A method and device for calculating the life of thermal barrier coating

Abstract

The present invention discloses a method for calculating the life of a thermal barrier coating, including: obtaining historical user usage data, component structural information of the thermal barrier coating, and planned usage conditions of the component; obtaining a life prediction model of the thermal barrier coating based on the acquired historical user usage data, component structural information of the thermal barrier coating, and planned usage conditions of the component; measuring the microstructural damage factor of the thermal barrier coating; correcting the fitting coefficient of the life prediction model by the measured microstructural damage factor of the thermal barrier coating, obtaining a corrected life prediction model, and obtaining the life of the thermal barrier coating. The thermal barrier coating nondestructive testing equipment is used to measure the crack distribution of the service component and the key parameters of the TGO layer. The measurement data can be used to verify and correct the thermal barrier coating life prediction algorithm and CFD boundary conditions, thereby improving the accuracy of the service life prediction of the thermal barrier coating and realizing the dynamic prediction of the thermal barrier coating life during the service period of the component.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermal barrier coating detection, and in particular relates to a method and device for calculating the life of a thermal barrier coating. Background Art

[0002] The hot end components of industrial gas turbines are not only subjected to high temperature and high pressure gas in the service environment, but also to high heat flux input, high temperature gradient, stress gradient, centrifugal force, etc. Thermal barrier coating (TBC) can effectively extend the service life of hot end components. Therefore, predicting the failure time of TBC can effectively predict the service life of gas turbine hot end components.

[0003] The common composition of TBC system is the outermost ceramic layer (TC), bonding layer (BC), and thermally grown oxide layer (TGO) in between that grows over time. The main reason for TBC coating failure is that with the extension of service time, the TGO layer gradually grows and thickens, and under the action of internal stress in thermal cycle, micro cracks continue to appear and expand at the interface of TGO and ceramic layer; when the extended crack size reaches the critical size, the stress in the thickness direction of the coating system causes the ceramic layer to cut off and peel off locally, causing the coating to fail. Therefore, the evaluation of the state of the TGO layer will become an effective means to predict the service life of TBC.

[0004] The patent with announcement number CN 102169531 A discloses a method for predicting the thermal fatigue life of a thermal barrier coating round tube, including step 1: establishing a thermal fatigue life model of the thermal barrier coating; step 2: determining the aluminum element concentration c in the bonding layer and the mechanical strain range Δε of the ceramic layer; step 3: predicting the thermal fatigue life; step 4: verifying the obtained thermal fatigue life prediction model of the thermal barrier coating. This method is based on the results of material performance testing under a simulated environment, and cannot achieve self-calibration and self-correction of the algorithm. The results obtained are not accurate enough. Summary of the invention

[0005] In view of the above-mentioned technical problems, the purpose of the present invention is to provide a method and equipment for calculating the service life of a thermal barrier coating, which adopts a customized method for detecting crack propagation failure of the thermal barrier coating to realize the initial calculation of the service life of the TBC coating; the thermal barrier coating non-destructive testing equipment is used to measure the crack distribution of the service components and the key parameters of the TGO layer. The measurement data can be used to verify and correct the thermal barrier coating life prediction algorithm and CFD boundary conditions, thereby improving the accuracy of the service life prediction of the thermal barrier coating and realizing the dynamic prediction of the thermal barrier coating life during the service life of the component.

[0006] In order to solve these problems in the prior art, the technical solution provided by the present invention is:

[0007] A method for calculating the life of a thermal barrier coating comprises the following steps:

[0008] S01: Obtain the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component;

[0009] S02: Obtaining a life prediction model for the thermal barrier coating based on the acquired user historical usage data, component structure information of the thermal barrier coating, and planned usage conditions of the component;

[0010] S03: Measurement of microstructural damage factor of thermal barrier coatings;

[0011] S04: Correcting the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the life of the thermal barrier coating.

[0012] In the preferred technical solution, the life prediction model in step S02 includes a TBC life prediction model based on the material dimension and a TBC life prediction model based on the component dimension; the TBC life prediction model A based on the material dimension is a fitting function obtained by fitting the material property m of the thermal barrier coating, the load condition l of the thermal barrier coating and the service time t of the thermal barrier coating, that is, A=f(m,l,t); the TBC life prediction model based on the component dimension adopts a statistical analysis method to obtain the probability distribution of the microstructure damage factor of the thermal barrier coating.

[0013] In the preferred technical solution, the component structure information of the thermal barrier coating and the planned use condition of the component are used to calculate and process the component as a whole using the computational fluid dynamics method to obtain the external load conditions at different positions of the component.

[0014] In a preferred technical solution, the microstructural damage factors of the thermal barrier coating include TGO layer thickness h, cracks at the TGO / TC interface c, and TGO / TC interface undulation ratio r.

[0015] In the preferred technical solution, in step S04, the linear regression method is used to obtain the fitting coefficient of the function when the variance is minimum through the measured data group as the corrected fitting coefficient.

[0016] The present invention also discloses a thermal barrier coating life calculation device, comprising:

[0017] Data acquisition module, which acquires the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component;

[0018] The life prediction module obtains the life prediction model of the thermal barrier coating based on the acquired user historical usage data, the component structure information of the thermal barrier coating, and the planned use conditions of the component;

[0019] Nondestructive testing module, measuring the microstructural damage factor of thermal barrier coatings;

[0020] The life prediction model correction module corrects the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating, obtains the corrected life prediction model, and obtains the life of the thermal barrier coating.

[0021] In the preferred technical scheme, the life prediction model in the life prediction module includes a TBC life prediction model based on the material dimension and a TBC life prediction model based on the component dimension; the TBC life prediction model A based on the material dimension is a fitting function obtained by fitting the material property m of the thermal barrier coating, the load condition l of the thermal barrier coating and the service time t of the thermal barrier coating, that is, A=f(m,l,t); The TBC life prediction model based on the component dimension uses a statistical analysis method to obtain the probability distribution of the microstructure damage factor of the thermal barrier coating.

[0022] In the preferred technical solution, the component structure information of the thermal barrier coating and the planned use condition of the component are used to calculate and process the component as a whole using the computational fluid dynamics method to obtain the external load conditions at different positions of the component.

[0023] In a preferred technical solution, the microstructural damage factors of the thermal barrier coating include TGO layer thickness h, cracks at the TGO / TC interface c, and TGO / TC interface undulation ratio r.

[0024] In a preferred technical solution, the life prediction model correction module uses a linear regression method through the measured data group to obtain the fitting coefficient of the function when the variance is minimum as the corrected fitting coefficient.

[0025] Compared with the solutions in the prior art, the advantages of the present invention are:

[0026] 1. The traditional thermal barrier coating life prediction method and thermal barrier coating damage nondestructive testing equipment are two independent research fields and modules. This method combines rapid thermal barrier coating detection means and accurate crack extension calculation, and uses measured data to verify and correct the failure calculation judgment model, providing a high-efficiency and high-precision gas turbine hot end component life prediction method for industrial sites, improving enterprise economic benefits and production efficiency. It can be applied to industrial applications.

[0027] 2. Most of the previous predictions of thermal barrier coating life are based on the results of material performance tests under simulated environments. The present invention uses a customized thermal barrier coating crack propagation failure detection method to achieve the initial calculation of the service life of the TBC coating; the thermal barrier coating non-destructive testing equipment is used to measure the crack distribution of the service component and the key parameters of the TGO layer. The measurement data can be used to verify and correct the thermal barrier coating life prediction algorithm and CFD boundary conditions, realize the self-calibration and self-correction of the algorithm, and greatly reduce the time and economic cost of thermal barrier coating life prediction in industrial processes. At the same time, the accuracy of the thermal barrier coating service life prediction is improved, and the dynamic prediction of the thermal barrier coating life during the service period of the component is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0029] Figure 1 This is a principle block diagram of the thermal barrier coating life calculation device of the present invention;

[0030] Figure 2 It is a processing schematic diagram of the thermal barrier coating life measurement device of the present invention;

[0031] Figure 3 It is the logic diagram of TBC life correction;

[0032] Figure 4 Schematic diagram of temperature distribution of turbine blades;

[0033] Figure 5 Schematic diagram of the stress distribution of turbine blades;

[0034] Figure 6 The figure is a flow chart of the method for calculating the life of thermal barrier coatings of the present invention. DETAILED DESCRIPTION

[0035] The above scheme is further described below in conjunction with specific examples. It should be understood that these examples are used to illustrate the present invention and are not limited to the scope of the present invention. The implementation conditions adopted in the examples can be further adjusted according to the conditions of the specific manufacturer, and the unspecified implementation conditions are usually the conditions in conventional experiments.

[0036] Example:

[0037] like Figure 1 As shown, a thermal barrier coating life estimation device comprises:

[0038] Data acquisition module, which acquires the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component;

[0039] The life prediction module obtains the life prediction model of the thermal barrier coating based on the acquired user historical usage data, the component structure information of the thermal barrier coating, and the planned use conditions of the component;

[0040] Nondestructive testing module, measuring the microstructural damage factor of thermal barrier coatings;

[0041] The life prediction model correction module corrects the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating, obtains the corrected life prediction model, and obtains the life of the thermal barrier coating.

[0042] like Figure 2 As shown, 1 is the input historical usage data, as well as the basic structure and composition of the component TBC;

[0043] 2 is the input component planned use condition;

[0044] 3 is the reliability standard required by the input customer;

[0045] 1, 2, and 3 constitute the input module for predicting TBC life;

[0046] 4 is a TBC coating life prediction module based on material dimension; its logic is as follows Figure 3 ;

[0047] 5 is the external load of the component under a certain service condition. Based on the component structure information in 1 and the component service condition input in 2, the computational fluid dynamics (CFD) method and structural finite element analysis method are used to pre-process, calculate and post-process the component as a whole. The purpose is to obtain the external load (temperature field, stress field distribution) at different positions of the component to reflect the service environment of the component, such as Figure 4 , 5, respectively characterizes the temperature distribution and stress distribution of the turbine blade (two views);

[0048] 6 is a specific model for TBC life prediction based on component dimension. For a specific position of a component, the life of its TBC is calculated using the method in 4, and the life of the component is determined by the minimum value of the life of all specific positions;

[0049] 1, 2, 3, 4, 5, and 6 together constitute a customized coating life prediction module;

[0050] 7 is a nondestructive testing module, which can collect the real geometric damage state of the TBC coating;

[0051] 8 is the TGO layer thickness h measured and collected during the nth shutdown maintenance. n , Crack at TGO / TC interface c n , TGO / TC interface fluctuation ratio r n,These data will not only be used for damage assessment of TBC coatings, but also to correct the computational model;

[0052] 9 is the output terminal of TBC life prediction result.

[0053] Figure 3 The logic for the continuous and accurate prediction of TBC life at the material level:

[0054] The microstructural parameters of TBC determine its lifespan. Figure 3 A represents the TBC microstructure damage factor, which includes the TGO layer thickness h, the crack at the TGO / TC interface c, and the TGO / TC interface undulation ratio r;

[0055] The conditions that affect the TBC microstructure damage factor mainly include the TBC material property m, the TBC load condition l (including mechanical load and thermal load), and the TBC service time t, that is: A = f(m, l, t).

[0056] Under specified conditions of use, m and l of a certain TBC are determined;

[0057] Whether TBC fails can be determined by determining whether A reaches its failure threshold value A. r , so let A=A r , the life span t of TBC can be solved;

[0058] The above is the logic of coating life prediction.

[0059] After the component has been in service for t1 time, the microstructure factor A of the TBC can be directly measured. Using the data set (t1, A1), the correlation coefficient of A=f(m,l,t) is corrected by functional regression to obtain A=f1(m,l,t), thereby enhancing its accuracy and fit.

[0060] Continue to let A = A r , the life t of the corrected TBC can be solved;

[0061] Therefore, every time the machine is shut down for maintenance, the measured data can be used to correct the calculation method of TBC life, thereby achieving dynamic prediction of TBC life.

[0062] The design and use method of the device of the present invention is as follows:

[0063] 1 Input the customer's usage history data, the planned use environment and conditions of the components, and the reliability standards required by the customer, complete the initial prediction of the TBC coating life through the crack propagation failure model of the thermal barrier coating, and output the life prediction report. The crack propagation failure model can be a detection method for crack propagation failure of thermal barrier coating and a crack propagation failure model in the system disclosed in application number 201911411832.1, and of course it can also be other crack propagation failure models.

[0064] The characteristic of this process is that it is different from the previous software that focuses on the universal prediction of material properties. This method is completely targeted at the needs of industrial processes and outputs corresponding predicted life reports based on the actual use environment and reliability control standards input by the customer. In addition, the input, calculation, and output modules are highly integrated into the customized GUI interface;

[0065] 2. Use TBC coating nondestructive testing equipment to regularly measure the TGO layer thickness h, cracks c at the TGO / TC interface, and TGO / TC interface fluctuation ratio r of the service parts. The results are not only used to characterize the TBC damage of the parts, but also used to verify and correct the TBC life prediction model. The characteristics of this method are that it can not only collect real coating information to evaluate the use status of the parts, but also use this data to correct potential deviations in the calculation module, and continuously improve the accuracy of the calculation module;

[0066] 3. Use the calibrated and corrected life prediction module to recalculate and output the service life of TBC. The characteristic of this process is that the life calculation model of TBC will be refined once with each acquisition of TGO microstructure, so the life of TBC coating can be predicted dynamically, that is, after completing TBC data collection during each shutdown and maintenance process, a more accurate prediction of TBC life can be given. At the same time, when the service conditions of the components change, this method can still predict the service life of TBC coating.

[0067] like Figure 6 As shown, the specific thermal barrier coating life calculation method includes the following steps:

[0068] S01: Obtain the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component;

[0069] S02: Obtaining a life prediction model for the thermal barrier coating based on the acquired user historical usage data, component structure information of the thermal barrier coating, and planned usage conditions of the component;

[0070] S03: Measurement of microstructural damage factor of thermal barrier coatings;

[0071] S04: Correcting the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the life of the thermal barrier coating.

[0072] In a preferred embodiment, the life prediction model in step S02 includes a TBC life prediction model based on the material dimension and a TBC life prediction model based on the component dimension; the TBC life prediction model A based on the material dimension is a fitting function obtained by fitting the material property m of the thermal barrier coating, the load condition l of the thermal barrier coating and the service time t of the thermal barrier coating, that is, A=f(m,l,t); the TBC life prediction model based on the component dimension uses a statistical analysis method to obtain the probability distribution of the microstructure damage factor of the thermal barrier coating.

[0073] In a preferred embodiment, the component structure information of the thermal barrier coating and the planned use condition of the component are used to calculate and process the component as a whole using a computational fluid dynamics method to obtain the external load conditions at different positions of the component.

[0074] In a preferred embodiment, the microstructure damage factors of the thermal barrier coating include the thickness of the TGO layer h, the cracks at the TGO / TC interface c, and the TGO / TC interface fluctuation ratio r.

[0075] In a preferred embodiment, in step S04, a linear regression method is used through the measured data set to obtain the fitting coefficient of the function when the variance is minimum as the corrected fitting coefficient.

[0076] Taking the hot end blades of a turbine gas turbine as an example, the implementation process of the technical solution is explained in detail.

[0077] Input data, which includes three types. The first is the customer's historical usage data, including the TBC coating information of the previously in-service blades, the service environment information, and the service life information. This information will be used as the database of the customized computing platform to provide data support for the computing platform and correct the corresponding computing model; the second is the original properties and structure information of the predicted TBC coating and the service environment information, which are the main data for calculating the life of the TBC coating; the third is the customer's reliability control standard, which is the customer's requirements for the accuracy and confidence interval of the calculation results.

[0078] The input TBC basic material properties and structural characteristics can establish a model relationship between TBC life and corresponding external loads. Combined with the input blade geometry data and operating conditions, the CFD method is used to calculate the external load conditions at each location of the component, thereby realizing the calculation of the life of any TBC position of the component. Using statistics and reliability principles, the TBC life of the component is predicted and a life prediction report is output;

[0079] h, r, and c are the characteristic indicators of TBC damage obtained in the process of calculating the life of thermal barrier coatings. When the gas turbine blades are regularly inspected and maintained, a rapid panoramic and accurate inspection can be performed to obtain data corresponding to the calculated h, r, and c. n 、r n 、c n ;

[0080] The prediction of TBC coating life is a computational prediction, and the data obtained through measurement can effectively verify and correct this computational prediction. Under certain working conditions, the life of TBC coating can be calculated based on h, r, and c. Now, taking the thickness of TGO layer h as an example, the specific algorithm logic is explained. For a thermal coating under given working conditions, the growth rate of its TGO thickness is As a function of m and l, the TGO thickness h is expressed as:

[0081] h=∫f(m,l)dt (1)

[0082] Where: m is the material performance parameter, l is the external load condition, and t is the service time.

[0083] Therefore, using the actual measured data h1, h2…h n Correction may include the following steps:

[0084] 1. Verify whether the TGO thickness calculated in formula (1) is consistent with the actual measurement;

[0085] 2. According to the measured input data set (t, h), the linear regression method is used to obtain the coefficient of the function when its variance is minimum, and the TGO thickness calculation model (1) is modified as follows:

[0086] h=∫f n (m,l)dt (2)

[0087] 3. For the thermal barrier coating of the workpiece as a whole, after serving for a certain period of time under a given working condition, the probability distribution of the TGO layer thickness actually conforms to:

[0088]

[0089] It is worth noting that formula (3) represents the distribution of TGO layer thickness under a specific service environment. The mean μ here is consistent with the h calculation method in (2). At a certain moment, the probability that the TGO layer thickness of the component is μ is the largest, and the accuracy of μ is determined by the accuracy of the initial algorithm. The greater the difference in load and service conditions at different positions of the component, the greater the degree of dispersion of h controlled by the variance σ.

[0090] Therefore, by judging the maximum probability thickness μ of the TGO layer at time t and the critical TGO thickness h r The 3σ criterion is usually used in industry, that is, when:

[0091] μ+3σ≥h r

[0092] The component is considered to have failed as a whole.

[0093] According to the actual measurement result of h at time t, formula (3) can also be corrected accordingly, namely:

[0094]

[0095] For the component level TBC life, h reaches the failure critical value h r The probability of is an important criterion for judging the life of TBC. Therefore, the continuous refinement of formula (1) and formula (3) realizes the precision of TBC life prediction from the perspective of material damage and component TBC damage distribution, respectively.

[0096] Moreover, the distribution of the corrected measurement results can in turn correct the boundary conditions of CFD. For example, if the discreteness of the measurement results is much greater than the discreteness of the calculated results, it means that the boundary conditions used in the CFD calculation are too small and should be enlarged.

[0097] Therefore, during the 1st, 2nd, ...nth shutdown and overhaul of the corresponding components, the 1st, 2nd, ...nth corrections to the TGO layer thickness calculation model and distribution model can be achieved. The crack c at the TGO / TC interface and the TGO / TC interface fluctuation ratio r, which are also microstructural factors, can also be fitted into the form of equations (1) and (3). Therefore, c and r are calculated according to the above-mentioned processing method for TGO thickness h, thereby achieving continuous and accurate prediction of TBC life;

[0098] Finally, the above process is applied according to the actual structure and specific working conditions of the components in engineering use to calculate the TBC coating life of the entire component.

[0099] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

Claims

1. A method for calculating the life of a thermal barrier coating, characterized in that: The following steps are involved: S01: Obtain the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component; S02: Obtaining a life prediction model for the thermal barrier coating based on the acquired user historical usage data, component structure information of the thermal barrier coating, and planned usage conditions of the component; S03: measuring the microstructure damage factor of the thermal barrier coating; the microstructure damage factor of the thermal barrier coating includes the thickness of the TGO layer h, the crack at the TGO / TC interface c, and the TGO / TC interface fluctuation ratio r; S04: Correcting the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the life of the thermal barrier coating; The life prediction model in step S02 includes a TBC life prediction model based on the material dimension and a TBC life prediction model based on the component dimension; the TBC life prediction model A based on the material dimension is based on the material properties of the thermal barrier coating. m , Loading conditions of thermal barrier coatings l and service life of thermal barrier coatings t The fitting function is obtained by fitting, that is, A=f ( m,l,t ); The TBC life prediction model based on component dimensions uses a statistical analysis method to obtain the probability distribution of the microstructural damage factor of the thermal barrier coating.

2. The thermal barrier coating life estimation method according to claim 1, characterized in that: Based on the structural information of the thermal barrier coating components and the planned operating conditions of the components, the computational fluid dynamics method is used to calculate and process the components as a whole to obtain the external load conditions at different positions of the components.

3. The thermal barrier coating life estimation method according to claim 1, characterized in that: In the step S04, the linear regression method is used to obtain the fitting coefficient of the function when the variance is minimum through the measured data group as the corrected fitting coefficient.

4. A thermal barrier coating life estimation device, characterized in that: include: Data acquisition module, which acquires the user's historical usage data, the component structure information of the thermal barrier coating, and the planned usage conditions of the component; The life prediction module obtains the life prediction model of the thermal barrier coating based on the acquired user historical usage data, the component structure information of the thermal barrier coating, and the planned use conditions of the component; A nondestructive testing module is used to measure the microstructure damage factor of the thermal barrier coating; the microstructure damage factor of the thermal barrier coating includes the thickness of the TGO layer h, the crack at the TGO / TC interface c, and the TGO / TC interface fluctuation ratio r; The life prediction model correction module corrects the fitting coefficient of the life prediction model by measuring the microstructure damage factor of the thermal barrier coating, obtains the corrected life prediction model, and obtains the life of the thermal barrier coating; The life prediction model in the life prediction module includes a TBC life prediction model based on the material dimension and a TBC life prediction model based on the component dimension; the TBC life prediction model A based on the material dimension is based on the material properties of the thermal barrier coating. m , Loading conditions of thermal barrier coatings l and service life of thermal barrier coatings t The fitting function is obtained by fitting, that is, A=f ( m,l, t ); The TBC life prediction model based on component dimensions uses a statistical analysis method to obtain the probability distribution of the microstructural damage factor of the thermal barrier coating.

5. The thermal barrier coating life estimation device according to claim 4, characterized in that: Based on the structural information of the thermal barrier coating components and the planned operating conditions of the components, the computational fluid dynamics method is used to calculate and process the components as a whole to obtain the external load conditions at different positions of the components.

6. The thermal barrier coating life estimation device according to claim 4, characterized in that: The life prediction model correction module uses a linear regression method through the measured data group to obtain the fitting coefficient of the function when the variance is minimum as the corrected fitting coefficient.

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