CN112765904A - Method and equipment for measuring and calculating service life of thermal barrier coating - Google Patents
Method and equipment for measuring and calculating service life of thermal barrier coating Download PDFInfo
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Abstract
The invention discloses a method for measuring and calculating the service life of a thermal barrier coating, which comprises the following steps: acquiring historical use data of a user, component structure information of a thermal barrier coating and a planned use condition of a component; obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component; measuring a microstructure damage factor of the thermal barrier coating; and correcting the fitting coefficient of the life prediction model through the measured microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the service life of the thermal barrier coating. The thermal barrier coating nondestructive testing equipment is adopted to measure the crack distribution and TGO layer key parameters of the service part, the measured data can be used for verifying and correcting the service life prediction algorithm and the CFD boundary condition of the thermal barrier coating, the service life prediction accuracy of the thermal barrier coating is improved, and the dynamic prediction of the service life of the thermal barrier coating in the service period of the part is realized.
Description
Technical Field
The invention belongs to the technical field of detection of thermal barrier coatings, and particularly relates to a method and equipment for measuring and calculating the service life of a thermal barrier coating.
Background
The hot end component of the industrial gas turbine not only bears high-temperature and high-pressure gas in a service environment, but also bears the actions of high heat flow input, high temperature gradient, stress gradient, centrifugal force and the like. Thermal Barrier Coating (TBC) can effectively extend the service life of hot end components. Therefore, predicting the failure time of the TBC can effectively realize the prediction of the service life of the hot end component of the gas turbine.
TBC systems are often constructed with an outermost ceramic layer (TC), a bond coat layer (BC), and an intervening Thermally Grown Oxide (TGO) layer that grows over time, the primary reason for failure of the TBC coating being that the TGO layer grows and thickens over time as service is extended and, under the effect of internal stresses in the thermal cycle, microcracks develop and propagate at the TGO and ceramic layer interface; when the size of the propagation crack reaches the critical size, the stress in the thickness direction of the coating system causes the ceramic layer to be cut off and locally peeled off, so that the coating fails. Therefore, the evaluation of the TGO layer state will become an effective means for predicting TBC service life.
The patent with the publication number of CN 102169531A discloses a method for predicting the thermal fatigue life of a thermal barrier coating round tube, which comprises the following steps: establishing a thermal fatigue life model of the thermal barrier coating; step two: determining the concentration c of aluminum elements in the bonding layer and the mechanical strain range delta epsilon of the ceramic layer; step three: prediction of thermal fatigue life; step four: and checking the obtained thermal fatigue life prediction model of the thermal barrier coating. The method is based on the result of material performance test in a simulation environment, and self-calibration and self-correction of the algorithm cannot be realized. The results obtained are not accurate enough.
Disclosure of Invention
Aiming at the technical problems, the invention aims to provide a method and equipment for measuring and calculating the service life of a thermal barrier coating, wherein the initial calculation of the service life of the TBC is realized by adopting a customized detection method for crack propagation failure of the thermal barrier coating; the thermal barrier coating nondestructive testing equipment is adopted to measure crack distribution and TGO layer key parameters of a service part, and the measured data can be used for verifying and correcting a thermal barrier coating service life prediction algorithm and CFD boundary conditions, so that the service life prediction accuracy of the thermal barrier coating is improved, and the dynamic prediction of the service life of the thermal barrier coating in the service period of the part is realized.
In order to solve the problems in the prior art, the technical scheme provided by the invention is as follows:
a method for measuring and calculating the service life of a thermal barrier coating comprises the following steps:
s01: acquiring historical use data of a user, component structure information of a thermal barrier coating and a planned use condition of a component;
s02: obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
s03: measuring a microstructure damage factor of the thermal barrier coating;
s04: and correcting the fitting coefficient of the life prediction model through the measured microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the service life of the thermal barrier coating.
In a preferred embodiment, the life prediction model in step S02 includes a TBC life prediction model based on a material dimension and a TBC life prediction model based on a component dimension; the TBC service 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, namely A is f (m, l, t); the probability distribution of the microstructure damage factors of the thermal barrier coating is obtained by the TBC life prediction model based on the component dimension by adopting a statistical analysis method.
In the preferred technical scheme, the overall part is calculated and processed by adopting a computational fluid dynamics method according to the structural information of the part of the thermal barrier coating and the planned use working condition of the part, so that the external load conditions of different positions of the part are obtained.
In a preferred technical scheme, the microstructure damage factors of the thermal barrier coating comprise TGO layer thickness h, cracks c at a TGO/TC interface and a TGO/TC interface fluctuation ratio r.
In a preferred embodiment, in step S04, a fitting coefficient of a function with the smallest variance is obtained as a modified fitting coefficient by using a linear regression method through the measured data set.
The invention also discloses a device for measuring and calculating the service life of the thermal barrier coating, which comprises:
the data acquisition module is used for acquiring historical use data of a user, component structure information of the thermal barrier coating and planned use working conditions of the component;
the service life prediction module is used for obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
the nondestructive testing module is used for measuring the microstructure damage factor of the thermal barrier coating;
and the service life prediction model correction module is used for correcting the fitting coefficient of the service life prediction model according to the measured microstructure damage factor of the thermal barrier coating to obtain a corrected service life prediction model and obtain the service life of the thermal barrier coating.
In a preferred technical solution, the life prediction model in the life prediction module includes a TBC life prediction model based on material dimensions and a TBC life prediction model based on component dimensions; the TBC service 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, namely A is f (m, l, t); the TBC service life prediction model based on component dimensions obtains the probability distribution of microstructure damage factors of the thermal barrier coating by adopting a statistical analysis method.
In the preferred technical scheme, the overall part is calculated and processed by adopting a computational fluid dynamics method according to the structural information of the part of the thermal barrier coating and the planned use working condition of the part, so that the external load conditions of different positions of the part are obtained.
In a preferred technical scheme, the microstructure damage factors of the thermal barrier coating comprise TGO layer thickness h, cracks c at a TGO/TC interface and a TGO/TC interface fluctuation ratio r.
In a preferred technical solution, the life prediction model correction module obtains a fitting coefficient of a function with a minimum variance as a corrected fitting coefficient by using a linear regression method through a measured data set.
Compared with the scheme in the prior art, the invention has the advantages that:
1. the traditional thermal barrier coating service life prediction method and the thermal barrier coating damage nondestructive testing device are two independent research fields and modules, the method performs rapid thermal barrier coating detection means and accurate crack extension calculation, utilizes measured data to perform verification and correction failure calculation judgment models, provides a high-efficiency and high-precision gas turbine hot-end component service life prediction method for an industrial field, and improves the economic benefit and the production efficiency of enterprises. Can be applied to industrial application.
2. The service life prediction of the prior thermal barrier coating is mostly based on the result of material performance test under a simulation environment, and the invention adopts a customized detection method of 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 nondestructive testing equipment is adopted to measure the crack distribution of the service part and the key parameters of the TGO layer, the measured data can be used for verifying and correcting the service life prediction algorithm of the thermal barrier coating and the CFD boundary conditions, the self-calibration and the self-correction of the algorithm are realized, and the time and the economic cost for predicting the service life of the thermal barrier coating in the industrial process are greatly reduced. Meanwhile, the service life prediction accuracy of the thermal barrier coating is improved, and the dynamic prediction of the service life of the thermal barrier coating during the service period of the component is realized.
Drawings
The invention is further described with reference to the following figures and examples:
FIG. 1 is a schematic block diagram of a thermal barrier coating life estimation apparatus of the present invention;
FIG. 2 is a schematic processing diagram of a thermal barrier coating life estimation apparatus of the present invention;
FIG. 3 is a TBC life correction logic diagram;
FIG. 4 is a schematic temperature distribution diagram of a turbine blade;
FIG. 5 is a schematic illustration of a stress distribution of a turbine blade;
FIG. 6 is a flowchart of a method for measuring and calculating the lifetime of a thermal barrier coating according to the present invention.
Detailed Description
The above-described scheme is further illustrated below with reference to specific examples. It should be understood that these examples are for illustrative purposes and are not intended to limit the scope of the present invention. The conditions used in the examples may be further adjusted according to the conditions of the particular manufacturer, and the conditions not specified are generally the conditions in routine experiments.
Example (b):
as shown in fig. 1, a thermal barrier coating life measuring device includes:
the data acquisition module is used for acquiring historical use data of a user, component structure information of the thermal barrier coating and planned use working conditions of the component;
the service life prediction module is used for obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
the nondestructive testing module is used for measuring the microstructure damage factor of the thermal barrier coating;
and the service life prediction model correction module is used for correcting the fitting coefficient of the service life prediction model according to the measured microstructure damage factor of the thermal barrier coating to obtain a corrected service life prediction model and obtain the service life of the thermal barrier coating.
As shown in fig. 2, 1 is the input historical usage data, as well as the basic structure and composition of the component TBC;
2, planning the use condition of the input component;
3, inputting a reliability standard required by a customer;
1. 2, 3 constitute an input module for predicting the service life of the TBC;
4, a TBC coating service life prediction module based on material dimension; the logic is as shown in FIG. 3;
5, performing pretreatment, calculation and post-treatment on the whole part by adopting a Computational Fluid Dynamics (CFD) method and a structural finite element analysis method according to the external load of the part under a certain use condition in the step 1 and the use condition of the part input in the step 2, so as to obtain the external load (temperature field and stress field distribution) conditions of different positions of the part, reflecting the service environment of the part, and respectively representing the temperature distribution and the stress distribution (two views) of the turbine blade as shown in fig. 4 and 5;
6 is a concrete model of TBC life prediction based on component dimension, for a specific position of a component, calculating the life of the TBC by using the method in 4, wherein the life of the component is determined by the minimum value of the lives of all the specific positions;
1, 2, 3, 4, 5, 6 together comprise a customized coating life prediction module;
7, a nondestructive testing module which can collect the real geometric damage state of the TBC coating;
8 is 7 TGO layer thickness h collected in the nth shutdown overhaul measurementnCracks at TGO/TC interface cnTGO/TC interface fluctuation ratio rnThese data will be used not only for damage assessment of the TBC coating, but also to modify the computational model;
and 9 is a TBC service life prediction result output end.
FIG. 3 is logic for continuous accurate prediction of TBC life at the material level:
the microstructure parameters of the TBC determine its lifetime, and A in FIG. 3 represents the TBC microstructure damage factors including the thickness h of the TGO layer, the cracks c at the TGO/TC interface, and the yield ratio r at the TGO/TC interface;
the conditions affecting the microstructure damage factor of the TBC mainly include the material property m of the TBC, the load condition l (including mechanical load and thermal load) of the TBC, the service time t of the TBC, that is: a ═ f (m, l, t).
Under the specified use condition, m and l of a certain TBC are determined;
whether the TBC fails or not can be judged by judging whether A reaches the failure critical value or notArTherefore, let A equal to ArThe service life t of the TBC can be solved;
the above is the logic for coating life prediction.
In service of component t1After time, the microstructure factor A of the TBC can be measured directly, using the data set (t)1,A1) The correlation coefficient of a ═ f (m, l, t) is corrected by means of functional regression, and a ═ f (m, l, t) is obtained1(m, l, t) to enhance accuracy and fitness.
Continue to make A ═ ArThe service life t of the TBC after correction can be solved;
therefore, the actual measurement data can be used for correcting the TBC service life calculation method every time of shutdown maintenance, and dynamic prediction of the TBC service life is achieved.
The design and use method of the device comprises the following steps:
1, inputting customer use historical data, planned use environment and conditions of a component and a reliability standard required by a customer, completing initial prediction of the service life of the TBC through a crack propagation failure model of the thermal barrier coating, and outputting a service life prediction report, wherein the crack propagation failure model can be a crack propagation failure detection method and a crack propagation failure model in a system for detecting the crack propagation failure of the thermal barrier coating disclosed by application number 201911411832.1, and can also be other crack propagation failure models.
The process is characterized in that different from the previous software focusing on material performance universality prediction, the method completely aims at the requirements of industrial processes, and corresponding predicted service life reports are output according to the real use environment input by a client and the reliability control standard. In addition, the input, calculation and output modules are highly integrated in a customized GUI interface;
2, using TBC coating nondestructive testing equipment to regularly measure the thickness h of a TGO layer of a service component, the cracks c at a TGO/TC interface and the fluctuation ratio r of the TGO/TC interface, wherein the result is used for representing the damage condition of the TBC of the component and verifying and correcting a TBC service life prediction model;
and 3, recalculating the service life of the TBC by using the service life prediction module after calibration and correction. The process is characterized in that a service life calculation model of the TBC can be accurately obtained once along with each acquisition of the TGO microstructure, so that the service life of the TBC coating can be dynamically predicted, namely, after TBC data acquisition is completed in each shutdown and overhaul process, more accurate prediction on the service life of the TBC can be given, and meanwhile, when the service condition of a component is changed, the service life of the TBC coating can still be predicted by the method.
As shown in fig. 6, the specific method for measuring the service life of a thermal barrier coating includes the following steps:
s01: acquiring historical use data of a user, component structure information of a thermal barrier coating and a planned use condition of a component;
s02: obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
s03: measuring a microstructure damage factor of the thermal barrier coating;
s04: and correcting the fitting coefficient of the life prediction model through the measured microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the service life of the thermal barrier coating.
In a preferred embodiment, the life prediction model in step S02 includes a TBC life prediction model based on material dimensions and a TBC life prediction model based on component dimensions; the TBC service 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, namely A is f (m, l, t); the probability distribution of the microstructure damage factors of the thermal barrier coating is obtained by the TBC life prediction model based on the component dimension by adopting a statistical analysis method.
In a preferred embodiment, the structural information of the component of the thermal barrier coating and the planned using working conditions of the component are used for calculating and processing the whole component by adopting a computational fluid dynamics method to obtain the external load conditions of different positions of the component.
In a preferred embodiment, 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.
In a preferred embodiment, the fitting coefficient of the function with the minimum variance is obtained as the modified fitting coefficient by using a linear regression method through the measured data set in step S04.
Taking a hot-end blade of a turbine gas turbine as an example, the implementation flow of the technical scheme is specifically explained.
The input data comprises three types, one is customer historical use data, and comprises previous service blade TBC coating information, service environment information, service life information and the like. The information is used as a database of a customized computing platform, so that the computing platform provides data support and modifies a corresponding computing model; secondly, the original property and structure information of the predicted TBC coating and service environment information are main data for calculating the service life of the TBC coating; and the third is the customer reliability control standard, which is the customer's requirement for the accuracy and confidence interval of the calculated result.
The input basic material attribute and structural feature of the TBC can establish a model relation between the service life of the TBC and the corresponding external load, and the external load condition of each part of the component is calculated by combining the input geometric configuration data of the blade and the use working condition through a CFD (computational fluid dynamics) method, so that the service life of any TBC position of the component is calculated, the service life of the TBC of the component is predicted by using a statistical and reliability principle, and a service life prediction report is output;
h. r and c are marked indexes of TBC damage obtained in the process of calculating the service life of the thermal barrier coating, when the gas turbine blade is periodically overhauled and maintained, the gas turbine blade is rapidly and panorama-type accurately detected, and data h corresponding to the calculated h, r and c can be obtained through measurementn、rn、cn；
Prediction of TBC coating life is a computational predictorBy measuring the acquired data, effective verification and correction of such calculated predictions can be achieved. Under a certain working condition, the service life of the TBC coating can be calculated according to h, r and c, the thickness h of the TGO layer is taken as an example to illustrate the specific algorithm logic, and for a thermal coating under a given working condition, the growth rate of the TGO thickness is
Expressed as a function of m, l, there is a TGO thickness h expressed as:
h＝∫f(m,l)dt (1)
wherein: m is a material performance parameter, l is an external load condition, and t is service time.
Thus, the actually measured data h is used1，h2…hnThe correction can comprise the following steps:
1. verifying whether the TGO thickness calculated in equation (1) meets the actual measurement;
2. according to the data set (t, h) of the measurement input, a linear regression method is used for obtaining the coefficient of the function when the variance is minimum, and the formula of a corrected TGO thickness calculation model (1) is as follows:
h＝∫fn(m,l)dt (2)
3. for the thermal barrier coating of the whole workpiece, after the thermal barrier coating is in service for a certain time under a given working condition, the thickness probability distribution of the TGO layer of the thermal barrier coating actually accords with the following conditions:
it is noted that equation (3) represents the distribution of TGO layer thickness in a particular service environment. The mean value μ here corresponds to the calculation method of h in (2). At some point, the probability of the TGO layer thickness of the part being μ is greatest, and the accuracy of μ is determined by the accuracy of the initial algorithm. The larger the difference of the load and the service condition of different positions of the component is, the larger the dispersion degree h controlled by the variance sigma is.
Therefore, the maximum probability thickness mu and the critical TGO thickness h of the TGO layer at the time t are determinedrIn the context of (a) or (b),the 3 σ criterion is commonly used in the industry when:
μ+3σ≥hr
the component is considered to fail as a whole.
The corresponding correction can also be made according to the actual measurement result at time t, i.e. equation (3), i.e.:
for TBC life at component level, h reaches a failure threshold hrThe probability of (3) is an important criterion for judging the service life of the TBC, therefore, the continuous accuracy of the formula (1) and the formula (3) realizes the accuracy of TBC service life prediction from the aspects of material damage and component TBC damage distribution respectively.
Moreover, the distribution of the measurement results after correction may be used to correct the boundary condition of the CFD in turn, for example, if the dispersion degree of the measurement results is much larger than the dispersion degree of the calculation results, it indicates that the boundary condition used in the CFD calculation is too small and should be enlarged.
Therefore, the 1 st, 2 nd and … nd times of correction of the TGO layer thickness calculation model and the distribution model can be realized in the 1 st, 2 nd and … th shutdown and overhaul processes of the corresponding parts. The cracks c at the TGO/TC interface and the fluctuation ratio r of the TGO/TC interface which are also used as the microstructure factors can be fit into the forms of the formula (1) and the formula (3), so that the c and the r are calculated according to the processing method for the TGO thickness h, and the continuous and accurate prediction of the service life of the TBC is realized;
and finally, according to the actual structure and the specific working condition of the component in engineering use, applying the process and calculating the service life of the TBC coating of the whole component.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention shall be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. A method for measuring and calculating the service life of a thermal barrier coating is characterized by comprising the following steps:
s01: acquiring historical use data of a user, component structure information of a thermal barrier coating and a planned use condition of a component;
s02: obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
s03: measuring a microstructure damage factor of the thermal barrier coating;
s04: and correcting the fitting coefficient of the life prediction model through the measured microstructure damage factor of the thermal barrier coating to obtain a corrected life prediction model and obtain the service life of the thermal barrier coating.
2. The thermal barrier coating life evaluation method of claim 1, wherein the life prediction model in step S02 comprises a TBC life prediction model based on material dimensions and a TBC life prediction model based on component dimensions; the TBC life prediction model A based on the material dimension uses the material property of the thermal barrier coatingmLoad condition of thermal barrier coatinglAnd service time of thermal barrier coatingtFitting a resulting fitting function, i.e.A=f(m,l,t) (ii) a The probability distribution of the microstructure damage factors of the thermal barrier coating is obtained by the TBC life prediction model based on the component dimension by adopting a statistical analysis method.
3. The method for measuring and calculating the service life of the thermal barrier coating according to claim 2, wherein the external load conditions of different positions of the component are obtained by calculating and processing the whole component by adopting a computational fluid dynamics method according to the structural information of the component of the thermal barrier coating and the planned using working conditions of the component.
4. The thermal barrier coating life evaluation method of claim 1, wherein the microstructural damage factors of the thermal barrier coating comprise TGO layer thickness h, cracks c at TGO/TC interface, and TGO/TC interface undulation ratio r.
5. The method for measuring and calculating the lifetime of a thermal barrier coating according to claim 1, wherein the fitting coefficient of the function with the minimum variance is obtained as the modified fitting coefficient by using a linear regression method through the measured data set in step S04.
6. A thermal barrier coating life gauging apparatus, comprising:
the data acquisition module is used for acquiring historical use data of a user, component structure information of the thermal barrier coating and planned use working conditions of the component;
the service life prediction module is used for obtaining a service life prediction model of the thermal barrier coating according to the obtained historical use data of the user, the component structure information of the thermal barrier coating and the planned use working condition of the component;
the nondestructive testing module is used for measuring the microstructure damage factor of the thermal barrier coating;
and the service life prediction model correction module is used for correcting the fitting coefficient of the service life prediction model according to the measured microstructure damage factor of the thermal barrier coating to obtain a corrected service life prediction model and obtain the service life of the thermal barrier coating.
7. The thermal barrier coating life gauging apparatus according to claim 6, wherein the life prediction model in said life prediction module comprises a TBC life prediction model based in material dimensions and a TBC life prediction model based in component dimensions; the TBC life prediction model A based on the material dimension uses the material property of the thermal barrier coatingmLoad condition of thermal barrier coatinglAnd service time of thermal barrier coatingtFitting a resulting fitting function, i.e.A=f(m,l,t) (ii) a The probability distribution of the microstructure damage factors of the thermal barrier coating is obtained by the TBC life prediction model based on the component dimension by adopting a statistical analysis method.
8. The thermal barrier coating life measuring and calculating equipment as claimed in claim 7, wherein the external load conditions of different positions of the component are obtained by calculating and processing the whole component by adopting a computational fluid dynamics method according to the component structure information of the thermal barrier coating and the planned use condition of the component.
9. The thermal barrier coating life evaluation device of claim 6, wherein the microstructure damage factor of the thermal barrier coating comprises TGO layer thickness h, crack at TGO/TC interface c, TGO/TC interface undulation ratio r.
10. The thermal barrier coating life estimation device according to claim 6, wherein the life prediction model correction module obtains a fitting coefficient of a function with minimum variance as a corrected fitting coefficient by using a linear regression method through the measured data set.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113850022A (en) * | 2021-09-26 | 2021-12-28 | 中国人民解放军陆军装甲兵学院 | Spraying layer contact fatigue life prediction method based on acoustic-thermal signals |
| CN116825243A (en) * | 2023-05-09 | 2023-09-29 | 安徽工程大学 | Multi-source data-based thermal barrier coating service life prediction method and system |
| CN117195743A (en) * | 2023-10-16 | 2023-12-08 | 西安交通大学 | Spraying parameter optimization method for crack structure of thermal barrier coating |
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2020
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113850022A (en) * | 2021-09-26 | 2021-12-28 | 中国人民解放军陆军装甲兵学院 | Spraying layer contact fatigue life prediction method based on acoustic-thermal signals |
| CN113850022B (en) * | 2021-09-26 | 2024-05-28 | 中国人民解放军陆军装甲兵学院 | Spray coating contact fatigue life prediction method based on acoustic-thermal signals |
| CN116825243A (en) * | 2023-05-09 | 2023-09-29 | 安徽工程大学 | Multi-source data-based thermal barrier coating service life prediction method and system |
| CN116825243B (en) * | 2023-05-09 | 2024-01-16 | 安徽工程大学 | Multi-source data-based thermal barrier coating service life prediction method and system |
| CN117195743A (en) * | 2023-10-16 | 2023-12-08 | 西安交通大学 | Spraying parameter optimization method for crack structure of thermal barrier coating |
| CN117195743B (en) * | 2023-10-16 | 2024-06-04 | 西安交通大学 | Spraying parameter optimization method for crack structure of thermal barrier coating |
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