

[0140]

[0141] The first term Aq / 3vlh is the key printing parameter that is preset and adjustable in the additive manufacturing process, and the second term 1 / ρC p (T m -T0) is the key thermal physical property parameter of the printing material in the additive manufacturing process. Figure 6 It can be seen that the process parameters for preparing Ti6Al4V using additive manufacturing technology are concentrated in Within the range. A larger value indicates sufficient energy input into the powder, while If the value is smaller, insufficient energy may result in incomplete fusion of powders. Indicates the effect of the same energy input in the additive manufacturing process, but different process variables combine to form the same It does not mean that the thermal cycle effect experienced by the material during the additive manufacturing process is the same. Due to different actual parameter sets, even if the same There will still be large differences in the molten pool morphology, defect feature size, etc. of the formed parts.

[0142] The fourth step is to develop an experimental plan for preparing Ti6Al4V using additive manufacturing process.

[0143] Figure 7 It is the dimensionless process diagram of additive materials formed by orthogonal design of reference process parameters. Figure 7 As shown, a three-factor three-level orthogonal design scheme is adopted. Based on the first dimensionless process parameter and the second dimensionless process parameter, q is selected. * , v * and h * As three factors, Figure 6 Within the process window of the dimensionless process diagram of Ti6Al4V prepared by additive manufacturing process guided by the method, three levels are set for each factor, and other parameters of the additive manufacturing process are set to fixed values. The parameter composition after orthogonal design is established as follows: Figure 7 The dimensionless process diagram of the additive manufacturing process for preparing Ti6Al4V material is shown to guide the experiment. It should be understood that the process window of the dimensionless process diagram of the additive manufacturing process for preparing Ti6Al4V here is determined based on the distribution density of the graphical representation of multiple groups of first dimensionless process parameters and corresponding second dimensionless process parameters of Ti6Al4V.

[0144] Step 5: Experimental verification.

[0145] Figure 8 This is the preparation process diagram of Ti6Al4V sample. Fig. 9 This is the size diagram of the Ti6Al4V sample in the uniaxial tension test. Fig.10 This is a diagram showing the tensile results of the Ti6Al4V sample in the embodiment of the present disclosure. Fig.11 The tensile properties of Ti6Al4V prepared by additive manufacturing process and other technical methods guided by the dimensionless process diagram of additive materials. Figure 8 to Figure 11 As shown in the figure, Ti6Al4V was prepared using additive manufacturing process equipment, and the parameters of the additive manufacturing process were determined by orthogonal experiments. The uniaxial tensile test of Ti6Al4V prepared by additive manufacturing process was carried out on a material testing machine. The tensile direction was parallel to the laser scanning direction, and the tensile strain rate was 5×10-4 / s, sample size Fig. 9 The test data was processed to measure the strength and elongation of the printed material. The tensile results are shown in Fig.10 As shown. Fig.11 From the comparison of the tensile performance results of Ti6Al4V prepared by various process guidance, it can be seen that the parameter determination method of the additive manufacturing process in the embodiment of the present disclosure uses the dimensionless process diagram of the additive material as an experimental design tool to study the additive manufacturing process parameters, and the performance of the obtained Ti6Al4V parts is at the advanced level of the process, indicating that the parameter selection using this method is very effective. At the same time, compared with the tensile performance of Ti6Al4V parts manufactured by electron beam melting (EBM), selective laser melting (SLM) additive manufacturing technology or other traditional methods, the parameter selection guided by the dimensionless process diagram of the additive material has the ability to directly manufacture high-strength and high-elongation titanium alloy parts without heat treatment, which verifies the feasibility of the dimensionless process diagram of the additive material to guide the additive preparation process to prepare components with excellent performance.

[0146] From the above, it can be seen that a relatively simple physical model is proposed in the parameter determination method of the additive manufacturing process provided in the embodiment of the present disclosure, so as to understand the interaction between parameters in the processing process based on the dimensionless equivalent energy density derived from the material parameters and the laser parameters, and effectively reduce the number of parameters that need to be studied in the additive manufacturing process. After comparing the theory with the experimental results, the connection between the process parameters and the material properties can be established. According to these basic characteristics, a simple theory can be used to predict the process window of the material, saving the experimental cost and cycle of researchers to determine the optimization process parameters in the early stage. And the performance of the deposited Ti6Al4V sample prepared under the guidance of the parameter determination method of the additive manufacturing process provided in the embodiment of the present disclosure is close to or even exceeds the level achieved by the traditional forging standards and other additive manufacturing technologies, showing the great advantages of the dimensionless process map in optimizing the process and tapping the potential of the mechanical properties of the material. At the same time, the parameter determination method of the additive manufacturing process provided by the embodiment of the present disclosure marks the process area of ​​the actual processing process on the dimensionless process diagram of additive manufacturing and divides the range of the process window. This framework can display a wide range of processing data, is simple and easy to use, and has high efficiency. Through theoretical prediction and experimental data comparison, the applicability of other metal materials in the processing of additive manufacturing processes can be evaluated, and the required process parameters can be estimated. By expanding the model, the dimensionless process diagram of additive manufacturing can be promoted and applied to the process development of various types of metal materials.

[0147] The above is an introduction to the solution provided by the embodiment of the present disclosure. It is understandable that, in order to achieve the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment disclosed herein, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0148] The embodiments of the present disclosure may divide the functional units of the device according to the above method examples. For example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments of the present disclosure is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0149] In the case of dividing each functional module according to each function, an exemplary embodiment of the present disclosure provides a parameter determination device for an additive manufacturing process. Fig.12 FIG. 1 is a schematic block diagram of a module of a parameter determination device for an additive manufacturing process according to an exemplary embodiment of the present disclosure. Fig.12 As shown, the additive material of the additive manufacturing process is the target additive material, and the parameter determination device 1200 of the additive manufacturing process includes:

[0150] The search module 1201 is used to search for target dimensionless process parameters of a target additive material from a process window of a dimensionless process map of an additive material.

[0151] The determination module 1202 is configured to determine a plurality of process parameters of the additive manufacturing process based on the target dimensionless process parameters and the material parameters of the target additive material.

[0152] The dimensionless process diagram is used to represent the mapping relationship between the first dimensionless process parameter and the second dimensionless process parameter. The first dimensionless process parameter is the dimensionless volume energy density, the second dimensionless process parameter is the ratio of the laser scanning spacing to the laser spot radius, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is the dimensionless equivalent energy density, and the target dimensionless process parameters include the first target dimensionless parameter and the second target dimensionless parameter located in the process window in the dimensionless process diagram of the additive material.

[0153] As a possible implementation manner, the material parameters of the additive material corresponding to the dimensionless process map of the additive material match the material parameters of the target additive material.

[0154] As a possible implementation method, the determination module 1202 is also used to dimensionlessly transform multiple sets of reference process parameters of additive materials in the additive manufacturing process to obtain multiple sets of dimensionless reference process parameters, each set of dimensionless reference process parameters including multiple dimensionless reference process parameters.

[0155] The determination module 1202 is further configured to determine a corresponding first dimensionless process parameter and a second dimensionless process parameter based on each set of dimensionless reference process parameters.

[0156] The determination module 1202 is also used to determine the dimensionless process diagram of the additive material based on the first dimensionless process parameter and the second dimensionless process parameter corresponding to different groups of dimensionless reference process parameters. The first dimensionless process parameter is used to determine the minimum dimensionless input energy required to lift the powder to the melting point, and the second dimensionless process parameter is used to determine the ratio of the laser scanning spacing to the laser spot radius.

[0157] In some embodiments, each set of reference process parameters includes basic reference process parameters and non-basic reference process parameters, and the non-basic reference process parameters are determined by the basic reference process parameters. The determination module 1202 is also used to determine the number of independent dimensions based on the dimensions of the same set of reference process parameters.

[0158] The determination module 1202 is further configured to obtain basic reference process parameters from the same set of reference process parameters, and the number of basic reference process parameters is the same as the number of independent dimensions.

[0159] The determination module 1202 is further configured to dimensionally transform the non-basic reference process parameters contained in each group of dimensionless reference process parameters based on the basic reference process parameters to obtain corresponding dimensionless reference process parameters.

[0160] In some embodiments, the multiple sets of reference process parameters are process parameters of multiple orthogonal experimental strategies determined by orthogonal experiments, and the determination module 1202 is also used to determine the process window of the dimensionless process diagram of the additive material based on the distribution density of the graphical representation of the mapping relationship in the dimensionless process diagram of the additive material.

[0161] The determination module 1202 is further configured to determine process parameters of multiple orthogonal test strategies within the process window of the dimensionless process map of the additive material.

[0162] The determination module 1202 is further configured to update multiple sets of reference process parameters using process parameters of multiple orthogonal test strategies.

[0163] In some embodiments, different orthogonal test strategies for the same additive material contain some of the same process parameters, and the determination module 1202 is further configured to determine a plurality of test factors of the orthogonal test based on the first dimensionless process parameter and the second dimensionless process parameter.

[0164] The determination module 1202 is further configured to determine a plurality of levels corresponding to each experimental factor based on the process window of the dimensionless process map of the additive material.

[0165] The determination module 1202 is further configured to determine multiple orthogonal test strategies for the additive material based on each test factor and multiple levels corresponding to each test factor.

[0166] As a possible implementation manner, the first dimensionless process parameter includes: dimensionless laser power, dimensionless scanning speed and dimensionless layer height, and the second dimensionless process parameter includes dimensionless scanning spacing.

[0167] In some embodiments, the product of the dimensionless laser scanning speed and the dimensionless layer height is proportional to the dimensionless laser power, and the ratio of the laser scanning pitch to the laser spot radius is determined by the dimensionless scanning pitch.

[0168] In some embodiments, the orthogonal test method is a three-factor three-level orthogonal test method, where the three factors include dimensionless laser power, dimensionless scanning speed, and dimensionless scanning spacing.

[0169] In some embodiments, each set of reference process parameters includes laser parameters, process variable parameters and material parameters, wherein the material parameters include material density (ρ), thermal diffusivity (α), thermal conductivity (λ), material melting point (T m ) and the initial material temperature (T0), the laser parameters include laser power (q), scanning speed (v), spot radius (r B ), the process variable parameters include layer height (l), scanning spacing (h) and powder feeding amount (ω).

[0170] Fig.13 Schematic block diagram of a chip of an exemplary embodiment of the present disclosure is shown. Fig.13 As shown, the chip 1300 includes one or more (including two) processors 1301 and a communication interface 1302. The communication interface 1302 can support the server to perform the data sending and receiving steps in the above method, and the processor 1301 can support the server to perform the data processing steps in the above method.

[0171] Optional, such as Fig.13As shown, the chip 1300 also includes a memory 1303, which may include a read-only memory and a random access memory, and provides operation instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory (NVRAM).

[0172] In some embodiments, Fig.13 As shown, the processor 1301 performs corresponding operations by calling the operation instructions stored in the memory (the operation instructions may be stored in the operating system). The processor 1301 controls the processing operations of any one of the terminal devices, and the processor may also be called a central processing unit (CPU). The memory 1303 may include a read-only memory and a random access memory, and provides instructions and data to the processor 1301. A portion of the memory 1303 may also include NVRAM. For example, in an application, the memory 1303, the communication interface 1302, and the processor 1301 are coupled together through a bus system 1304, wherein the bus system may include a power bus, a control bus, and a status signal bus in addition to a data bus. However, for the sake of clarity, in Fig.13 Various buses are labeled as bus system 1304 .

[0173] The method disclosed in the above-mentioned embodiment of the present disclosure can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (digital signal processing, DSP), an ASIC, a field-programmable gate array (field-programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiment of the present disclosure can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware.

[0174] The exemplary embodiment of the present disclosure also provides an electronic device, comprising: a processor; and a memory storing a program. The memory stores a computer program executable by the processor, and when the computer program is executed by the processor, the electronic device executes the method according to the embodiment of the present disclosure.

[0175] The exemplary embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to perform the method according to the embodiments of the present disclosure.

[0176] The exemplary embodiments of the present disclosure further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor of a computer, the computer is used to enable the computer to perform the method according to the embodiments of the present disclosure.

[0177] refer to Fig.14 , a block diagram of an electronic device 1400 that can be used as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0178] like Fig.14 As shown, the electronic device 1400 includes a computing unit 1401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) or a computer program loaded from a storage unit 1408 into a random access memory (RAM) 1403. In the RAM 1403, various programs and data required for the operation of the device 1400 can also be stored. The computing unit 1401, the ROM 1402, and the RAM 1403 are connected to each other via a bus 1404. An input / output (I / O) interface 1405 is also connected to the bus 1404.

[0179] Multiple components in the electronic device 1400 are connected to the I / O interface 1405, including: an input unit 1406, an output unit 1407, a storage unit 1408, and a communication unit 1409. The input unit 1406 can be any type of device that can input information to the electronic device 1400, and the input unit 1406 can receive input digital or character information, and generate key signal input related to the user settings and / or function control of the electronic device. The output unit 1407 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1408 can include but is not limited to a disk, an optical disk. The communication unit 1409 allows the electronic device 1400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth TM device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0180] like Fig.14 As shown, the computing unit 1401 can be various general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1401 performs the various methods and processes described above. For example, in some embodiments, the method of the exemplary embodiments of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1408. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 1400 via the ROM 1402 and / or the communication unit 1409. In some embodiments, the computing unit 1401 can be configured to execute the method in any other appropriate manner (e.g., by means of firmware).

[0181] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0182] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0183] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0184] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0185] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0186] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0187] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present disclosure is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, a tape; it may also be an optical medium, for example, a digital video disc (DVD); it may also be a semiconductor medium, for example, a solid state drive (SSD).

[0188] Although the present disclosure has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present disclosure. Accordingly, this specification and the drawings are merely exemplary illustrations of the present disclosure as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present disclosure. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A method for determining parameters of an additive manufacturing process, characterized in that: The additive material of the additive manufacturing process is a target additive material, and the parameter determination method of the additive manufacturing process includes: Searching for a target dimensionless process parameter of the target additive material from a process window of a dimensionless process map of the additive material, wherein the method for determining the dimensionless process map of the additive material includes: Non-dimensionalizing multiple sets of reference process parameters of additive materials in the additive manufacturing process to obtain multiple sets of dimensionless reference process parameters, each set of dimensionless reference process parameters including multiple dimensionless reference process parameters; Determining a corresponding first dimensionless process parameter and a second dimensionless process parameter based on each set of the dimensionless reference process parameters; Determining the dimensionless process map of the additive material based on the first dimensionless process parameters and the second dimensionless process parameters corresponding to different groups of the dimensionless reference process parameters; Determining a plurality of process parameters of the additive manufacturing process based on the target dimensionless process parameters and the material parameters of the target additive material, wherein the material parameters of the additive material corresponding to the dimensionless process diagram of the additive material match the material parameters of the target additive material; The dimensionless process diagram of the additive material is used to represent the mapping relationship between a first dimensionless process parameter and a second dimensionless process parameter, the first dimensionless process parameter is a dimensionless volume energy density, the second dimensionless process parameter is a ratio of a laser scanning spacing to a laser spot radius, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is a dimensionless equivalent energy density, and the target dimensionless process parameters include a first target dimensionless parameter and a second target dimensionless parameter located within the process window in the dimensionless process diagram of the additive material.

2. The method for determining parameters of an additive manufacturing process according to claim 1, characterized in that: Each group of reference process parameters includes basic reference process parameters and non-basic reference process parameters, and the non-basic reference process parameters are determined by the basic reference process parameters. The multiple groups of reference process parameters of the additive material in the additive manufacturing process are dimensionless to obtain multiple groups of dimensionless reference process parameters, and each group of dimensionless reference process parameters includes multiple dimensionless process parameters, including: determining a dimensionally independent quantity based on the dimensions of the same set of reference process parameters; Obtaining basic reference process parameters from the same set of reference process parameters, the number of the basic reference process parameters being the same as the number of the independent dimensions; The non-basic reference process parameters contained in each group of the dimensionless reference process parameters are dimensionally transformed based on the basic reference process parameters to obtain the corresponding dimensionless reference process parameters.

3. The method for determining parameters of an additive manufacturing process according to claim 1, characterized in that: The multiple groups of reference process parameters are process parameters of multiple orthogonal test strategies determined by orthogonal tests, and the method for determining the dimensionless process diagram of the additive material further includes: Determining a process window of the dimensionless process diagram of the additive material based on a distribution density of the graphical representation of the mapping relationship in the dimensionless process diagram of the additive material; Determining process parameters of a plurality of the orthogonal experimental strategies within the process window of the dimensionless process map of the additive material; A plurality of sets of reference process parameters are updated using the process parameters of a plurality of orthogonal experimental strategies.

4. The method for determining parameters of an additive manufacturing process according to claim 3, characterized in that: The orthogonal test strategies for different types of the same additive material contain some of the same process parameters, and the method for determining the dimensionless process diagram of the additive material further includes: Determining a plurality of experimental factors of the orthogonal experiment based on the first dimensionless process parameter and the second dimensionless process parameter; Determining a plurality of levels corresponding to each of the experimental factors based on a process window of a dimensionless process map of the additive material; A plurality of the orthogonal experimental strategies for the additive material are determined based on each of the experimental factors and the plurality of levels corresponding to each of the experimental factors.

5. The method for determining parameters of an additive manufacturing process according to claim 1, characterized in that: The first dimensionless process parameter is determined by dimensionless laser power, dimensionless scanning speed and dimensionless layer height, and the second dimensionless process parameter is determined by dimensionless scanning spacing; The first dimensionless process parameter is proportional to the dimensionless laser power, the product of the dimensionless scanning speed and the dimensionless layer height is inversely proportional to the first dimensionless process parameter, and the second dimensionless process parameter is inversely proportional to the laser scanning spacing.

6. The method for determining parameters of an additive manufacturing process according to claim 3 or 4, characterized in that: The orthogonal test method is a three-factor three-level orthogonal test method, and the three factors include dimensionless laser power, dimensionless scanning speed and dimensionless scanning spacing.

7. The method for determining parameters of an additive manufacturing process according to claim 1, characterized in that: Each set of reference process parameters includes laser parameters, process variable parameters and material parameters, wherein the material parameters include material density (ρ), thermal diffusivity (α), thermal conductivity (λ), material melting point (T m ) and the initial temperature of the material (T0), the laser parameters include laser power (q), scanning speed (v), spot radius (r B ), the process variable parameters include layer height (l), scanning spacing (h) and powder feeding amount (ω).

8. A device for determining parameters of an additive manufacturing process, characterized in that: The additive material of the additive manufacturing process is a target additive material, and the parameter determination device of the additive manufacturing process includes: A search module is used to search for a target dimensionless process parameter of the target additive material from a process window of a dimensionless process map of the additive material, wherein the method for determining the dimensionless process map of the additive material includes: Non-dimensionalizing multiple groups of reference process parameters of additive materials in the additive manufacturing process to obtain multiple groups of dimensionless reference process parameters, each group of dimensionless reference process parameters including multiple dimensionless reference process parameters; Determining a corresponding first dimensionless process parameter and a second dimensionless process parameter based on each set of the dimensionless reference process parameters; Determining the dimensionless process map of the additive material based on the first dimensionless process parameters and the second dimensionless process parameters corresponding to different groups of the dimensionless reference process parameters; a determination module, configured to determine a plurality of process parameters of the additive manufacturing process based on the target dimensionless process parameters and the material parameters of the target additive material, wherein the material parameters of the additive material corresponding to the dimensionless process diagram of the additive material match the material parameters of the target additive material; The dimensionless process diagram of the additive material is used to represent the mapping relationship between a first dimensionless process parameter and a second dimensionless process parameter, the first dimensionless process parameter is a dimensionless volume energy density, the second dimensionless process parameter is a ratio of a laser scanning spacing to a laser spot radius, the ratio of the first dimensionless process parameter to the second dimensionless process parameter is a dimensionless equivalent energy density, and the target dimensionless process parameters include a first target dimensionless parameter and a second target dimensionless parameter located within the process window in the dimensionless process diagram of the additive material.

9. An electronic device, characterized in that: include: processor; as well as, A memory for storing programs; The program includes instructions, which, when executed by the processor, cause the processor to execute the parameter determination method for the additive manufacturing process according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the parameter determination method of the additive manufacturing process according to any one of claims 1 to 7.

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