Numerical simulation method and system for structural defects of water turbine blade based on fluid-structure coupling

Abstract

The application discloses a kind of numerical simulation method and system for structural defect of water turbine blade based on fluid-structure coupling, comprising: on the basis of defect modeling, under the framework of fluid-structure coupling, the flow field distribution is solved using computational fluid dynamics method, the response of blade structure is solved using finite element method, and the two-way coupling of fluid domain and structure domain is realized through pressure boundary, to obtain fluid-structure coupling result;Under each operating condition of the water turbine, the efficiency loss, pressure pulsation characteristics and stress concentration distribution are calculated respectively, and the comprehensive influence of defects on the performance and safety of the water turbine blade is analyzed;Based on the evolution model of defect expansion, the growth law of defects with running time is predicted, and the efficiency decay curve and fatigue life of the water turbine blade are predicted by combining the fluid-structure coupling result, which can simultaneously consider the flow field and structural response for numerical simulation of structural defect of water turbine blade, realize dynamic prediction and life assessment of blade defect development process.

Description

Technical Field

[0001] This invention belongs to the field of hydraulic machinery and hydropower engineering technology, and relates to a numerical simulation method and system for structural defects of turbine blades based on fluid-structure interaction. Background Technology

[0002] As the core power equipment of hydropower stations, turbines are often subjected to the impact of sediment-laden water flow, cavitation, and fatigue loads during long-term operation. This leads to structural defects such as cracks, cavitation pits, and localized wear on the surface and interior of the blades. These defects can cause localized flow separation, abnormal pressure distribution, and stress concentration, resulting in decreased efficiency, increased pressure pulsation, and even fatigue failure. With increasing operating time, these defects may gradually expand and intensify, posing a serious threat to the safe operation of the unit. Therefore, accurately modeling and simulating turbine blade defects and quantitatively assessing their impact on hydrodynamic performance and structural strength is a critical technical challenge that the hydropower industry urgently needs to address.

[0003] Existing research employs simplified geometric models to represent cracks or craters and analyzes their impact on flow field characteristics through computational fluid dynamics simulations; other methods use the finite element method to calculate the stress distribution at the crack tip. However, most of these methods are limited to the analysis of a single physical field, neglecting the interaction between water flow and blade structure, making it difficult to accurately reflect the coupling effects during defect development. Furthermore, existing studies typically only analyze static defect morphology, lacking dynamic simulations of defect expansion over operating time, resulting in insufficient applicability of prediction results in lifespan assessment and operational decision-making.

[0004] Furthermore, traditional defect analysis methods still have two problems when applied to engineering practice: first, they have low computational efficiency and are difficult to meet the prediction needs under full operating conditions and multiple defect combinations; second, they lack a prediction mechanism that combines with monitoring data and cannot quickly assess the impact of blade defects on performance and safety in on-site operation and maintenance.

[0005] Therefore, there is an urgent need for a fluid-structure interaction numerical simulation method that can simultaneously consider flow field and structural response, has the ability to model defect extension, and can improve computational efficiency through surrogate models, so as to achieve dynamic prediction and life assessment of blade defect development process. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a numerical simulation method and system for turbine blade structural defects based on fluid-structure interaction. This method and system can simultaneously consider the flow field and structural response to perform numerical simulation of turbine blade structural defects, and also has the ability to model defect expansion, thereby realizing dynamic prediction and life assessment of the blade defect development process.

[0007] To achieve the above objectives, this invention discloses a numerical simulation method for structural defects in hydraulic turbine blades based on fluid-structure interaction, comprising: Obtain a three-dimensional geometric model of the turbine blades and identify the defects in the turbine blades; The identified defects are modeled using a parametric method; Based on defect modeling, within the fluid-structure interaction framework, computational fluid dynamics is used to solve the flow field distribution, the finite element method is used to solve the blade structure response, and the two-way coupling between the fluid domain and the structural domain is achieved through pressure boundary to obtain the fluid-structure interaction results. Efficiency loss, pressure pulsation characteristics, and stress concentration distribution of the turbine were calculated under various operating conditions to analyze the comprehensive impact of defects on turbine blade performance and safety. Based on the evolutionary model of defect propagation, the growth law of defects with operating time is predicted, and combined with the fluid-structure interaction results, the efficiency decay curve and fatigue life of turbine blades are predicted.

[0008] Furthermore, the defects in the turbine blades include cracks, cavitation pits, and wear.

[0009] Furthermore, the process of modeling the identified defects using a parametric method is as follows: Modeling of crack defects using elliptical or semi-elliptical geometric functions; Gaussian concavity function is used to model pit defects; Piecewise linear functions are used to model wear defects.

[0010] Furthermore, the fluid domain is solved using incompressible RANS equations.

[0011] Furthermore, the structural domain is obtained using the finite element method.

[0012] Furthermore, the fluid pressure field is applied to the blade surface as a boundary load, and the updated structural displacement is then fed back to the fluid domain, achieving bidirectional coupling.

[0013] Furthermore, the specific steps for predicting the growth pattern of defects over runtime are as follows: For crack propagation, based on the laws of fracture mechanics, the growth rate of crack length with increasing load cycle number is described.

[0014] For pothole expansion, an exponential saturation function is used to reflect the characteristics of rapid initial growth followed by saturation.

[0015] For wear development, a linear or piecewise function is used to reflect the relationship between wear depth and operating time.

[0016] This invention discloses a numerical simulation system for structural defects in hydraulic turbine blades based on fluid-structure interaction, comprising: The acquisition module is used to acquire the three-dimensional geometric model of the turbine blades and identify the defects in the turbine blades. The modeling module is used to model the identified defects using parametric methods; The coupling module is used to solve the flow field distribution using computational fluid dynamics methods and the response of the blade structure using finite element methods, based on defect modeling and within the fluid-structure interaction framework, and to achieve bidirectional coupling between the fluid domain and the structural domain through pressure boundaries, so as to obtain the fluid-structure interaction results. The analysis module is used to calculate efficiency loss, pressure pulsation characteristics and stress concentration distribution under various operating conditions of the turbine, and to analyze the comprehensive impact of defects on the performance and safety of the turbine blades. The prediction module is used to predict the growth pattern of defects over time based on the evolution model of defect expansion, and combined with the fluid-structure interaction results, to predict the efficiency decay curve and fatigue life of turbine blades.

[0017] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for generating and sending trusted status alarm information.

[0018] The present invention discloses a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the method for generating and uploading trusted status alarm information are implemented.

[0019] The present invention has the following beneficial effects: The numerical simulation method and system for turbine blade structural defects based on fluid-structure interaction (FSI) described in this invention, in practical operation, introduces parametric modeling of cracks, cavitation pits, and wear, and performs bidirectional iterative calculations of the flow field and structural response within the FSI framework. This not only realistically reflects the dual impact of structural defects on hydrodynamic performance and structural safety, but also enables efficiency degradation and lifespan prediction by combining defect propagation laws. Compared with existing technologies, this invention has advantages such as a more comprehensive analysis scope, more dynamic prediction capabilities, higher computational accuracy, and superior application efficiency. It can provide scientific support for turbine operation optimization, lifespan assessment, and maintenance cycle formulation, and has significant engineering application value. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a graph showing the expansion of crack length over time. Figure 3 This is a graph showing the decrease in unit efficiency as the crack propagates. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0024] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0025] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0026] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0027] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0029] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0030] Example 1 refer to Figure 1 The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction described in this invention includes the following steps: 1) Obtain a three-dimensional geometric model of the turbine blade and identify defect areas with cracks, cavitation pits or local wear, wherein the defects include crack defects, cavitation pits and local wear; Crack defects: often appear at the base or leading edge of the blade, and should be marked carefully; Cavitation pits: mostly occur on the suction side and trailing edge of blades; Localized wear: occurs in areas with strong sand-laden impact.

[0031] 2) A parametric method is used to model the identified defects. Crack defects are described by parameters such as length, depth, and inclination angle, while pit defects are described by parameters such as radius, depth, and distribution density. Specifically, mathematical functions are used to model the defect morphology: Modeling of crack defects: Elliptical or semi-elliptical geometric functions are used, with key parameters being crack depth d, length l, and inclination angle θ; Modeling of pit defects: A Gaussian concavity function is used, with parameters including maximum depth h0 and expansion range σ; Modeling of wear defects: A piecewise linear function is used to describe the change in surface thickness loss over time.

[0032] The parameterized model allows for flexible adjustment of defect geometry at different stages of operation.

[0033] 3) Under the fluid-structure interaction framework, computational fluid dynamics is used to solve the flow field distribution, finite element method is used to solve the blade structure response, and pressure boundary is used to achieve bidirectional coupling between the fluid domain and the structural domain. The fluid-structure interaction calculation adopts a two-way coupling method. During the iteration process, the pressure on the blade surface and the structural displacement are mutually transmitted to achieve synchronous updates of the fluid domain and the structural domain.

[0034] The fluid domain is solved using the incompressible RANS equations, i.e.:

[0035] SST is preferred for turbulence model k-ω The mesh is densified in defect areas to capture flow separation and cavitation.

[0036] The structural domain, when constructed using the finite element method, satisfies the following equilibrium equations:

[0037] Where K is the structural stiffness matrix, {u} is the displacement vector, and {F} is the fluid force.

[0038] In each iteration, the fluid pressure field is applied to the blade surface as a boundary load, and the structural displacement is updated and then fed back to the fluid domain, thus achieving bidirectional coupling.

[0039] 4) Calculate efficiency loss, pressure pulsation characteristics, and stress concentration distribution under various operating conditions, and analyze the comprehensive impact of defects on turbine performance and safety; Calculate the following parameters under small opening, rated opening, and large opening conditions: Hydrodynamic parameters: efficiency-flow rate curve, cavitation number and cavitation margin, pressure pulsation amplitude; Structural mechanical parameters: stress concentration factor, stress distribution, and maximum displacement in the defect area.

[0040] By comparing the results with and without defects, the impact of defects on performance and safety is quantitatively analyzed.

[0041] 5) Based on the evolutionary model of defect propagation, predict the growth law of defects with running time, and estimate the lifetime by combining the output efficiency decay curve of the simulation results.

[0042] Introduce an evolution function for defects over runtime: Crack propagation: Based on the laws of fracture mechanics, it describes the rate at which crack length increases with the number of load cycles.

[0043] Pothole expansion: An exponential saturation function is used to reflect the characteristics of rapid initial growth followed by saturation.

[0044] Wear development: A linear or piecewise function is used to reflect the relationship between wear depth and operating time.

[0045] By combining the results with fluid-structure interaction, the efficiency decay curve and fatigue life can be predicted.

[0046] 6) Reduced-order prediction of the surrogate model; To improve computational efficiency, this invention further introduces a surrogate model. The input parameters are defect characteristics and operating conditions, and the outputs are efficiency, pressure fluctuations, and lifespan indicators, thereby achieving rapid prediction. The surrogate model can be a Kriging model, a radial basis function network, or a deep neural network; preferably, the Kriging model is used.

[0047] Example 2 Taking a bulb turbine unit with an installed capacity of 35MW as an example, this invention is used to simulate and predict blade crack defects.

[0048] An initial crack, approximately 10 mm long and 3 mm deep, with an inclination angle of 45°, was found near the root of the blade leading edge of the unit. The crack morphology was parametrically modeled using a semi-elliptic function in the three-dimensional geometric model, and the mesh was locally refined in the crack region to ensure that the element size at the crack tip was less than 0.5 mm, thus guaranteeing accurate capture of stress concentration effects.

[0049] Subsequently, a fluid-structure interaction simulation model was established. The fluid domain was solved using the CFD method to determine the water flow field, with an inlet flow rate of 150 m³ / s and a rotational speed of 70 rpm, considering cavitation effects. The structural domain was solved using the FEM method, with ZG0Cr13Ni5Mo stainless steel as the material. Through bidirectional iteration, the blade surface pressure was applied to the structural domain in each cycle, while the structural deformation was fed back to the fluid domain, realizing the interaction between the fluid and the solid.

[0050] Numerical calculations were performed under three operating conditions: small opening, rated opening, and large opening. The results show that the presence of cracks reduces the unit efficiency by approximately 2.5% and increases the amplitude of the fundamental frequency pressure pulsation on the blade surface by 40%. The stress concentration factor at the crack tip reaches 3.1, demonstrating a significant strength weakening effect.

[0051] like Figure 1 As shown, the crack length continuously expands over operating time, initially at 10 mm, increasing to approximately 28 mm after 5 years of operation, and approaching the critical length of 35 mm after 6 years, indicating a risk of fatigue fracture. The crack development process exhibits a non-linear relationship with operating time, with rapid expansion in the early stages and a gradual approach to the failure limit in the later stages.

[0052] like Figure 2 As shown, the unit efficiency gradually decreases as the cracks propagate. The initial efficiency is about 93%, which decreases by about 5% after 5 years of operation, reaching the preset maintenance threshold. When the unit continues to operate for 6 years, the efficiency decreases by more than 6%, which significantly affects the unit's operating economy and safety.

[0053] In summary, this embodiment successfully obtained the crack propagation law through parametric modeling of crack defects, fluid-structure interaction calculation, and defect evolution prediction. Figure 1 ) and efficiency decay law ( Figure 2 Based on this, it is recommended that maintenance or blade replacement be carried out around the 5th year. This invention can effectively realize the dynamic simulation and life prediction of crack defects, providing a scientific basis for power plant operation and maintenance.

[0054] Compared with the prior art, the present invention has the following advantages and effects: This invention introduces parametric modeling of cracks, cavitation pits, and wear, and performs bidirectional iterative calculations of the flow field and structural response within a fluid-structure interaction framework. This not only realistically reflects the dual impact of structural defects on hydrodynamic performance and structural safety, but also enables efficiency degradation and lifespan prediction by incorporating defect propagation patterns. Compared to existing technologies, this invention offers advantages such as a more comprehensive analysis scope, more dynamic predictive capabilities, higher computational accuracy, and superior application efficiency. It provides scientific support for turbine operation optimization, lifespan assessment, and maintenance cycle planning, demonstrating significant engineering application value.

[0055] Example 3 The numerical simulation system for structural defects in turbine blades based on fluid-structure interaction as described in this invention includes: The acquisition module is used to acquire the three-dimensional geometric model of the turbine blades and identify the defects in the turbine blades. The modeling module is used to model the identified defects using parametric methods; The coupling module is used to solve the flow field distribution using computational fluid dynamics methods and the response of the blade structure using finite element methods, based on defect modeling and within the fluid-structure interaction framework, and to achieve bidirectional coupling between the fluid domain and the structural domain through pressure boundaries, so as to obtain the fluid-structure interaction results. The analysis module is used to calculate efficiency loss, pressure pulsation characteristics and stress concentration distribution under various operating conditions of the turbine, and to analyze the comprehensive impact of defects on the performance and safety of the turbine blades. The prediction module is used to predict the growth pattern of defects over time based on the evolution model of defect expansion, and combined with the fluid-structure interaction results, to predict the efficiency decay curve and fatigue life of turbine blades.

[0056] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0057] Example 4 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the numerical simulation method for structural defects in a turbine blade based on fluid-structure interaction (FSI). For example, the steps include: acquiring a three-dimensional geometric model of the turbine blade and identifying existing defects; modeling the identified defects using a parametric method; based on the defect modeling, solving the flow field distribution using computational fluid dynamics within the FSI framework, solving the blade structure response using the finite element method, and achieving bidirectional coupling between the fluid domain and the structural domain through pressure boundaries to obtain FSI results; calculating efficiency loss, pressure pulsation characteristics, and stress concentration distribution under various operating conditions of the turbine, analyzing the comprehensive impact of defects on the performance and safety of the turbine blade; predicting the growth law of defects over operating time based on a defect propagation evolution model, and predicting the efficiency decay curve and fatigue life of the turbine blade based on the FSI results. The memory may include main memory, such as high-speed random access memory (RAM), or non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which may be an industry-standard architecture bus, a peripheral component interconnection standard bus, or an extended industry-standard architecture bus. The bus can be categorized as an address bus, data bus, or control bus. The memory stores programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0058] Example 5 A computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the numerical simulation method for structural defects in a turbine blade based on fluid-structure interaction (FSI). For example, the method includes: acquiring a three-dimensional geometric model of the turbine blade and identifying existing defects; modeling the identified defects using a parametric method; based on the defect modeling, solving the flow field distribution using computational fluid dynamics within a FSI framework, solving the blade structure response using the finite element method, and achieving bidirectional coupling between the fluid domain and the structural domain through pressure boundaries to obtain FSI results; calculating efficiency loss, pressure pulsation characteristics, and stress concentration distribution under various operating conditions of the turbine, analyzing the comprehensive impact of defects on the performance and safety of the turbine blade; predicting the growth law of defects over operating time based on a defect propagation evolution model, and predicting the efficiency decay curve and fatigue life of the turbine blade based on the FSI results. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0059] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0061] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0062] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0063] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0064] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0065] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A numerical simulation method for structural defects in hydraulic turbine blades based on fluid-structure interaction, characterized in that, include: Obtain a three-dimensional geometric model of the turbine blades and identify the defects in the turbine blades; The identified defects are modeled using a parametric method; Based on defect modeling, within the fluid-structure interaction framework, computational fluid dynamics is used to solve the flow field distribution, the finite element method is used to solve the blade structure response, and the two-way coupling between the fluid domain and the structural domain is achieved through pressure boundary to obtain the fluid-structure interaction results. Efficiency loss, pressure pulsation characteristics, and stress concentration distribution of the turbine were calculated under various operating conditions to analyze the comprehensive impact of defects on turbine blade performance and safety. Based on the evolutionary model of defect propagation, the growth law of defects with operating time is predicted, and combined with the fluid-structure interaction results, the efficiency decay curve and fatigue life of turbine blades are predicted.

2. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 1, characterized in that, The defects in the turbine blades include cracks, cavitation pits, and wear.

3. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 2, characterized in that, The process of modeling the identified defects using a parametric method is as follows: Modeling of crack defects using elliptical or semi-elliptical geometric functions; Gaussian concavity function is used to model pit defects; Piecewise linear functions are used to model wear defects.

4. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 1, characterized in that, The fluid domain is solved using incompressible RANS equations.

5. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 1, characterized in that, The structural domain was obtained using the finite element method.

6. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 1, characterized in that, The fluid pressure field is applied to the blade surface as a boundary load, and the structural displacement is updated and then fed back to the fluid domain, thus achieving bidirectional coupling.

7. The numerical simulation method for structural defects of turbine blades based on fluid-structure interaction according to claim 2, characterized in that, The specific steps for predicting the growth pattern of defects over runtime are as follows: For crack propagation, based on the laws of fracture mechanics, the growth rate of crack length with increasing load cycle number is described; For pothole expansion, an exponential saturation function is used to reflect the characteristics of rapid initial growth followed by saturation. For wear development, a linear or piecewise function is used to reflect the relationship between wear depth and operating time.

8. A numerical simulation system for structural defects in hydraulic turbine blades based on fluid-structure interaction, characterized in that, include: The acquisition module is used to acquire the three-dimensional geometric model of the turbine blades and identify the defects in the turbine blades. The modeling module is used to model the identified defects using parametric methods; The coupling module is used to solve the flow field distribution using computational fluid dynamics methods and the response of the blade structure using finite element methods, based on defect modeling and within the fluid-structure interaction framework, and to achieve bidirectional coupling between the fluid domain and the structural domain through pressure boundaries, so as to obtain the fluid-structure interaction results. The analysis module is used to calculate efficiency loss, pressure pulsation characteristics and stress concentration distribution under various operating conditions of the turbine, and to analyze the comprehensive impact of defects on the performance and safety of the turbine blades. The prediction module is used to predict the growth pattern of defects over time based on the evolution model of defect expansion, and combined with the fluid-structure interaction results, to predict the efficiency decay curve and fatigue life of turbine blades.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for generating and sending trusted status alarm information as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for generating and sending trusted status alarm information as described in any one of claims 1-7.

Images