A method for barrel grinding and finishing of thermal barrier coatings in stages

Abstract

The present invention belongs to the technical field of thermal barrier coating preparation and surface finishing, and in particular relates to a method for barrel finishing of thermal barrier coating in stages. The thermal barrier coating comprises a substrate, an adhesive layer and a ceramic layer, and the processing method is a combination of barrel finishing of the substrate surface, barrel finishing of the adhesive layer surface and barrel finishing of the ceramic layer surface. The process parameters used in the barrel finishing of the substrate surface are evaluated by the substrate surface evaluation index. P Optimization is performed; the process parameters used in the roller finishing of the bonding layer surface are evaluated by the bonding layer surface evaluation index Q Optimization is performed; the process parameters used in the barrel grinding and finishing of the ceramic layer are determined by the ceramic layer surface evaluation index R The present invention can synergistically improve the surface integrity of the substrate, bonding layer, and ceramic layer during the thermal barrier coating manufacturing process, and construct multi-dimensional surface evaluation indicators based on the processing requirements of the multi-layer structure surface to achieve refined selection and optimization of staged process parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal barrier coating preparation and surface finishing, and in particular to a full-process staged barrel grinding and finishing method for thermal barrier coating. Background Art

[0002] With the rapid development of modern industrial technology, particularly in the aerospace, energy, chemical, and automotive industries, the issue of material protection in high-temperature environments has become increasingly prominent. Thermal barrier coatings (TBCs), as an advanced surface protection technology, have become a key approach to addressing material failure in high-temperature environments due to their outstanding high-temperature protection, oxidation resistance, and thermal insulation properties. A typical TBC typically consists of a substrate, a bond coat, and a ceramic layer. During the service life of a TBC, the surface integrity of its multilayer structure significantly impacts its overall performance and long-term service life. For the substrate surface, surface roughness and cleanliness significantly influence the performance of TBCs. Appropriate surface roughness enhances the mechanical locking effect between the coating and the substrate, thereby improving the bond strength between the two. A clean substrate surface effectively slows the oxidation and corrosion of the coating by impurities such as oil. Furthermore, the bond coat surface, serving as the interface between the bond coat and the ceramic layer, is widely considered a sensitive area for spalling failure in TBC systems. The surface profile of the bond coat directly influences the distribution of thermal oxides and stress concentration at the interface, factors that are crucial in determining a coating's ability to resist spalling failure. The ceramic layer is the final working surface of the hot-end component, and its surface integrity also significantly affects the performance of the thermal barrier coating; reducing the surface roughness of the ceramic layer can improve the aerodynamic performance of the component surface, while reducing the adhesion of corrosive substances and thus improving corrosion resistance; on the other hand, a higher surface hardness can improve the wear resistance of the thermal barrier coating and comprehensively extend the service life of the thermal barrier coating.

[0003] Currently, surface treatment technologies for thermal barrier coatings (TBCs) are still in the exploratory stage, with their application largely limited to single-layer surface treatments for substrates, bonding layers, or ceramic layers. This makes it difficult to meet the demands of collaborative manufacturing of multilayer TBC structures. Furthermore, in the practical application of existing TBC surface treatment technologies, process parameter selection is often determined by experience, lacking evaluation metrics to support decision-making. This situation not only greatly limits the precise control and repeatability of surface treatment effects, but also severely impacts the consistency of TBC surface quality and the long-term service stability. Therefore, there is an urgent need to develop a staged surface finishing method for the entire TBC manufacturing process, based on optimized process parameters to meet the diverse processing requirements of multilayer structures. Summary of the Invention

[0004] In order to solve the technical bottlenecks of unsatisfactory surface treatment effects and poor synergy between layers in the practice of existing thermal barrier coating surface treatment technology, as well as the technical defects of excessive reliance on experience in the selection of process parameters and lack of systematic evaluation indicators as a basis for scientific decision-making, the present invention provides a staged barrel finishing method for the entire process of thermal barrier coating.

[0005] The present invention provides a method for barrel finishing a thermal barrier coating in a staged manner. The thermal barrier coating comprises a substrate, a bonding layer, and a ceramic layer. The method comprises the following multi-stage process combination set M:

[0006] M = {(a), (b), (c), (a,b), (b,c), (a,c), (a,b,c)}, where a is the barrel finishing of the substrate surface, b is the barrel finishing of the bonding layer surface, and c is the barrel finishing of the ceramic layer surface;

[0007] When the substrate surface is subjected to barrel finishing, the process parameters are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed based on the surface roughness and the residual oil content on the surface:

[0008]

[0009] Where Ra sub is the surface roughness of the substrate after processing, Ra std The surface roughness of the substrate before spraying according to the technical requirements of different bonding layers, Ra tol is the allowable tolerance value of the substrate surface roughness before spraying, W is the residual oil content of the surface after processing measured by the oil test paper method, and W0 is the maximum allowable residual oil content on the substrate surface;

[0010] When the bonding layer surface is barrel-finished, the process parameters used are optimized by the bonding layer surface evaluation index Q; the bonding layer surface evaluation index Q is constructed:

[0011]

[0012] Where, l r is the test length, Z(x) is the height of the contour corresponding to the test point, is the second-order derivative of the test point;

[0013] When the ceramic layer surface is barrel-finished, the process parameters used are optimized based on the ceramic layer surface evaluation index R. The surface roughness difference ΔRa and surface microhardness difference ΔHV before and after processing for each set of process parameters are calculated to construct the ceramic layer evaluation index R:

[0014]

[0015] Where, ΔRak is the surface roughness difference before and after processing of the kth group of process parameters, ΔRa max ΔHV is the maximum difference in surface roughness before and after processing in all process parameter groups. k is the difference in surface microhardness before and after processing of the kth group of process parameters, ΔHV max is the maximum difference in surface microhardness before and after processing in all process parameter groups, ω1 and ω2 are weighted distribution coefficients and their sum is 1.

[0016] Preferably, the process of optimizing the process parameters for barrel finishing of the substrate surface comprises the following steps:

[0017] Step A1, setting the grinding block material to one of silicon carbide, brown corundum, and white corundum, setting the grinding block shape to one of spherical, oblique triangle, and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-40 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block;

[0018] Step A2: using a barrel finishing machine to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing using a surface roughness meter, testing the residual oil content on the substrate surface using an oil test paper, and calculating the substrate surface evaluation index P;

[0019] Step A3, repeating steps A1 to A2 to form different process parameter combinations, and obtaining the surface evaluation index P of the processed substrate corresponding to the different process parameter combinations;

[0020] Step A4: Repeat step A3 multiple times until the substrate surface evaluation index P reaches a minimum value, and the corresponding process parameter combination is the optimal substrate surface barrel finishing processing parameter.

[0021] Preferably, the process for optimizing process parameters for barrel finishing of the bonding layer surface comprises the following steps: step B1, setting the grinding block material to one of brown corundum, white corundum and high-alumina porcelain, setting the grinding block shape to one of spherical, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-90 min, where the grinding block size is the diameter of spherical particles of equivalent volume of a single grinding block;

[0022] Step B2: Prepare a bonding layer on the surface of the substrate after barrel finishing, obtain a bonding layer sample, test the surface profile of the initial bonding layer sample, and calculate the initial bonding layer surface evaluation index Q bef ;

[0023] Step B3: Use barrel finishing equipment to barrel finish the bonding layer sample, test the surface profile of the bonding layer after processing, and calculate the surface evaluation index Q of the bonding layer after processing. aft ;

[0024] Step B4: preparing a ceramic layer on the surface of the processed bonding layer described in Step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, using a spalling area exceeding 5% as a criterion for determining thermal cycle failure, and calculating the thermal cycle life of the thermal barrier coating;

[0025] Step B5, repeating steps B1 to B4 multiple times, using different process parameter combinations to perform barrel finishing of the bonding layer, constructing a barrel finishing database for the bonding layer, and normalizing various data in the barrel finishing database for the bonding layer. Each set of data in the barrel finishing database for the bonding layer includes an initial bonding layer surface evaluation index Q bef , process parameters, surface evaluation index Q of bonding layer after processing aft and thermal cycling life;

[0026] Step B6: Obtain the optimal surface evaluation index Q of the bonding layer after processing by comparing the maximum thermal cycle life in the bonding layer barrel finishing database. max ;

[0027] Step B7: Establish a prediction model for the bonding layer barrel finishing process, wherein multiple groups of initial bonding layer surface evaluation indicators Q bef and process parameters as input, multiple groups of surface evaluation indicators Q of the bonding layer after processing aft As output, neural network training is performed to obtain the bonding layer barrel finishing prediction model;

[0028] Step B8: Using the optimal bonding layer surface evaluation index Q after processing max To optimize the target, a fitness function is established based on the bonding layer roller finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of the bonding layer with different initial bonding layers. bef The process parameters of the bonding layer are optimized.

[0029] Preferably, the process of optimizing process parameters for the barrel finishing of the ceramic layer surface includes the following steps: step C1, setting the grinding block material to one of brown corundum, zirconium corundum, and elastic resin, setting the grinding block shape to one of spherical and conical, setting the grinding block size to 2 to 10 mm, and setting the processing time to 10 to 120 min, where the grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block;

[0030] Step C2, preparing a ceramic layer on the surface of the bonding layer after the barrel finishing process to obtain a ceramic layer sample, performing surface testing on the surface of the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer sample using a surface roughness meter and a Vickers surface hardness tester;

[0031] Step C3, performing barrel finishing on the ceramic layer sample using a barrel finishing process, and testing the surface roughness and surface microhardness of the ceramic layer after processing using a surface roughness tester and a Vickers surface hardness tester;

[0032] Step C4, repeating steps C1 to C3 multiple times, using different process combinations to perform barrel finishing on the ceramic layer;

[0033] Step C5: Calculate and compare the ceramic layer evaluation index R corresponding to each set of process parameters. The process parameter combination corresponding to the maximum R value is the optimal ceramic layer barrel finishing processing parameter.

[0034] The technical solution provided by the present invention has the following beneficial effects compared with the prior art: the method for the staged roller finishing of the entire process of thermal barrier coatings described in the present invention can synergistically improve the surface integrity of the substrate, bonding layer and ceramic layer in the manufacturing process of thermal barrier coatings, and construct multi-dimensional surface evaluation indicators based on the processing requirements of the multi-layer structure surface, so as to realize the refined selection and optimization of the staged process parameters. In addition, with the development of thermal barrier coatings, the surface processing requirements of multi-layer structures will inevitably undergo dynamic changes. The processing method provided by the present invention has good flexibility and can select process parameters efficiently and quickly according to the parameter optimization method, thereby reducing the time and cost required to change the process flow. At the same time, the roller finishing process has good adaptability to the part configuration and has good application prospects in the preparation process of thermal barrier coatings for hot end components with complex configurations. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0037] Figure 1 Schematic diagram of a process for barrel finishing of a thermal barrier coating in stages according to an embodiment of the present invention;

[0038] Figure 2 Schematic diagram of the structure of the bonding layer rolling finishing prediction model described in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the scheme of the present invention will be further described below. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention can also be implemented in other ways different from those described herein; it is obvious that the embodiments in the description are only some embodiments of the present invention, not all embodiments.

[0040] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0041] In one embodiment, Figure 1 As shown, a method for barrel finishing of a thermal barrier coating in stages is provided. The thermal barrier coating includes a substrate, a bonding layer, and a ceramic layer. The method includes the following multi-stage process combination set M:

[0042] M = {(a), (b), (c), (a,b), (b,c), (a,c), (a,b,c)}, where a is the barrel finishing of the substrate surface, b is the barrel finishing of the bonding layer surface, and c is the barrel finishing of the ceramic layer surface;

[0043] When the substrate surface is subjected to barrel finishing, the process parameters are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed based on the surface roughness and the residual oil content on the surface:

[0044]

[0045] Where Ra sub is the surface roughness of the substrate after processing, Ra std The surface roughness of the substrate before spraying according to the technical requirements of different bonding layers, Ra tol is the allowable tolerance value of the substrate surface roughness before spraying, W is the residual oil content of the surface after processing measured by the oil test paper method, and W0 is the maximum allowable residual oil content on the substrate surface;

[0046] When the bonding layer surface is barrel-finished, the process parameters used are optimized by the bonding layer surface evaluation index Q; the bonding layer surface evaluation index Q is constructed:

[0047]

[0048] Where, l r is the test length, Z(x) is the height of the contour corresponding to the test point, is the second-order derivative of the test point;

[0049] When the ceramic layer surface is barrel-finished, the process parameters used are optimized based on the ceramic layer surface evaluation index R. The surface roughness difference ΔRa and surface microhardness difference ΔHV before and after processing for each set of process parameters are calculated to construct the ceramic layer evaluation index R:

[0050]

[0051] Where, ΔRa k is the surface roughness difference before and after processing of the kth group of process parameters, ΔRa max ΔHV is the maximum difference in surface roughness before and after processing in all process parameter groups. k is the difference in surface microhardness before and after processing of the kth group of process parameters, ΔHV max is the maximum difference in surface microhardness before and after processing in all process parameter groups, ω1 and ω2 are weighted distribution coefficients and their sum is 1.

[0052] In a specific embodiment, the thermal barrier coating includes a nickel-based high-temperature alloy substrate, a NiCrAlYSi bonding layer prepared by arc ion plating technology, and a YSZ ceramic layer prepared by electron beam physical vapor deposition technology, wherein the substrate thickness is 3 mm, the bonding layer thickness is 40 to 70 μm, and the ceramic layer thickness is 200 to 300 μm.

[0053] Based on the above embodiment, in a preferred embodiment, the process of optimizing the process parameters for barrel finishing of the substrate surface includes the following steps:

[0054] Step A1, setting the grinding block material to one of silicon carbide, brown corundum, and white corundum, setting the grinding block shape to one of spherical, oblique triangle, and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-40 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block;

[0055] Step A2: using a barrel finishing machine to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing using a surface roughness meter, testing the residual oil content on the substrate surface using an oil test paper, and calculating the substrate surface evaluation index P;

[0056] Step A3, repeating steps A1 to A2 to form different process parameter combinations, and obtaining the surface evaluation index P of the processed substrate corresponding to the different process parameter combinations;

[0057] Step A4: Repeat step A3 multiple times until the substrate surface evaluation index P reaches a minimum value, and the corresponding process parameter combination is the optimal substrate surface barrel finishing processing parameter.

[0058] In this embodiment, the surface roughness Ra required by the arc ion plating technology before spraying is stdThe maximum allowable residual oil content on the substrate surface is 10 μm, and the allowable tolerance is 2 μm. According to the national standard GB / T13312-1991 "Test method for oil removal degree of steel parts before painting", the maximum allowable residual oil content W0 on the substrate surface is 0.12 g / m 2 The equipment used for the barrel finishing of the substrate surface is a vertical centrifugal barrel finishing equipment, with a drum speed of 300 r / min, a grinding block filling volume of 70%, and a liquid processing medium of water and HA-FC grinding fluid (volume ratio of 10:1).

[0059] Based on the above embodiment, in a preferred embodiment, the process of optimizing the process parameters for the barrel finishing process of the bonding layer surface includes the following steps:

[0060] Step B1, setting the grinding block material to one of brown corundum, white corundum and high-aluminum porcelain, setting the grinding block shape to one of spherical, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-90 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block;

[0061] Step B2: Prepare a bonding layer on the surface of the substrate after barrel finishing, obtain a bonding layer sample, test the surface profile of the initial bonding layer sample, and calculate the initial bonding layer surface evaluation index Q bef ;

[0062] Step B3: Use barrel finishing equipment to barrel finish the bonding layer sample, test the surface profile of the bonding layer after processing, and calculate the surface evaluation index Q of the bonding layer after processing. aft ;

[0063] Step B4: preparing a ceramic layer on the surface of the processed bonding layer described in Step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, using a spalling area exceeding 5% as a criterion for determining thermal cycle failure, and calculating the thermal cycle life of the thermal barrier coating;

[0064] Step B5, repeating steps B1 to B4 multiple times, using different process parameter combinations to perform barrel finishing of the bonding layer, constructing a barrel finishing database for the bonding layer, and normalizing various data in the barrel finishing database for the bonding layer. Each set of data in the barrel finishing database for the bonding layer includes an initial bonding layer surface evaluation index Q bef , process parameters, surface evaluation index Q of the bonding layer after processing aft and thermal cycling life;

[0065] Step B6: Obtain the optimal surface evaluation index Q of the bonding layer after processing by comparing the maximum thermal cycle life in the bonding layer barrel finishing database. max ;

[0066] Step B7: Establish a prediction model for the bonding layer barrel finishing process, wherein multiple groups of initial bonding layer surface evaluation indicators Q bef and process parameters as input, multiple groups of surface evaluation indicators Q of the bonding layer after processing aft As output, neural network training is performed to obtain the bonding layer barrel finishing prediction model;

[0067] Step B8: Using the optimal bonding layer surface evaluation index Q after processing max To optimize the target, a fitness function is established based on the bonding layer roller finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of the bonding layer with different initial bonding layers. bef The process parameters of the bonding layer are optimized.

[0068] In this example, a Mahr-M400 surface roughness tester was used to perform stylus testing on the surface. The surface profile height corresponding to the test points within the test length was recorded. The bonding layer surface was barrel-finished using a vertical centrifugal barrel-finishing machine, with a drum speed of 300 rpm, a 70% abrasive block fill, and a liquid processing medium consisting of water and HA-FC abrasive solution (10:1 by volume). Referring to the national standard GB / T42259-2022, "Test Method for Thermal Cycling and Thermal Shock Resistance of Thermal Barrier Coatings of Metallic and Other Inorganic Coatings," the thermal cycling test involved a single cycle temperature profile consisting of a 10-minute heating period from 200°C to 900°C, a 30-minute hold, a 15-minute cooling period from 900°C to 200°C, and a 5-minute hold at low temperature. When calculating the spalling area, image analysis can be used to evaluate the spalling area of ​​the thermal barrier coating. If multiple spalling areas occur, the spalling area should be the sum of all spalling areas.

[0069] The various data in the bonding layer barrel finishing database are normalized, and the calculation formula is as follows:

[0070]

[0071] Where, X ij is the jth data value of the i-th category data after normalization, X ij is the jth original data value of the i-th category data, X imin is the minimum value of the i-th category data, X imax is the maximum value of the i-th category data.

[0072] Among them, when normalizing the material of the grinding block, the hardness of the grinding blocks of different materials is quantitatively characterized; when normalizing the shape of the grinding block, the grinding rate requirements of grinding blocks of different shapes are quantitatively characterized with reference to the mechanical industry standard JB / T10153-2013 "Consolidated Abrasive Rolling Blocks". The grinding rate ratio of spherical grinding blocks, oblique triangular grinding blocks and oblique cylindrical grinding blocks is 3:6:4.

[0073] In this embodiment, BP neural network is used to construct the prediction model of bonding layer barrel finishing. Figure 2 The schematic diagram of the neural network structure, where the input layer includes 4 nodes, corresponding to the initial bonding layer surface evaluation index Q bef , grinding block size, grinding block filling amount and processing time, the output layer is 1 node, corresponding to the surface evaluation index Q of the bonding layer after processing aft , the number of hidden layer nodes is n. During the training process, the data from the bonding layer barrel finishing database is sequentially input into the network, and 10,000 rounds of training are performed to obtain the neural network prediction model. The empirical calculation formula for the number of hidden layer nodes is:

[0074]

[0075] Where: i is the number of input layer nodes; k is the number of output layer nodes; h is the number of hidden layer nodes; α is a constant between 0 and 10.

[0076] In this embodiment, different initial bonding layer surface evaluation indicators Q bef As a fixed value, according to the obtained bonding layer barrel finishing prediction model, the process parameters are optimized by genetic algorithm to achieve the optimal bonding layer surface evaluation index Q after processing. max .

[0077] Based on the above embodiment, in a preferred embodiment, the process of optimizing the process parameters for the barrel finishing of the ceramic layer surface includes the following steps:

[0078] Step C1, setting the grinding block material to one of brown corundum, zirconium corundum, and elastic resin, setting the grinding block shape to one of spherical and conical, setting the grinding block size to 2-10 mm, and setting the processing time to 10-120 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block;

[0079] Step C2, preparing a ceramic layer on the surface of the bonding layer after the barrel finishing process to obtain a ceramic layer sample, performing surface testing on the surface of the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer sample using a surface roughness meter and a Vickers surface hardness tester;

[0080] Step C3, performing barrel finishing on the ceramic layer sample using a barrel finishing process, and testing the surface roughness and surface microhardness of the ceramic layer after processing using a surface roughness tester and a Vickers surface hardness tester;

[0081] Step C4, repeating steps C1 to C3 multiple times, using different process combinations to perform barrel finishing on the ceramic layer;

[0082] Step C5: Calculate and compare the ceramic layer evaluation index R corresponding to each set of process parameters. The process parameter combination corresponding to the maximum R value is the optimal ceramic layer barrel finishing processing parameter.

[0083] In this embodiment, the equipment selected for the roller finishing of the ceramic layer surface is a vertical centrifugal roller finishing equipment, the drum speed is 300r / min, the grinding block filling amount is 70%, and the liquid processing medium is water and HA-FC grinding fluid (volume ratio is 10:1).

[0084] In this embodiment, the weighted allocation weight ω1=ω2=0.5.

[0085] The above description is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Although detailed descriptions have been made with reference to the aforementioned embodiments, those skilled in the art should understand that they may still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents; and such modifications or replacements do not deviate from the essence of the corresponding technical solutions within the scope of the technical solutions of the embodiments, and they should all be included in the scope of protection of the claims.

Claims

1. A method for barrel finishing of a thermal barrier coating in stages, wherein the thermal barrier coating comprises a substrate, a bonding layer and a ceramic layer, characterized in that: The processing method includes the following multi-stage process combination set M: M = {(a), (b), (c), (a,b), (b,c), (a,c), (a,b,c)}, where a is the barrel finishing of the substrate surface, b is the barrel finishing of the bonding layer surface, and c is the barrel finishing of the ceramic layer surface; When the substrate surface is subjected to barrel finishing, the process parameters are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed based on the surface roughness and the residual oil content on the surface: Where Ra sub is the surface roughness of the substrate after processing, Ra std The surface roughness of the substrate before spraying according to the technical requirements of different bonding layers, Ra tol is the allowable tolerance value of the substrate surface roughness before spraying, W is the residual oil content of the surface after processing measured by the oil test paper method, and W0 is the maximum allowable residual oil content on the substrate surface; When the bonding layer surface is barrel-finished, the process parameters used are optimized by the bonding layer surface evaluation index Q; the bonding layer surface evaluation index Q is constructed: Where, l r is the test length, Z(x) is the height of the contour corresponding to the test point, is the second-order derivative of the test point; When the ceramic layer surface is barrel-finished, the process parameters used are optimized based on the ceramic layer surface evaluation index R. The surface roughness difference ΔRa and surface microhardness difference ΔHV before and after processing for each set of process parameters are calculated to construct the ceramic layer evaluation index R: Where, ΔRa k is the surface roughness difference before and after processing of the kth group of process parameters, ΔRa max ΔHV is the maximum difference in surface roughness before and after processing in all process parameter groups. k is the difference in surface microhardness before and after processing of the kth group of process parameters, ΔHV max is the maximum difference in surface microhardness before and after processing in all process parameter groups, ω1 and ω2 are weighted distribution coefficients and their sum is 1.

2. A method for barrel finishing of a thermal barrier coating in stages throughout the entire process according to claim 1, characterized in that: The process of optimizing the process parameters for barrel finishing of the substrate surface includes the following steps: Step A1, setting the grinding block material to one of silicon carbide, brown corundum, and white corundum, setting the grinding block shape to one of spherical, oblique triangle, and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-40 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block; Step A2: using a barrel finishing machine to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing using a surface roughness meter, testing the residual oil content on the substrate surface using an oil test paper, and calculating the substrate surface evaluation index P; Step A3, repeating steps A1 to A2 to form different process parameter combinations, and obtaining the surface evaluation index P of the processed substrate corresponding to the different process parameter combinations; Step A4: Repeat step A3 multiple times until the substrate surface evaluation index P reaches a minimum value, and the corresponding process parameter combination is the optimal substrate surface barrel finishing processing parameter.

3. The method for barrel finishing of a thermal barrier coating in a staged manner throughout the entire process according to claim 1, characterized in that: The process of optimizing the process parameters for the barrel finishing of the bonding layer surface includes the following steps: Step B1, setting the grinding block material to one of brown corundum, white corundum and high-aluminum porcelain, setting the grinding block shape to one of spherical, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, and setting the processing time to 10-90 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block; Step B2: Prepare a bonding layer on the surface of the substrate after barrel finishing, obtain a bonding layer sample, test the surface profile of the initial bonding layer sample, and calculate the initial bonding layer surface evaluation index Q bef ; Step B3: Use barrel finishing equipment to barrel finish the bonding layer sample, test the surface profile of the bonding layer after processing, and calculate the surface evaluation index Q of the bonding layer after processing. aft ; Step B4: preparing a ceramic layer on the surface of the processed bonding layer described in Step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, using a spalling area exceeding 5% as a criterion for determining thermal cycle failure, and calculating the thermal cycle life of the thermal barrier coating; Step B5, repeating steps B1 to B4 multiple times, using different process parameter combinations to perform barrel finishing of the bonding layer, constructing a barrel finishing database for the bonding layer, and normalizing various data in the barrel finishing database for the bonding layer. Each set of data in the barrel finishing database for the bonding layer includes an initial bonding layer surface evaluation index Q bef , process parameters, surface evaluation index Q of the bonding layer after processing aft and thermal cycling life; Step B6: Obtain the optimal surface evaluation index Q of the bonding layer after processing by comparing the maximum thermal cycle life in the bonding layer barrel finishing database. max ; Step B7: Establish a prediction model for the bonding layer barrel finishing process, wherein multiple groups of initial bonding layer surface evaluation indicators Q bef and process parameters as input, multiple groups of surface evaluation indicators Q of the bonding layer after processing aft As output, neural network training is performed to obtain the bonding layer barrel finishing prediction model; Step B8: Using the optimal bonding layer surface evaluation index Q after processing max To optimize the target, a fitness function is established based on the bonding layer roller finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of the bonding layer with different initial bonding layers. bef The process parameters of the bonding layer are optimized.

4. The method for barrel finishing of a thermal barrier coating in a staged manner throughout the entire process according to claim 1, characterized in that: The process of optimizing the process parameters for barrel finishing of the ceramic layer surface includes the following steps: Step C1, setting the grinding block material to one of brown corundum, zirconium corundum, and elastic resin, setting the grinding block shape to one of spherical and conical, setting the grinding block size to 2-10 mm, and setting the processing time to 10-120 min. The grinding block size is the diameter of a spherical particle with an equivalent volume of a single grinding block; Step C2, preparing a ceramic layer on the surface of the bonding layer after the barrel finishing process to obtain a ceramic layer sample, performing surface testing on the surface of the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer sample using a surface roughness meter and a Vickers surface hardness tester; Step C3, performing barrel finishing on the ceramic layer sample using a barrel finishing process, and testing the surface roughness and surface microhardness of the ceramic layer after processing using a surface roughness tester and a Vickers surface hardness tester; Step C4, repeating steps C1 to C3 multiple times, using different process combinations to perform barrel finishing on the ceramic layer; Step C5: Calculate and compare the ceramic layer evaluation index R corresponding to each set of process parameters. The process parameter combination corresponding to the maximum R value is the optimal ceramic layer barrel finishing processing parameter.

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