Gas turbine performance quantitative evaluation method and system based on blade tip wear

Abstract

The embodiment of the invention provides a gas turbine performance quantitative evaluation method and system based on blade tip wear, and the method comprises the steps: obtaining turbine geometric parameters of a target gas turbine, and constructing a turbine three-dimensional model based on the geometric parameters; based on periodic overhaul measured data, a dynamic incidence relation of turbine blade cold-state blade top clearance changes along with set operation time length changes is established; creating a numerical calculation grid based on the turbine three-dimensional model, and setting a multi-load working condition boundary condition; through multi-physics field coupling numerical calculation, determining the operation thermal deformation of the turbine blade under different loads corresponding to the unit operation duration; based on the dynamic incidence relation and the operation thermal deformation amount, determining thermal state blade top gaps of different operation durations, and based on the thermal state blade top gaps, constructing a turbine numerical calculation model corresponding to the operation durations and load working conditions; and comparing the performance parameters of different blade tip gaps under the same boundary condition, and quantifying the influence of blade tip wear on the turbine performance.

Description

Technical Field

[0001] This application relates to the technical field of gas turbines, specifically to a method and system for quantitative evaluation of gas turbine performance based on blade tip wear. Background Technology

[0002] As a core component of energy conversion, the performance of a gas turbine directly affects the overall efficiency and output power of the gas turbine. The clearance between the turbine blade tip and the casing is one of the key factors affecting the turbine's aerodynamic performance. Blade tip wear leads to increased clearance, exacerbating gas leakage and causing serious consequences such as decreased turbine efficiency and reduced output power. With accumulated operating time, blade tip wear intensifies, further deteriorating turbine performance and potentially causing increased blade vibration, shortened lifespan, and ultimately leading to a decline in the overall performance of the gas turbine, even affecting the safe and stable operation of the unit.

[0003] Currently, research on the impact of blade tip wear on turbine performance mainly employs simplified analysis methods, which assess performance loss by artificially setting a fixed variation in blade tip clearance. This method has significant limitations: firstly, it fails to consider the geometric characteristics and operating conditions of specific gas turbine models, leading to discrepancies between the analysis results and actual engineering applications; secondly, most existing studies do not consider the progressive wear characteristics of turbine blades caused by complex factors such as thermal load and mechanical stress during long-term operation, failing to accurately reflect the dynamic correlation between blade tip wear and turbine performance degradation, and thus hindering the precise optimization of gas turbine operation and maintenance strategies and life prediction.

[0004] Therefore, there is an urgent need for an effective quantitative evaluation scheme for gas turbine performance based on blade tip wear to solve the above problems. Summary of the Invention

[0005] This application proposes a method and system for quantifying gas turbine performance based on blade tip wear, in order to overcome the deficiencies of the prior art.

[0006] According to a first aspect of the embodiments of this application, a method for quantitatively evaluating the performance of a gas turbine based on tip wear is provided, comprising: Obtain the turbine geometry parameters of the target gas turbine, and construct a three-dimensional turbine model based on the geometry parameters; Based on the measured data from periodic maintenance, a dynamic correlation was established between the operating time of the randomized group of cold-state tip clearance of turbine blades. A numerical computation mesh was created based on the aforementioned three-dimensional turbine model, and boundary conditions for multiple load conditions were set. The thermal deformation of turbine blades under different loads corresponding to the operating time of the unit was determined by multi-physics field coupled numerical calculation. Based on the dynamic correlation and the thermal deformation during operation, the hot tip clearance for different operating lengths is determined, and a turbine numerical calculation model corresponding to the operating length and load condition is constructed based on the hot tip clearance. Based on the turbine numerical calculation model, the performance parameters of different blade tip clearances under the same boundary conditions are compared, and the impact of blade tip wear on turbine performance is quantified.

[0007] In some embodiments, the turbine geometry parameters include stationary / moving blade profiles, casing profiles, endwall profiles, and dynamic / stationary assembly clearances. Before constructing a three-dimensional turbine model based on these geometry parameters, the following steps are included: Data processing is performed to reduce noise and splice the airfoil profiles of the stationary / moving blades, the casing profile, the end wall profile, and the assembly gap between the stationary and moving blades.

[0008] In some implementations, establishing a dynamic correlation between the cold-state tip clearance of turbine blades and the randomized running time variation based on periodic maintenance measurement data includes: Using the initial commissioning gap as a baseline, monitor whether the blades were replaced after maintenance. When it is detected that the blades have not been replaced after maintenance, the measured gap change in each period of the periodic maintenance data is accumulated to the total running time. When it is detected that the blades have been replaced after maintenance, the measured gap change of the new blades during the periodic maintenance measurement data is correlated with the corresponding operating time period.

[0009] In some implementations, determining the hot tip clearance for different operating lengths based on the dynamic correlation and the operating thermal deformation includes: The hot tip clearance for different operating lengths is calculated based on the difference between the cold tip clearance and the thermal deformation of the turbine blade under the corresponding load.

[0010] In some implementations, determining the operating thermal deformation of the turbine blades under different loads corresponding to the unit's operating time through multiphysics coupling numerical calculation includes: Based on the boundary conditions of each load condition and the turbine geometry parameters at the corresponding location, the elongation of each stage of turbine blades is calculated respectively. The corresponding position is consistent with the position of the cold blade tip gap of the turbine blade.

[0011] In some embodiments, constructing a turbine numerical calculation model corresponding to the operating time and load conditions based on the hot tip clearance includes: Based on the hot tip clearance, the tip clearance value is adjusted, and by inheriting the mesh partitioning method of the numerical calculation mesh, the turbine numerical calculation model corresponding to different running lengths and load conditions is constructed. The number of nodes in the turbine numerical calculation model is the same as the number of nodes in the numerical calculation grid.

[0012] In some embodiments, the effect of the quantified blade tip wear on turbine performance includes: Quantitative analysis of the degradation patterns of target performance parameters of gas turbines; The target performance parameters include the turbine's overall aerodynamic efficiency, single-stage blade flow loss, and turbine output power.

[0013] In some implementations, the multi-load operating condition boundary conditions include inlet temperature, pressure, flow rate, and outlet pressure; wherein, if there is no measuring point data for the inlet temperature, it is obtained through unit thermal balance calculation.

[0014] In some embodiments, obtaining the turbine geometry parameters of the target gas turbine includes: The turbine geometry parameters of the target gas turbine are obtained by combining laser scanning with tool measurement. The area measured by the tool includes the dynamic and static assembly clearance, which includes axial clearance and radial clearance.

[0015] According to a second aspect of this application, a quantitative evaluation system for gas turbine performance based on blade tip wear is provided, comprising: A turbine 3D model construction module is used to obtain the turbine geometric parameters of the target gas turbine and construct a turbine 3D model based on the geometric parameters. The dynamic correlation building module is used to establish dynamic correlations of turbine blade tip clearance changes during random group operation based on periodic maintenance measurement data. The boundary condition setting module is used to create a numerical calculation mesh based on the turbine three-dimensional model and set boundary conditions for multiple load conditions. The thermal deformation determination module is used to determine the operating thermal deformation of turbine blades under different loads corresponding to the operating time of the unit through multi-physics field coupled numerical calculation. The numerical calculation model construction module is used to determine the hot tip clearance for different operating lengths based on the dynamic correlation and the operating thermal deformation, and to construct a turbine numerical calculation model for the corresponding operating length and load condition based on the hot tip clearance. The turbine performance evaluation module is used to compare the performance parameters of different blade tip clearances under the same boundary conditions based on the turbine numerical calculation model, and to quantify the impact of blade tip wear on turbine performance.

[0016] The beneficial effects of the gas turbine performance quantitative evaluation method and system based on blade tip wear in this application include at least the following: This application's embodiments solve the problem of geometric deviation between traditional simplified models and actual units by accurately measuring key structural parameters such as turbine blades, casings, and end walls of the actual unit. The constructed three-dimensional model can faithfully reproduce the flow channel characteristics of a specific type of gas turbine, laying a geometric foundation for subsequent numerical calculations. This ensures that the performance analysis results strictly correspond to the physical structure of the real turbine, avoiding engineering errors caused by general models. By utilizing the changes in blade tip clearance measured during multiple overhauls and cylinder openings, a dynamic mapping relationship between cold clearance and operating time is established. This relationship can distinguish between blade replacement / non-replacement scenarios, accurately reflecting the gradual wear pattern during long-term operation, replacing the simplified assumption of artificially set fixed clearances, and providing real data support for performance degradation. The computational mesh is generated based on the real geometric model, ensuring the physical rationality of the numerical simulation. By covering the actual operating range of the gas turbine with multi-load operating condition boundary conditions, the limitations of single-condition analysis are solved. The boundary conditions are... Supplementing the unit's thermal balance data avoids calculation distortion caused by missing measurement points. Combining aerodynamic heat transfer and structural deformation coupling calculations quantifies the blade thermal expansion under different loads. By strictly aligning the deformation calculation location with the maintenance measurement area, spatial consistency with the aforementioned cold-state clearance data is ensured. By revealing the dynamic deformation mechanism of the blades during hot operation, key inputs are provided for hot-state clearance calculations. By integrating the dynamic correlation of cold-state clearance with thermal deformation, the hot-state clearance for different operating durations is accurately derived. The numerical model built based on this maintains consistency with the mesh generation, ensuring single-variable control in performance comparisons and eliminating other interference factors. By comparing performance parameters under the same boundary conditions, the quantitative relationship between the increase in blade tip clearance and performance degradation is directly correlated. The decay law of turbine efficiency at different operating stages can be identified, providing data-driven decision-making basis for operation and maintenance strategy optimization and solving the problem that traditional methods cannot dynamically predict long-term performance degradation. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating one embodiment of the gas turbine performance quantitative evaluation method based on blade tip wear according to this application. Figure 2 This is a schematic diagram of a three-dimensional model structure of a heavy-duty gas turbine according to an embodiment of this application; Figure 3 This is a schematic diagram of the mesh generation for the turbine numerical calculation model according to an embodiment of this application; Figure 4 This is a schematic diagram of the mesh generation for two different turbine numerical calculation models with different tip clearances according to embodiments of this application. Figure 5 This is a schematic diagram showing the changes in aerodynamic efficiency of turbine blades at each stage under three maintenance phases at 100% load, according to an embodiment of this application. Figure 6This is a schematic diagram of the structure of a gas turbine performance quantitative evaluation system based on blade tip wear, according to an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of the present application, but merely to illustrate selected embodiments of the present application. Other embodiments obtained by those skilled in the art based on the embodiments of the present application without inventive effort are all within the scope of protection of the embodiments of the present application.

[0020] It can be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it will not be further defined and explained in subsequent figures according to the embodiments of this application.

[0021] This application discloses a method for quantitatively evaluating the performance of a gas turbine based on blade tip wear. It aims to address the problems of performance distortion and difficulty in accurately correlating unit operating time caused by artificially setting a fixed variation in blade tip clearance in existing technologies. This provides a more accurate and engineering-applicable solution. The method is executed by a gas turbine performance quantitative evaluation system based on blade tip wear. (See attached figure.) Figure 1 As shown, the method includes steps 110-160.

[0022] Step 110: Obtain the turbine geometry parameters of the target gas turbine and construct a three-dimensional turbine model based on these geometry parameters.

[0023] In some embodiments, obtaining the turbine geometry parameters of the target gas turbine includes obtaining the turbine geometry parameters of the target gas turbine by combining laser scanning with tool measurement.

[0024] For example, the geometric parameters of a component can be obtained by surveying and mapping by using laser scanning to obtain the outline of the moving and stationary blades of each stage of the gas turbine, as well as the casing, end walls, and other structures. For the geometric parameters of the component areas that are difficult to survey and scan, they can be obtained by measuring with tools such as calipers, feeler gauges, and depth gauges.

[0025] For example, the area measured by the tool includes the dynamic and static assembly clearance, which includes axial clearance and radial clearance.

[0026] The turbine geometry parameters include the stationary / moving blade profiles, casing profile, endwall profile, and the clearance between the stationary and moving parts.

[0027] In some implementations, prior to constructing the three-dimensional turbine model based on the geometric parameters, data processing is performed to reduce noise and stitch together the stationary / dynamic blade profiles, the casing profile, the endwall profile, and the dynamic / static assembly clearances.

[0028] For example, this application takes a heavy-duty gas turbine as the research object. For the gas turbine unit model under study, it maps and measures key geometric parameters such as the blade profiles of the turbine's stationary and moving blades, the casing profile, the endwall profile, and the dynamic and static assembly clearances. Specifically, this application uses blue light scanning to map the turbine's flow passages, such as the turbine's various stages of moving and stationary blades, as well as the casing and endwalls, acquiring their external contours. The scanned data is saved and output in point cloud or triangular patch format. For geometric parameters of areas difficult to map, such as the axial and radial clearances between the moving and stationary blades, tools like calipers, feeler gauges, and depth gauges are used. These geometric dimensions are used for subsequent positioning and alignment of the mapping data and for modeling key local structures in the 3D model.

[0029] For example, see Appendix Figure 2 As shown, this embodiment of the application takes a heavy-duty gas turbine as the research object. Based on the key geometric parameters of the turbine obtained through mapping and measurement, data noise reduction and stitching are performed, and a three-dimensional model of the turbine is constructed based on the processed mapping data. Abnormal isolated points are deleted from the point cloud or triangular patch data obtained from the mapping. Based on the measured dynamic and static assembly gaps, the data of the turbine's moving blades and stationary blades are aligned and stitched together, merging the data from multiple scans into a unified coordinate system. A three-dimensional model of the turbine is then constructed based on the processed mapping data.

[0030] Step 120: Based on the measured data from periodic maintenance, establish a dynamic correlation between the running time of the turbine blade tip clearance random group in the cold state.

[0031] In some implementations, establishing a dynamic correlation between the cold-state tip clearance of turbine blades and the randomized operation time variation based on periodic maintenance measurement data includes: using the initial commissioning clearance as a baseline value, monitoring whether the blades have been replaced after maintenance.

[0032] When it is detected that the blades have not been replaced after maintenance, the measured gap change in each cycle of the periodic maintenance data is accumulated to the total running time.

[0033] Specifically, when it is detected that the blades have been replaced after maintenance, the measured gap change of the new blades during the periodic maintenance period is correlated with the corresponding operating time period in the periodic maintenance measurement data.

[0034] For example, this application takes a heavy-duty gas turbine as the research object. Based on the changes in the tip clearance of turbine blades at different maintenance stages of the gas turbine unit, the relationship between the tip clearance of the turbine blades of this type of gas turbine and the unit's operating time is obtained. The tip clearances of turbine blades at different operating times are taken as the cold tip clearances when the unit is shut down. Determining the cold tip clearances of turbine blades at different operating times under the shutdown state includes: using the tip clearance measured before the unit's initial commissioning as the initial clearance; the change in the tip clearance of turbine blades at different maintenance stages compared to the tip clearance measured when the unit is commissioned corresponds to the change in tip clearance from initial commissioning to the first maintenance period; if, after the first maintenance, the turbine blades and tip guards are not replaced, but only the cylinder is opened for inspection and then the original turbine blades are used for continued operation, then the change in tip clearance measured during the second maintenance stage is based on the change in operating time during the first maintenance stage. The change in tip clearance after the second overhaul phase, i.e., the change in turbine tip clearance during the first and second overhaul phases combined, corresponds to the operating time from the initial commissioning of the unit to the cylinder opening during the second overhaul. If the turbine blades and tip guards are replaced after the first overhaul, the change in tip clearance measured during the cylinder opening during the second overhaul is the change in turbine blade tip clearance only during the second overhaul phase. This change in tip clearance is relative to the change in tip clearance after the replacement of the new turbine blades and tip guards during the first overhaul, and corresponds to the operating time from the cylinder closure during the first overhaul to the cylinder opening during the second overhaul. Similarly, depending on whether new turbine blades and matching tip guard structures are replaced after the overhaul, the changes in tip clearance of each stage of turbine blades during different overhaul periods are obtained using the above two methods, yielding the relationship between the cold-state tip clearance of the turbine blades under shutdown conditions and the operating time.

[0035] For example, this embodiment takes a heavy-duty gas turbine as the research object, and Table 1 below shows the changes in the tip clearance of each stage of the turbine blades under three maintenance stages. In this embodiment, the turbine blades and retaining ring structure were not replaced after the first maintenance stage, but were replaced after the second maintenance stage.

[0036]

[0037] Table 1 As shown in Table 1 above, at the initial commissioning, the cold tip clearances of the turbine's third-stage moving blades are A, B, and C, respectively. After the first maintenance phase's operating time δT1, the changes in the cold tip clearances of the turbine's third-stage moving blades are δA1, δB1, and δC1, respectively. Based on this, after the second maintenance phase's operating time δT2, the further changes in the cold tip clearances of the turbine's third-stage moving blades are δA2, δB2, and δC2, respectively. Since the turbine blades and retaining ring structure were replaced after the second maintenance, after the third maintenance phase's operating time, the changes in the cold tip clearances of the turbine's third-stage blades relative to the tip clearances A', B', and C' after the replacement of the new blades are δA3, δB3, and δC3, respectively. Among them, A', B', and C' are basically consistent with the initial tip clearances A, B, and C, but there will be slight differences due to installation reasons. Based on the tip clearance of turbine blades at different maintenance stages, the relationship between the cold tip clearance of turbine blades at different stages and the operating time is as follows: After an operating time of δT1, the changes in the cold tip clearance of the turbine's third-stage moving blades are δA1, δB1, and δC1, respectively; after an operating time of δT1+δT2, the changes in the cold tip clearance of the turbine's third-stage moving blades are δA1+δA2, δB1+δB2, and δC1+δC2, respectively; after an operating time of δT3, the changes in the cold tip clearance of the turbine's third-stage moving blades are δA3, δB3, and δC3, respectively.

[0038] Step 130: Create a numerical calculation grid based on the three-dimensional turbine model and set boundary conditions for multiple load conditions.

[0039] In some implementations, the multi-load condition boundary conditions include inlet temperature, pressure, flow rate, and outlet pressure.

[0040] For example, if there is no measurement data for the inlet temperature, it can be obtained through unit heat balance calculation.

[0041] For example, in this embodiment of the application, a numerical calculation model is created and meshed based on the constructed three-dimensional turbine model, and the numerical calculation boundary conditions of the turbine are determined according to the actual unit operating conditions. (See attached figure.) Figure 3 As shown, the turbine numerical calculation model specifically created in this application embodiment includes turbine blades at each stage, casing surface, end wall surface, and circumferential periodic flow channel interface, and is meshed. When determining the turbine numerical calculation boundary conditions based on the actual operating conditions of the unit, this application embodiment includes multiple unit load conditions, such as 50%, 75%, and 100% load conditions. The turbine boundary conditions include inlet temperature, inlet pressure, inlet flow rate, and outlet pressure. If there is no corresponding measuring point for the turbine inlet temperature, it can be obtained through unit heat balance calculation.

[0042] Step 140: Through multi-physics coupled numerical calculation, determine the amount of thermal deformation of turbine blades under different loads corresponding to the operating time of the unit.

[0043] In some implementations, determining the operating thermal deformation of turbine blades under different loads corresponding to the unit's operating time through multi-physics coupled numerical calculations includes: calculating the elongation of each stage of turbine blades based on the boundary conditions of each load condition and the corresponding turbine geometric parameters.

[0044] For example, the corresponding position is consistent with the position of the cold tip gap of the turbine blade.

[0045] For example, this embodiment of the application performs numerical calculations of aerodynamic heat transfer and structural deformation based on the turbine numerical calculation model and boundary conditions, and obtains the blade elongation of each stage of the turbine blades under centrifugal force and thermal stress during actual operation of the unit. Specifically, when calculating the blade elongation of each stage of the turbine blades under centrifugal force and thermal stress under hot start-up conditions, this embodiment of the application calculates the elongation of each stage of the turbine blades under different load conditions according to the boundary conditions corresponding to each load condition. For instance, the location of the blade elongation obtained under different load conditions in this embodiment of the application is consistent with the region of the blade tip clearance measured during maintenance, such as the middle of the blade tip.

[0046] Step 150: Based on the dynamic correlation and the thermal deformation during operation, determine the hot tip clearance for different operating lengths, and construct a turbine numerical calculation model for the corresponding operating length and load condition based on the hot tip clearance.

[0047] In some implementations, determining the hot tip clearance for different operating lengths based on the dynamic correlation and the operating thermal deformation includes: calculating the hot tip clearance for different operating lengths based on the difference between the cold tip clearance and the operating thermal deformation of the turbine blade under the corresponding load.

[0048] In some implementations, constructing a turbine numerical calculation model corresponding to the operating time and load condition based on the hot tip clearance includes: adjusting the tip clearance value based on the hot tip clearance, and constructing the turbine numerical calculation model corresponding to different operating times and load conditions by inheriting the mesh partitioning method of the numerical calculation mesh.

[0049] For example, the number of nodes in the turbine numerical computation model is the same as the number of nodes in the numerical computation grid.

[0050] For example, this embodiment of the application creates numerical calculation models and computational grids corresponding to different operating durations and load conditions based on the hot tip clearances of turbine blades at different operating lengths and load conditions. For instance, different operating durations and load conditions may lead to differences in the tip clearances of turbine blades at different operating stages during hot operation. This embodiment of the application constructs a numerical calculation model and computational grid for the turbine based on the hot tip clearances corresponding to the unit's operating duration and load conditions. In this embodiment of the application, the number of grid nodes and the meshing method of the numerical calculation model remain consistent across different operating durations and load conditions. (See attached figure) Figure 4 As shown, the meshing details of the numerical calculation models of the turbine first-stage moving blade under two different operating lengths are displayed. Except for the difference in the tip clearance, the numerical calculation models under the two different operating lengths are consistent.

[0051] For example, referring to Table 2 below, the thermal elongation of the third-stage turbine blade under centrifugal force and thermal stress at 50% load is βA1, βB1, and βC1, respectively; the thermal elongation of the third-stage turbine blade under centrifugal force and thermal stress at 75% load is βA2, βB2, and βC2, respectively; and the thermal elongation of the third-stage turbine blade under centrifugal force and thermal stress at 100% load is βA3, βB3, and βC3, respectively.

[0052]

[0053] Table 2 As shown in Table 2 above, the embodiments of this application determine the hot tip clearance of turbine blades under different operating lengths and load conditions based on the cold tip clearance of turbine blades at different operating lengths under the obtained shutdown state and the blade elongation under the start-up operating state obtained by numerical calculation.

[0054]

[0055] Table 3 As shown in Table 3 above, the hot tip clearance of each stage of turbine blades under 100% load conditions changes with operating time. Under initial operating conditions, the hot tip clearances of the three-stage turbine blades are A-βA3, B-βB3, and C-βC3, respectively. After an operating time of δT1, the hot tip clearances of the three-stage turbine blades are A+δA1-βA3, B+δB1-βB3, and C+δC1-βC3, respectively. After an operating time of δT1+δT2, the hot tip clearances of the three-stage turbine blades are A+δA1+δA2-βA3, B+δB1+δB2-βB3, and C+δC1+δC2-βC3, respectively. After an operating time of δT3, the hot tip clearances of the three-stage turbine blades are A+δA3-βA3, B+δB3-βB3, and C+δC3-βC3, respectively.

[0056] Step 160: Based on the turbine numerical calculation model, compare the performance parameters of different blade tip clearances under the same boundary conditions, and quantify the impact of blade tip wear on turbine performance.

[0057] In some implementations, the quantification of the impact of blade tip wear on turbine performance includes: quantifying the degradation patterns of target performance parameters of the gas turbine.

[0058] For example, the target performance parameters include the turbine's overall aerodynamic efficiency, single-stage blade flow loss, and turbine output power.

[0059] For example, different operating durations and load conditions can lead to differences in the tip clearance of turbine blades at each stage during hot operation. In this embodiment, a numerical calculation model and computational grid for the turbine are constructed based on the hot tip clearance corresponding to the unit's operating duration and load conditions. Specifically, in this embodiment, the number of grid nodes and the meshing method of the numerical calculation model remain consistent under different operating durations and load conditions.

[0060] For example, this application embodiment performs numerical solutions for turbine models under different operating lengths and load conditions with different tip clearances under the same boundary conditions, compares key turbine performance parameters, and analyzes the impact of tip clearance changes caused by tip wear on gas turbine performance under different operating lengths. For instance, when analyzing the impact of tip clearance changes caused by tip wear on gas turbine performance under different operating lengths, this application embodiment can analyze key turbine parameters such as the aerodynamic efficiency, flow loss, and power of each stage of blades, or the aerodynamic efficiency, flow loss, and power of the entire turbine. (See attached figure) Figure 5 As shown in the figure, this embodiment demonstrates the decline in aerodynamic efficiency of turbine blades at each stage under three maintenance phases at 100% load. Compared with the initial operating state, the aerodynamic efficiency of the turbine decreased by 0.72%, 1.12%, and 1.37% respectively after the three maintenance phases.

[0061] This application's embodiments solve the problem of geometric deviation between traditional simplified models and actual units by accurately measuring key structural parameters such as turbine blades, casings, and end walls of the actual unit. The constructed three-dimensional model can faithfully reproduce the flow channel characteristics of a specific type of gas turbine, laying a geometric foundation for subsequent numerical calculations. This ensures that the performance analysis results strictly correspond to the physical structure of the real turbine, avoiding engineering errors caused by general models. By utilizing the changes in blade tip clearance measured during multiple overhauls and cylinder openings, a dynamic mapping relationship between cold clearance and operating time is established. This relationship can distinguish between blade replacement / non-replacement scenarios, accurately reflecting the gradual wear pattern during long-term operation, replacing the simplified assumption of artificially set fixed clearances, and providing real data support for performance degradation. The computational mesh is generated based on the real geometric model, ensuring the physical rationality of the numerical simulation. By covering the actual operating range of the gas turbine with multi-load operating condition boundary conditions, the limitations of single-condition analysis are solved. The boundary conditions are... Supplementing the unit's thermal balance data avoids calculation distortion caused by missing measurement points. Combining aerodynamic heat transfer and structural deformation coupling calculations quantifies the blade thermal expansion under different loads. By strictly aligning the deformation calculation location with the maintenance measurement area, spatial consistency with the aforementioned cold-state clearance data is ensured. By revealing the dynamic deformation mechanism of the blades during hot operation, key inputs are provided for hot-state clearance calculations. By integrating the dynamic correlation of cold-state clearance with thermal deformation, the hot-state clearance for different operating durations is accurately derived. The numerical model built based on this maintains consistency with the mesh generation, ensuring single-variable control in performance comparisons and eliminating other interference factors. By comparing performance parameters under the same boundary conditions, the quantitative relationship between the increase in blade tip clearance and performance degradation is directly correlated. The decay law of turbine efficiency at different operating stages can be identified, providing data-driven decision-making basis for operation and maintenance strategy optimization and solving the problem that traditional methods cannot dynamically predict long-term performance degradation.

[0062] This application also discloses a quantitative evaluation system for gas turbine performance based on blade tip wear. (See attached document.) Figure 6 As shown, the system includes: a turbine 3D model construction module 610, a dynamic relationship building module 620, a boundary condition setting module 630, a thermal deformation determination module 640, a numerical calculation model construction module 650, and a turbine performance evaluation module 660.

[0063] The turbine 3D model construction module 610 is used to obtain the turbine geometry parameters of the target gas turbine and construct a turbine 3D model based on these geometry parameters.

[0064] The dynamic correlation building module 620 is used to establish a dynamic correlation of the change in the running time of the cold-state tip clearance of turbine blades based on the measured data of periodic maintenance.

[0065] The boundary condition setting module 630 is used to create a numerical calculation mesh based on the three-dimensional turbine model and set boundary conditions for multiple load conditions.

[0066] The thermal deformation determination module 640 is used to determine the operating thermal deformation of turbine blades under different loads corresponding to the operating time of the unit through multi-physics field coupled numerical calculation.

[0067] The numerical calculation model construction module 650 is used to determine the hot tip clearance for different operating lengths based on the dynamic correlation and the operating thermal deformation, and to construct a turbine numerical calculation model for the corresponding operating length and load condition based on the hot tip clearance.

[0068] The turbine performance evaluation module 660 is used to compare the performance parameters of different blade tip clearances under the same boundary conditions based on the turbine numerical calculation model, and to quantify the impact of blade tip wear on turbine performance.

[0069] Compared with the simplified assumptions in the prior art that typically use a fixed variation in the tip clearance of gas turbine blades to assess turbine performance loss, this application's embodiments construct a high-fidelity numerical calculation model using actually measured turbine geometric parameters, ensuring that it can accurately reflect the real operating characteristics of a specific type of gas turbine. Simultaneously, based on measured cold-state tip clearance data of turbine blades during different maintenance cycles, and combined with the hot-state deformation of each stage of turbine blades obtained through multi-physics coupled numerical simulation, the relationship between hot-state tip clearance and operating conditions with operating time is established. Through the constructed high-precision three-dimensional turbine model and the relationship between the hot-state tip clearance of each stage of turbine blades with operating time and operating conditions, a quantitative correlation is achieved between the performance degradation of gas turbines caused by tip wear and operating time. This allows for accurate prediction of the turbine's performance degradation pattern under different operating cycles and load conditions, thus providing reliable quantitative criteria for gas turbine performance evaluation and fault diagnosis.

[0070] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of this application, and this application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this application, and these modifications and improvements are also considered to be within the scope of protection of this application.

Claims

1. A method for quantitatively evaluating performance of a gas turbine turbine based on blade tip wear, characterized by, The method comprises the following steps: acquiring turbine geometric parameters of a target gas turbine, and constructing a turbine three-dimensional model based on the geometric parameters; based on periodic maintenance measured data, establishing a dynamic correlation relationship of turbine blade cold state tip clearance changing with random group running time; creating a numerical calculation grid based on the turbine three-dimensional model, and setting boundary conditions of multiple load conditions; determining the running thermal deformation amount of the turbine blade under different loads corresponding to the unit running time through multi-physical field coupling numerical calculation; based on the dynamic correlation relationship and the running thermal deformation amount, determining the hot state tip clearance of different running times, and constructing a turbine numerical calculation model corresponding to the running time and load condition based on the hot state tip clearance; based on the turbine numerical calculation model, comparing the performance parameters of different tip clearances under the same boundary conditions, and quantifying the influence of tip wear on turbine performance.

2. The method of claim 1, wherein, The turbine geometric parameters include static / dynamic blade profiles, casing profiles, end wall profiles, and dynamic / static assembly clearances, and before constructing the turbine three-dimensional model based on the geometric parameters, the following steps are included: data processing of noise reduction and splicing for the static / dynamic blade profiles, the casing profiles, the end wall profiles, and the dynamic / static assembly clearances.

3. The method of claim 1, wherein, The dynamic correlation relationship of turbine blade cold state tip clearance changing with random group running time is established based on periodic maintenance measured data, which includes the following steps: taking the initial commissioning clearance as the reference value, monitoring whether the blade is replaced after maintenance; when it is monitored that the blade is not replaced after maintenance, accumulating the change amount of each cycle measured clearance in the periodic maintenance measured data to the total running time; when it is monitored that the blade is replaced after maintenance, correlating the measured clearance change amount of the new blade use cycle in the periodic maintenance measured data with the corresponding running time period.

4. The method of claim 1, wherein, Based on the dynamic correlation relationship and the running thermal deformation amount, the hot state tip clearance of different running times is determined, which includes the following steps: the hot state tip clearance of different running times is calculated based on the difference between the cold state tip clearance and the running thermal deformation amount of the turbine blade under corresponding load.

5. The method of claim 1, wherein, The running thermal deformation amount of the turbine blade under different loads corresponding to the unit running time is determined through multi-physical field coupling numerical calculation, which includes the following steps: based on the boundary conditions of each load condition and the turbine geometric parameters at the corresponding position, the elongation of each stage of turbine blade is calculated respectively; wherein, the corresponding position is consistent with the position of the turbine blade cold state tip clearance.

6. The method of claim 1, wherein, Based on the hot state tip clearance, the turbine numerical calculation model corresponding to the running time and load condition is constructed, which includes the following steps: adjusting the tip clearance value based on the hot state tip clearance, and constructing the turbine numerical calculation model corresponding to different running times and load conditions by inheriting the mesh partitioning method of the numerical calculation grid; wherein, the number of nodes of the turbine numerical calculation model is consistent with that of the numerical calculation grid.

7. The method of claim 1, wherein, The influence of tip wear on turbine performance is quantified, which includes the following steps: quantitative analysis of the decline law of the target performance parameters of the gas turbine; wherein, the target performance parameters include turbine overall aerodynamic efficiency, single stage blade flow loss, and turbine output power.

8. The method of claim 1, wherein, The multi-load condition boundary condition comprises an inlet temperature, a pressure, a flow rate and an outlet pressure; wherein, if there is no measured point data of the inlet temperature, the inlet temperature is obtained by unit heat balance calculation.

9. The method of claim 2, wherein, The turbine geometry parameters of the target gas turbine are obtained by means of laser scanning combined with tool measurement. The turbine geometry parameters of the target gas turbine are obtained by means of laser scanning combined with tool measurement. The tool measurement region comprises the rotating and static assembly gap, and the rotating and static assembly gap comprises an axial gap and a radial gap.

10. A gas turbine turbine performance quantification system based on blade tip wear, characterized by, The turbine geometry parameters of the target gas turbine are obtained by means of laser scanning combined with tool measurement. A turbine performance evaluation module is configured to compare performance parameters of different blade tip clearances under the same boundary condition based on the turbine numerical calculation model, and quantify the influence of blade tip wear on turbine performance. A turbine performance evaluation module is configured to compare performance parameters of different blade tip clearances under the same boundary condition based on the turbine numerical calculation model, and quantify the influence of blade tip wear on turbine performance. ​ ​ ​ ​

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