Multi-field SN characteristic curve test and construction method, system, equipment and medium

Abstract

The invention discloses a multi-field SN characteristic curve test and construction method, system, equipment and medium, and belongs to the technical field of multi-body dynamics modeling and stress analysis, comprising the steps of analyzing stress distribution of a part under different working conditions by adopting a finite element simulation technology, and analyzing by adopting multi-field coupling simulation. And comprehensively describing the stress-life relationship under various working conditions, comparing the stress-life relationship with an SN curve under a traditional single working condition, fitting multi-working-condition data through a weighted least square method, and predicting the fatigue life of the part. According to the method, the influence of load spectrums under various working conditions on the service life of key components of the GIS operating mechanism can be considered; according to the method, the fitting effect of the multi-working-condition SN curve is optimized through the weighted least square method, the accuracy and reliability of fatigue life prediction are improved through the weight adjustment optimization algorithm, accurate data support can be provided for fault diagnosis and life prediction of GIS equipment, and the method has important engineering application value for design and maintenance of a GIS operating mechanism.

Description

Technical Field

[0001] This invention relates to the field of multibody dynamics modeling and stress analysis technology, specifically to a method, system, device, and medium for testing and constructing multi-field SN characteristic curves. Background Technology

[0002] With the continuous development of power system equipment, gas-insulated switchgear (GIS) is widely used in power systems. Key components of its operating mechanism are subjected to various loads during operation, especially under transient currents and mechanical shocks, where localized stress concentration is significant, posing a potential threat to the safety and reliability of the equipment. Therefore, how to scientifically and effectively assess the fatigue life of these key components has become a research hotspot in this field.

[0003] Currently, some studies have adopted fatigue life prediction methods based on SN curves, but most methods are limited to the analysis of a single working condition and cannot accurately characterize the complex alternating loads that components bear in actual operation. Their prediction results often deviate significantly from the actual situation. Therefore, it is particularly important to propose a method for constructing SN characteristic curves that can comprehensively consider the effects of multi-field coupling. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the present invention aims to provide a method for testing and constructing multi-field SN characteristic curves for local stress concentration in key components of vacuum-severable GIS. By systematically testing and constructing SN curves of components under multi-field coupling effects under different working conditions, and combining them with an improved fatigue life prediction algorithm, a reliable basis is provided for the operation monitoring and life prediction of key GIS components.

[0006] This invention relates to the field of multibody dynamics modeling and stress analysis of operating mechanisms for gas-insulated switchgear (GIS), and is applicable to dynamic response analysis, impact load assessment, and optimization design of GIS operating mechanisms.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for testing and constructing multi-field SN characteristic curves, comprising, By combining multi-field coupled simulation analysis, the stress distribution of key components of vacuum-breaking GIS under different working conditions is simulated and analyzed, and stress cloud maps are generated. Static and dynamic stress tests were conducted on key components to simulate load waveforms under different working conditions. At the same time, stress response data of key components were collected, and SN curves were plotted. The multi-field SN curve construction method constructs the SN curve for a single working condition based on the test data, and combines the stress-life data under different working conditions to obtain the comprehensive SN curve under multi-field coupling conditions. An improved fatigue damage prediction algorithm is used, combined with a comprehensive SN curve, to predict the fatigue life of the component. The predicted fatigue life of the component is compared with the actual operating data to determine if there are any deviations, and further analysis and optimization are carried out.

[0008] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method described in this invention, the generation of stress cloud map includes using finite element analysis combined with multi-field coupling simulation technology to simulate and analyze the stress distribution of key components of vacuum-breaking GIS under different working conditions. Get the material properties of the component material settings; Apply boundary condition constraints and fixed ends to the components according to the actual working conditions, and apply corresponding load conditions for each working condition.

[0009] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method described in this invention, the generation of stress cloud map further includes obtaining the stress distribution under each working condition by using coupled analysis of electromagnetic field, thermal field and force field during the simulation process. Through multi-field coupled simulation, stress cloud maps are generated for key components of vacuum-breaking GIS under each working condition, focusing on areas of local stress concentration.

[0010] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method of the present invention, the step of drawing the SN curve includes performing static and dynamic stress tests on the component to simulate load waveforms under different working conditions. Apply the corresponding load for each working condition, record the stress response of the component, and measure the stress response data at a specified number of cycles; Based on the collected stress response data, stress-life curves, i.e. SN curves, are plotted for each working condition.

[0011] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method described in this invention, the method for obtaining the comprehensive SN curve under multi-field coupling conditions includes: based on stress response data, plotting the SN curve for each working condition; and obtaining the relationship between stress and life by fitting experimental data. Where σ is the stress amplitude, N is the cycle life, a and b are material constants, and C is a constant; Based on the SN curves under two or more operating conditions, the curves are combined using the least squares method. For each operating condition's SN curve, weights are assigned according to importance or frequency of occurrence, and weighted processing is performed. The least squares method optimizes the parameters of the fitted curve by minimizing the sum of squared errors, thus obtaining the comprehensive SN curve; The comprehensive curve is optimized by smoothing the obtained comprehensive SN curve and removing outliers and noise.

[0012] The preferred technical solution in the embodiments of the present invention has the following beneficial effects: by accurately simulating the stress distribution of key components through multi-field coupling simulation, the local stress concentration area can be effectively identified, thereby improving the reliability and optimization efficiency of product design.

[0013] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method described in this invention, the predicted fatigue life of the component includes: using the obtained multi-field coupled SN curve as input to the algorithm, calculating fatigue damage using the Miner's rule of the combined SN curve, and calculating the corresponding damage for each working condition. in, It is the load frequency of the k-th load cycle. Under operating condition i, the load Fatigue life, for each working condition, degree of damage This indicates the degree of damage to the component under the current operating conditions; Total damage and remaining life prediction, calculating comprehensive damage under all operating conditions. : Where M represents the total number of operating conditions, and the remaining life prediction formula after calculating the comprehensive damage is as follows: in, Initial lifespan of a component.

[0014] The beneficial effects of the preferred technical solution in the embodiments of the present invention are as follows: based on static and dynamic stress tests, real stress-life data are obtained, providing experimental basis for fatigue life analysis and ensuring the accuracy of life prediction.

[0015] As a preferred embodiment of the multi-field SN characteristic curve testing and construction method described in this invention, the analysis and optimization includes comparing the fatigue life predicted by the algorithm with the fatigue life of the component during actual operation, and adjusting the algorithm based on experimental data when there is a deviation. The weights are adjusted using gradient descent to minimize the damage prediction error. The objective function F is: in, It is the predicted lifespan for the i-th operating condition. It represents the actual lifetime, and the goal is to minimize the current error function; After each weight adjustment, the composite SN curve is calculated using the new weights, and the consistency between the composite SN curve calculated with the actual data is verified. The weights are iteratively optimized until the optimal prediction effect is achieved.

[0016] The preferred technical solution in the embodiments of the present invention has the following beneficial effects: by integrating stress-life data under multiple working conditions, a more comprehensive fatigue life curve is obtained through weighted and smoothed processing, thereby enhancing the adaptability to complex working conditions.

[0017] Another objective of this invention is to provide a system for testing and constructing multi-field SN characteristic curves.

[0018] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a multi-field SN characteristic curve testing and construction system, comprising: a simulation analysis module, a testing module, a plotting module, a prediction module, and an optimization module; The simulation analysis module, combined with multi-field coupled simulation analysis, simulates and analyzes the stress distribution of key components of vacuum-breaking GIS under different working conditions, and generates stress cloud maps. The testing module performs static and dynamic stress tests on key components, simulates load waveforms under different working conditions, and collects stress response data of key components to plot SN curves. The plotting module uses a multi-field SN curve construction method. Based on the data obtained from the test, it constructs the SN curve for a single working condition and combines the stress-life data under different working conditions to obtain the comprehensive SN curve under multi-field coupling conditions. The prediction module uses an improved fatigue damage prediction algorithm, combined with a comprehensive SN curve, to predict the fatigue life of the component. The optimization module compares the predicted fatigue life of components with the actual operating data to determine if there are any deviations, and then performs further analysis and optimization.

[0019] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the multi-field SN characteristic curve testing and construction method described above.

[0020] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the multi-field SN characteristic curve testing and construction method described above.

[0021] The beneficial effects of this invention are as follows: This invention proposes for the first time a method for constructing SN characteristic curves combining multi-field coupling effects, which can more comprehensively evaluate the fatigue performance of key components of vacuum-interrupted GIS operating mechanisms. Through an improved fatigue damage prediction algorithm, considering stress distribution and load spectra under various working conditions, a mathematical model is provided for equipment life prediction. Compared with traditional single-working-condition prediction methods, the comprehensive SN curve and life prediction model constructed using the method of this invention are expected to improve prediction accuracy by more than 20%, providing a new approach for the operation monitoring and preventive maintenance of GIS operating mechanisms, and improving the operational safety and reliability of the equipment. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 The above is a flowchart of a method for testing and constructing multi-field SN characteristic curves according to an embodiment of the present invention.

[0024] Figure 2 The image shows an SN curve diagram of a multi-field SN characteristic curve testing and construction method provided in one embodiment of the present invention. Detailed Implementation

[0025] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0026] Example 1, referring to Figures 1-2 This is one embodiment of the present invention, which provides a method for testing and constructing multi-field SN characteristic curves, including: S100. Combining multi-field coupled simulation analysis, the stress distribution of key components of vacuum-breaking GIS under different working conditions is simulated and analyzed, and stress cloud maps are generated. S200. Perform static and dynamic stress tests on key components to simulate load waveforms under different working conditions, and simultaneously collect stress response data of key components to plot SN curves. S300, a multi-field SN curve construction method, constructs an SN curve for a single working condition based on the test data, and obtains a comprehensive SN curve under multi-field coupling conditions by integrating stress-life data under different working conditions. S400: An improved fatigue damage prediction algorithm is used, combined with a comprehensive SN curve, to predict the fatigue life of components. S500: Compare the predicted fatigue life of the component with the actual operating data to determine if there is any deviation, and then further analyze and optimize. It should be noted that existing technologies often have the disadvantage of failing to accurately identify local stress concentration areas in key components under complex multi-field coupling; relying on SN curves under a single operating condition cannot fully reflect the comprehensive fatigue characteristics of components under actual variable operating conditions; traditional fatigue life prediction methods have large errors and lack a closed-loop process for comparison and verification with actual operating data and continuous optimization.

[0027] Therefore, in response to the above-mentioned problems, through steps S100-S500, this invention proposes a method for testing and constructing multi-field SN characteristic curves for local stress concentration in key components of vacuum-severable GIS. This method effectively solves the problem of inaccurate fatigue life prediction caused by local stress concentration and multi-field coupling effects. Furthermore, through a closed-loop process of "prediction-comparison-optimization", it significantly improves the accuracy of fatigue life prediction and the reliability of component design.

[0028] Example 2, refer to Figures 1-2 This is one embodiment of the present invention, which provides a method for testing and constructing multi-field SN characteristic curves, including: In this embodiment of the invention, S100 combines multi-field coupled simulation analysis to simulate and analyze the stress distribution of key components of vacuum-breaking GIS under different working conditions, generating a stress cloud map, including the following steps S101-S102: S101. Combining multi-field coupling simulation analysis, the stress distribution of key components of vacuum-breaking GIS under different working conditions is simulated and analyzed. In an embodiment of the present invention, the stress distribution of key components of a vacuum-splitting GIS under different operating conditions is simulated and analyzed, including the following steps A1-A2: A1. Using finite element analysis (FEA) software, combined with multi-field coupled simulation technology such as electromagnetic field, thermal field and force field, the stress distribution of key components under different working conditions is simulated and analyzed. In an optional implementation, the simulation analysis in S101 can be based on multi-field coupled simulation analysis using the boundary element method. This involves establishing a surface geometric model of the key components of a vacuum-breaking GIS and generating a boundary mesh, ignoring the internal volume mesh division. The boundary element method is applied to establish boundary integral equations for the electromagnetic, thermal, and force fields, and material properties and boundary conditions are set. Through coupled boundary conditions, multi-field coupled iterative calculations are performed to simulate the field distribution of the key components under different operating conditions. Solving the boundary integral equations directly yields the stress distribution on the component surface, and extrapolates to generate an overall stress cloud map.

[0029] In another optional implementation, the simulation analysis in S101 can also be based on multi-field coupled simulation analysis using the finite difference method. A regular three-dimensional computational grid for key components of a vacuum-breaking GIS is established, the computational region is discretized into uniform grid cells, the control equations for the electromagnetic field, thermal field, and force field are discretized using the finite difference method, field variables are initialized, multi-field coupled boundary conditions are set, coupled simulation calculations are performed through time step iterations, stress values ​​on grid nodes are calculated, and stress distribution clouds of key components under different working conditions are generated through post-processing interpolation.

[0030] In an embodiment of the present invention, a corresponding load condition is applied to each working condition, including the following steps B1-B3: B1. Material properties need to be considered when building the model. The elastic modulus, Poisson's ratio and coefficient of thermal expansion of the material should be set according to the material of the component. B2. Boundary condition constraints and fixed ends need to be applied to the components according to the actual working conditions; B3. Apply the corresponding current load, temperature field and force load to each operating condition.

[0031] In an optional implementation, the corresponding load conditions applied in S101 can be applied sequentially. When the model is established, the basic properties of the material, such as the elastic modulus, Poisson's ratio, and coefficient of thermal expansion, are set according to the material of the component. Simple boundary condition constraints are applied to the component according to the actual working conditions. Load conditions are applied sequentially for each working condition: first, the temperature field load is applied and the steady-state thermal stress is calculated, and then the current load and force load are applied on this basis to perform sequential coupling analysis.

[0032] In another alternative implementation, the corresponding load conditions applied in S101 can also be set when the model is built by setting the elastic modulus, Poisson's ratio and coefficient of thermal expansion of the material. However, when using a simplified material model and applying boundary conditions, symmetric or periodic boundary conditions are used to reduce the complexity of the model and the amount of calculation. Standardized load conditions are applied to each working condition, and multi-field analysis is performed, but the load input is relatively simplified. However, this implementation cannot accurately capture the stress concentration and transient response under multi-field interaction.

[0033] S102. During the simulation, the stress distribution under each working condition is obtained by using coupled analysis of electromagnetic field, thermal field and force field. Through multi-field coupled simulation, stress cloud maps are generated for key components of vacuum-breaking GIS under each working condition, focusing on areas of local stress concentration.

[0034] In this embodiment of the invention, in step S200, static and dynamic stress tests are performed on key components to simulate load waveforms under different working conditions. Simultaneously, stress response data of the key components are collected, and SN curves are plotted. This includes the following steps S201-S203: S201. A testing system designed to capture the stress response of components under different working conditions, using testing equipment such as strain gauges and pressure sensors; S202. Apply the corresponding load for each working condition, record the stress response of the component, and measure the stress response data at the specified number of cycles; S203. Based on the collected stress response data, plot the stress-life curve, i.e., the SN curve, for each working condition.

[0035] In an embodiment of the present invention, in step S300, a single-condition SN curve is constructed based on the test data, and a comprehensive SN curve under multi-field coupling conditions is obtained by integrating stress-life data under different conditions, including the following steps S301-S302: In an embodiment of the present invention, S301, constructing the SN curve for a single operating condition includes the following steps C1-C2: C1. Based on the stress response data, plot the SN curve for each working condition to construct a single working condition; C2. By fitting the experimental data, the relationship between stress and life is obtained: Where σ is the stress amplitude, N is the cycle life, a and b are material constants, and C is a constant.

[0036] In an optional implementation, the SN curve for a single working condition in S301 can be constructed based on the SN curve construction of the grouped averaging method. Stress response data for each working condition is collected, including stress amplitude and corresponding cycle life data points. The stress amplitude range is divided into several equally spaced groups. For each stress amplitude group, the arithmetic mean of all cycle life data in the group is calculated. The data points are plotted with stress amplitude as the abscissa and average cycle life as the ordinate and connected into a smooth curve to form the SN curve for a single working condition. However, this implementation will ignore local variations due to data grouping. In another alternative implementation, the SN curve for a single working condition in S301 can also be constructed based on the SN curve of an empirical trend line. Stress response data for each working condition is collected, including stress amplitude and corresponding cycle life data points. According to the general properties of the material, the typical shape of the SN curve is predetermined. By visually observing the distribution of data points, a trend line passing through most data points is manually drawn, or linear interpolation is used to connect the data points to form the SN curve for a single working condition. However, this implementation relies on subjective judgment or pre-assumptions and cannot reflect the actual material behavior.

[0037] In an embodiment of the present invention, S302, by integrating stress-life data under different operating conditions, a comprehensive SN curve under multi-field coupling conditions is obtained, including the following steps D1-D3: D1. Based on the SN curves under two or more operating conditions, combine the curves using the least squares method. For the SN curve under each operating condition, assign weights according to importance or frequency of occurrence and perform weighted processing. D2. The least squares method optimizes the parameters of the fitted curve by minimizing the sum of squared errors, thus obtaining the comprehensive SN curve; D3. Comprehensive curve optimization: The obtained comprehensive SN curve is smoothed to remove outliers and noise.

[0038] In an optional implementation, the integrated SN curve obtained in S302 under multi-field coupling conditions can be constructed based on the integrated SN curve using the moving average method. Stress-life data points for each operating condition are collected, including stress amplitude and corresponding cycle life. Weights are assigned according to the importance or frequency of each operating condition, and the life value of each data point is weighted and calculated. After sorting by stress amplitude, the weighted life value is smoothed using the moving average method. The integrated life value is calculated step by step, and the integrated SN curve is formed by connecting the data points after the moving average. The continuity of the curve is then checked. However, this implementation loses the details of key stress concentration areas, resulting in a conservative life prediction.

[0039] In another optional implementation, the integrated SN curve obtained in S302 under multi-field coupling conditions can also be constructed based on a piecewise linear fitting integrated SN curve. The SN curve under each working condition is divided into multiple stress intervals. Within each stress interval, the data points of each working condition are weighted and averaged according to the weights to obtain the representative data points of that interval. The representative data points of each stress interval are connected using a piecewise linear function to form an integrated SN curve, ensuring that the curve is continuous at the interval connection points. Fine-tuning is performed on the piecewise connection points, and the overall curve is simply smoothed. However, in this implementation, piecewise linear fitting introduces unnatural turns at the boundaries of stress intervals, affecting the accuracy of the curve under varying working conditions.

[0040] In an embodiment of the present invention, an improved fatigue damage prediction algorithm is used in S400, combined with a comprehensive SN curve, to predict the fatigue life of the component, including the following steps S401-S402: S401. Using the obtained multi-field coupled SN curves as input to the algorithm, fatigue damage is calculated using the Miner's rule of the combined SN curves. For each working condition, the corresponding damage is calculated: in, It is the load frequency of the k-th load cycle. Under operating condition i, the load Fatigue life, for each working condition, degree of damage This indicates the degree of damage to the component under the current operating conditions.

[0041] S402. Total Damage and Remaining Life Prediction: Calculate the comprehensive damage under all operating conditions. : Where M represents the total number of operating conditions, and the remaining life prediction formula after calculating the comprehensive damage is as follows: in, Initial lifespan of a component.

[0042] In an embodiment of the present invention, step S500 compares the predicted fatigue life of the component with the actual operating data to determine whether there is a deviation, and further analyzes and optimizes the process, including: The fatigue life predicted by the algorithm is compared with the fatigue life of the component during actual operation. If there is a deviation, the algorithm is adjusted based on experimental data to further optimize the algorithm. The weights are adjusted using gradient descent to minimize the damage prediction error. The objective function F is: in, It is the predicted lifespan for the i-th operating condition. It represents the actual lifetime, and the goal is to minimize the current error function. The weight corresponding to the i-th working condition; Example 3 is an embodiment of the present invention, and the above is an illustrative scheme of a multi-field SN characteristic curve testing and construction method. It should be noted that the technical solution of a multi-field SN characteristic curve testing and construction system and the technical solution of the above-described multi-field SN characteristic curve testing and construction method belong to the same concept. Details not described in detail in the technical solution of the multi-field SN characteristic curve testing and construction system in this embodiment can be found in the description of the technical solution of the above-described multi-field SN characteristic curve testing and construction method.

[0043] This embodiment provides a multi-field SN characteristic curve testing and construction system, including: a simulation analysis module, a testing module, a plotting module, a prediction module, and an optimization module; The simulation analysis module, combined with multi-field coupled simulation analysis, simulates and analyzes the stress distribution of key components of vacuum-breaking GIS under different working conditions, and generates stress cloud maps. The testing module performs static and dynamic stress tests on key components, simulates load waveforms under different working conditions, and collects stress response data of key components to plot SN curves. The plotting module uses a multi-field SN curve construction method. Based on the data obtained from the test, it constructs the SN curve for a single working condition and combines the stress-life data under different working conditions to obtain the comprehensive SN curve under multi-field coupling conditions. The prediction module uses an improved fatigue damage prediction algorithm, combined with a comprehensive SN curve, to predict the fatigue life of the component. The optimization module compares the predicted fatigue life of components with the actual operating data to determine if there are any deviations, and then performs further analysis and optimization.

[0044] This embodiment also provides an electronic device applicable to a multi-field SN characteristic curve testing and construction method, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the multi-field SN characteristic curve testing and construction method proposed in the above embodiment.

[0045] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for testing and constructing multi-field SN characteristic curves as proposed in the above embodiments.

[0046] The storage medium proposed in this embodiment and the method for testing and constructing a multi-field SN characteristic curve proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0047] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0048] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for testing and constructing multi-field SN characteristic curves, characterized in that: include, By combining multi-field coupled simulation analysis, the stress distribution of key components of vacuum-breaking GIS under different working conditions is simulated and analyzed, and stress cloud maps are generated. Static and dynamic stress tests were conducted on key components to simulate load waveforms under different working conditions. At the same time, stress response data of key components were collected, and SN curves were plotted. The multi-field SN curve construction method constructs the SN curve for a single working condition based on the test data, and combines the stress-life data under different working conditions to obtain the comprehensive SN curve under multi-field coupling conditions. An improved fatigue damage prediction algorithm is used, combined with a comprehensive SN curve, to predict the fatigue life of the component. The predicted fatigue life of the component is compared with the actual operating data to determine if there are any deviations, and further analysis and optimization are carried out.

2. The method for testing and constructing multi-field SN characteristic curves as described in claim 1, characterized in that: The generation of stress cloud map includes using finite element analysis combined with multi-field coupling simulation technology to simulate and analyze the stress distribution of key components of vacuum-breaking GIS under different working conditions. Get the material properties of the component material settings; Apply boundary condition constraints and fixed ends to the components according to the actual working conditions, and apply corresponding load conditions for each working condition.

3. The method for testing and constructing multi-field SN characteristic curves as described in claim 2, characterized in that: The generation of stress cloud maps also includes using coupled analysis of electromagnetic field, thermal field and force field during the simulation process to obtain the stress distribution under each working condition; Through multi-field coupled simulation, stress cloud maps are generated for key components of vacuum-breaking GIS under each working condition, focusing on areas of local stress concentration.

4. The method for testing and constructing multi-field SN characteristic curves as described in claim 3, characterized in that: The process of plotting the SN curve includes performing static and dynamic stress tests on the component to simulate load waveforms under different working conditions. Apply the corresponding load for each working condition, record the stress response of the component, and measure the stress response data at a specified number of cycles; Based on the collected stress response data, stress-life curves, i.e. SN curves, are plotted for each working condition.

5. The method for testing and constructing multi-field SN characteristic curves as described in claim 4, characterized in that: The process of obtaining the integrated stress-response (SN) curve under multi-field coupling conditions includes: plotting a single-condition SN curve for each working condition based on stress response data; and obtaining the relationship between stress and life by fitting experimental data. Where σ is the stress amplitude, N is the cycle life, a and b are material constants, and C is a constant; Based on the SN curves under two or more operating conditions, the curves are combined using the least squares method. For each operating condition's SN curve, weights are assigned according to importance or frequency of occurrence, and weighted processing is performed. The least squares method optimizes the parameters of the fitted curve by minimizing the sum of squared errors, thus obtaining the comprehensive SN curve; The comprehensive curve is optimized by smoothing the obtained comprehensive SN curve and removing outliers and noise.

6. The method for testing and constructing multi-field SN characteristic curves as described in claim 5, characterized in that: The predicted fatigue life of the component includes using the obtained multi-field coupled SN curves as input to the algorithm, and calculating fatigue damage using the Miner's rule of the combined SN curves. For each working condition, the corresponding damage is calculated: in, It is the load frequency of the k-th load cycle. Under operating condition i, the load Fatigue life, for each working condition, degree of damage This indicates the degree of damage to the component under the current operating conditions; Total damage and remaining life prediction, calculating comprehensive damage under all operating conditions. : Where M represents the total number of operating conditions, and the remaining life prediction formula after calculating the comprehensive damage is as follows: in, Initial lifespan of a component.

7. The method for testing and constructing multi-field SN characteristic curves as described in claim 6, characterized in that: The analysis and optimization include comparing the fatigue life predicted by the algorithm with the fatigue life of the component during actual operation, and adjusting the algorithm based on experimental data when there are deviations. The weights are adjusted using gradient descent to minimize the damage prediction error. The objective function F is: in, It is the predicted lifespan for the i-th operating condition. It represents the actual lifetime, and the goal is to minimize the current error function; After each weight adjustment, the composite SN curve is calculated using the new weights, and the consistency between the composite SN curve calculated with the actual data is verified. The weights are iteratively optimized until the optimal prediction effect is achieved.

8. A system for testing and constructing multi-field SN characteristic curves, using the method for testing and constructing multi-field SN characteristic curves as described in any one of claims 1 to 7, characterized in that, include: Simulation analysis module, testing module, plotting module, prediction module, optimization module; The simulation analysis module, combined with multi-field coupled simulation analysis, simulates and analyzes the stress distribution of key components of vacuum-breaking GIS under different working conditions, and generates stress cloud maps. The testing module performs static and dynamic stress tests on key components, simulates load waveforms under different working conditions, and collects stress response data of key components to plot SN curves. The plotting module uses a multi-field SN curve construction method. Based on the data obtained from the test, it constructs the SN curve for a single working condition and combines the stress-life data under different working conditions to obtain the comprehensive SN curve under multi-field coupling conditions. The prediction module uses an improved fatigue damage prediction algorithm, combined with a comprehensive SN curve, to predict the fatigue life of the component. The optimization module compares the predicted fatigue life of components with the actual operating data to determine if there are any deviations, and then performs further analysis and optimization.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the multi-field SN characteristic curve testing and construction method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-field SN characteristic curve testing and construction method according to any one of claims 1 to 7.

Images