A method and system for energy consumption prediction and process optimization of selective laser cladding forming

Abstract

The present invention discloses a method and system for predicting energy consumption and optimizing process of selective laser cladding forming. The present invention comprises establishing a specific energy consumption model based on process parameters of selective laser cladding forming. For the specific energy consumption model, a specified optimization algorithm is used to solve the optimal process parameter value when the specific energy consumption model is optimal. The functional relationship between the energy consumption and process parameters of a selective laser cladding system is represented by the specific energy consumption model. The coupling change relationship between the process parameters and the energy consumption of the equipment can be explored. The energy consumption of the selective laser cladding system can be changed by accurately adjusting a single or multiple process parameters under different working conditions. The change trend of the energy consumption of the equipment with the process parameters under different working conditions is explored, so that the optimal process parameter value when the specific energy consumption is optimal can be quickly solved, and the efficiency of solving the optimal process parameters can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of additive manufacturing process control and process optimization, and in particular to a method and system for energy consumption prediction and process optimization of selective laser cladding forming. Background Art

[0002] Selective Laser Melting (SLM) plays an increasingly important role in the fields of rapid prototyping and surface modification of materials, and is increasingly widely used in aerospace, medical, metallurgy, engineering and other fields. In the context of energy conservation and emission reduction as a key topic, how to reasonably control the SLM system to achieve the optimal energy efficiency of the selective laser cladding additive manufacturing process is of great significance to the development of this field.

[0003] At present, there have been some studies on the energy consumption prediction and energy efficiency optimization of the selective laser cladding additive manufacturing system. Invention patent 201811238146.4 discloses a method for energy consumption prediction and energy-saving control of the selective laser melting process. By obtaining the energy consumption and working time of each component of the equipment, the total energy consumption of the equipment is obtained, and different process parameters and component layouts are adjusted to compare the total energy consumption, so as to select the best process solution. Patent 202110656151.2 discloses a laser remanufacturing process energy consumption monitoring system and optimization method. By establishing an energy consumption model and a fitting function of process parameters and equipment subsystems, the process parameter values ​​when the energy consumption is optimal are obtained in combination with an optimization algorithm.

[0004] However, the current energy consumption prediction method mainly measures the power of local subsystems of the equipment and the working time of the corresponding subsystems, and it is difficult to quickly and accurately establish the relationship between process parameters and energy consumption. It takes a long time to measure the power of equipment subsystems and their working time through experiments many times, which consumes a lot of energy and is costly. The optimization process of process parameters is fragmented, and it is difficult to accurately locate the optimal parameters, which is not universally applicable. Not only that, energy consumption optimization also needs to consider the volume cladding efficiency of the processed material, that is, the system working energy efficiency. Therefore, establishing a mathematical relationship between process parameters and equipment energy efficiency, and combining optimization algorithms to complete global optimization can reduce experimental dependence, while having higher prediction accuracy, optimization efficiency and universality. Summary of the invention

[0005] Technical problem to be solved by the present invention: In view of the above-mentioned problems in the prior art, a method and system for predicting energy consumption and optimizing process of selective laser cladding forming are provided. The present invention establishes a specific energy consumption model based on the process parameters of selective laser cladding forming. The functional relationship between the energy consumption and process parameters of the selective laser cladding system is represented by the specific energy consumption model. The coupling change relationship between the process parameters and the energy consumption of the equipment can be explored. The energy consumption of the selective laser cladding system can be changed by accurately adjusting a single or multiple process parameters under different working conditions. The changing trend of the energy consumption of the equipment with the process parameters under different working conditions is explored, so that the optimal process parameter value when the specific energy consumption model is optimal can be quickly solved, which can effectively improve the efficiency of solving the optimal process parameters.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for energy consumption prediction and process optimization of selective laser cladding forming, comprising:

[0008] 1) Establish a specific energy consumption model based on the process parameters of selective laser cladding forming, which is the total energy consumption E in the additive manufacturing stage. a The forming volume V in the additive process a The ratio of

[0009] 2) For the specific energy consumption model, the specified optimization algorithm is used to solve the optimal process parameter values ​​when the specific energy consumption model is optimal.

[0010] Optionally, the process parameters of the selected area laser cladding forming in step 1) include laser cladding power P0, laser scanning speed v, lateral overlap rate λ and powder thickness h s .

[0011] Optionally, the total energy consumption E of the additive manufacturing stage is a The calculation function expression is:

[0012] E a =E sa +E ma +E ca +E ga +E p +E l +E tab ,

[0013] In the above formula, E sa is the energy consumption of the CNC system in the additive manufacturing stage; E ma is the energy consumption of the lighting module during the additive manufacturing stage; E ca is the energy consumption of the cooling module during the additive manufacturing stage; E ga is the energy consumption of the shielding gas delivery module during the additive manufacturing stage; E p is the energy consumption of the powder laying module; El is the energy consumption of laser cladding module; E tab is the energy consumption of the workbench motion control module; among them, the energy consumption of the laser cladding module is E l The calculation function expression is:

[0014] E l =E lw +E lm +E ld =P lw ·t lw +P0·t lm +P ld ·t ld ,

[0015] In the above formula, E lw E is the standby energy consumption; lm is the cladding energy consumption; E ld Interlayer stop energy consumption; P lw is the standby power of the laser cladding module; P0 is the laser cladding power; P ld is the inter-layer stopping power; t lw is the standby time of laser cladding module; t lm is the laser cladding time, laser cladding time t lm It is obtained by dividing the total length of the cladding path S by the laser scanning speed v; t ld It is the interval time between layers.

[0016] Optionally, the forming volume V during the additive process is a The calculation function expression is:

[0017] V a =S(1-λ)wh s ,

[0018] In the above formula, S is the total length of the cladding track; λ is the lateral overlap rate; w is the width of a single cladding track; h s The thickness of the powder.

[0019] Optionally, when the specific energy consumption model based on the process parameters of the selective laser cladding forming is established in step 1), the workpiece formed by the selective laser cladding forming is a regular cubic workpiece, and the calculation function expression of the total length S of the cladding path is:

[0020]

[0021] In the above formula, n is the number of cladding layers; m i is the number of cladding passes in the i-th layer; l is the length of the cladding pass; W i is the width of the workpiece in the i-th layer; where the number of cladding passes in the i-th layer is m i The calculation function expression is:

[0022]

[0023] In the above formula, W i is the maximum physical width of the i-th layer; Δs is the laser scanning spacing; λ is the lateral overlap rate; w is the width of a single cladding track; the calculation function expression of the cladding layer number n is:

[0024]

[0025] In the above formula, H is the height of the workpiece; μ is the longitudinal overlap rate; h is the height of the cladding track; d is the depth of the cladding track; and the calculation function expression of the longitudinal overlap rate μ is:

[0026]

[0027] In the above formula, c z is the longitudinal overlap height of the cladding track; h is the height of the cladding track; d is the depth of the cladding track; h s The thickness of the powder.

[0028] Optionally, when the specific energy consumption model based on the process parameters of the selective laser cladding forming is established in step 1), the workpiece formed by the selective laser cladding forming is an asymmetric workpiece, and the calculation function expression of the total length S of the cladding path is:

[0029] S=L total +m total (1-λ)wn,

[0030] In the above formula, L total is the total length of the cladding path in the y-axis direction; m total is the total number of cladding paths in the Y-axis direction required for the workpiece to be fully formed; λ is the lateral overlap rate; w is the width of a single cladding path; n is the number of cladding layers; where the total length of the cladding path in the Y-axis direction is L total The calculation function expression is:

[0031]

[0032] In the above formula, j is the layer number when calculating the cladding path length; n is the number of cladding layers; m b is the number of cladding passes in the workpiece width at stage b; λ is the lateral overlap rate; w is the width of a single cladding pass; f L (i) j is the length function f L (i) The length at the jth layer; where the length function f L The calculation function expression of (i) is:

[0033]

[0034] In the above formula, l iis the actual length of the ith cladding pass; W is the workpiece width; λ is the lateral overlap rate; w is the width of a single cladding pass. Each time the laser moves to process the next cladding pass, the cladding width increases by ΔW = (1-λ)w. The calculation function expression f for the length of the ith cladding pass processed in any stage b is L(b) (i) is:

[0035] f L(b) (i) = f L(b-1) (i b-1 )±(1-λ)w(ii b-1 )tanα i ,

[0036] In the above formula, f L(b-1) (i b-1 ) Processing the i-th b-1 The length of the cladding path, i b-1 The laser scan is translated to a width W b-1 Total number of additive layers at the time; α i is the angle between the outer contour of the workpiece and the xz plane. When the length of the workpiece increases with the width, the "±" in the above formula is taken as "+", otherwise it is taken as "-". The total number of cladding passes in the Y-axis direction required for the workpiece to be fully formed is m total The calculation function expression is:

[0037]

[0038] In the above formula, n a The height is H a The number of cladding layers of the workpiece; μ is the longitudinal overlap rate; h is the cladding track height; d is the cladding track depth; f w (i) is the width function of the i-th cladding path, and:

[0039]

[0040] In the above formula, W i is the maximum physical width of the workpiece at layer i; f W(a) (i) corresponds to H a-1 <H≤H a The entity width function of the a-th stage; H a is the height of the upper boundary of the workpiece at stage a; H is the workpiece height; h is the height of the cladding track; d is the depth of the cladding track; μ is the longitudinal overlap rate; the solid width function f at stage a W(a) The calculation function expression of (i) is:

[0041] f w(a) (i) = f W(a-1) (i a-1 )±h s (iia-1 )tanθ i ,

[0042] In the above formula, f W(a-1) (i a-1 ) is the entity width function of the a-1 stage; i a-1 To add material to H a-1 Total number of additive layers at height; h s is the powder thickness, θ i It is the angle between the outer contour of the workpiece and the yz plane. When the physical width of the workpiece increases with the height, the "±" in the above formula takes "+", otherwise it takes "-".

[0043] Optionally, when establishing a specific energy consumption model based on process parameters of selective laser cladding forming in step 1), a single cladding track width w, cladding track height h and cladding track depth d are all calculated based on a linear regression model of laser cladding power P0 and laser scanning speed v.

[0044] Optionally, the optimization algorithm specified in step 2) refers to a genetic algorithm, a particle swarm algorithm or a simulated annealing algorithm.

[0045] In addition, the present invention also provides a selective laser cladding forming energy consumption prediction and process optimization system, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the steps of the selective laser cladding forming energy consumption prediction and process optimization method.

[0046] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute the selective laser cladding forming energy consumption prediction and process optimization method.

[0047] Compared with the prior art, the present invention has the following advantages:

[0048] 1. In the full-process energy consumption analysis of the SLM system, the energy consumption in the additive manufacturing stage is the research focus. Specific energy consumption, as a characterization of energy efficiency, is the objective function of optimization. The lower the specific energy consumption, the less energy the system consumes when cladding the same volume of material, the higher the system energy efficiency, and the more energy-saving. The present invention includes establishing a specific energy consumption model based on the process parameters of selective laser cladding forming. For the specific energy consumption model, a specified optimization algorithm is used to solve the optimal process parameter values ​​when the specific energy consumption model is optimal. The functional relationship between the energy consumption and process parameters of the selective laser cladding system is represented by the specific energy consumption model, and the coupling change relationship between the process parameters and the energy consumption of the equipment can be explored. The energy consumption of the selective laser cladding system can be changed by accurately adjusting a single or multiple process parameters under different working conditions, and the changing trend of the equipment energy consumption with the process parameters under different working conditions can be explored.

[0049] 2. The present invention can explore the coupling change relationship between process parameters and equipment energy consumption, can change the energy consumption of the selective laser cladding system by accurately adjusting a single or multiple process parameters under different working conditions, and explore the changing trend of equipment energy consumption with process parameters under different working conditions. Based on this, the specified optimization algorithm is used to adjust the process parameters in a direction and purposeful manner, and the optimal process parameter values ​​when the specific energy consumption model is optimal can be quickly solved, which can effectively improve the efficiency of solving the optimal process parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a basic flow chart of the method of Embodiment 1 / Embodiment 2 of the present invention.

[0051] Figure 2 Schematic diagram of the laser cladding scanning path and workpiece size in Example 1 of the present invention.

[0052] Figure 3 Schematic diagram of the dimensions of the cladding track in the first embodiment of the present invention.

[0053] Figure 4 Schematic diagram of the size function division of the irregular workpiece in the x-axis direction in the second embodiment of the present invention.

[0054] Figure 5 Schematic diagram of the width function division of an irregular workpiece in the z-axis direction in the second embodiment of the present invention.

[0055] Figure 6 Schematic diagram of the shape and size of the honeycomb structure workpiece in the second embodiment of the present invention.

[0056] Figure 7 It is a schematic diagram of the horizontal stacking and vertical stacking processing scheme of the honeycomb workpiece in the second embodiment of the present invention.

[0057] Figure 8 The figure is a comparison of the total energy consumption of the forming auxiliary subsystem and the laser forming subsystem under two schemes in the second embodiment of the present invention.

[0058] Fig. 9 The figure compares the energy consumption of the laser cladding module under two schemes in the second embodiment of the present invention. DETAILED DESCRIPTION

[0059] Embodiment 1:

[0060] like Figure 1 As shown, the energy consumption prediction and process optimization method of selective laser cladding forming in this embodiment includes:

[0061] 1) Establish a specific energy consumption model based on the process parameters of selective laser cladding forming. The specific energy consumption model is the total energy consumption E in the additive manufacturing stage. a The forming volume V in the additive processa The ratio of

[0062] 2) For the specific energy consumption model, the specified optimization algorithm is used to solve the optimal process parameter values ​​when the specific energy consumption model is optimal.

[0063] In this embodiment, the process parameters of the laser cladding forming in the selected area in step 1) include the laser cladding power P0, the laser scanning speed v, the lateral overlap rate λ and the powder thickness h. s .

[0064] In this embodiment, the total energy consumption E in the additive manufacturing stage is a The calculation function expression is:

[0065] E a =E sa +E ma +E ca +E ga +E p +E l +E tab ,

[0066] In the above formula, E sa is the energy consumption of the CNC system in the additive manufacturing stage; E ma is the energy consumption of the lighting module during the additive manufacturing stage; E ca is the energy consumption of the cooling module during the additive manufacturing stage; E ga is the energy consumption of the shielding gas delivery module during the additive manufacturing stage; E p is the energy consumption of the powder laying module; E l is the energy consumption of laser cladding module; E tab is the energy consumption of the workbench motion control module; among them, the energy consumption of the laser cladding module is E l The calculation function expression is:

[0067] E l =E lw +E lm +E ld =P lw ·t lw +P0·t lm +P ld ·t ld ,

[0068] In the above formula, E lw E is the standby energy consumption; lm is the cladding energy consumption; E ld Interlayer stop energy consumption; P lw is the standby power of the laser cladding module; P0 is the laser cladding power; P ld is the inter-layer stopping power; t lw is the standby time of the laser cladding module; t lmis the laser cladding time, laser cladding time t lm The total length of the cladding path S is divided by the laser scanning speed v (i.e. t lm =S / v); t ld is the interval time between layers. In order to complete the accumulation of materials layer by layer, a layer of powder material needs to be laid before the laser scanning of each layer. After the laser scanning, the powder melts and solidifies, so as to realize the stacking of the processed parts. Therefore, the energy consumption of the powder laying module is E p The calculation function expression is:

[0069] E p =P p ·t ps n,

[0070] In the above formula, E p is the total energy consumption of the powder laying module; P p is the power of the powder laying module; t ps is the time required for each layer of powder; n is the number of layers of additive processing. The interlayer pause time can be approximately equal to the time required for each layer of powder by the powder laying module. The cladding power P lm = ... tab It is related to the shape and size of the processing object.

[0071] Assume P s , P m , P c , P g are the measured powers of the CNC module, lighting module, cooling module and protective gas delivery module respectively, then the total energy consumption E in the additive manufacturing stage is a The calculation function expression can also be expressed as:

[0072]

[0073] In the above formula, t2 is the time point when the system enters the additive manufacturing stage; t3 is the time point when it enters the next stage.

[0074] The total energy consumption of the selective laser cladding system is composed of the energy consumption of three subsystems: the laser forming subsystem, the forming auxiliary subsystem, and the worktable motion control module. The laser forming subsystem includes a powder spreading module and a laser cladding module, and the forming auxiliary subsystem includes a CNC module, a lighting module, a cooling module, and a protective gas delivery module. The total energy consumption model of the system can be expressed as:

[0075] E=Ep +E l +E s +E m +E c +E g +E tab ,

[0076] In the above formula: E is the total energy consumption; E p E is the energy consumption of the powder laying module; l is the energy consumption of laser cladding module; E s is the energy consumption of the CNC module; E m is the energy consumption of the lighting module; E c is the energy consumption of cooling module; E g Energy consumption for protecting gas delivery module; E tab is the energy consumption of the workbench motion control module. The entire process flow of the selective laser cladding system can be divided into the startup standby stage, the additive manufacturing stage, and the end standby stage. From the moment of power-on, the system enters the startup standby stage. At this time, the forming auxiliary subsystem is started, and the protective gas delivery module inputs inert protective gases such as nitrogen into the working space to form an oxygen-free environment to prevent the workpiece from oxidizing during processing. The laser transmitter in the laser cladding module is positioned to the starting point of the processing path. In this process, the energy consumption mainly comes from the CNC module, the lighting module, the cooling module and the protective gas delivery module, and their powers are P respectively. s , P m , P c , P g Therefore, the total energy consumption calculation formula for the startup standby stage is:

[0077]

[0078] In the above formula: E w is the total energy consumption in the startup and standby phase; E sw E is the energy consumption of the CNC module during the startup standby phase; mw E is the energy consumption of the lighting module during the startup standby phase; cw E is the energy consumption of the cooling module during the startup standby phase; gw is the energy consumption of the protective gas delivery module in the startup standby stage; t1 is the time point when the system enters the startup standby stage, and t2 is the time point when the system enters the additive manufacturing stage; P s , P m , P c , P g They are the power of CNC module, lighting module, cooling module and protective gas delivery module respectively.

[0079] When the additive manufacturing stage is completed and the system enters the end standby stage, each working module in the forming auxiliary subsystem gradually stops working. The energy consumption calculation formula for this stage is:

[0080]

[0081] In the above formula: E v is the total energy consumption at the end of the standby phase; E sv The energy consumption of the CNC module at the end of the standby phase; E mv The energy consumption of the lighting module when the standby phase ends; E cv The energy consumption of the cooling module at the end of the standby phase; E gv The energy consumption of the protective gas delivery module at the end of the standby phase; P s , P m , P c , P g They are the power of the numerical control module, lighting module, cooling module and protective gas delivery module respectively; t3 is the time point of entering the end of the standby stage; t4 is the shutdown time point.

[0082] In this embodiment, the forming volume V in the additive process a The calculation function expression is:

[0083] V a =S(1-λ)wh s ,

[0084] In the above formula, S is the total length of the cladding track; λ is the lateral overlap rate; w is the width of a single cladding track; h s The thickness of the powder.

[0085] Specific energy consumption refers to the energy required to form a unit volume of material or remove a unit volume of material. Its calculation function expression is:

[0086]

[0087] In the above formula, e a is specific energy consumption; E pro is the energy consumed; V is the volume of the formed or removed material. In this embodiment, in the additive manufacturing process, the specific energy consumption model refers to the total energy consumption E in the additive manufacturing stage. a The forming volume V in the additive process a The calculation function expression is:

[0088]

[0089] In the above formula: e is specific energy consumption; E a is the total energy consumption in the additive manufacturing stage; V a is the cladding forming volume in the additive process; P s , P m , P c , P gThey are the power of CNC module, lighting module, cooling module and protective gas delivery module respectively; E p , E l , E tab are the energy consumption of the powder laying module, the laser cladding module and the worktable motion control module respectively; t2 is the time point when the additive manufacturing stage is included; t3 is the time point when the standby stage ends; S is the total length of the cladding path; λ is the lateral overlap rate; w is the width of a single cladding path; h s The thickness of the powder.

[0090] In this embodiment, when the specific energy consumption model based on the process parameters of the selective laser cladding forming is established in step 1), the workpiece formed by the selective laser cladding forming is a regular cubic workpiece.

[0091] In the process of additive manufacturing, in order to make the width and height of the cladding path as uniform as possible, the laser scanning is performed at a constant speed. Therefore, as long as the total length of the cladding path is known, that is, the total length of the laser scanning path, the working time of the laser scanning can be calculated; for workpieces with regular cubic structures, the total length of the laser scanning path can be calculated based on the axial dimensions of the workpiece and the dimensions of the cladding path. Figure 2 As shown: Assume that the laser scans along the y-axis, translates along the x-axis, and stacks along the z-axis; the width of the workpiece in the x-axis direction is W, the length in the y-axis direction is L, the height in the z-axis direction is H, the number of stacking layers in the z-axis direction is n, and the number of cladding passes in each layer is m. The width of each cladding pass is w, the length is l, the height is h, the depth is d, and the overlap length of the cladding pass in the transverse direction (x-axis direction) is c x , the overlap height of the longitudinal (z-axis direction) cladding track is c z , the thickness of the powder layer is h s ,like Figure 3 shown.

[0092] In this embodiment, the calculation function expression of the total length S of the cladding track is:

[0093]

[0094] In the above formula, n is the number of cladding layers; m i is the number of cladding passes in the i-th layer; l is the length of the cladding pass; W i is the width of the workpiece at the i-th layer; the total width of the cladding layer based on the regular cubic structure is equal to the width of the workpiece W, and is also approximately equal to the sum of the single-layer laser scanning spacing. The number of cladding passes at the i-th layer is m i The calculation function expression is:

[0095]

[0096] In the above formula, W iis the maximum physical width of the i-th layer; Δs is the laser scanning spacing; λ is the lateral overlap ratio; w is the width of a single cladding track;

[0097] Since the total height of the cladding layer is equal to the workpiece height H, the calculation function expression of the cladding layer number n is:

[0098]

[0099] In the above formula, H is the height of the workpiece; μ is the longitudinal overlap rate; h is the height of the cladding track; d is the depth of the cladding track; and the calculation function expression of the longitudinal overlap rate μ is:

[0100]

[0101] In the above formula, c z is the longitudinal overlap height of the cladding track; h is the height of the cladding track; d is the depth of the cladding track; h s is the powder thickness. The overlap rate μ in the z-axis direction refers to the ratio of the overlap height of every two cladding passes in the z-axis direction to the total height of a single cladding pass. The overlap height in the z-axis direction is determined by the height and depth of the molten pool and the thickness of the powder layer. The total height of the cladding pass must be greater than the thickness of the powder layer.

[0102] The transverse overlap ratio λ refers to the ratio of the overlap length of every two cladding passes in the x-axis direction to the width of a single cladding pass, that is:

[0103]

[0104] In the above formula, λ is the transverse overlap ratio; c x is the overlapping length of the transverse cladding paths; w is the width of a single cladding path.

[0105] In this embodiment, when the specific energy consumption model of the process parameters based on the selective laser cladding forming is established in step 1), the single cladding track width w, cladding track height h and cladding track depth d are all calculated based on the linear regression model of the laser cladding power P0 and the laser scanning speed v. The linear regression model f can be expressed as:

[0106] D=f(P0,v),

[0107] In the above formula, D is the size parameter of the cladding path (single cladding path width w, cladding path height h and cladding path depth d); P0 is the laser cladding power; v is the laser scanning speed. For example, when Ti-47Al-2Cr-2Nb alloy is used as the cladding material, the linear regression model f of the single cladding path width w, cladding path height h and cladding path depth d are respectively:

[0108]

[0109]

[0110]

[0111] Undoubtedly, the functional expression of the linear regression model f will be different for different cladding materials. The linear regression model f of the corresponding single cladding track width w, cladding track height h and cladding track depth d can be obtained by conducting experiments based on the actual cladding materials used, which will not be elaborated here.

[0112] The optimization algorithm specified in step 2) of this embodiment refers to a genetic algorithm. In step 2) of this embodiment, the optimal process parameter value when the genetic algorithm is used to solve the optimal specific energy consumption model adopts a function expression, which can be expressed as:

[0113] e min =ming(P0, v, λ, h s ),

[0114] In the above formula, e min is the optimal value of the specific energy consumption model, g(P0, v, λ, h s ) is the specific energy consumption model for laser cladding power P0, laser scanning speed v, lateral overlap rate λ and powder thickness h s Function form. It should be noted that the optimization algorithm can also select other optimization algorithms as needed, such as particle swarm algorithm, simulated annealing algorithm, etc. It should be noted that the present invention only involves the basic application of genetic algorithm, particle swarm algorithm and simulated annealing algorithm, and does not involve any improvement of genetic algorithm, particle swarm algorithm and simulated annealing algorithm. Therefore, the implementation of genetic algorithm, particle swarm algorithm and simulated annealing algorithm will not be described in detail here.

[0115] In summary, there is currently little research on the energy consumption prediction of the selective laser cladding system during the entire process. The present invention implements a new energy consumption prediction method, starting from the forming path modeling of the processing object, analyzing the overlap between the laser scanning path and the cladding path at the micro level, and combining the process parameters to deduce the working time of each subsystem in the laser cladding process, and then obtain the energy consumption of the entire system. The functional relationship between the energy consumption and process parameters of the selective laser cladding system is represented by the specific energy consumption model, which can explore the coupling change relationship between the process parameters and the energy consumption of the equipment, and can change the energy consumption of the selective laser cladding system by accurately adjusting a single or multiple process parameters under different working conditions, and explore the changing trend of the equipment energy consumption with the process parameters under different working conditions. While being able to explore the coupling change relationship between process parameters and equipment energy consumption, being able to change the energy consumption of the selective laser cladding system by accurately adjusting single or multiple process parameters under different working conditions, and exploring the changing trend of equipment energy consumption with process parameters under different working conditions, combined with the genetic optimization algorithm, the process parameters can be adjusted directionally and purposefully, and the optimal process parameter values ​​when the specific energy consumption model is optimal can be quickly solved, which can effectively improve the efficiency of solving the optimal process parameters.

[0116] In addition, this embodiment also provides a selective laser cladding forming energy consumption prediction and process optimization system, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the steps of the aforementioned selective laser cladding forming energy consumption prediction and process optimization method.

[0117] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute the aforementioned selective laser cladding forming energy consumption prediction and process optimization method.

[0118] Embodiment 2:

[0119] This embodiment is basically the same as the first embodiment, and the main difference is that when establishing the specific energy consumption model based on the process parameters of the selective laser cladding forming in step 1) of this embodiment, the workpiece formed by the selective laser cladding is an asymmetric workpiece, and the calculation method of the total length S of the cladding path is different.

[0120] In this embodiment, for an asymmetric workpiece, the calculation function expression of the total length S of the cladding path is:

[0121] S=L total +m total (1-λ)wn,

[0122] In the above formula, L total is the total length of the cladding path in the y-axis direction; m totalis the total number of cladding paths in the Y-axis direction required for the workpiece to be fully formed; λ is the lateral overlap rate; w is the width of a single cladding path; n is the number of cladding layers; where the total length of the cladding path in the Y-axis direction is L total The calculation function expression is:

[0123]

[0124] In the above formula, j is the layer number when calculating the cladding path length; n is the number of cladding layers; m b is the number of cladding passes in the workpiece width at stage b; λ is the lateral overlap rate; w is the width of a single cladding pass; f L (i) j is the length function f L (i) length at the jth layer;

[0125] In the translation direction of the laser scanning (i.e., the x-axis direction), there is a linear relationship between the length l of each laser scanning cladding pass and its horizontal position, i.e., the number of cladding passes. Figure 4 The method shown is divided into different areas in the x-axis direction. In each area, the actual length of the cladding track is approximately proportional or inversely proportional to the cladding track width, overlap rate and number of cladding tracks. It is divided into b function areas, and the length function f L The calculation function expression of (i) is:

[0126]

[0127] In the above formula, l i is the actual length of the ith cladding pass; W is the workpiece width; λ is the lateral overlap rate; w is the width of a single cladding pass. Each time the laser moves to process the next cladding pass, the cladding width increases by ΔW = (1-λ)w. The calculation function expression f for the length of the ith cladding pass processed in any stage b is L(b) (i) is:

[0128] f L(b) (i) = f L(b-1) (i b-1 )±(1-λ)w(ii b-1 )tanα i ,

[0129] In the above formula, f L(b-1) (i b-1 ) Processing the i-th b-1 The length of the cladding path, i b-1 The laser scan is translated to a width W b-1 Total number of additive layers at the time; α iis the angle between the outer contour of the workpiece and the xz plane. When the length of the workpiece increases with the width, the "±" in the above formula is taken as "+", otherwise it is taken as "-". The total number of cladding passes in the Y-axis direction required for the workpiece to be fully formed is m total The calculation function expression is:

[0130]

[0131] In the above formula, n a The height is H a The number of cladding layers of the workpiece; μ is the longitudinal overlap rate; h is the cladding track height; d is the cladding track depth; f w (i) is the width function of the i-th cladding path.

[0132] In asymmetric workpieces, the physical width of each layer may be different. For a workpiece of a given shape and size, the maximum physical width of a layer in the x-axis direction is determined by the number of layers it is in. In the stacking direction, the physical width of certain height areas of the workpiece is proportional or inversely proportional to the height, so the workpiece is divided into different function areas, such as Figure 5 As shown, we have:

[0133]

[0134] In the above formula, W i is the maximum physical width of the workpiece at layer i; f W(a) (i) corresponds to H a-1 <H≤H a The entity width function of the a-th stage; H a is the height of the upper boundary of the workpiece at stage a; H is the height of the workpiece; h is the height of the cladding track; d is the depth of the cladding track; μ is the longitudinal overlap rate;

[0135] After each powder coating, the workpiece is raised by h s The maximum entity width varies with the height, so the entity width function f in stage a W(a) The calculation function expression of (i) is:

[0136] f W(a) (i) = f w(a-1) (i a-1 )±h s (ii a-1 )tanθ i ,

[0137] In the above formula, f W(a-1) (i a-1 ) is the entity width function of the a-1 stage; i a-1 To add material to H a-1 Total number of additive layers at height; h sis the powder thickness, θ i It is the angle between the outer contour of the workpiece and the yz plane. When the physical width of the workpiece increases with the height, the "±" in the above formula takes "+", otherwise it takes "-".

[0138] In this embodiment, the energy efficiency optimization of the SLM system is solved by processing a Ti-47Al-2Cr-2Nb alloy honeycomb structure workpiece. Figure 6 Two different processing procedures are designed to achieve rapid prototyping of honeycomb structure workpieces, which is used to further explore the influence of different processing procedures on system energy consumption. Figure 7 As shown in the figure: the first process scheme is to scan the laser along the y-axis direction, translate in the x-axis direction, and stack in the z-axis direction (i.e., the cross-sectional direction); the second process scheme is to scan the laser along the x-axis direction, translate in the z-axis direction, and stack in the y-axis direction (i.e., the longitudinal cross-sectional direction). The optimal process parameters and specific energy consumption of the two process schemes are compared through the energy efficiency optimization strategy.

[0139] In this embodiment, the parameters of each subsystem are obtained as shown in Table 1.

[0140] Table 1: Parameters of each subsystem.

[0141]

[0142]

[0143] Finally, the calculation results under the two processing schemes, that is, the optimal process parameter values, are obtained, as shown in Table 2.

[0144] Table 2: Optimal process parameter values ​​under two processing schemes.

[0145] Technology <![CDATA[P 0 / W ]]> <![CDATA[v / (mm·s -1 )]]> <![CDATA[h s / mm ]]> λ w / mm h / mm d / mm S / mm <![CDATA[e / (J·mm -3) ]]> Horizontal stacking 373.495 90.0 0.150 0.301 0.448 0.073 0.092 31 583.492 677.529 Vertical stacking 373.073 90.0 0.148 0.301 0.448 0.073 0.092 31 883.209 920.771

[0146] Comparison of total energy consumption of forming auxiliary subsystem and laser forming subsystem under two processing schemes (lateral stacking and longitudinal stacking scheme) Figure 8 As shown in the figure, the energy consumption of laser cladding module is compared. Fig. 9 As shown. Therefore, the optimal process parameter value under one of the two processing schemes (Scheme 1: horizontal stacking and Scheme 2: vertical stacking scheme) can be selected according to the needs. Through the above method, the energy consumption prediction and process optimization method of selective laser cladding forming of the present invention is not only applicable to regular cubic workpieces, but also to asymmetric workpieces, and achieves the same technical effect as that of embodiment 1.

[0147] In addition, this embodiment also provides a selective laser cladding forming energy consumption prediction and process optimization system, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the steps of the aforementioned selective laser cladding forming energy consumption prediction and process optimization method.

[0148] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute the aforementioned selective laser cladding forming energy consumption prediction and process optimization method.

[0149] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0150] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for energy consumption prediction and process optimization of selective laser cladding forming, characterized in that: include: 1) Establish a specific energy consumption model based on the process parameters of selective laser cladding forming, which is the total energy consumption E in the additive manufacturing stage. a The forming volume V in the additive process a The ratio of 2) For the specific energy consumption model, the specified optimization algorithm is used to solve the optimal process parameter values ​​when the specific energy consumption model is optimal; The forming volume V in the additive process a The calculation function expression is: V a =S(1-λ)wh s , In the above formula, S is the total length of the cladding track; λ is the lateral overlap rate; w is the width of a single cladding track; h s is the thickness of the powder; When the specific energy consumption model based on the process parameters of the selective laser cladding forming is established in step 1), the workpiece formed by the selective laser cladding forming is a regular cubic workpiece, and the calculation function expression of the total length S of the cladding path is: In the above formula, n is the number of cladding layers; m i is the number of cladding passes in the i-th layer; l is the length of the cladding pass; W i is the width of the workpiece in the i-th layer; where the number of cladding passes in the i-th layer is m i The calculation function expression is: In the above formula, W i is the maximum physical width of the i-th layer; Δs is the laser scanning spacing; λ is the lateral overlap rate; w is the width of a single cladding track; the calculation function expression of the cladding layer number n is: In the above formula, H is the height of the workpiece; μ is the longitudinal overlap rate; h is the height of the cladding track; d is the depth of the cladding track; and the calculation function expression of the longitudinal overlap rate μ is: In the above formula, c z is the longitudinal overlap height of the cladding track; h is the height of the cladding track; d is the depth of the cladding track; h s The thickness of the powder.

2. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 1 is characterized in that: The process parameters of the laser cladding forming in the selected area in step 1) include the laser cladding power P0, the laser scanning speed v, the lateral overlap rate λ and the powder thickness h s .

3. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 2 is characterized in that: The total energy consumption E of the additive manufacturing stage a The calculation function expression is: AND a =And sa +E ma +E ca +E ga +E p +E l +E tab , In the above formula, E sa is the energy consumption of the CNC system in the additive manufacturing stage; E ma is the energy consumption of the lighting module during the additive manufacturing stage; E ca is the energy consumption of the cooling module during the additive manufacturing stage; E ga E is the energy consumption of the shielding gas delivery module during the additive manufacturing stage; p is the energy consumption of the powder laying module; E1 is the energy consumption of the laser cladding module; E tab is the energy consumption of the workbench motion control module; among them, the calculation function expression of the energy consumption E1 of the laser cladding module is: E l =E lw +E lm +E ld =P lw ·t lw +P0·t lm +P ld ·t ld , In the above formula, E lw E is the standby energy consumption; lm is the cladding energy consumption; E ld Interlayer stop energy consumption; P lw is the standby power of the laser cladding module; P0 is the laser cladding power; P ld is the interlayer stop power; t lw is the standby time of laser cladding module; t lm is the laser cladding time, laser cladding time t lm It is obtained by dividing the total length of the cladding path S by the laser scanning speed v; t ld It is the interval time between layers.

4. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 1 is characterized in that: When the specific energy consumption model of the process parameters based on the selective laser cladding forming is established in step 1), the single cladding track width w, cladding track height h and cladding track depth d are all calculated based on the linear regression model of the laser cladding power P0 and the laser scanning speed v.

5. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 1 is characterized in that: The optimization algorithm specified in step 2) refers to a genetic algorithm, a particle swarm algorithm, or a simulated annealing algorithm.

6. A method for energy consumption prediction and process optimization of selective laser cladding forming, characterized in that: include: 1) Establish a specific energy consumption model based on the process parameters of selective laser cladding forming, which is the total energy consumption E in the additive manufacturing stage. a The forming volume V in the additive process a The ratio of 2) For the specific energy consumption model, the specified optimization algorithm is used to solve the optimal process parameter values ​​when the specific energy consumption model is optimal; The forming volume V in the additive process a The calculation function expression is: V a =S(1-λ)wh s , In the above formula, S is the total length of the cladding track; λ is the lateral overlap rate; w is the width of a single cladding track; h s is the thickness of the powder; When the specific energy consumption model based on the process parameters of the selective laser cladding forming is established in step 1), the workpiece formed by the selective laser cladding forming is an asymmetric workpiece, and the calculation function expression of the total length S of the cladding path is: S=L total +m total (1-λ)w-n, In the above formula, L total is the total length of the cladding path in the y-axis direction; m total is the total number of cladding paths in the Y-axis direction required for the workpiece to be fully formed; λ is the lateral overlap rate; w is the width of a single cladding path; n is the number of cladding layers; where the total length of the cladding path in the Y-axis direction is L total The calculation function expression is: In the above formula, j is the layer number when calculating the cladding path length; n is the number of cladding layers; m b is the number of cladding passes in the workpiece width at stage b; λ is the lateral overlap rate; w is the width of a single cladding pass; f L (i) j is the length function f L (i) The length at the jth layer; where the length function f L The calculation function expression of (i) is: In the above formula, l i is the actual length of the i-th cladding pass; W is the workpiece width; λ is the lateral overlap rate; w is the width of a single cladding pass; each time the laser moves to process the next cladding pass, the cladding width increases by ΔW = (1-λ)w. The calculation function expression f for the length of the i-th cladding pass processed in any stage b is L(b) (i) is: f L(b) (i)=f L(b-1) (i b-1 )±(1-λ)w(i-i b-1 )tanα i , In the above formula, f L(b-1) (i b-1 ) Processing the i-th b-1 The length of the cladding path, i b-1 The laser scan is translated to a width W b-1 Total number of additive layers at the time; α i is the angle between the outer contour of the workpiece and the xz plane. When the length of the workpiece increases with the width, the "±" in the above formula is "+", otherwise it is "-". The total number of cladding passes in the Y-axis direction required for the workpiece to be fully formed is m total The calculation function expression is: In the above formula, n a The height is H a The number of cladding layers of the workpiece; μ is the longitudinal overlap rate; h is the height of the cladding track; d is the depth of the cladding track; f w (i) is the width function of the i-th cladding path, and: In the above formula, W i is the maximum physical width of the workpiece at layer i; f W(a) (i) corresponds to H a-1 <H≤H a The entity width function of the a-th stage; H a is the height of the upper boundary of the workpiece at stage a; H is the workpiece height; h is the height of the cladding track; d is the depth of the cladding track; μ is the longitudinal overlap rate; the solid width function f at stage a W(a) The calculation function expression of (i) is: f W(a) (i)=f W(a-1) (i a-1 )±h s (i-i a-1 )tanθ i , In the above formula, f W(a-1) (i a-1 ) is the entity width function of the a-1 stage; i a-1 To add material to H a-1 Total number of additive layers at height; h s is the powder thickness, θ i It is the angle between the outer contour of the workpiece and the yz plane. When the physical width of the workpiece increases with the height, the "±" in the above formula takes "+", otherwise it takes "-".

7. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 6 is characterized in that: The process parameters of the laser cladding forming in the selected area in step 1) include the laser cladding power P0, the laser scanning speed v, the lateral overlap rate λ and the powder thickness h s .

8. The method for energy consumption prediction and process optimization of selective laser cladding forming according to claim 6 is characterized in that: The total energy consumption E of the additive manufacturing stage a The calculation function expression is: AND a =And sa +E ma +E ca +E ga +E p +E l +E tab , In the above formula, E sa is the energy consumption of the CNC system in the additive manufacturing stage; E ma is the energy consumption of the lighting module during the additive manufacturing stage; E ca is the energy consumption of the cooling module during the additive manufacturing stage; E ga E is the energy consumption of the shielding gas delivery module during the additive manufacturing stage; p is the energy consumption of the powder laying module; E1 is the energy consumption of the laser cladding module; E tab is the energy consumption of the workbench motion control module; among them, the calculation function expression of the energy consumption E1 of the laser cladding module is: E l =E lw +E lm +e ld =P lw ·t lw +P0·t lm +P ld ·t ld , In the above formula, E lw E is the standby energy consumption; lm is the cladding energy consumption; E ld Interlayer stop energy consumption; P lw is the standby power of the laser cladding module; P0 is the laser cladding power; P ld is the interlayer stop power; t lw is the standby time of laser cladding module; t lm is the laser cladding time, laser cladding time t lm It is obtained by dividing the total length of the cladding path S by the laser scanning speed v; t ld is the interlayer dwell time; when the specific energy consumption model of the process parameters based on the selective laser cladding forming is established in step 1), the single cladding track width w, cladding track height h and cladding track depth d are all calculated based on the linear regression model of the laser cladding power P0 and the laser scanning speed v; the optimization algorithm specified in step 2) refers to the genetic algorithm, or the particle swarm algorithm, or the simulated annealing algorithm.

9. A system for energy consumption prediction and process optimization of selective laser cladding forming, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the steps of the method for energy consumption prediction and process optimization of selective laser cladding forming as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that is programmed or configured to execute the method for energy consumption prediction and process optimization of selective laser cladding forming as described in any one of claims 1 to 8.

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