A laser cladding process optimization method for ceramic phase reinforced composite coating

Abstract

The present invention relates to a laser cladding process optimization method for ceramic phase reinforced composite coating, comprising the following steps: using a single factor experimental method to optimize the melting power interval of ceramic phase composite powder, and determining the relationship between powder feeding rate, line speed and power; using a recursive method to derive the corresponding proportional relationship between power and various process parameters and coating parameters; using the corresponding relationship range value of power, line speed and powder feeding rate, setting the range of power, line speed and powder feeding rate, and multi-channel overlap, orthogonal experiment, determine the relationship between process parameters and coating parameters; using a combination of forward selection and reverse elimination, according to the relationship between process parameters and coating parameters, determine the process parameters and perform group experiments for the actual required coating thickness, and select the optimal process parameters. The present invention uses a progressive regression analysis method to conduct a comprehensive process exploration, which is convenient for obtaining suitable process parameters to obtain an ideal ceramic phase reinforced composite coating.

Description

Technical Field

[0001] The invention relates to the technical field of laser cladding, and in particular to a laser cladding process optimization method for ceramic phase reinforced composite coating. Background Art

[0002] Laser cladding is an emerging technology that uses high-energy lasers to quickly melt the workpiece surface and the alloy powder added simultaneously to form a dense alloy layer bonded to the substrate. Laser cladding ceramic phase reinforced composite coating is a coating prepared on a metal substrate by laser cladding technology. It combines the high hardness of ceramic materials with the high toughness and high strength of metal materials. It is currently widely used in petrochemical, coal mining and other fields to significantly improve the wear resistance of its parts.

[0003] The setting of laser cladding process parameters plays a vital role in the quality of the cladding layer. The optimal parameters of laser cladding vary depending on the type of powder used and the type of equipment. In short, even if the same powder is used, when cladding on different equipment or different powders are used on the same equipment, the parameters need to be adjusted to achieve the best effect.

[0004] In the preparation of ceramic phase reinforced composite coatings, ceramic phases such as WC, TiC, SiC, B4C are used for nickel-based, cobalt-based and iron-based alloy reinforced coatings. The process parameters not only directly affect the shape, metallurgical bonding, thickness, dilution rate, porosity and cracks of the molten pool, but also affect the retention of the reinforcement phase particles. These factors often become the key to restricting industrial applications. In industrial applications, it is often necessary to prepare coatings of specific thickness. Therefore, the adjustment of the process is always unilateral and cannot ensure that the process parameters reach the most ideal state. At present, under the same thickness, the research on the influence of process parameters on the porosity, cracks and ceramic phase content in ceramic phase reinforced composite coatings lacks comprehensiveness. Therefore, carefully adjusting the process parameters of laser cladding can ensure the thickness while optimizing the content of the reinforcement phase in the coating while reducing the generation of pores and cracks, which is an urgent problem to be solved. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies in the prior art and provide a method for optimizing the laser cladding process for a ceramic phase reinforced composite coating.

[0006] The present invention is achieved through the following technical solutions:

[0007] A laser cladding process optimization method for ceramic phase reinforced composite coating comprises the following steps:

[0008] S1. Optimize the melting power range of ceramic composite powder by single factor experimental method, and determine the relationship between powder feeding rate, linear speed and power;

[0009] S2. Using the recursive method to derive the corresponding proportional relationship between the melting power and each process parameter and coating parameter;

[0010] S3. Using the corresponding range values ​​of melting power, line speed and powder feeding rate, set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments to determine the relationship between process parameters and coating parameters;

[0011] S4. Using a combination of positive selection and reverse elimination, based on the actual required coating thickness and the relationship between process parameters and coating parameters, determine the process parameters and conduct group experiments to select the optimal process parameters.

[0012] According to the above technical solution, preferably, step S1 includes:

[0013] S11. The alloy powder is mixed with the ceramic phase powder to form the ceramic phase composite powder;

[0014] S12. Use coaxial powder feeding method for laser cladding, select multiple groups of melting power for single-pass cladding, and record the molten pool width and maximum molten pool temperature at each melting power, as well as coating thickness, melting depth, and coating dilution rate;

[0015] S13. Determine the melting power range according to the peak point of the coating thickness and the coating dilution rate;

[0016] S14. Combined with the cross section of the cladding layer, calculate the powder melting efficiency, linear energy density, and molten pool duration at each melting power, and optimize the melting power range based on the coating thickness and melting efficiency.

[0017] According to the above technical solution, preferably, in step S12, coaxial powder feeding is used for laser cladding, wherein the shielding gas is maintained at 22 L / min, the powder carrier gas is maintained at 5 L / min, the spot size is fixed at 3.5 mm, and the powder is fed at a rate of 28 g / min. At a line speed of 1 m / min, multiple groups of melting powers are selected for single-pass cladding.

[0018] According to the above technical solution, preferably, in step S14, the cross-sectional area S is calculated according to the molten pool width d and the coating thickness h of the cross section of the cladding layer.

[0019] ,

[0020] According to the cladding length L, composite powder density ρ and cross-sectional area S, the mass M of the single-pass cladding layer is calculated.

[0021] ,

[0022] According to the single-pass cladding layer quality M, line speed v, cladding length L, powder feeding rate V P , calculate the powder melting efficiency η,

[0023] ,

[0024] According to the melting power P and the linear speed v, the linear energy density Q is calculated.

[0025] ,

[0026] According to the molten pool width d and line speed v, calculate the molten pool duration t.

[0027] .

[0028] According to the above technical solution, preferably, step S2 includes:

[0029] S21. According to the optimized melting power range, the linear energy density Q, the powder melting efficiency η and the molten pool duration t are calculated, and the amount of molten powder m in the unit molten pool is calculated to obtain the range values ​​of the linear energy density Q and the amount of molten powder m in the unit molten pool;

[0030] S22. Through regression fitting analysis, the relationship between the molten pool width d and the melting power P is obtained, and then the relationship between the melting power P, the line speed and the coating thickness is derived.

[0031] According to the above technical solution, preferably, in step S21, the amount of molten powder m in the unit molten pool is expressed as:

[0032] ,

[0033] Where t is the duration of the molten pool, V P is the powder feeding rate and η is the powder melting efficiency.

[0034] According to the above technical solution, preferably, in step S22, through regression fitting analysis, the relationship between the molten pool width d and the melting power P is obtained as follows:

[0035] d=1.2502ln(P)-6.1401,

[0036] The relationship between melting power P, line speed v and coating thickness h is derived as follows:

[0037] .

[0038] According to the above technical solution, preferably, step S3 includes:

[0039] S31. Using the corresponding range values ​​of melting power, line speed and powder feeding rate, set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments;

[0040] S32. Obtain the corresponding relationship between power, linear velocity, powder feeding rate and thickness, porosity, number of cracks and ceramic phase content;

[0041] S33. Based on the mean and variance obtained from the orthogonal experiment, determine the order of influence.

[0042] According to the above technical scheme, preferably, in step S4, a combination of forward selection and reverse elimination is used to select process parameters with qualified ceramic phase content, porosity and crack number according to the optimal parameter results of porosity, crack number and reinforcing phase content for the actual required coating thickness, and group experiments are carried out to select the optimal process parameters.

[0043] The beneficial effects of the present invention are:

[0044] Aiming at the problem of powder utilization rate in the industrial application of laser cladding, the present invention combines the single factor experimental method with the recursive method to determine the corresponding relationship between power, line speed and powder feeding rate, which effectively improves the one-sidedness of process parameter adjustment in order to ensure coating thickness during process exploration. While obtaining the target coating thickness, the exploration of process parameters is comprehensive, which helps to fully understand the availability of its powder;

[0045] At the same time, the present invention uses the progressive regression analysis method to conduct a comprehensive process exploration to address the various problems of pores, cracks, and ceramic phase loss in ceramic phase reinforced composite coatings, thereby facilitating the acquisition of appropriate process parameters to obtain an ideal ceramic phase reinforced composite coating. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a data relationship diagram of melting power, thickness, melting depth, dilution rate and molten pool width in Example 2 of the present invention.

[0047] Figure 2 It is a data relationship diagram of melting power, single-pass coating mass powder, melting efficiency, linear energy density, and molten pool duration in Example 2 of the present invention.

[0048] Figure 3 It is a data relationship diagram of the melting power, linear energy density, and the amount of molten powder in the unit molten pool of Example 2 of the present invention.

[0049] Figure 4 It is the orthogonal experiment table and experimental results of Example 2 of the present invention.

[0050] Figure 5It is a schematic diagram of mean values ​​and extreme values ​​of process parameters related to thickness in Example 2 of the present invention.

[0051] Figure 6 It is a schematic diagram of mean and extreme values ​​of process parameters regarding porosity in Example 2 of the present invention.

[0052] Figure 7 It is a schematic diagram of mean and extreme values ​​of process parameters related to cracks in Example 2 of the present invention.

[0053] Figure 8 It is a schematic diagram of the mean and extreme values ​​of process parameters regarding TiC content in Example 2 of the present invention.

[0054] Fig. 9 It is a schematic diagram of the grouping test results of step S4 in Example 2 of the present invention.

[0055] Fig.10 It is a metallographic photograph under the optimal process parameters in Example 2 of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and the best embodiment. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the invention.

[0057] Embodiment 1: As shown in the figure, the present invention comprises the following steps:

[0058] S1. Use the single factor experimental method to optimize the melting power range of ceramic composite powder and determine the relationship between powder feeding rate, line speed and power. Specifically include:

[0059] S11. Mixing the alloy powder with the ceramic phase powder to form the ceramic phase composite powder.

[0060] S12. The powder was fed at a rate of 28 g / min. At a linear speed of 1 m / min, single-pass cladding was performed using 600 W, 900 W, 1200 W, 1500 W, 1800 W, 2100 W, 2400 W, 2700 W, 3000 W, 3300 W, 3600 W, 3900 W, 4200 W, and 4500 W. During the process, an infrared thermal imager was used to measure the molten pool width at each power and a pyrometer was used to measure the maximum molten pool temperature. After the cladding was completed, the molten coating was cut off by wire cutting. After the surface was ground to a smooth surface, the coating thickness and penetration depth were measured using a metallographic microscope, and the coating dilution rate was calculated.

[0061] S13. Determine the melting power range according to the peak point of the coating thickness and the coating dilution rate. Specifically, the heat required for melting the alloy powder is the product of the melting latent heat and the mass. During the laser cladding process, the high-energy laser quickly melts the workpiece surface and the alloy powder added synchronously. Therefore, the melting degree of the same mass of powder will reach a peak value as the temperature increases in the same time. The melting degree of the powder is positively correlated with the coating thickness. Determine the peak point of its thickness and the appropriate dilution rate to determine the power range.

[0062] S14. Considering the typical bow shape of the cross section of the well-coated cladding layer, the cross-sectional area S is calculated according to the molten pool width d and coating thickness h of the cross section of the cladding layer.

[0063] ,

[0064] According to the cladding length L, composite powder density ρ and cross-sectional area S, the mass M of the single-pass cladding layer is calculated.

[0065] ,

[0066] According to the single-pass cladding layer quality M, line speed v, cladding length L, powder feeding rate V P , calculate the powder melting efficiency η,

[0067] ,

[0068] According to the melting power P and the linear speed v, the linear energy density Q is calculated.

[0069] ,

[0070] According to the molten pool width d and line speed v, calculate the molten pool duration t.

[0071] ,

[0072] Combined with the cross section of the cladding layer, the powder melting efficiency, linear energy density, and molten pool duration at each melting power are calculated. Combined with the coating thickness and melting efficiency, the melting power range is optimized.

[0073] S2. Use the recursive method to derive the corresponding proportional relationship between the melting power and each process parameter and coating parameter. Specifically including:

[0074] S21. According to the optimized melting power range, the linear energy density Q, the powder melting efficiency η and the molten pool duration t are calculated, and the amount of molten powder m in the unit molten pool is calculated to obtain the range values ​​of the linear energy density Q and the amount of molten powder m in the unit molten pool. The amount of molten powder m in the unit molten pool is expressed as:

[0075] ,

[0076] Where t is the duration of the molten pool, V P is the powder feeding rate and η is the powder melting efficiency.

[0077] S22. Through regression fitting analysis, the relationship between the molten pool width d and the melting power P is obtained, and then the relationship between the melting power P, the line speed and the coating thickness is derived as follows:

[0078] d=1.2502ln(P)-6.1401,

[0079] According to the previous formula, the relationship between melting power P, line speed v and coating thickness h can be obtained as follows:

[0080] .

[0081] S3. Use the corresponding range values ​​of melting power, line speed and powder feeding rate to set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments to determine the relationship between process parameters and coating parameters. Specifically include:

[0082] S31. Using the corresponding range values ​​of melting power, line speed and powder feeding rate, set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments.

[0083] S32. Obtain the corresponding relationship between power, linear velocity, powder feeding rate, thickness, porosity, number of cracks and ceramic phase content.

[0084] S33. Based on the mean and variance obtained from the orthogonal experiment, determine the order of influence.

[0085] S4. Using a combination of positive selection and reverse elimination, based on the actual required coating thickness, according to the optimal parameter results of porosity, number of cracks and reinforcing phase content, select process parameters with qualified ceramic phase content, porosity and number of cracks, conduct group experiments, and select the optimal process parameters.

[0086] Embodiment 2:

[0087] Step S1: Use an alloy powder with a chromium content of 21%, an iron content of 4%, a molybdenum content of 13%, and a nickel content of 62%. Then mix 70% of this alloy powder and 30% TiC powder. The particle size range of the alloy powder and TiC powder is 50-106μm. The mixed powder is mixed on a powder mixer for 8 hours at a speed of 100r / min. Then dry it in a drying oven at 120℃ for 2h. The density of the mixed powder is ρ=7.437g / cm 3 .

[0088] Coaxial powder feeding was used for laser cladding, in which the shielding gas was maintained at 22 L / min, the powder carrier gas was maintained at 5 L / min, and the spot size was fixed at 3.5 mm.

[0089] First, the powder was fed at a rate of 28g / min, and single-pass cladding was performed at 600W, 900W, 1200W, 1500W, 1800W, 2100W, 2400W, 2700W, 3000W, 3300W, 3600W, 3900W, 4200W, and 4500W at a linear speed of 1m / min. During the process, an infrared thermal imager was used to measure the width of the molten pool under each power, and a pyrometer was used to measure the maximum temperature of the molten pool. After the cladding was completed, the molten coating was cut off by wire cutting, and after the surface was polished to be smooth, the coating thickness and penetration were measured by a metallographic microscope, and the coating dilution rate was calculated.

[0090] The heat required to melt alloy powder is the product of latent heat of melting and mass. During laser cladding, high-energy laser quickly melts the workpiece surface and the alloy powder added simultaneously. Therefore, the melting degree of the same mass of powder will reach a peak value as the temperature rises in the same time. The melting degree of powder is positively correlated with the thickness of the coating. The peak point of its thickness and the appropriate dilution rate are determined to determine the power range. Figure 1 As shown, it can be found that in the power range of 1500W-3300W, there are obvious fluctuations in thickness and dilution rate relative to lower power and higher power.

[0091] Combined with the typical bow shape of the cross section of the cladding layer, the cross-sectional area S (unit: mm) is calculated according to the molten pool width d and coating thickness h of the cross section of the cladding layer. 2 ),

[0092] ,

[0093] According to the cladding length L, composite powder density ρ (unit, g / cm 3 ) and cross-sectional area S, calculate the mass M (unit, g) of the single-pass cladding layer,

[0094] ,

[0095] The calculation results show that at each power, the cladding length L = 100 mm and the selected composite powder density ρ = 7.437 g / cm 3 The quality of single-pass cladding layer is as follows: Figure 2 shown.

[0096] Among them, the powder feeding rate V PThe values ​​are all 28g / min, i.e. 0.47g / s, the cladding length L=100mm, and the line speed is 1m / min. According to the single-pass cladding layer mass M, line speed v, cladding length L, and powder feeding rate V P , calculate the powder melting efficiency η,

[0097] ,

[0098] According to the melting power P (unit, W) and the line speed v (unit, m / min), the line energy density Q (unit, J / mm) is calculated.

[0099] ,

[0100] According to the molten pool width d and line speed v, calculate the molten pool duration t (unit, s),

[0101] ,

[0102] Combination Figure 2 The thickness of the coating and the melting efficiency are adjusted to optimize the melting power range, and 2400W-3000W is selected as the power range.

[0103] Step S2: According to Figure 2 The data in the middle, at this time the amount of molten powder m in the unit molten pool is expressed as:

[0104] ,

[0105] Where t is the duration of the molten pool, V P is the powder feeding rate, η is the powder melting efficiency, and the calculation results are as follows: Figure 3 .

[0106] Through regression fitting analysis, the obtained data is used for regression fitting to obtain the relationship between power, molten pool width and power:

[0107] d=1.2502ln(P)-6.1401,

[0108] Where d is in mm and P is in W.

[0109] According to the previous formula, the relationship between melting power P, line speed v and coating thickness h can be obtained as follows:

[0110] .

[0111] According to the cladding efficiency results, the melting efficiencies corresponding to the linear energy densities Q of 143.7 J / mm, 161.7 J / mm and 179.6 J / mm are 85.75%, 84.41% and 88.55% respectively. According to the powder utilization rate and the retention of the ceramic phase, the 143.7 J / mm with higher cladding efficiency and lower linear energy density is selected. When the powder feeding rate is 28 g / min, the amount of molten powder in the unit molten pool m=0.098 g is the optimal parameter. The relationship between the powder feeding rate and the amount of molten powder in the unit molten pool m is set,

[0112]

[0113] Set v and h, get P according to Q, get m according to h and P, and get m according to m and V P The powder feeding rate can be obtained from the corresponding relationship.

[0114] Step S3: At this time, the line speed can be selected according to the needs. At this time, 1.0m / min, 1.2m / min, and 1.5m / min are selected. The thickness is 1.2mm. According to the line energy formula, the power range is 2400W, 2900W, and 3600W. The overlap rate is fixed at 50%, so the single-channel lateral displacement is b=50%d. The single-channel lateral displacement is 1.8mm, 2.0mm, and 2.1mm in the power range of 2400W, 2900W, and 3600W. Using the above relationship between power, line speed, powder feeding rate, and thickness, the powder feeding rate is set to 28g / min, 33g / min, and 38g / min. Obtain an orthogonal experimental table, and conduct experiments to obtain the experimental results as shown below Figure 4 .

[0115] Among them, the mean and extreme values ​​of the process parameters related to thickness are as follows: Figure 5 As shown in Figure 1, according to the range analysis, the order of influence of process parameters on thickness is: line speed > powder feeding rate > single-pass traverse > power. The mean and extreme values ​​of process parameters for porosity are shown in Figure 1. Figure 6 As shown in the figure, according to the range analysis, the order of influence of process parameters on porosity is: powder feeding rate > line speed > single-channel traverse > power, and using Figure 6 The mean values ​​1-3 in the figure show that when the power is 2400W, the line speed is 1.2m / min, the powder feeding rate is 28g / min, and the single-pass traverse is 1.8mm, the minimum porosity is possible. Figure 7 As shown in Figure 2, according to the range analysis, the order of influence of process parameters on cracks is: powder feeding rate > line speed > single-channel traverse > power, and using Figure 7The mean values ​​1-3 in the figure show that when the power is 2400W, the line speed is 1.5m / min, the powder feeding rate is 33g / min, and the single-pass traverse is 2.1mm, the minimum number of cracks is possible. The mean and extreme values ​​of the process parameters for TiC content are as follows: Figure 8 As shown in the figure, according to the range analysis, the order of influence of process parameters on TiC content is: power > powder feeding rate > line speed > single-channel traverse, and using Figure 8 From the average values ​​1-3, it can be obtained that when the power is 2400W, the line speed is 1m / min, the powder feeding rate is 33g / min, and the single-channel lateral displacement is 1.8mm, there is a possibility of increasing the TiC content.

[0116] Step S4: It can be found that among the process parameters, the line speed and powder feeding rate have a great influence on each parameter. According to the above-mentioned optimal parameter results of porosity, crack number and TiC content, the power is limited to 2400W, the line speed value range is 1, 1.2, 1.5mm / min, the powder feeding rate is 28, 33g / min, and the single-channel lateral displacement is 1.8, 2.1mm. Combining the relationship between power, line speed, powder feeding rate and thickness, the experiment is carried out by combining positive selection with reverse elimination and the experimental results are obtained, such as Fig. 9 As shown, after comprehensive analysis of the optimized experiments 10-15, experiment 10 has the best comprehensive performance, with small porosity, few cracks and high TiC content.

[0117] The present application discloses a laser cladding process optimization method based on ceramic phase reinforced composite coating. The progressive regression analysis method is used. First, the single factor experimental method is combined with the recursive method. By adjusting the power range, the dilution rate and thickness are used as evaluation indicators of the powder fusion effect and the single-pass cladding layer forming effect, and the corresponding relationship between power, line speed and powder feeding rate is obtained. Then, the corresponding relationship between power, line speed, powder feeding rate and thickness, porosity, cracks and ceramic phase content is obtained through orthogonal experiments of multi-pass cladding layer forming. The influence degree and influence order of each process parameter on the porosity of the cladding layer are analyzed by range and variance. Finally, the forward selection and reverse elimination are combined. According to the required cladding layer thickness and the above experimental results, the process parameters with qualified ceramic phase content, porosity and number of cracks are selected, and group experiments are carried out to select the optimal process parameters.

[0118] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A laser cladding process optimization method for ceramic phase reinforced composite coating, characterized in that: The steps include: S1. Use the single factor experimental method to optimize the melting power range of the ceramic phase composite powder and determine the relationship between the powder feeding rate, line speed and power, which specifically includes: S11. The alloy powder is mixed with the ceramic phase powder to form the ceramic phase composite powder; S12. Use coaxial powder feeding method for laser cladding, select multiple groups of melting power for single-pass cladding, and record the molten pool width and maximum molten pool temperature at each melting power, as well as coating thickness, melting depth, and coating dilution rate; S13. Determine the melting power range according to the peak point of the coating thickness and the coating dilution rate; S14. Calculate the powder melting efficiency, linear energy density, and molten pool duration at each melting power based on the cross section of the cladding layer, and optimize the melting power range based on the coating thickness and melting efficiency; S2. The corresponding proportional relationship between the melting power and each process parameter and coating parameter is derived by recursive method, which specifically includes: S21. According to the optimized melting power range, the linear energy density Q, the powder melting efficiency η and the molten pool duration t are calculated, and the amount of molten powder m in the unit molten pool is calculated to obtain the range values ​​of the linear energy density Q and the amount of molten powder m in the unit molten pool; S22. Through regression fitting analysis, the relationship between the molten pool width d and the melting power P is obtained, and then the relationship between the melting power P, the line speed and the coating thickness is derived; S3. Use the corresponding range values ​​of melting power, line speed and powder feeding rate to set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments to determine the relationship between process parameters and coating parameters, including: S31. Using the corresponding range values ​​of melting power, line speed and powder feeding rate, set the range of melting power, line speed and powder feeding rate, and overlap multiple channels to conduct orthogonal experiments; S32. Obtain the corresponding relationship between power, linear velocity, powder feeding rate and thickness, porosity, number of cracks and ceramic phase content; S33. Based on the mean and variance obtained from the orthogonal experiment, determine the order of influence; S4. Utilize a combination of forward selection and reverse elimination, for the actual required coating thickness, according to the relationship between process parameters and coating parameters, determine the process parameters and conduct group experiments to select the optimal process parameters, wherein, utilize a combination of forward selection and reverse elimination, for the actual required coating thickness, according to the optimal parameter results of porosity, number of cracks and reinforcing phase content, select process parameters with qualified ceramic phase content, porosity and number of cracks, conduct group experiments and select the optimal process parameters.

2. The laser cladding process optimization method for ceramic phase reinforced composite coating according to claim 1, characterized in that: In step S12, coaxial powder feeding is used for laser cladding, wherein the shielding gas is maintained at 22 L / min, the powder carrier gas is maintained at 5 L / min, and the spot size is fixed at 3.5 mm. The powder feeding rate was 28 g / min, and at a line speed of 1 m / min, multiple groups of melting powers were selected for single-pass cladding.

3. The laser cladding process optimization method for ceramic phase reinforced composite coating according to claim 2, characterized in that: In step S14, the cross-sectional area S is calculated according to the molten pool width d and the coating thickness h of the cross-sectional area of ​​the cladding layer. ， According to the cladding length L, composite powder density ρ and cross-sectional area S, the mass M of the single-pass cladding layer is calculated. ， According to the single-pass cladding layer quality M, line speed v, cladding length L, powder feeding rate V P , calculate the powder melting efficiency η, ， According to the melting power P and the linear speed v, the linear energy density Q is calculated. ， According to the molten pool width d and line speed v, calculate the molten pool duration t. 。 4. The laser cladding process optimization method for ceramic phase reinforced composite coating according to claim 3, characterized in that: In step S21, the amount of molten powder m in the unit molten pool is expressed as: ， Where t is the duration of the molten pool, V P is the powder feeding rate and η is the powder melting efficiency.

5. The laser cladding process optimization method for ceramic phase reinforced composite coating according to claim 4, characterized in that: In step S22, through regression fitting analysis, the relationship between the molten pool width d and the melting power P is obtained as follows: d=1.2502ln(P)-6.1401, The relationship between melting power P, line speed v and coating thickness h is derived as follows: 。

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