Thermal barrier coating full-process staged tumbling finishing method

Abstract

The invention belongs to the technical field of thermal barrier coating preparation and surface finishing, and particularly relates to a thermal barrier coating full-process staged tumbling finishing machining method. The thermal barrier coating comprises a base body, a bonding layer and a ceramic layer, and the machining method is different combination sets of base body surface roll-polishing finishing machining, bonding layer surface roll-polishing finishing machining and ceramic layer surface roll-polishing finishing machining. The technological parameters adopted by the base body surface barreling finishing processing are optimized through the base body surface evaluation index P; the technological parameters adopted by the binding layer surface roll-polishing finishing processing are optimized through the binding layer surface evaluation index Q; and technological parameters adopted by the ceramic layer surface tumbling finishing processing are optimized through the ceramic layer surface evaluation index R. According to the method, the surface integrity of the base body, the bonding layer and the ceramic layer in the manufacturing process of the thermal barrier coating can be synergistically improved, multi-dimensional surface evaluation indexes are constructed from the processing requirements of the multi-layer structure surface, and refined selection and optimization of staged process parameters are achieved.

Description

Technical Field

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

[0002] With the rapid development of modern industrial technology, especially in the fields of aerospace, energy, chemical industry and automobile industry, the problem of material protection in high temperature environment has become increasingly prominent. As an advanced surface protection technology, thermal barrier coating has gradually become a key means to solve the problem of material failure in high temperature environment due to its excellent high temperature protection, anti-oxidation and thermal insulation performance. Typical thermal barrier coatings usually include substrate, bonding layer and ceramic layer. During the service life of thermal barrier coatings, the surface integrity of its multilayer structure greatly affects the overall performance and long-term service life of thermal barrier coatings. For the substrate surface, the surface roughness and cleanliness have a significant impact on the performance of thermal barrier coatings; appropriate surface roughness can enhance the mechanical locking effect between the coating and the substrate, thereby improving the bonding strength between the two, and a clean substrate surface effectively delays the oxidation and corrosion process of impurities such as oil and dirt on the coating. Furthermore, the bonding layer surface, as the interface between the bonding layer and the ceramic layer, is generally regarded as a sensitive area for spalling failure in thermal barrier coating systems; the surface profile characteristics of the bonding layer directly affect the distribution of thermal oxides and stress concentration at the interface, and these factors are the key to determining whether the coating can 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 products 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] At present, the surface treatment technology of thermal barrier coatings is still in the exploratory stage, and its application is mostly limited to the single surface treatment of the substrate, bonding layer or ceramic layer, which is difficult to meet the collaborative manufacturing requirements of the multi-layer structure of thermal barrier coatings. In addition, in the practice of existing thermal barrier coating surface treatment technology, the selection of process parameters is often determined by experience, and there is a lack of evaluation indicators as a decision-making support. This situation not only greatly limits the precise control and repeatability of the surface treatment effect, but also seriously affects the consistency of the surface quality of the thermal barrier coating and the stability of long-term service. Therefore, it is urgent to develop a staged surface finishing method for the entire process of thermal barrier coatings, and based on the optimization of process parameters, meet the different processing requirements of the multi-layer structure surface. Summary of the invention

[0004] In order to solve the technical bottlenecks of unsatisfactory surface treatment effect 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 process parameter selection and lack of systematic evaluation indicators as a basis for scientific decision-making, the present invention provides a staged rolling and finishing method for the entire process of thermal barrier coating.

[0005] The present invention provides a method for barrel grinding and finishing of a thermal barrier coating in a whole process in stages. The thermal barrier coating comprises a substrate, a bonding layer and a ceramic layer. The processing 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 process of the substrate surface, b is the barrel finishing process of the bonding layer surface, and c is the barrel finishing process of the ceramic layer surface;

[0007] When the substrate surface is subjected to roller finishing, the process parameters used are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed according to 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 layer preparation, 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 roller-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] In the formula, 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 tumbled and polished, the process parameters used are optimized by the ceramic layer surface evaluation index R; the surface roughness difference ΔRa and the surface microhardness difference ΔHV before and after 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 the barrel grinding and finishing process 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 sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-40 min, and setting the grinding block size to be the diameter of spherical particles of equivalent volume of a single grinding block;

[0018] Step A2, using a barrel finishing equipment to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing by a surface roughness meter, testing the residual oil content on the substrate surface by means of 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 rolling and finishing processing parameter.

[0021] Preferably, the process of optimizing the process parameters of the rolling and finishing process 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-aluminum porcelain, setting the grinding block shape to one of sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-90 min, and the grinding block size is the diameter of the spherical particles of the equivalent volume of a single grinding block;

[0022] Step B2: prepare a bonding layer on the surface of the substrate after roller 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 a barrel polishing equipment to perform barrel polishing on 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 in step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, taking a peeling area exceeding 5% as a standard 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 roller polishing of the bonding layer, constructing a roller polishing database for the bonding layer, and normalizing various types of data in the roller polishing database for the bonding layer. Each group of data in the roller polishing 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 cycle 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 grinding and finishing database max ;

[0027] Step B7: Establish a prediction model for the bonding layer rolling and 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 grinding and 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 rolling finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of different initial bonding layers. bef Optimize the process parameters of the bonding layer.

[0029] Preferably, the process of optimizing the process parameters of the ceramic layer surface roller finishing process 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, wherein the grinding block size is the diameter of a spherical particle of equivalent volume of a single grinding block;

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

[0031] Step C3, using a barrel finishing equipment to perform barrel finishing on the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer after processing by 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 roller grinding and finishing on the ceramic layer;

[0033] Step C5, calculating and comparing the ceramic layer evaluation index R corresponding to each set of process parameters, and the process parameter combination corresponding to the maximum R value is the optimal ceramic layer rolling and 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 rolling and finishing of the whole process of thermal barrier coating 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 coating, 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 staged process parameters. In addition, with the development of thermal barrier coatings, the surface processing requirements of multi-layer structures will inevitably change dynamically. 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 rolling and 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 parts 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 It is a schematic diagram of a process of a staged barrel finishing method for the entire process of a thermal barrier coating according to an embodiment of the present invention;

[0038] Figure 2 It is a structural schematic diagram of the bonding layer rolling and finishing prediction model described in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to more clearly understand the above-mentioned purposes, features and advantages of the present invention, the scheme of the present invention will be further described below. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict. 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; obviously, the embodiments in the specification are only part of the embodiments of the present invention, not all of the 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 grinding and finishing of a thermal barrier coating in a staged manner throughout the entire process, wherein the thermal barrier coating comprises a substrate, a bonding layer and a ceramic layer, and the processing method comprises 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 process of the substrate surface, b is the barrel finishing process of the bonding layer surface, and c is the barrel finishing process of the ceramic layer surface;

[0043] When the substrate surface is subjected to roller finishing, the process parameters used are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed according to 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 layer preparation, 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 roller-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] In the formula, 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 tumbled and polished, the process parameters used are optimized by the ceramic layer surface evaluation index R; the surface roughness difference ΔRa and the surface microhardness difference ΔHV before and after 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 embodiments, in a preferred embodiment, the process of optimizing the process parameters of the substrate surface barrel finishing process 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 sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-40 min, and setting the grinding block size to be the diameter of spherical particles of equivalent volume of a single grinding block;

[0055] Step A2, using a barrel finishing equipment to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing by a surface roughness meter, testing the residual oil content on the substrate surface by means of 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 rolling and finishing processing parameter.

[0058] In this embodiment, the arc ion plating technology requires the surface roughness Ra before spraying. stdThe maximum value of residual oil content on the substrate surface is 10 μm, and the allowable tolerance value is 2 μm; referring to the national standard GB / T13312-1991 "Test method for degreasing degree of steel parts before painting", the maximum allowable residual oil content on the substrate surface is W0 0.12 g / m 2 The equipment used for the barrel grinding and finishing of the substrate surface is a vertical centrifugal barrel grinding and 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 liquid (volume ratio is 10:1).

[0059] Based on the above embodiments, in a preferred embodiment, the process of optimizing the process parameters of the tumbling and finishing process on 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 sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-90 min, and the grinding block size is the diameter of spherical particles of equivalent volume of a single grinding block;

[0061] Step B2: prepare a bonding layer on the surface of the substrate after roller 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 a barrel polishing equipment to perform barrel polishing on 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 in step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, taking a peeling area exceeding 5% as a standard 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 roller polishing of the bonding layer, constructing a roller polishing database for the bonding layer, and normalizing various types of data in the roller polishing database for the bonding layer. Each group of data in the roller polishing 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 cycle 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 grinding and finishing database max ;

[0066] Step B7: Establish a prediction model for the bonding layer rolling and 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 grinding and 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 rolling finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of different initial bonding layers. bef Optimize the process parameters of the bonding layer.

[0068] In this embodiment, a Mahr-M400 surface roughness meter is used to perform a stylus test on the surface, and the surface profile height corresponding to the test point within the test length is recorded. The equipment selected for the roller finishing of the bonding 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 liquid (volume ratio is 10:1). Referring to the national standard GB / T42259-2022 "Test method for thermal cycle and thermal shock performance of thermal barrier coatings of metals and other inorganic coatings", during the thermal cycle test, the temperature curve of a single cycle includes heating from 200℃ to 900℃ for 10min, heat preservation for 30min, cooling from 900℃ to 200℃ for 15min, and low temperature insulation for 5min. When calculating the peeling area, the peeling area of ​​the thermal barrier coating can be evaluated by image analysis method. If there are multiple areas of peeling, the peeling area should be the sum of all peeling 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 and Polishing Blocks", and 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, a BP neural network is used to construct a prediction model for the bonding layer barrel grinding and finishing process. 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 in the bonding layer rolling and finishing database are input into the network in sequence, and 10,000 rounds of training are performed to obtain the neural network prediction model. Among them, 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 rolling finishing prediction model, the process parameters are optimized through genetic algorithm to achieve the optimal bonding layer surface evaluation index Q after processing. max .

[0077] Based on the above embodiments, in a preferred embodiment, the process of optimizing the process parameters for the barrel grinding and 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, wherein the grinding block size is the diameter of spherical particles of equivalent volume of a single grinding block;

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

[0080] Step C3, using a barrel finishing equipment to perform barrel finishing on the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer after processing by 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 roller grinding and finishing on the ceramic layer;

[0082] Step C5, calculating and comparing the ceramic layer evaluation index R corresponding to each set of process parameters, and the process parameter combination corresponding to the maximum R value is the optimal ceramic layer rolling and 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 is only a specific implementation of the present invention, which enables those skilled in the art to understand or implement the present invention. Although detailed descriptions are given with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments, and they should all be covered by the protection scope of the claims.

Claims

1. A method for barrel finishing of a thermal barrier coating in stages during the entire process, 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 process of the substrate surface, b is the barrel finishing process of the bonding layer surface, and c is the barrel finishing process of the ceramic layer surface; When the substrate surface is subjected to roller finishing, the process parameters used are optimized by the substrate surface evaluation index P; the substrate surface evaluation index P is constructed according to 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 for different bonding layer preparation technical requirements, 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 roller-finished, the process parameters used are optimized by the bonding layer surface evaluation index Q; the bonding layer surface evaluation index Q is constructed: In the formula, 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 tumbled and polished, the process parameters used are optimized by the ceramic layer surface evaluation index R; the surface roughness difference ΔRa and the surface microhardness difference ΔHV before and after 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 thermal barrier coating in stages during the whole process according to claim 1, characterized in that: The process of optimizing the process parameters for the barrel grinding and 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 sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-40 min, and setting the grinding block size to be the diameter of spherical particles of equivalent volume of a single grinding block; Step A2, using a barrel finishing equipment to perform barrel finishing on the substrate sample, testing the surface roughness of the substrate after processing by a surface roughness meter, testing the residual oil content on the substrate surface by means of 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 rolling and finishing processing parameter.

3. A method for barrel finishing of thermal barrier coating in stages during the whole process according to claim 1, characterized in that: The process of optimizing the process parameters for the roller 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 sphere, oblique triangle and oblique cylinder, setting the grinding block size to 2-5 mm, setting the processing time to 10-90 min, and the grinding block size is the diameter of spherical particles of equivalent volume of a single grinding block; Step B2: prepare a bonding layer on the surface of the substrate after roller 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 a barrel polishing equipment to perform barrel polishing on 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 in step B3 to obtain a thermal barrier coating sample, and performing a thermal cycle test on the thermal barrier coating sample, taking a peeling area exceeding 5% as a standard 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 roller polishing of the bonding layer, constructing a roller polishing database for the bonding layer, and normalizing various types of data in the roller polishing database for the bonding layer. Each group of data in the roller polishing 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 cycle 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 grinding and finishing database max ; Step B7: Establish a prediction model for the bonding layer rolling and 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 grinding and 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 rolling finishing prediction model constructed in step B7, and a genetic algorithm is used to evaluate the surface evaluation index Q of different initial bonding layers. bef Optimize the process parameters of the bonding layer.

4. A method for barrel grinding and finishing of thermal barrier coatings in stages throughout the entire process according to claim 1, characterized in that: The process of optimizing the process parameters for the barrel grinding and 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, wherein the grinding block size is the diameter of spherical particles of equivalent volume of a single grinding block; Step C2, preparing a ceramic layer on the surface of the bonding layer after the roller grinding and finishing process to obtain a ceramic layer sample, performing a surface test on the surface of the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer sample by a surface roughness meter and a Vickers surface hardness tester; Step C3, using a barrel finishing equipment to perform barrel finishing on the ceramic layer sample, and testing the surface roughness and surface microhardness of the ceramic layer after processing by 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 roller grinding and finishing on the ceramic layer; Step C5, calculating and comparing the ceramic layer evaluation index R corresponding to each set of process parameters, and the process parameter combination corresponding to the maximum R value is the optimal ceramic layer rolling and finishing processing parameter.

Images