Online monitoring method for service life of thermal barrier coating of thermal component of gas turbine

Abstract

The invention relates to the technical field of thermal barrier coatings, in particular to an online monitoring method for the service life of a thermal barrier coating of a thermal component of a gas turbine. Comprising the following steps: S1, constructing a thermal barrier coating service life monitoring model; s2, determining parameters in the thermal barrier coating service life monitoring model; s3, constructing a three-dimensional model of the gas turbine hot component with the thermal barrier coating; s4, stress-strain fields of the thermal barrier coating under different working conditions are calculated; s5, obtaining a working temperature, a positive strain range and a shear strain range; s6, the parameters determined in the step S2 and the working temperature, the positive strain range and the shear strain range determined in the step S5 are substituted into the thermal barrier coating life monitoring model in the step S1, the fatigue life of the thermal barrier coating under various load working conditions is obtained, total accumulated damage is calculated, and whether the thermal barrier coating fails or not is judged according to the total accumulated damage; and the method is suitable for predicting the service life of the thermal barrier coating at the edge of the thermal component structure of the gas turbine.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal barrier coatings, and particularly to an on-line monitoring method for the life of thermal barrier coatings on hot components of gas turbines. Background Art

[0002] A thermal barrier coating is a ceramic coating deposited on the surface of a high-temperature resistant metal or superalloy. The thermal barrier coating plays a role in heat insulation for the substrate material, reducing the substrate temperature, enabling the devices made of it to operate at high temperatures, and improving the thermal efficiency of the devices. It is widely used in hot components of gas turbines. Due to the harsh working environment of the thermal barrier coating, it has to bear high-temperature loads and simultaneously undergo frequent heating-cooling thermal cycles. In view of the requirements of high reliability and long life for heavy-duty gas turbines, the evaluation and prediction of the service life of thermal barrier coatings have become one of the hot research issues.

[0003] The prior art CN113704915B discloses a method for predicting the thermal fatigue life of thermal barrier coatings on heavy-duty gas turbine turbine blades, including the steps: Step 1: Establish a prediction model for the thermal fatigue life of thermal barrier coatings on heavy-duty gas turbine turbine blades; Step 2: Compare and check the prediction results of the thermal fatigue life of the turbine blade thermal barrier coating with the test results; Step 3: Evaluate the consumption of the thermal fatigue life of the thermal barrier coating on the heavy-duty gas turbine turbine blade. However, the thermal barrier coating fatigue life prediction model constructed in the above method does not consider the influence of coating failure caused by the growth of TGO and the influence of structural edge effects on coating failure. Therefore, the prediction of the thermal fatigue life of the thermal barrier coating in the above method is not accurate enough and is not applicable to the prediction of the life of thermal barrier coatings at the structural edges of gas turbine hot components.

[0004] Therefore, there is an urgent need to provide an on-line monitoring method for the life of thermal barrier coatings on hot components of gas turbines. Compared with the prior art, it improves the accuracy of predicting the life of thermal barrier coatings and is applicable to the prediction of the life of thermal barrier coatings at the structural edges of gas turbine hot components. Summary of the Invention

[0005] The present invention solves the technical problems existing in the prior art, and provides an on-line monitoring method for the life of thermal barrier coatings on hot components of gas turbines.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] An on-line monitoring method for the life of thermal barrier coatings on hot components of gas turbines, comprising the following steps:

[0008] S1. Based on the TGO growth model and the structural edge effect model, construct a thermal barrier coating life monitoring model, expressed as:

[0009]

[0010] In the above formula, N f represents the fatigue life of the thermal barrier coating. C1, C2, C3, A1, and α all represent constants. Q represents the activation energy. R represents the thermodynamic constant. T represents the working temperature. e represents the natural logarithm. Δε r represents the positive strain range. Δγ represents the shear strain range. m represents the exponential constant. t c represents the holding time;

[0011] S2. Determine the values of C1, C2, C3, A1, Q, m, and α in the thermal barrier coating life monitoring model;

[0012] S3. Construct a three-dimensional model of the hot components of the gas turbine with the thermal barrier coating;

[0013] S4. Based on the three-dimensional model of the hot components of the gas turbine constructed in step S3, calculate the stress and strain fields of the thermal barrier coating under different working conditions;

[0014] S5. Establish reduced-order equations for the overall actual operating parameters of the gas turbine, the temperature field of the thermal barrier coating, and the strain field of the thermal barrier coating through a deep learning algorithm; obtain the overall actual operating parameters of the gas turbine through sensors, and determine the working temperature, positive strain range, and shear strain range of the coating according to the overall actual operating parameters of the gas turbine, the reduced-order equations of the temperature field of the thermal barrier coating, and the reduced-order equations of the strain field of the thermal barrier coating;

[0015] S6. Substitute the C1, C2, C3, A1, Q, m, and α determined in step S2, and the working temperature, positive strain range, and shear strain range determined in step S5 into the thermal barrier coating life monitoring model in step S1 to obtain the fatigue life of the thermal barrier coating under various load conditions, thereby calculating the total cumulative damage, and judging whether the thermal barrier coating fails according to the total cumulative damage.

[0016] Furthermore, the total cumulative damage in step S6 is calculated according to the following formula:

[0017]

[0018] In the above formula, D represents the total cumulative damage, N fm represents the fatigue life of the thermal barrier coating under the m-th load condition, n m represents the number of cycles under the m-th condition, and E represents the total number of load conditions.

[0019] Even further, the specific method for judging whether the thermal barrier coating fails according to the total cumulative damage is: when D≥1, it means the thermal barrier coating fails; when D<1, it means the thermal barrier coating does not fail.

[0020] Furthermore, S1 specifically includes the following steps:

[0021] S11. Based on the Manson - Coffin model, construct an initial thermal barrier coating life monitoring model, expressed as:

[0022] N f = C1(δ + C2Δε) m ;

[0023] In the above formula, δ represents the critical failure thickness of TGO;

[0024] S12. Construct a TGO growth model, expressed as:

[0025]

[0026] In the above formula, t represents the total operating duration;

[0027] S13. Construct a structural edge effect model, expressed as:

[0028]

[0029] S14. Substitute the TGO growth model constructed in step S12 and the structural edge effect model constructed in step S13 into the initial thermal barrier coating life monitoring model constructed in step S11 to obtain the thermal barrier coating life monitoring model.

[0030] Furthermore, S2 specifically includes the following steps:

[0031] S21. Set up thermal barrier coating specimens, conduct static oxidation tests at multiple different temperatures. During the static oxidation test at each temperature, weigh at different times. According to the relationship between the TGO thickness and mass, obtain the TGO thickness at each moment. Then, obtain the corresponding relationship between the total duration and the critical failure thickness of TGO at each temperature. Combining with the TGO growth model, obtain the values of C3, A1, and Q;

[0032] S22. For the thermal barrier coating specimens, conduct cyclic oxidation tests at multiple different temperatures and different cycle durations. Use three - dimensional non - contact full - field strain measurement technology to obtain the coating strain ranges of the thermal barrier coating specimens under multiple different high - temperature environments and different cycle durations. Combining with the TGO growth model, obtain the values of C1, C2, and m;

[0033] S23. Set up tubular specimens, coat thermal barrier coatings on the outer surface of the tubular specimens, conduct heat - resistant cycle tests. Respectively measure the normal strain range and shear strain range of the thermal barrier coating through a three - dimensional non - contact full - field strain gauge. According to the structural edge effect model and the initial thermal barrier coating life monitoring model, fit out α.

[0034] Further, the three-dimensional model of the hot components of the gas turbine constructed in step S3 includes a hot component matrix, an adhesive layer, and a thermal barrier coating. The adhesive layer is disposed outside the hot component matrix, and the thermal barrier coating is disposed outside the adhesive layer.

[0035] Furthermore, the hot component matrix includes a turbine blade, a combustion chamber liner, and a retaining ring.

[0036] Further, step S4 specifically includes the following steps:

[0037] S41. Perform structured grid division on the three-dimensional model of the hot components of the gas turbine;

[0038] S42. Assign material property parameters to the hot component matrix, the bonding layer, and the thermal barrier coating respectively;

[0039] S43. Adopt the fluid-thermal-solid coupling technology to obtain the temperature field distributions of the hot component matrix, the bonding layer, and the thermal barrier coating under different working conditions;

[0040] S44. Perform strain calculation on the thermal barrier coating by using the non-linear stress-strain technology, in which a viscoplastic constitutive model is introduced into the deformation characteristics of the thermal barrier coating, and the normal strain range and shear strain range of the thermal barrier coating corresponding to a set range at the edge of the hot component matrix are obtained through the non-linear stress-strain analysis technology.

[0041] Furthermore, the viscoplastic constitutive model introduced in step S44 is expressed as:

[0042]

[0043] In the above formula, Ω represents the flow potential function of the viscoplastic constitutive model of the ceramic material of the thermal barrier coating, K, H, n, h, and μ all represent material constants, F represents the yield criterion of the three-parameter Willam-Warnke model, G represents the recovery function, represents the inelastic strain rate tensor, c0, c1, c2, c3, c4, c5, and c6 all represent constants, δ ij represents the Kronecker function, S ij 、S qi 、S iq represents the deviatoric stress component, a ij 、a qi 、a iq all represent the internal variables of the material non-linear kinematic hardening, J2δ ij represents the stress invariant.

[0044] Further, in step S5, the real-time overall parameters of the actual operation of the gas turbine are obtained through sensors, including the gas flow rate at the turbine inlet, the average total temperature at the compressor outlet, the average total gas temperature at the turbine inlet, the average gas temperature at the turbine outlet, the temperature at the turbine cold air inlet, and the engine speed.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0046] Taking into account the coating failure caused by TGO growth and the influence of the structural edge effect on coating failure, the present invention is applicable to the prediction of the coating life at the structural edge of the hot components of a gas turbine, improving the accuracy of the coating life prediction at the structural edge of the hot components of a gas turbine. Description of the Drawings

[0047] Figure 1 is the flow chart of the present invention.

[0048] Figure 2 is the comparison chart of the coating life calculated by the present invention, the actual value, and the coating life calculated by the existing method. Detailed Embodiments

[0049] The technical solution of the present invention will be clearly described below in conjunction with the description of the drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0050] As Figure 1 shown, the present invention provides an on-line monitoring method for the thermal barrier coating life of the hot components of a gas turbine, including the following steps:

[0051] S1. Based on the TGO growth model and the structural edge effect model, construct a thermal barrier coating life monitoring model, which specifically includes the following steps:

[0052] S11. Based on the Manson-Coffin model, construct an initial thermal barrier coating life monitoring model, and the initial thermal barrier coating life monitoring model is expressed by the following formula:

[0053] N f = C1(δ + C2Δε) m ;

[0054] In the above formula, N f represents the fatigue life of the thermal barrier coating, C1 and C2 represent constants, δ represents the critical failure thickness of TGO, Δε represents the strain range, and m represents the exponential constant.

[0055] S12. Construct a TGO growth model, and the TGO growth model is expressed by the following formula:

[0056]

[0057] In the above formula, C3 and A1 represent constants, Q represents the activation energy, R represents the thermodynamic constant, T represents the working temperature, e represents the natural logarithm, and t represents the total operating duration.

[0058] S13. Construct a structural edge effect model, which is expressed by the following formula:

[0059]

[0060] In the above formula, Δε r represents the range of normal strain, Δγ represents the range of shear strain, and α represents a constant.

[0061] S14. Substitute the TGO growth model constructed in step S12 and the structural edge effect model constructed in step S13 into the initial thermal barrier coating life monitoring model constructed in step S11 to obtain a thermal barrier coating life monitoring model, which is expressed by the following formula:

[0062]

[0063] t = N f ×t c ;

[0064] In the above formula, t c represents the holding time.

[0065] S2. Determine the parameters in the thermal barrier coating life monitoring model, specifically determine C1, C2, C3, A1, Q, m, α. The specific steps are as follows:

[0066] S21. Set up thermal barrier coating specimens. For the thermal barrier coating specimens, conduct static oxidation tests in multiple different high-temperature environments, and weigh the thermal barrier coating specimens during the tests to determine C3, A1, Q; the specific method is as follows:

[0067] Set multiple different temperatures, conduct static oxidation tests at each temperature, and weigh at different times, record the mass at each time, obtain the TGO thickness at each time according to the relationship between the TGO thickness and the mass, and then obtain the corresponding relationship between the total duration and the TGO thickness at each temperature; according to the corresponding relationship between the total duration and the TGO thickness at different temperatures and the TGO growth model, fit to obtain the values of C3, A1, Q.

[0068] S22. For the thermal barrier coating specimens, conduct cyclic oxidation tests in multiple different high-temperature environments and different cycle durations, and use three-dimensional non-contact full-field strain measurement technology to obtain the coating strain ranges of the thermal barrier coating specimens in multiple different high-temperature environments and different cycle durations, so as to determine C1, C2, m, and the specific method is as follows:

[0069] Conduct cyclic oxidation tests at a certain temperature, and record N f, three-dimensional non-contact full-field strain measurement technology is also carried out to obtain Δε. According to the initial thermal barrier coating life monitoring model and the TGO growth model, δ is calculated, and then C1, C2, and m at this temperature are obtained by fitting. Cyclic oxidation tests and three-dimensional non-contact full-field strain measurement technology are carried out at multiple different temperatures to obtain C1, C2, and m corresponding to different temperatures.

[0070] S23. Set up a tubular specimen. Coat the outer surface of the tubular specimen with a thermal barrier coating and carry out a heat resistance cycle test. Use three-dimensional non-contact full-field strain measurement technology to obtain the coating strain of the tubular specimen, so as to correct α.

[0071] The outer surface of the tubular test is coated with a thermal barrier coating. A heat resistance cycle test is carried out, and the number of cycles and temperature range are recorded. The normal strain range Δε r and shear strain range Δγ of the thermal barrier coating are measured respectively by a three-dimensional non-contact full-field strain gauge. According to the structural edge effect model and the initial thermal barrier coating life monitoring model; finally, α is obtained by fitting.

[0072] S3. Construct a three-dimensional model of a gas turbine hot component with a thermal barrier coating, including a hot component matrix, a bond coat, and a thermal barrier coating. The bond coat is arranged outside the hot component matrix, and the thermal barrier coating is arranged outside the bond coat. The hot component matrix includes a combustion chamber liner, a turbine rotor blade, a turbine stator blade, a high-temperature retaining ring, etc.; the bond coat is made of a metal matrix material with a thickness of 0.1-0.2 mm, and the thermal barrier coating is made of a ceramic matrix material with a thickness of 0.3-0.5 mm.

[0073] S4. Based on the three-dimensional model of the gas turbine hot component constructed in step S3, use nonlinear finite element technology to calculate the stress and strain fields of the thermal barrier coating under different working conditions. The specific steps are as follows:

[0074] S41. Carry out structured mesh division on the three-dimensional model of the gas turbine hot component.

[0075] S42. Assign material property parameters to the hot component matrix, bond coat, and thermal barrier coating in the three-dimensional model of the gas turbine hot component. The material property parameters include elastic modulus, Poisson's ratio, shear modulus, coefficient of linear expansion, density, and thermal conductivity.

[0076] S43. Adopt fluid-thermal-solid coupling technology to obtain the temperature field distributions of the hot component matrix, bond coat, and thermal barrier coating under different working conditions. There will be a thermal stress only when there is a temperature distribution gradient in the temperature field distribution obtained in this step.

[0077] S44. The strain of the thermal barrier coating is calculated using the non-linear stress-strain technique, in which a viscoplastic constitutive model is introduced into the deformation characteristics of the thermal barrier coating. Since the viscoplastic constitutive model reflects the mechanical behavior of the material, the normal strain range Δε of the thermal barrier coating corresponding to a set range at the edge of the hot component matrix is obtained through the non-linear stress-strain analysis technique. r and the shear strain range Δγ; the viscoplastic constitutive model is specifically expressed by the following formula:

[0078]

[0079] In the above formula, Ω represents the flow potential function of the viscoplastic constitutive model of the ceramic material of the thermal barrier coating, K, H, n, h, and μ all represent material constants, F represents the yield criterion of the three-parameter Willam-Warnke model, G represents the recovery function, represents the inelastic strain rate tensor, c0, c1, c2, c3, c4, c5, c6 all represent constants, δ ij represents the Kronecker function, S ij 、S qi 、S iq represent the deviatoric stress components, a ij 、a qi 、a iq all represent the internal variables of the material's non-linear kinematic hardening, J2δ ij represents the stress invariant.

[0080] S5. Establish the reduced-order equations for the overall actual operating parameters of the gas turbine, the temperature field of the thermal barrier coating, and the strain field of the thermal barrier coating. Obtain the overall actual operating parameters of the gas turbine through sensors, and determine the working temperature, normal strain range, and shear strain range of the coating through the reduced-order equations for the overall actual operating parameters of the gas turbine, the temperature field of the thermal barrier coating, and the strain field of the thermal barrier coating; the overall actual operating parameters of the gas turbine include the gas flow rate at the turbine inlet, the average total temperature at the compressor outlet, the average total gas temperature at the turbine inlet, the average gas temperature at the turbine outlet, the temperature at the turbine cold air inlet, and the gas turbine speed.

[0081] The specific content of step S5 refers to the content in the application publication number CN118013814A.

[0082] S6. According to C1, C2, C3, A1, Q, m, α determined in step S2, and the working temperature, normal strain range Δε r 、shear strain range Δγ of the thermal barrier coating determined in step S5, substitute them into the thermal barrier coating life monitoring model constructed in step S1 to obtain the fatigue life of the thermal barrier coating under various load conditions, thereby calculating the total cumulative damage, and judging whether the thermal barrier coating fails according to the total cumulative damage.

[0083] The total cumulative damage is calculated by the following formula:

[0084]

[0085] In the above formula, D represents the total cumulative damage, and N fm represents the thermal barrier coating fatigue life under the m-th load condition, and n m represents the number of cycles under the m-th condition, and E represents the total number of load conditions.

[0086] The specific method for judging whether the thermal barrier coating fails according to the total cumulative damage is as follows: when D≥1, it indicates that the thermal barrier coating fails; when D<1, it indicates that the thermal barrier coating does not fail.

[0087] As Figure 2 It can be seen that the prediction effect of the present invention on the coating life at the edge of the hot component structure of the gas turbine is about three times greater than that of the existing method. Therefore, considering the coating failure caused by the growth of TGO and the influence of the edge effect of the structure on the coating failure, the present invention is applicable to the prediction of the coating life at the edge of the hot component structure of the gas turbine, and improves the prediction accuracy of the coating life at the edge of the hot component structure of the gas turbine.

[0088] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than a limitation on the protection scope of the present invention. Any simple modification or equivalent replacement of the technical solution of the present invention by those of ordinary skill in the art does not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for online monitoring of thermal barrier coating life of hot parts of a gas turbine, characterized in that: The following steps are involved: S1. Based on the TGO growth model and the structural edge effect model, a thermal barrier coating life monitoring model is constructed, which is expressed as: In the above formula, N f represents the fatigue life of thermal barrier coating, C1, C2, C3, A1, α are all constants, Q represents activation energy, R represents thermodynamic constant, T represents working temperature, e represents natural logarithm, Δε r represents the normal strain range, Δγ represents the shear strain range, m represents the exponential constant, and t c Indicates the holding time; S2. Determine the values ​​of C1, C2, C3, A1, Q, m, and α in the thermal barrier coating life monitoring model; S3, constructing a three-dimensional model of a gas turbine hot component with a thermal barrier coating; S4, based on the three-dimensional model of the gas turbine hot parts constructed in step S3, calculating the stress-strain field of the thermal barrier coating under different working conditions; S5. Establish the overall parameters of the actual operation of the gas turbine, the reduced-order equations of the temperature field of the thermal barrier coating, and the reduced-order equations of the strain field through deep learning algorithms; The actual overall operating parameters of the gas turbine are obtained through sensors, and the operating temperature, normal strain range, and shear strain range of the coating are determined based on the actual overall operating parameters of the gas turbine, the reduced-order equation of the temperature field of the thermal barrier coating, and the reduced-order equation of the strain field; S6. Bring C1, C2, C3, A1, Q, m, α determined in step S2, and the operating temperature, normal strain range, and shear strain range determined in step S5 into the thermal barrier coating life monitoring model in step S1 to obtain the fatigue life of the thermal barrier coating under various load conditions, thereby calculating the total cumulative damage and judging whether the thermal barrier coating has failed based on the total cumulative damage.

2. The method for online monitoring of thermal barrier coating life of hot parts of a gas turbine according to claim 1, characterized in that: The total accumulated damage in step S6 is calculated according to the following formula: In the above formula, D represents the total cumulative damage, N fm represents the fatigue life of the thermal barrier coating under the mth load condition, n m represents the number of cycles under the mth load condition, and E represents the total number of load conditions.

3. The method for online monitoring the life of thermal barrier coatings of hot parts of a gas turbine according to claim 2, characterized in that: The specific method for judging whether the thermal barrier coating has failed based on the total cumulative damage is: when D ≥ 1, it means that the thermal barrier coating has failed; when D < 1, it means that the thermal barrier coating has not failed.

4. The method for online monitoring of thermal barrier coating life of hot parts of a gas turbine according to claim 1, characterized in that: S1 specifically includes the following steps: S11. Based on the Manson-Coffin model, the initial thermal barrier coating life monitoring model is constructed, which is expressed as: N f =C1(δ+C2δε) m ; In the above formula, δ represents the critical failure thickness of TGO; S12. Construct a TGO growth model, expressed as: In the above formula, t represents the total running time; S13. Construct a structural edge effect model, expressed as: S14. The TGO growth model constructed in step S12 and the structural edge effect model constructed in step S13 are introduced into the initial thermal barrier coating life monitoring model constructed in step S11 to obtain the thermal barrier coating life monitoring model.

5. The method for online monitoring of thermal barrier coating life of hot parts of a gas turbine according to claim 1, characterized in that: S2 specifically includes the following steps: S21. Set up a thermal barrier coating test piece and carry out static oxidation tests at multiple different temperatures. During the static oxidation test at each temperature, weigh it at different times. According to the relationship between TGO thickness and mass, obtain the TGO thickness at each time. Then, obtain the corresponding relationship between the total time and the critical failure thickness of TGO at each temperature. Combined with the TGO growth model, obtain the values ​​of C3, A1, and Q. S22. For thermal barrier coating specimens, cyclic oxidation tests are carried out at multiple different temperatures and different cycle durations. The coating strain range of the thermal barrier coating specimens in multiple different high temperature environments and different cycle durations is obtained using a three-dimensional non-contact full-field strain measurement technology. Combined with the TGO growth model, the values ​​of C1, C2, and m are obtained; S23. Set up a tubular specimen, coat the thermal barrier coating on the outer surface of the tubular specimen, carry out a heat resistance cycle test, measure the positive strain range and shear strain range of the thermal barrier coating respectively by a three-dimensional non-contact full-field strain gauge, and fit α based on the structural edge effect model and the initial thermal barrier coating life monitoring model.

6. The method for online monitoring of thermal barrier coating life of hot parts of a gas turbine according to claim 1, characterized in that: The three-dimensional model of the hot component of the gas turbine constructed in step S3 includes a hot component substrate, an adhesive layer and a thermal barrier coating, wherein the adhesive layer is arranged outside the hot component substrate, and the thermal barrier coating is arranged outside the adhesive layer.

7. The method for online monitoring the life of thermal barrier coatings of hot parts of a gas turbine according to claim 6, characterized in that: The hot component matrix includes turbine blades, a flame tube, and a guard ring.

8. The method for online monitoring the life of thermal barrier coatings of hot parts of a gas turbine according to claim 1, characterized in that: S4 specifically includes the following steps: S41, performing structured meshing on the three-dimensional model of the gas turbine hot component; S42, assigning material performance parameters to the thermal component substrate, bonding layer, and thermal barrier coating respectively; S43, using fluid-heat-solid coupling technology to obtain the temperature field distribution of the hot component substrate, bonding layer, and thermal barrier coating under different working conditions; S44. The strain of the thermal barrier coating is calculated by using nonlinear stress-strain technology, wherein a viscoplastic constitutive model is introduced into the deformation characteristics of the thermal barrier coating. The positive strain range and shear strain range of the thermal barrier coating corresponding to the set range of the edge of the thermal component substrate are obtained through nonlinear stress-strain analysis technology.

9. The method for online monitoring the life of thermal barrier coatings of hot parts of a gas turbine according to claim 8, characterized in that: The viscoplastic constitutive model introduced in step S44 is expressed as: In the above formula, Ω represents the flow potential function of the viscoplastic constitutive model of ceramic materials for thermal barrier coatings, K, H, n, h and μ all represent material constants, F represents the yield criterion of the three-parameter Willam-Warnke model, G represents the recovery function, represents the inelastic strain rate tensor, c0, c1, c2, c3, c4, c5, c6 are all expressed as constants, δ ij represents the Kronecker function, S ij , S qi , S iq represents the deviatoric stress component, a ij 、a qi 、a iq Both represent the internal variables of the material's nonlinear kinematic hardening, J2δ ij represents the stress invariant.

10. The method for online monitoring the life of thermal barrier coatings of hot parts of a gas turbine according to claim 1, characterized in that: In step S5, the real-time overall parameters of the actual operation of the gas turbine are obtained through sensors, including turbine inlet gas flow, compressor outlet average total temperature, turbine inlet average gas total temperature, turbine outlet average gas temperature, turbine cooling air inlet temperature, and gas turbine speed.

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