An optimization method for process parameters of laser cladding on surface of aluminum alloy

Abstract

The application provides an optimization method for laser cladding process parameters of an aluminum alloy surface, relates to the technical field of laser additive repair, and aims at solving the problems of insufficient research on the optimization of laser cladding process parameters of the aluminum alloy surface in the prior art and high porosity of a cladding layer. Firstly, a simulation model of a single-track cladding layer is established, a dilution rate is used as an evaluation index of the forming effect of the single-track cladding layer, and the initial range of each process parameter is determined; then, single-factor experiments of the single-track cladding layer are carried out, the forming law of the single-track cladding layer is analyzed, and the process parameter range of multi-track and multi-layer cladding layers is determined; finally, the process parameters are used as the parameters to be optimized, the reduction of the porosity of the cladding layer is used as the target, and orthogonal experiments of the multi-track and multi-layer cladding are carried out, so that the process parameter combination with the lowest porosity is determined. The optimal process parameter combination obtained by the method successfully prepares a cladding layer with good appearance, metallurgical bonding with the aluminum alloy substrate and extremely low porosity on the aluminum alloy substrate.

Description

Technical Field

[0001] This invention relates to the field of laser additive repair technology, and more specifically, to a method for optimizing the process parameters of laser cladding on aluminum alloy surfaces. Background Technology

[0002] Laser cladding, also known as directional energy deposition, is a coaxial powder-feed laser metal additive manufacturing technology. Laser cladding can prepare metallurgically bonded coatings on metal surfaces, primarily used for metal surface repair or strengthening. Due to its advantages such as low heat input, low material consumption, and ease of obtaining fine-grained structures, laser cladding repair of steel substrates has been extensively studied, with successful cases of repairing core components such as gears, blades, and bearings. However, there are few reports on laser cladding repair of aluminum alloys.

[0003] Aluminum alloys are widely used as structural materials in aerospace, aviation, transportation, and construction. Although aluminum alloy structural components are widely used, their relatively low hardness and wear resistance affect the service life of parts. For example, in piston-type aero engines, the contact surfaces of the aluminum alloy engine casing are prone to fretting wear, significantly limiting the casing's lifespan. Surface damage to these core aluminum alloy components can cause substantial economic losses. Therefore, there is an urgent need to find a coating technology that can efficiently repair surface damage to core aluminum alloy components and thus extend their lifespan.

[0004] Laser cladding technology can be used to prepare metallurgically bonded coatings on metal surfaces for repair or strengthening. Laser melting deposition technology shows broad application prospects for repairing damaged surfaces of aluminum alloy parts. However, laser cladding on aluminum alloy surfaces is very challenging. Due to the high laser reflectivity, good thermal conductivity, easy formation of oxide films, and low melting point of aluminum alloy substrates, excessive laser energy input can lead to over-melting and collapse of the substrate, while insufficient laser energy input makes it difficult for the cladding layer to form a metallurgical bond with the substrate metal. Furthermore, poor cladding layer formation and significant defects such as porosity are common problems with aluminum alloy substrates.

[0005] Process parameters directly affect the morphology of the molten pool, the formation of metallurgical bonds, and the porosity of the cladding layer. By optimizing and finding a suitable combination of process parameters, the desired single-pass cladding layer morphology can be obtained and the porosity of the cladding layer can be reduced, thereby avoiding the degradation of the cladding layer's quality and performance due to porosity defects. However, existing reports lack research on the influence of process parameters on the cladding layer's forming effect and porosity. Summary of the Invention

[0006] The technical problem to be solved by this invention is:

[0007] Existing technologies lack sufficient research on optimizing laser cladding process parameters for aluminum alloy surfaces, resulting in high porosity in the cladding layer.

[0008] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0009] This invention provides a method for optimizing the process parameters of laser cladding on aluminum alloy surfaces, comprising the following steps:

[0010] Step 1: Establish a simulation model of the laser cladding process for a single cladding layer, and simulate the cross-sectional morphology and temperature field of the molten pool to predict the morphology parameters of the cladding layer, including the molten height H, molten depth h, and molten width W.

[0011] Step 2: Use the dilution rate as an evaluation index for the forming effect of a single-pass cladding layer, i.e.

[0012]

[0013] Where B is the total melt height, in mm, which is the sum of melt height H and melt depth h;

[0014] The cross-sectional morphology of a single cladding layer is analyzed to determine the optimal range of the dilution rate, and the influence of process parameters on the dilution rate of the cladding layer is established. The initial range of each process parameter is determined through the optimal range of the dilution rate.

[0015] Step 3: Conduct single-factor experiments on single-pass cladding layers based on the initial range of each process parameter, detect the cladding layer cross-section melt height H, melt depth h, melt width W, and total melt height B, establish the relationship between each process parameter and the parameters melt height H, melt depth h, melt width W, and total melt height B, analyze the forming law of single-pass cladding layers, and determine the range of process parameters for multi-pass multi-layer cladding layers.

[0016] Step 4: Based on the determined range of process parameters for multi-pass, multi-layer cladding, design an orthogonal experimental scheme with the process parameters as the parameters to be optimized and the minimum porosity of the cladding layer as the objective. Conduct multi-pass, multi-layer cladding experiments according to the orthogonal experimental scheme, detect the porosity of the cladding layer under each set of process parameters, and determine the process parameter combination with the minimum porosity.

[0017] Furthermore, the construction process of the simulation model for the single-pass cladding layer laser cladding process described in step one includes:

[0018] A two-dimensional geometric model of the cladding layer cross section was established. To reduce the amount of computation, Boolean operations were used to divide the processed and unprocessed areas, and a half-geometric model was established using symmetry. The mesh was generated using a "freely partitioned triangular mesh", and the mesh cell size was calibrated to a hydrodynamic mesh. The mesh was refined in the processed area. The governing equations were established, including a laser heat source model, a dynamic tracking model of the gas / liquid interface of the molten pool, a phase change heat transfer model, and a liquid metal flow model.

[0019] The laser heat source model is as follows: the heat flux density distribution of the heat source is approximated by a Gaussian heat source model that conforms to a normal distribution. The Gaussian heat source model introduces a time variable τ, which can describe the distribution of laser heat source energy during the dynamic process of the laser beam passing through the simulated cladding layer cross-section at a scanning speed v. The boundary conditions of the laser heat source at the gas / liquid interface are as follows:

[0020]

[0021] Where: I(x) — heat flux density (J / m³) 2 .s); P—laser power (W); η l —Laser energy absorption coefficient; r —Spot radius (m); v —Scanning speed (m / s); x, y —Distance from the center of the laser beam (m); h —Convection heat transfer coefficient (W / (m²)) 2 ·K); T0—Ambient temperature (K); T—Processing temperature (K); σ b — Boltzmann constant; ε — Material absorption rate;

[0022] The approximate time for the laser beam to act on the processing location is:

[0023]

[0024] The dynamic tracking model of the gas / liquid interface in the molten pool is as follows: During the laser cladding powder feeding process, the distribution of powder particles in the powder beam is approximated by a Gaussian distribution. The time variable is introduced into the Gaussian model to describe the interface movement speed of the powder beam as it passes through the simulated cladding layer cross section at a scanning speed v. The deposition process of the cladding layer on the surface of the molten pool was simulated using a mesh deformation method, and the interface migration velocity due to mass addition was considered. for:

[0025]

[0026] Where: m f —Powder delivery rate (mg / min); η p —Powder capture efficiency; ρ p —Powder density (kg / m³) 3 ), r p —Powder flow radius (m) —The unit vector in the direction of elevation;

[0027] The phase change heat transfer model is as follows: a laser beam rapidly forms a molten metal pool locally on an aluminum alloy substrate, and the theory of metal phase change is analyzed; considering the influence of latent heat of fusion in the heat transport equation, the energy conservation equation is:

[0028]

[0029] Where: ρ — density (kg / m³) 3 );c p —Specific heat (J / (kg·K)); T —Temperature (K); t —Time; u i — Velocity component in the i-th direction (m / s); k — Thermal conductivity (W / (m·K)); ΔH — Latent enthalpy of fusion (J / kg);

[0030] Where ΔH is:

[0031] ΔH=L·f l

[0032] In the formula, L represents the latent heat of fusion (J / kg); f l —Liquid phase mass fraction,

[0033] Where f l for:

[0034]

[0035] In the formula, the subscripts s and l represent the solid phase and liquid phase, respectively; T s It is the initial melting temperature; T l It is the total melting temperature;

[0036] The liquid metal flow model is as follows: the flow of liquid metal in the molten pool affects the heat transfer process and the morphology of the molten pool, making theoretical analysis of the liquid metal flow field necessary; the temperature gradient on the surface of the molten pool leads to a surface tension gradient, driving Marangoni convection in the liquid metal fluid, which in turn leads to heat and mass transfer within the molten pool; the incompressible Navier-Stokes equations are used to describe the liquid metal in the molten pool, and its mass conservation equation can be expressed as:

[0037]

[0038] Its momentum conservation equation can be expressed as:

[0039]

[0040] Where: μ—viscosity (Pa·s); p—pressure (Pa); K0—a constant characterizing the porous medium morphology in the viscous dissipation term; B—a decimal number set in the viscous dissipation term to avoid a denominator of zero; F—includes the combined effects of volume force, gravity, and melt surface tension (N / m). 3 ), can be represented as:

[0041]

[0042] Where: g — acceleration due to gravity (m / s²) 2); β—coefficient of thermal expansion of the metal (1 / K); γ—temperature coefficient of surface tension (N / (K·m)); σ—surface tension (N / m); κ—interfacial curvature (1 / m) 2 );

[0043] The thermodynamic parameters of the material are established. Based on the constituent elements and element content of the target alloy, the thermophysical properties such as density, thermal conductivity, specific heat, viscosity, and enthalpy of the target alloy can be obtained using the overmixing formula.

[0044]

[0045] In the formula, P is the thermal property parameter of the composite material; P1 is the thermal property parameter of the matrix; and P2 is the thermal property parameter of the reinforcing material. —Volume fraction of substrate; —Volume fraction of reinforcing materials.

[0046] Furthermore, the process parameters mentioned in step two include: laser power W, scanning speed mm / s, and powder feeding rate mg / min.

[0047] The orthogonal experimental design described in step four is a three-factor, three-level orthogonal experimental design.

[0048] Furthermore, in step two, the optimal range for the dilution rate is determined to be 15%–55%.

[0049] Furthermore, in step four, the porosity is characterized by the proportion of pores in the cross-section of the cladding layer to the area of ​​the entire cross-section of the cladding layer. Specifically, the process involves obtaining an image of the cross-section of the cladding layer, extracting an image of the stable processing position in the cladding layer as the calculation region image, performing binarization on the calculation region image, and determining the percentage of black pixels in the calculation region to the total number of pixels as the porosity of the cross-section of the cladding layer.

[0050] Furthermore, in step four, range analysis is used to evaluate the influence of each process parameter on the porosity of the cladding layer; variance analysis is used to analyze the significance of the influence of each process parameter on the porosity of the cladding layer, and factors with a P value less than 0.05 are considered as significant influencing factors.

[0051] Furthermore, after step four is completed, cladding experiments are carried out based on the determined combination of process parameters for the lowest porosity. The experimental results under the combination of process parameters for the lowest porosity are compared with the experimental results under other parameters in the orthogonal experiment to verify the accuracy and feasibility of the combination of process parameters.

[0052] Compared with the prior art, the beneficial effects of the present invention are:

[0053] This invention discloses a method for optimizing laser cladding process parameters on aluminum alloy surfaces. First, the dilution rate is used as an evaluation index for the forming effect of a single-pass cladding layer, and a suitable process window is found through simulation. Then, single-factor experiments on single-pass cladding layers are conducted to analyze the forming law of the single-pass cladding layer, eliminating process parameter ranges unfavorable to multi-pass cladding layer forming, and determining the range of multi-pass, multi-layer process parameters that result in good geometric dimensions of the cladding layer on the aluminum alloy surface, providing a basis for subsequent orthogonal experiments. Finally, orthogonal experiments are used to optimize process parameters to suppress the porosity of the cladding layer. Range and variance analyses are performed to determine the degree and significance of the influence of each process parameter on the porosity of the cladding layer, identifying process parameters with significant influence, providing guidance for targeted optimization of process parameters. The optimal combination of process parameters obtained by this invention successfully prepares a cladding layer with good morphology, metallurgical bonding with the aluminum alloy substrate, and extremely low porosity on the aluminum alloy substrate, improving the cladding quality and stability of the aluminum alloy surface, and providing technical guidance and reference for laser cladding repair of aluminum alloy parts. Attached Figure Description

[0054] Figure 1 This is a flowchart of the method for optimizing the laser cladding process parameters on the aluminum alloy surface in an embodiment of the present invention;

[0055] Figure 2 This is a simulation model and mesh diagram of the single-pass laser cladding process in an embodiment of the present invention;

[0056] Figure 3 This is one of the phase transition field diagrams of the cladding layer molten pool in the embodiments of the present invention;

[0057] Figure 4 This is a schematic diagram of calibrating the cladding layer size using a super depth-of-field microscope in an embodiment of the present invention;

[0058] Figure 5 This is a graph showing the influence of laser processing parameters on the cladding layer melt height in an embodiment of the present invention.

[0059] Figure 6 This is a graph showing the influence of laser processing parameters on the cladding depth in an embodiment of the present invention.

[0060] Figure 7 This is a graph showing the influence of laser processing parameters on the weld width of the cladding layer in an embodiment of the present invention.

[0061] Figure 8 This is a graph showing the influence of laser processing parameters on the total cladding height in an embodiment of the present invention.

[0062] Figure 9 This is a trend diagram of experimental factor levels and porosity in an embodiment of the present invention;

[0063] Figure 10 The images show a comparison of the pore distribution of the cladding layer in the embodiments of the present invention. In the image, a) is the pore distribution of the cladding layer under the process parameters of laser power 2000W, powder feed rate 1600mg / min, and scanning speed 5mm / s; b) is the pore distribution of the cladding layer under the process parameter combination with the lowest porosity. Detailed Implementation

[0064] In the description of this invention, it should be noted that the terms "first," "second," and "third" mentioned in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," and "third" may explicitly or implicitly include one or more of that feature.

[0065] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0066] Combination Figures 1 to 10 As shown, this invention provides a method for optimizing the process parameters of laser cladding on aluminum alloy surfaces, such as... Figure 1 As shown, it includes the following steps:

[0067] Step 1: Establish a simulation model of the laser cladding process for a single cladding layer, and simulate the cross-sectional morphology and temperature field of the molten pool to predict the morphology parameters of the cladding layer, including: molten height H, molten depth h, and molten width W.

[0068] like Figure 2 As shown, a two-dimensional geometric model of the cladding layer cross section is established. To reduce the amount of computation, Boolean operations are used to divide the processed and unprocessed areas, and symmetry is used to establish a half-geometric model. The "freely partitioned triangular mesh" is used for mesh generation, and the mesh cell size is calibrated to the fluid dynamics mesh generation. The mesh of the processed area is refined. The governing equations are established, including the laser heat source model, the dynamic tracking model of the gas / liquid interface of the molten pool, the phase change heat transfer model, and the liquid metal flow model.

[0069] The laser heat source model is as follows: the heat flux density distribution of the heat source is approximated by a Gaussian heat source model that conforms to a normal distribution. The Gaussian heat source model introduces a time variable τ, which can describe the distribution of laser heat source energy during the dynamic process of the laser beam passing through the simulated cladding layer cross-section at a scanning speed v. The boundary conditions of the laser heat source at the gas / liquid interface are as follows:

[0070]

[0071] Where: I(x) — heat flux density (J / m³) 2 .s); P—laser power (W); η l—Laser energy absorption coefficient; r —Spot radius (m); v —Scanning speed (m / s); x, y —Distance from the center of the laser beam (m); h —Convection heat transfer coefficient (W / (m²)) 2 ·K); T0—Ambient temperature (K); T—Processing temperature (K); σ b — Boltzmann constant; ε — Material absorption rate;

[0072] The approximate time for the laser beam to act on the processing location is:

[0073]

[0074] The dynamic tracking model of the gas / liquid interface in the molten pool is as follows: During the laser cladding powder feeding process, the distribution of powder particles in the powder beam is approximated by a Gaussian distribution. The time variable is introduced into the Gaussian model to describe the interface movement speed of the powder beam as it passes through the simulated cladding layer cross section at a scanning speed v. The deposition process of the cladding layer on the surface of the molten pool was simulated using a mesh deformation method, and the interface migration velocity due to mass addition was considered. for:

[0075]

[0076] Where: m f —Powder delivery rate (mg / min); η p —Powder capture efficiency; ρ p —Powder density (kg / m³) 3 ), r p —Powder flow radius (m) —The unit vector in the direction of elevation;

[0077] The phase change heat transfer model is as follows: a laser beam rapidly forms a molten metal pool locally on an aluminum alloy substrate, and the theory of metal phase change is analyzed; considering the influence of latent heat of fusion in the heat transport equation, the energy conservation equation is:

[0078]

[0079] Where: ρ — density (kg / m³) 3 );c p —Specific heat (J / (kg·K)); T —Temperature (K); t —Time; u i — Velocity component in the i-th direction (m / s); k — Thermal conductivity (W / (m·K)); ΔH — Latent enthalpy of fusion (J / kg);

[0080] Where ΔH is:

[0081] ΔH=L·f l

[0082] In the formula, L represents the latent heat of fusion (J / kg); f l —Liquid phase mass fraction,

[0083] Where f l for:

[0084]

[0085] In the formula, the subscripts s and l represent the solid phase and liquid phase, respectively; T s It is the initial melting temperature; T l It is the total melting temperature;

[0086] The liquid metal flow model is as follows: the flow of liquid metal in the molten pool affects the heat transfer process and the morphology of the molten pool, making theoretical analysis of the liquid metal flow field necessary; the temperature gradient on the surface of the molten pool leads to a surface tension gradient, driving Marangoni convection in the liquid metal fluid, which in turn leads to heat and mass transfer within the molten pool; the incompressible Navier-Stokes equations are used to describe the liquid metal in the molten pool, and its mass conservation equation can be expressed as:

[0087]

[0088] Its momentum conservation equation can be expressed as:

[0089]

[0090] Where: μ—viscosity (Pa·s); p—pressure (Pa); K0—a constant characterizing the porous medium morphology in the viscous dissipation term; B—a decimal number set in the viscous dissipation term to avoid a denominator of zero; F—includes the combined effects of volume force, gravity, and melt surface tension (N / m). 3 ), can be represented as:

[0091]

[0092] Where: g — acceleration due to gravity (m / s²) 2 ); β—coefficient of thermal expansion of the metal (1 / K); γ—temperature coefficient of surface tension (N / (K·m)); σ—surface tension (N / m); κ—interfacial curvature (1 / m) 2 );

[0093] The thermodynamic parameters of the material are established. Based on the constituent elements and element content of the target alloy, the thermophysical properties such as density, thermal conductivity, specific heat, viscosity, and enthalpy of the target alloy can be obtained using the overmixing formula.

[0094]

[0095] In the formula, P is the thermal property parameter of the composite material; P1 is the thermal property parameter of the matrix; and P2 is the thermal property parameter of the reinforcing material. —Volume fraction of substrate; —Volume fraction of reinforcing materials.

[0096] The model was initialized by setting process parameters such as laser power W, scanning speed mm / s, and powder feed rate mg / min. The temperature field and phase transition of the two-dimensional cross-section of the cladding layer were then solved, yielding the following results: Figure 3 The phase transition field of the cladding layer molten pool is shown under laser power of 1800W, scanning speed of 6mm / s, and powder feeding rate of 2200mg / min. The lines in the figure correspond to the solid phase line and liquid phase line of the molten pool. The solid phase line is used to construct the morphology of the two-dimensional cross-section of the cladding layer molten pool.

[0097] Step 2: Use the dilution rate as an evaluation index for the forming effect of a single-pass cladding layer, i.e.

[0098]

[0099] Where B is the total melt height in mm, and H is the sum of melt height H and melt depth h;

[0100] The cross-sectional shape of the single-pass cladding layer was analyzed, and the optimal range of dilution rate was determined to be 15% to 55%. The influence of process parameters on the dilution rate of the cladding layer was established. The initial range of each process parameter was determined through the optimal range of dilution rate: laser power of 1700 to 2000 W, scanning speed of 6 to 12 mm / s, and powder feeding rate of 1200 to 2400 mg / min.

[0101] When the dilution rate is too high, the melting depth accounts for an excessively large proportion of the total melting height of the cladding layer. In this case, the laser energy required for powder melting is relatively small, and most of the laser energy is input to the substrate metal, causing the substrate metal to easily melt and collapse due to excessive energy. Conversely, when the dilution rate is too low, the melting depth is shallow, and the area of ​​the dilution zone between the cladding layer and the substrate metal shrinks, which is not conducive to the formation of metallurgical bonding between the cladding layer metal and the substrate metal. Therefore, selecting the laser processing parameters corresponding to a suitable dilution rate is crucial. Thus, the optimal range for the dilution rate was determined to be 15%–55%, and the process parameters were optimized accordingly.

[0102] Step 3: Conduct single-factor experiments on single-pass cladding layers based on the initial range of each process parameter, detect the cladding layer cross-section melt height H, melt depth h, melt width W, and total melt height B, establish the relationship between each process parameter and the parameters melt height H, melt depth h, melt width W, and total melt height B, analyze the forming law of single-pass cladding layers, and determine the process parameter range for multi-pass, multi-layer cladding layers.

[0103] The single-factor experimental design is shown in Table 1.

[0104] Table 1

[0105]

[0106] Note: The values ​​marked with "*" in Table 1 are the values ​​selected for this factor when exploring other variables.

[0107] With laser power P as the variable, starting at 1700W and with a gradient of 100W, the scanning speed v was selected as 6mm / s and 10mm / s respectively, and the powder feeding rate f was selected as 1200mg / min and 2000mg / min respectively, and a single-pass cladding experiment was conducted.

[0108] With scanning speed v as the variable, starting at 6 mm / s and with a gradient of 2 mm / s, laser power P was selected as 1800 W and 2000 W respectively, and powder feeding rate f was selected as 1200 mg / min and 2000 mg / min respectively, and single-pass cladding experiments were conducted.

[0109] With the powder feeding rate f as the variable, starting at 1200 mg / min and with a gradient of 400 mg / min, the laser power P was selected as 1800 W and 2000 W respectively, and the scanning speed v was selected as 6 mm / s and 10 mm / s respectively, and a single-pass cladding experiment was conducted.

[0110] The experimental procedure includes:

[0111] Substrate Pretreatment: Before laser cladding, the aluminum alloy test plate is chemically cleaned to remove surface oil, organic matter, and oxide film. First, it is immersed in a 5% NaOH aqueous solution for 5 minutes, followed by an immersion in a 20% HNO3 aqueous solution for 5 minutes. Then, it is rinsed with clean water to remove any remaining solution, wiped with anhydrous ethanol, and dried with an air gun. The treated substrate must be tested immediately to prevent re-oxidation.

[0112] Powder material pretreatment: The powder material is AlSi10Mg spherical powder with a particle size of 40-90 μm, which is vacuum dried at 110℃ for 2 h.

[0113] Instrument and equipment inspection and experimental parameters: Check the coaxiality of the laser beam output from the cladding head, whether the powder feeding is stable and smooth, and whether the protective lens has any stains. After confirming that the equipment is normal, adjust the gas pressure to 0.2MPa, exhaust the gas until the internal pressure reaches -3MPa, and then fill with argon gas. Repeat twice. During the cladding test, always maintain the oxygen content below 1%. During laser cladding, the powder carrier gas is 3L / s and the coaxial protective gas is 10L / s to ensure stable powder feeding. Produce light according to the set parameters, and move the CNC test bench to achieve single-pass cladding.

[0114] Experimental Results Detection: The experimentally obtained samples were subjected to wire electrical discharge machining (EDM) and sanding. The cross-sectional dimensions of the cladding layer were then observed and calibrated using a super depth-of-field microscope. The results are as follows: Figure 4 As shown.

[0115] Because the stability of stacking and the overheating of the substrate caused by continuous heat input need to be considered when multiple layers are overlapped, the process parameters need to be adjusted appropriately.

[0116] Analyze the forming law of single-pass cladding layer and determine the process parameter range of multi-pass, multi-layer cladding layer, such as... Figure 5 , 6 As shown in Figures 7 and 8, the melting height increases significantly with decreasing scanning speed and increasing powder feeding rate, and is not significantly affected by laser power. Under various process parameters, the melting height varies from 200 to 1000 μm. If the melting height is too small, the cladding forming efficiency will be too low. If the cladding layer is too high, the defects in the unmelted part at the overlap will increase. Therefore, the melting height range is selected as 300 to 800 μm when overlapping multiple layers of cladding.

[0117] The penetration depth increases with increasing laser power and decreases with increasing powder feed rate. Scanning speed has little effect on the penetration depth. If the penetration depth is too small, less laser energy is input into the substrate, which can easily lead to incomplete fusion defects during multi-pass, multi-layer cladding. If the penetration depth is too large, more laser energy is input into the substrate, which can easily lead to substrate collapse during multi-pass, multi-layer cladding. Therefore, the penetration depth range for multi-pass, multi-layer cladding is selected as 200–500 μm.

[0118] The weld width is less affected by powder feed rate and scanning speed, but more significantly by laser power. When the laser power is 1700W, the weld width is in the range of 2200–2400 μm; when the laser power is 1800W, it is in the range of 2400–2700 μm; when the laser power increases to 1900W, the weld width is 2600–2900 μm; and as the laser power increases to 2000W, the weld width range increases to 2700–3100 μm. A weld width that is too small results in low overlap forming efficiency. Therefore, when overlapping multiple layers of cladding, the weld width range is selected to be 2400–3000 μm.

[0119] The total fusion height increases with increasing laser power, increasing powder feed rate, and decreasing scanning speed. If the total fusion height is too large, incomplete fusion defects are prone to occur at the overlap; if the total fusion height is too small, the efficiency of overlap formation is too low. Therefore, the range of total fusion height is selected as 800–1000 μm for multi-pass, multi-layer cladding overlap.

[0120] When the laser power reaches 1800W or higher, the weld width of the cladding layer tends to stabilize. At 1700W, the weld width is relatively small, which is not conducive to multi-pass, multi-layer cladding. Therefore, the laser power should be selected within the range of 1800-2000W for multi-pass, multi-layer cladding. When the scanning speed increases to 12mm / s, the weld height and total weld height of the cladding layer decrease sharply. At a laser power of 2000W and a powder feed rate of 1200mg / min, the weld height of the cladding layer is less than 250μm and the total weld height is 720μm. At this point, most of the laser energy is input into the substrate metal, which is not conducive to multi-layer cladding processing and easily leads to… This leads to excessive melting of the cladding layer and the substrate metal; therefore, the scanning speed should be appropriately reduced during multi-pass, multi-layer cladding processing, and the scanning speed range should be adjusted to 5-11 mm / s; when the powder feed rate is increased from 2000 mg / min to 2400 mg / min, the melting height of the cladding layer increases to 1.5 times that of 2000 mg / min, and the melting depth also decreases. At this time, multi-pass, multi-layer cladding will lead to an increase in defects in the unmelted part at the cladding layer overlap, which is not conducive to the preparation of a high-quality cladding layer. Therefore, the powder feed rate should be selected in the range of 1200-2000 mg / min.

[0121] In summary, the process parameters for the multi-pass, multi-layer cladding layer are determined as follows: laser power 1800–2000W; scanning speed 5–11 mm / s; powder feed rate 1200–2000 mg / min.

[0122] Step 4: Based on the determined range of process parameters for multi-pass, multi-layer cladding, design an orthogonal experimental scheme with the process parameters as the parameters to be optimized and the goal of minimizing the porosity of the cladding layer. Conduct multi-pass, multi-layer cladding experiments according to the orthogonal experimental scheme, detect the porosity of the cladding layer under each set of process parameters, and determine the process parameter combination with the lowest porosity.

[0123] As shown in Table 2, an orthogonal experimental scheme was designed using the three-factor, three-level orthogonal analysis method.

[0124] Table 2

[0125]

[0126] The orthogonal experimental design scheme and the corresponding porosity results of the cladding layer are shown in Table 3.

[0127] Table 3

[0128]

[0129] Range analysis was performed on the porosity results, and the results are shown in Table 4.

[0130] Table 4

[0131]

[0132] Analysis of variance was performed on the porosity results, and the results are shown in Table 5.

[0133] Table 5

[0134]

[0135] The range value reflects the influence of three factors—laser power, powder feed rate, and porosity—on the porosity of the cladding layer. The larger the range, the greater the influence of the corresponding factor on the porosity result. According to the results in Table 4, laser power has the greatest impact on the porosity of the cladding layer, followed by powder feed rate, while scanning speed has the least impact on the porosity of the cladding layer.

[0136] The p-value in the analysis of variance can determine whether the effects of the three experimental factors on the porosity of the cladding layer are statistically significant. With a significance level of α of 0.05 for the orthogonal experiment, according to the variance results shown in Table 5, the p-values ​​for laser power and powder feeding rate are both less than 0.05, while the p-value for scanning speed is greater than 0.05. This indicates that, statistically, the porosity of the cladding layer is significantly affected by laser power and powder feeding rate, and less affected by scanning speed.

[0137] The results of range analysis and variance analysis show that, under the parameter range of 1800-2000W laser power, 1200-2000mg / min powder feed rate, and 5-11mm / s scanning speed, laser power and powder feed rate are the main factors affecting the porosity of the cladding layer, and the influence of laser power on porosity is greater than that of powder feed rate.

[0138] In this embodiment, the multi-layer, multi-pass cladding layer adopts a staggered scanning overlap strategy, that is, the width of the overlap between each pass of each layer is 40% of the weld width of a single pass cladding layer, adjacent cladding layers are staggered, and the offset between adjacent layers is 30% of the weld width of a single pass cladding layer.

[0139] In this embodiment, porosity is characterized by the proportion of pores in the cladding layer cross-section to the total cross-sectional area of ​​the cladding layer. First, the cladding layer cross-section is obtained using wire electrical discharge machining (EDM). Then, the cladding layer is polished using 7000-grit sandpaper to ensure a scratch-free surface and avoid affecting the porosity calculation. Next, an image of the cladding layer cross-section is obtained using a super-depth-of-field microscope. An image of a stable processing position within the cladding layer is extracted as the calculation region image. This calculation region image is then binarized, and the percentage of black pixels in the calculation region relative to the total number of pixels represents the porosity of the cladding layer cross-section.

[0140] like Figure 9 As shown, through the analysis of the experimental factor level-porosity trend, the process parameter combination with the lowest porosity was determined to be: laser power 1800W, powder feed rate 1600mg / min, and scanning speed 8mm / s.

[0141] Cladding experiments were conducted based on the determined combination of process parameters for minimum porosity, such as... Figure 10 As shown, the experimental results under the process parameter combination with the lowest porosity are compared with the experimental results of sequence 8 in the orthogonal experiment. The porosity of the cladding layer prepared under the process parameter combination with the lowest porosity is as low as 0.09%, which is a significant improvement compared to the porosity results of the process parameters before optimization in the orthogonal experiment. It should be noted that the porosity of the aluminum alloy laser cladding layer using existing methods is generally above 0.2%, and large pores or even cracks are prone to occur. The lowest porosity process parameters determined in this invention greatly reduce the porosity of the cladding layer.

[0142] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for optimizing laser cladding process parameters on aluminum alloy surfaces, characterized in that, Includes the following steps: Step 1: Establish a simulation model of the laser cladding process for a single cladding layer, and simulate the cross-sectional morphology and temperature field of the molten pool to predict the morphology parameters of the cladding layer, including the molten height H, molten depth h, and molten width W. Step 2: Use the dilution rate as an evaluation index for the forming effect of a single-pass cladding layer, i.e. Where B is the total melt height, in mm, which is the sum of melt height H and melt depth h; The cross-sectional morphology of a single cladding layer is analyzed to determine the optimal range of the dilution rate, and the influence of process parameters on the dilution rate of the cladding layer is established. The initial range of each process parameter is determined through the optimal range of the dilution rate. Step 3: Conduct single-factor experiments on single-pass cladding layers based on the initial range of each process parameter, detect the cladding layer cross-section melt height H, melt depth h, melt width W, and total melt height B, establish the relationship between each process parameter and the parameters melt height H, melt depth h, melt width W, and total melt height B, analyze the forming law of single-pass cladding layers, and determine the range of process parameters for multi-pass multi-layer cladding layers. Step 4: Based on the determined range of process parameters for multi-pass, multi-layer cladding, design an orthogonal experimental scheme with the process parameters as the parameters to be optimized and the minimum porosity of the cladding layer as the objective. Conduct multi-pass, multi-layer cladding experiments according to the orthogonal experimental scheme, detect the porosity of the cladding layer under each set of process parameters, and determine the process parameter combination with the minimum porosity. The construction process of the simulation model for the single-pass laser cladding process described in step one includes: A two-dimensional geometric model of the cladding layer cross section was established. To reduce the amount of computation, Boolean operations were used to divide the processed and unprocessed areas, and symmetry was used to establish a half-geometric model. The mesh was generated using a "freely partitioned triangular mesh", and the mesh cell size was calibrated to the fluid dynamics mesh. The mesh was refined in the processed area. The governing equations were established, including the laser heat source model, the dynamic tracking model of the gas / liquid interface of the molten pool, the phase change heat transfer model, and the liquid metal flow model. The laser heat source model is as follows: the heat flux density distribution of the heat source is approximated by a Gaussian heat source model that conforms to a normal distribution. The Gaussian heat source model introduces a time variable τ, which can describe the distribution of laser heat source energy during the dynamic process of the laser beam passing through the simulated cladding layer cross-section at a scanning speed v. The boundary conditions of the laser heat source at the gas / liquid interface are as follows: In the formula: —Heat flux density (J / m³) 2 .s); P—laser power (W); η l —Laser energy absorption coefficient; r —Spot radius (m); v —Scanning speed (m / s); x, y —Distance from the center of the laser beam (m); h —Convection heat transfer coefficient (W / (m²)) 2 ·K); T0—Ambient temperature (K); T—Processing temperature (K); σ b — Boltzmann constant; ɛ — Material absorption rate; The approximate time for the laser beam to act on the processing location is: The dynamic tracking model of the gas / liquid interface in the molten pool is as follows: During the laser cladding powder feeding process, the distribution of powder particles in the powder beam is approximated by a Gaussian distribution. The time variable is introduced into the Gaussian model to describe the interface movement speed of the powder beam as it passes through the simulated cladding layer cross section at a scanning speed v. The deposition process of the cladding layer on the surface of the molten pool was simulated using a mesh deformation method, and the interface migration velocity caused by mass addition was considered. for: Where: m f —Powder delivery rate (mg / min); η p —Powder capture efficiency; ρ p —Powder density (kg / m³) 3 ), r p —Powder flow radius (m) —The unit vector in the direction of elevation; The phase change heat transfer model is as follows: a laser beam rapidly forms a molten metal pool locally on an aluminum alloy substrate, and the theory of metal phase change is analyzed; considering the influence of latent heat of fusion in the heat transport equation, the energy conservation equation is: Where: ρ — density (kg / m³) 3 ); c p —Specific heat (J / (kg·K)); T —Temperature (K); t —Time; u i — Velocity component in the i-th direction (m / s); k — Thermal conductivity (W / (m·K)); —Latent enthalpy of melting (J / kg); in for: In the formula, L represents the latent heat of fusion (J / kg); f l —Liquid phase mass fraction, Where f l for: In the formula, the subscripts s and l represent the solid phase and the liquid phase, respectively; It is the initial melting temperature; It is the total melting temperature; The liquid metal flow model is as follows: the flow of liquid metal in the molten pool affects the heat transfer process and the morphology of the molten pool, making theoretical analysis of the liquid metal flow field necessary; the temperature gradient on the surface of the molten pool leads to a surface tension gradient, driving Marangoni convection in the liquid metal fluid, which in turn leads to heat and mass transfer within the molten pool; the incompressible Navier-Stokes equations are used to describe the liquid metal in the molten pool, and its mass conservation equation can be expressed as: Its momentum conservation equation can be expressed as: Where: μ—viscosity (Pa·s); p—pressure (Pa); K0—a constant characterizing the porous medium morphology in the viscous dissipation term; B—a decimal in the viscous dissipation term to avoid a zero denominator; F—includes the combined effects of volume force, gravity, and melt surface tension (N / m). 3 ), can be represented as: In the formula: —Acceleration due to gravity (m / s²) 2 ); β—coefficient of thermal expansion of the metal (1 / K); γ—temperature coefficient of surface tension (N / (K·m)); σ—surface tension (N / m); κ—interfacial curvature (1 / m) 2 ); The thermodynamic parameters of the material are established. Based on the constituent elements and element content of the target alloy, the density, thermal conductivity, specific heat, viscosity, and enthalpy-heat properties of the target alloy can be obtained using the overmixing formula. In the formula, P is the thermal property parameter of the composite material; P1 is the thermal property parameter of the matrix; and P2 is the thermal property parameter of the reinforcing material. —Volume fraction of substrate; —Volume fraction of reinforcing materials.

2. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 1, characterized in that, The process parameters mentioned in step two include: laser power (W), scanning speed (mm / s), and powder feeding rate (mg / min).

3. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 2, characterized in that, The orthogonal experimental design described in step four is a three-factor, three-level orthogonal experimental design.

4. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 1, characterized in that, In step two, the optimal range for the dilution rate was determined to be 15% to 55%.

5. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 1, characterized in that, In step four, the porosity is characterized by the proportion of pores in the cross-section of the cladding layer to the total area of ​​the cladding layer. Specifically, the process involves obtaining an image of the cladding layer cross-section, extracting an image of the stable processing position in the cladding layer as the calculation region image, performing binarization on the calculation region image, and determining the percentage of black pixels in the calculation region to the total number of pixels as the porosity of the cladding layer cross-section.

6. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 1, characterized in that, In step four, range analysis was used to evaluate the influence of each process parameter on the porosity of the cladding layer; variance analysis was used to analyze the significance of the influence of each process parameter on the porosity of the cladding layer, and factors with a P value less than 0.05 were considered as significant influencing factors.

7. The method for optimizing the laser cladding process parameters on aluminum alloy surfaces according to claim 1, characterized in that, After step four is completed, cladding experiments are carried out based on the determined combination of process parameters for the lowest porosity. The experimental results under the combination of process parameters for the lowest porosity are compared with the experimental results under other parameters in the orthogonal experiment to verify the accuracy and feasibility of the combination of process parameters.

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