Water turbine top cover bolt time-varying reliability assessment method and device based on parameter sensitivity analysis

Abstract

The invention relates to the technical field of hydroelectric power generation equipment structure reliability evaluation, and particularly provides a water turbine top cover bolt time-varying reliability evaluation method and device based on parameter sensitivity analysis. According to the technical scheme provided by the invention, key variables are highlighted through parameter sensitivity analysis, and the response surface method and Monte Carlo simulation are combined, so that the calculation efficiency is remarkably improved while the precision is ensured, and the reliability evolution rule of the bolt in the whole life cycle can be scientifically represented; and an important basis is provided for maintenance decision and structure optimization of the water turbine top cover bolt.

Description

Technical Field

[0001] This invention relates to the field of structural reliability assessment technology for hydropower equipment, specifically to a method and apparatus for assessing the time-varying reliability of turbine top cover bolts based on parameter sensitivity analysis. Background Technology As core equipment in hydroelectric power plants and pumped storage power plants, the safety and stability of hydroelectric turbines directly affect the power generation efficiency and lifespan of the unit. In this type of equipment, the top cover and its fixing bolts are crucial structural units for connection and load-bearing. These bolts must not only withstand the hydrostatic pressure from the water flow but also bear the periodic dynamic loads and sudden hydraulic impacts generated during unit operation. If the bolts loosen, crack, or even break, it can easily lead to serious consequences such as top cover leakage, equipment damage, or even unit shutdown. Therefore, the safety and reliability of the bolts are key technical issues that must be focused on for the long-term stable operation of hydroelectric turbines.

[0002] Existing bolt design and verification methods largely rely on classical mechanical design theory and static calculation methods. Simplified models are typically used in structural calculations, neglecting bolt thread details, preload decay, contact nonlinearity effects, and material performance degradation during long-term service. Furthermore, current methods rely heavily on empirical safety factors, lacking systematic analysis based on probability statistics and reliability theory. This leads to two main problems in bolt design: firstly, excessive redundancy to ensure safety results in material waste and increased manufacturing costs; secondly, insufficient safety factors pose a risk of bolt failure during service. In recent years, the development of finite element analysis (FEM) technology has provided new insights into the stress analysis of complex structures. By establishing a three-dimensional refined finite element model, the geometric characteristics of bolts, material nonlinearity, and contact behavior between bolts and caps can be realistically reproduced, yielding stress distribution results closer to actual working conditions. Simultaneously, combining dynamic and static simulations with hydraulic impact simulations can reveal the failure mechanism of bolts under extreme loads. However, finite element analysis alone is insufficient to comprehensively evaluate the long-term reliability of bolts because its results depend on deterministic input parameters, making it difficult to account for factors such as material property fluctuations, manufacturing deviations, and uncertainties in the working environment. Summary of the Invention

[0003] To overcome the above-mentioned shortcomings, this invention proposes a method and apparatus for evaluating the time-varying reliability of turbine top cover bolts based on parameter sensitivity analysis.

[0004] Firstly, a time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis is provided, the method comprising: A parametric finite element model of the turbine top cover bolts was established based on the turbine's operating parameters and design drawings, and structural simulation was carried out under actual operating conditions. Based on the finite element calculation results, key parameters affecting the stress of the top cover bolts were identified through orthogonal experiments and variance analysis. Based on the identified key parameters and combined with the finite element simulation results, a response surface limit state function is constructed to determine whether the structure has failed. Based on the response surface limit state function, random samples are generated for Monte Carlo simulation, the structural failure probability is statistically analyzed, and the structural failure probability is used as a reliability evaluation index. Establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and analyze the reliability evaluation index of the turbine top cover bolts as a function of time within the design reference period.

[0005] Preferably, the step of establishing a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and conducting structural simulation under actual operating conditions, includes: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

[0006] Preferably, the key parameters affecting the stress of the top cover bolts are identified based on the finite element calculation results through orthogonal experiments and variance analysis, including: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

[0007] Furthermore, the contribution of the parameters is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

[0008] Preferably, the step of constructing a response surface limit state function for determining whether a structure has failed, based on the identified key parameters and combined with finite element simulation results, includes: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using the Latin hypercube sampling method. For each combination of parameters at the sampling points, the structural response is calculated using the parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

[0009] Preferably, the step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

[0010] Furthermore, when the calculated value of the response surface limit state function is less than 0, it is determined that the structure has failed; when the calculated value of the response surface limit state function is greater than 0, it is determined that the structure has not failed.

[0011] Secondly, a time-varying reliability assessment device for turbine top cover bolts based on parameter sensitivity analysis is provided, the device comprising: The simulation module is used to establish a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and to conduct structural simulation under actual operating conditions. The identification module is used to identify key parameters affecting the stress of the top cover bolts based on finite element calculation results, through orthogonal experiments and variance analysis. The module is used to construct a response surface limit state function to determine whether a structure has failed, based on the identified key parameters and the results of finite element simulation. The statistics module is used to generate random samples based on the response surface limit state function to perform Monte Carlo simulation, calculate the structural failure probability, and use the structural failure probability as a reliability evaluation index. The demonstration module is used to establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and to analyze the reliability evaluation index of turbine top cover bolts as they change over time within the design reference period.

[0012] Preferably, the step of establishing a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and conducting structural simulation under actual operating conditions, includes: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

[0013] Preferably, the key parameters affecting the stress of the top cover bolts are identified based on the finite element calculation results through orthogonal experiments and variance analysis, including: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

[0014] Furthermore, the contribution of the parameters is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

[0015] Preferably, the step of constructing a response surface limit state function for determining whether a structure has failed, based on the identified key parameters and combined with finite element simulation results, includes: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using a Latin hypercube sampling device. For each combination of parameters at the sampling points, the structural response is calculated using a parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

[0016] Preferably, the step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

[0017] Furthermore, when the calculated value of the response surface limit state function is less than 0, it is determined that the structure has failed; when the calculated value of the response surface limit state function is greater than 0, it is determined that the structure has not failed.

[0018] Thirdly, a computer device is provided, comprising: one or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis is implemented.

[0019] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed, the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis is implemented.

[0020] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects: This invention provides a method and apparatus for evaluating the time-varying reliability of turbine top cover bolts based on parameter sensitivity analysis. The method includes: establishing a parameterized finite element model of the turbine top cover bolts based on turbine operating parameters and design drawings, and conducting structural simulation under actual operating conditions; identifying key parameters affecting the stress of the top cover bolts based on the finite element calculation results through orthogonal experiments and variance analysis; constructing a response surface limit state function to determine whether the structure has failed, based on the identified key parameters and the finite element simulation results; generating random samples based on the response surface limit state function for Monte Carlo simulation, statistically analyzing the structural failure probability, and using the structural failure probability as a reliability evaluation index; establishing a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and analyzing the reliability evaluation index of the turbine top cover bolts changing over time within the design reference period. The technical solution provided by this invention accurately identifies key parameters affecting bolt reliability through parameter sensitivity analysis, establishes an efficient limit state function approximation model using the response surface method, and significantly improves computational efficiency by combining important sampling Monte Carlo simulation, ultimately achieving accurate evaluation of time-varying reliability within the design reference period. Compared with existing technologies, this invention has the following outstanding advantages: it highlights key points through sensitive parameter analysis, significantly reducing the amount of computation; it uses a response surface model to replace complex finite element calculations, greatly improving analysis efficiency; it provides accurate reliability index calculations based on Monte Carlo simulation; and its time-varying reliability assessment is more in line with actual engineering needs, providing a scientific basis for the optimized design and safety assessment of turbine top cover bolts. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the main steps of the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis according to an embodiment of the present invention. Detailed Implementation

[0022] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0023] 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 embodiments of the present invention, not all embodiments. 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.

[0024] Example 1 See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis, according to an embodiment of the present invention. Figure 1 As shown, the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis in this embodiment of the invention mainly includes the following steps: Step S101: Based on the turbine operating parameters and design drawings, establish a parametric finite element model of the turbine top cover bolts, and conduct structural simulation under actual operating conditions; Based on the finite element calculation results, key parameters affecting the stress of the top cover bolts were identified through orthogonal experiments and variance analysis. Based on the identified key parameters and combined with the finite element simulation results, a response surface limit state function is constructed to determine whether the structure has failed. Based on the response surface limit state function, random samples are generated for Monte Carlo simulation, the structural failure probability is statistically analyzed, and the structural failure probability is used as a reliability evaluation index. Establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and analyze the reliability evaluation index of the turbine top cover bolts as a function of time within the design reference period.

[0025] In this embodiment, the step of establishing a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and conducting structural simulation under actual operating conditions, includes: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

[0026] In one specific implementation, step S101 is carried out according to the following steps: Step 1011: Based on the 3D engineering drawings and 3D design data provided by the purchaser, use the 3D modeling software UG to create a 3D geometric model of the top cover and bolts. Accurately reproduce the geometric features of bolt threads, bolt holes, preload sections, nut end faces, and local reinforcing ribs of the top cover. For the bolt thread area, a refined modeling method is adopted to ensure that the stress concentration area is accurately reflected.

[0027] Step 1012 assigns accurate material properties to each component, such as the elastic modulus, Poisson's ratio, yield strength, tensile strength, etc. According to the actual operating conditions of the turbine, loads and boundary conditions are applied to the finite element model, including bolt preload, water pressure, mechanical constraints, and temperature loads.

[0028] Step 1013: The entire area of ​​the top cover bolt is divided into tetrahedral or hexahedral elements. The bolt thread and contact area are locally densified. The element size is controlled within the range of 0.2 to 0.5 mm to ensure the accuracy of stress distribution calculation in the high stress gradient area. The final number of elements and the division scheme are determined through mesh independence analysis.

[0029] Step 1014: Apply water pressure, temperature load and dynamic pressure load that may occur during actual operation, compare the finite element simulation calculation results with existing experimental data or engineering data, verify the accuracy of the model, adjust material parameters or contact conditions, and ensure that the finite element model can reflect the actual stress performance of the prototype structure.

[0030] Step 1015 involves parameterizing the geometric parameters, material parameters, and load parameters of the top cover bolts as design variables, establishing the correlation between the parameters and the stress response parameters of the top cover bolts, and constructing a parameterized finite element calculation model for the top cover bolts.

[0031] In this embodiment, the identification of key parameters affecting the stress of the top cover bolts based on finite element calculation results, through orthogonal experiments and variance analysis, includes: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. The key response results include the maximum equivalent stress, contact surface slip, axial tensile force, and resistance index.

[0032] Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

[0033] In one implementation, the contribution of the parameter is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

[0034] In this embodiment, the construction of the response surface limit state function for determining whether a structure has failed, based on the identified key parameters and combined with finite element simulation results, includes: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using the Latin hypercube sampling method. For each combination of parameters at the sampling points, the structural response is calculated using the parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

[0035] The response surface limit state function is used to calculate the approximate limit state function value. The coefficient of determination is used to evaluate the overall goodness of fit, and the maximum relative error (MRE) verifies the model's approximation accuracy on the training samples. Only when the coefficient of determination is greater than 0.95 and the maximum relative error is greater than 0.9 is the response surface model considered to accurately represent the response surface limit state function.

[0036] In this embodiment, the step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

[0037] In one implementation, when the calculated value of the response surface limit function is less than 0, the structure is determined to have failed; when the calculated value of the response surface limit function is greater than 0, the structure is determined not to have failed.

[0038] In one specific implementation, step S105 is carried out as follows: Step 1051: Establish mathematical models for the degradation of key parameters over time to accurately describe time-varying characteristics. The material performance degradation model adopts an exponential decay model to describe the law of material strength degradation over time; the preload relaxation model adopts an exponential function; and the load time-varying model adopts a linear growth model.

[0039] Step 1052, based on the above time-varying model, performs reliability calculations and discretizes the design reference period into several time points using an equal-interval division method.

[0040] Step 1053 updates the parameter values ​​for each time point, corrects the response surface model, embeds the Monte Carlo simulation into the time series framework, calculates the failure probability at the current time, and calculates the reliability index at the corresponding time.

[0041] Step 1054: Plot the reliability index change curve over time to visually demonstrate the reliability evolution trend. Based on engineering specifications and industry requirements, set a reliability target threshold to assess whether the results meet the design reference period requirements. Based on the time-varying reliability results, conduct in-depth analysis and propose optimization measures.

[0042] Example 2 Based on the same inventive concept, this invention also provides a time-varying reliability assessment device for turbine top cover bolts based on parameter sensitivity analysis, the time-varying reliability assessment device for turbine top cover bolts based on parameter sensitivity analysis comprising: The simulation module is used to establish a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and to conduct structural simulation under actual operating conditions. The identification module is used to identify key parameters affecting the stress of the top cover bolts based on finite element calculation results, through orthogonal experiments and variance analysis. The module is used to construct a response surface limit state function to determine whether a structure has failed, based on the identified key parameters and the results of finite element simulation. The statistics module is used to generate random samples based on the response surface limit state function to perform Monte Carlo simulation, calculate the structural failure probability, and use the structural failure probability as a reliability evaluation index. The demonstration module is used to establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and to analyze the reliability evaluation index of turbine top cover bolts as they change over time within the design reference period.

[0043] Preferably, the step of establishing a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and conducting structural simulation under actual operating conditions, includes: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

[0044] Preferably, the key parameters affecting the stress of the top cover bolts are identified based on the finite element calculation results through orthogonal experiments and variance analysis, including: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

[0045] Furthermore, the contribution of the parameters is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

[0046] Preferably, the step of constructing a response surface limit state function for determining whether a structure has failed, based on the identified key parameters and combined with finite element simulation results, includes: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using a Latin hypercube sampling device. For each combination of parameters at the sampling points, the structural response is calculated using a parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

[0047] Preferably, the step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

[0048] Furthermore, when the calculated value of the response surface limit state function is less than 0, it is determined that the structure has failed; when the calculated value of the response surface limit state function is greater than 0, it is determined that the structure has not failed.

[0049] Example 3 Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis in the above embodiments.

[0050] Example 4 Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis in the above embodiments.

[0051] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.

[0052] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0053] 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.

[0054] 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.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis, characterized in that, The method includes: A parametric finite element model of the turbine top cover bolts was established based on the turbine's operating parameters and design drawings, and structural simulation was carried out under actual operating conditions. Based on the finite element calculation results, key parameters affecting the stress of the top cover bolts were identified through orthogonal experiments and variance analysis. Based on the identified key parameters and combined with the finite element simulation results, a response surface limit state function is constructed to determine whether the structure has failed. Based on the response surface limit state function, random samples are generated for Monte Carlo simulation, the structural failure probability is statistically analyzed, and the structural failure probability is used as a reliability evaluation index. Establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and analyze the reliability evaluation index of the turbine top cover bolts as a function of time within the design reference period.

2. The method as described in claim 1, characterized in that, The process involves establishing a parametric finite element model of the turbine top cover bolts based on turbine operating parameters and design drawings, and conducting structural simulation under actual operating conditions, including: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

3. The method as described in claim 1, characterized in that, Based on the finite element analysis results, key parameters affecting the stress of the top cover bolts were identified through orthogonal experiments and variance analysis, including: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

4. The method as described in claim 3, characterized in that, The contribution of the parameters is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

5. The method as described in claim 1, characterized in that, Based on the identified key parameters and combined with finite element simulation results, a response surface limit state function is constructed to determine whether the structure has failed, including: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using the Latin hypercube sampling method. For each combination of parameters at the sampling points, the structural response is calculated using the parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

6. The method as described in claim 1, characterized in that, The step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

7. The method as described in claim 6, characterized in that, When the calculated value of the response surface limit state function is less than 0, the structure is determined to have failed; when the calculated value of the response surface limit state function is greater than 0, the structure is determined not to have failed.

8. A time-varying reliability assessment device for turbine top cover bolts based on parameter sensitivity analysis, characterized in that, The device includes: The simulation module is used to establish a parametric finite element model of the turbine top cover bolts based on the turbine's operating parameters and design drawings, and to conduct structural simulation under actual operating conditions. The identification module is used to identify key parameters affecting the stress of the top cover bolts based on finite element calculation results, through orthogonal experiments and variance analysis. The module is used to construct a response surface limit state function to determine whether a structure has failed, based on the identified key parameters and the results of finite element simulation. The statistics module is used to generate random samples based on the response surface limit state function to perform Monte Carlo simulation, calculate the structural failure probability, and use the structural failure probability as a reliability evaluation index. The demonstration module is used to establish a model of the degradation law of material properties over time and the time-varying characteristics of external loads, and to analyze the reliability evaluation index of turbine top cover bolts as they change over time within the design reference period.

9. The apparatus as claimed in claim 8, characterized in that, The process involves establishing a parametric finite element model of the turbine top cover bolts based on turbine operating parameters and design drawings, and conducting structural simulation under actual operating conditions, including: Based on the design dimensions and parameters of the turbine top cover bolts, a three-dimensional model of the turbine top cover bolts was established. Based on the aforementioned three-dimensional model, meshing was performed, material properties were assigned to each component of the top cover bolt, and boundary conditions and loads were set according to the actual operating conditions of the top cover bolt to obtain the finite element model of the top cover bolt. The finite element model of the top cover bolt is parametrically set, and the material property parameters, geometric dimension parameters and load parameters of the top cover bolt are input as controllable variable parameters.

10. The apparatus as claimed in claim 8, characterized in that, Based on the finite element analysis results, key parameters affecting the stress of the top cover bolts were identified through orthogonal experiments and variance analysis, including: The orthogonal experimental design method is used to select the appropriate orthogonal table based on the number of design variables of the turbine top cover bolts, and generate a finite combination scheme of design parameters for the turbine top cover bolts. Each set of parameter combinations generated in the orthogonal test table is input into the finite element analysis software to construct a finite element model of the top cover bolt. The model is then calculated to obtain the key response results of the bolt. Perform variance analysis on the finite element calculation results to calculate the total sum of squares and the sum of squares of each factor; The contribution of each parameter is calculated based on the total sum of squares and the sum of squares of each factor. Parameters whose contribution exceeds the preset value are considered as key parameters affecting the stress of the top cover bolts.

11. The apparatus as claimed in claim 10, characterized in that, The contribution of the parameters is as follows: P=(ST / SF)100% In the above formula, P represents the contribution of the parameter, ST represents the total sum of squares, and SF represents the sum of squares of the total sum of squares and the sum of squares of the parameter.

12. The apparatus as claimed in claim 8, characterized in that, Based on the identified key parameters and combined with finite element simulation results, a response surface limit state function is constructed to determine whether the structure has failed, including: Using key parameters as input variables, a set of sampling points is generated in the multidimensional parameter space using a Latin hypercube sampling device. For each combination of parameters at the sampling points, the structural response is calculated using a parameterized finite element model of the turbine top cover bolts, and a set of relationships between input and output parameters is established. Based on the relation set, the response surface limit state function is constructed using the response surface method.

13. The apparatus as claimed in claim 8, characterized in that, The step of generating random samples based on the response surface limit state function to perform Monte Carlo simulation and statistically analyzing the structural failure probability includes: Key parameters are modeled using probability distributions, and important sampling methods are used to sample input variables. Monte Carlo simulations were performed on the sampled data. The simulation results were input into the response surface limit state function. The number of structural failure events was recorded, and the structural failure probability was calculated.

14. The apparatus as claimed in claim 13, characterized in that, When the calculated value of the response surface limit state function is less than 0, the structure is determined to have failed; when the calculated value of the response surface limit state function is greater than 0, the structure is determined not to have failed.

15. A computer device, characterized in that, include: One or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis as described in any one of claims 1 to 7 is implemented.

16. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the time-varying reliability assessment method for turbine top cover bolts based on parameter sensitivity analysis as described in any one of claims 1 to 7.

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