Vacuum breaking type GIS multi-field coupling method, system and device for introducing material degradation function into pressure-strength interference and medium

Abstract

The invention discloses a vacuum breaking type GIS multi-field coupling method, system, equipment and medium for introducing a material degradation function into pressure-strength interference, and the method comprises the steps: achieving the quantitative description of the dynamic attenuation of the strength of a part along with the time through the building of the material degradation function, and enabling a reliability model to better fit the actual service condition; a multi-field coupling finite element model is constructed, potential distribution is accurately simulated by solving a Poisson equation, and dynamic load characteristics of a key area are analyzed and identified through stress response. Meanwhile, an improved particle swarm algorithm with an adaptive inertia weight and a variation mechanism is introduced in a model parameter identification link, so that the convergence speed and the global optimization capability of parameter optimization are effectively improved, and the accuracy and the efficiency of model calibration are ensured. Interference integration is carried out on time-varying intensity and pressure distribution, large-scale random sampling verification is carried out by adopting a Monte Carlo method, and accurate prediction of the dynamic reliability of the part in the whole life cycle is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of multi-body dynamics optimization of a high-voltage gas insulated switchgear (GIS) operating mechanism, and in particular to a vacuum breaking type GIS multi-field coupling method, system, device and medium that introduces a material degradation function into pressure-strength interference. BACKGROUND

[0002] The vacuum breaking type gas insulated switchgear is a key device in a high-voltage power transmission and distribution system, and its internal key operating mechanism is long-term operated in a complex multi-field coupling environment of high electric field, high mechanical stress and thermal shock. During long-term service, the key components of the vacuum breaking type gas insulated switchgear not only bear steady-state mechanical load and thermal load, but also are subjected to the superimposed effects of electric field breakdown, temperature accumulation effect and stress cycle, which leads to gradual degradation of material performance, decay of strength with time, and further affects the overall reliability and service life of the device.

[0003] At present, the reliability evaluation method of the component is mainly based on the static strength criterion or the single stress interference theory, and the existing evaluation method does not consider the time-varying degradation characteristics of the material under the long-term multi-field coupling effect, and it is difficult to accurately reflect the synergistic degradation effect of temperature, electric field and mechanical cyclic load on the material performance in the actual working condition. The results of the existing reliability evaluation method deviate from the actual situation, and the life prediction has a large deviation. In addition, although some technologies in the existing research use finite element-statistical methods for reliability analysis, most of them do not deeply integrate the material degradation mechanism and multi-field stress response, and still lack the modeling ability of dynamic evolution of strength distribution with time.

[0004] Therefore, there is an urgent need for a vacuum breaking type GIS multi-field coupling method that introduces a material degradation function into pressure-strength interference, to realize accurate prediction of the reliability and life evaluation of the key components of the vacuum breaking type GIS in the whole life cycle. SUMMARY

[0005] In view of the above existing problems, the present application is proposed.

[0006] Therefore, the present application provides a vacuum breaking type GIS multi-field coupling method, system, device and medium that introduces a material degradation function into pressure-strength interference, to solve the problem that the existing technology cannot accurately describe the strength degradation and multi-field stress superposition effect of the key components of the vacuum breaking type GIS during service.

[0007] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a vacuum breaking type GIS multi-field coupling method that introduces a material degradation function into pressure-strength interference, comprising: Key bearing components in vacuum interrupter type GIS operating mechanism are selected, and a solid finite element model integrating multiple loads is established according to three-dimensional geometric parameters; Based on the solid finite element model, a material degradation function is established according to the degradation mechanism of the material under the action of temperature accumulation, electric field breakdown and stress cycle; According to the material degradation function, a pressure distribution function is constructed, and the reliability is calculated by interference integral combined with the strength distribution function; The simulation data and experimental data of the solid finite element model are used to construct a comprehensive error objective function, the first optimization algorithm is used to obtain the optimal solution of the comprehensive error objective function, and the parameters of the pressure distribution function and the strength distribution function are corrected through the optimal solution; The service life interval of the component is discretized into multiple time steps, the reliability is calculated step by step based on the corrected function, and the Monte Carlo method is used to verify the calculation result.

[0008] As a preferred scheme of the vacuum interrupter type GIS multi-field coupling method of introducing a material degradation function into pressure-strength interference, wherein: the establishment of the material degradation function comprises: The key mechanisms of material degradation are the organization softening caused by temperature accumulation, the micro-crack growth caused by electric field breakdown and the fatigue damage induced by stress cycle, the key mechanisms of material degradation are coupled, and the material degradation function is established; Based on the material degradation function and the initial strength of the material, the instantaneous strength of the material at any time is calculated; Randomness is introduced based on the instantaneous strength, and it is assumed that the material strength obeys normal distribution, wherein the distribution mean value is determined by the instantaneous strength, and the standard deviation is obtained according to experimental statistics, and then the time-varying probability distribution of the material strength is constructed.

[0009] As a preferred scheme of the vacuum interrupter type GIS multi-field coupling method of introducing a material degradation function into pressure-strength interference, wherein: the pressure distribution function is constructed according to the material degradation function, combined with the strength distribution function, and the reliability is calculated by interference integral, comprising: The pressure distribution function is constructed according to the material degradation function, wherein it is assumed that the pressure obeys normal distribution, and the mean value and the standard deviation change with time; Based on the time-varying probability distribution of the material strength, the strength distribution function is obtained; The pressure distribution function and the strength distribution function are subjected to interference integral calculation, and the reliability of the component at any given time is obtained.

[0010] As a preferred scheme of the vacuum breaking type GIS multi-field coupling method of introducing material degradation function into pressure-strength interference, wherein: the component service life interval is discretized into a plurality of time steps, and the reliability is calculated step by step based on the modified function, comprising: The component service life interval is discretized into a plurality of time steps, and the probability distribution of strength and the probability distribution of pressure are recalculated at each time step based on the modified material degradation function and the pressure distribution function; At each discrete time step, the pressure-strength interference integral calculation is performed to obtain the dynamic reliability corresponding to the time.

[0011] As a preferred scheme of the vacuum breaking type GIS multi-field coupling method of introducing material degradation function into pressure-strength interference, wherein: the entity finite element model integrating multiple loads is established according to three-dimensional geometric parameters, comprising: An entity finite element model is established according to the three-dimensional geometric parameters of the key load-bearing component, and mesh refinement is performed on the stress transmission path and high stress concentration area of the model, and the mesh element size is required to be not greater than a set value; Synchronous application of three types of boundary conditions of mechanical load, thermal load and electric field load on the entity finite element model, wherein the mechanical load includes the steady-state working pressure applied on the sealing ring contact surface and the contact pressure stress applied on the key contact pair, the thermal load includes the environmental temperature boundary applied on the outer surface of the shell and the exposed surface of the insulating part, and the electric field load is obtained by applying the rated voltage on the outer surface of the insulating part and solving the Poisson equation to obtain the electric potential distribution; Based on the applied load conditions, the stress response of the model under the action of multi-field coupling is solved by finite element analysis, and the dynamic load data of the key area is extracted.

[0012] The beneficial effects of the preferred technical scheme are: considering the superposition of heat, electricity, force and other fields, reflecting the stress response under the real service environment.

[0013] As a preferred scheme of the vacuum breaking type GIS multi-field coupling method of introducing material degradation function into pressure-strength interference, wherein: the construction of the comprehensive error objective function comprises: The simulation data and experimental data of the entity finite element model are used to construct a comprehensive error objective function F(x), which is expressed as: Wherein, And Indicates the weight coefficient, which is used to balance the relative importance of pressure and strength error; m indicates the number of pressure data points for fitting, and n indicates the number of strength data points for fitting, Indicates the model at time The simulated pressure value, Indicates at time The measured pressure value, Indicates the strength of the model's prediction. This represents the intensity data measured in the experiment.

[0014] As a preferred embodiment of the vacuum-severed GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in this invention, wherein: obtaining the optimal solution of the comprehensive error objective function using a first optimization algorithm includes: Set the particle swarm size and randomly generate the initial position and velocity of each particle, where each particle represents a set of parameter combinations to be identified. In each iteration, the velocity and position of each particle are updated based on its own historical best position and the group's historical best position, combined with adaptively changing inertial weights and learning factors. Monitor the diversity of the particle swarm. When the diversity of the swarm is lower than the first threshold, apply an adaptive mutation operation to some particles to avoid the algorithm from converging to a local optimum too early. Set an iteration termination condition: when the improvement rate of the objective function is lower than the first threshold or the maximum number of iterations is reached for several consecutive generations, output the current population's historical best position as the optimal parameter solution.

[0015] The beneficial effects of this preferred technical solution are: the introduction of an improved particle swarm optimization algorithm improves the accuracy of model parameter identification and the speed of computational convergence.

[0016] Secondly, this invention provides a vacuum-severed GIS multi-field coupling system that incorporates material degradation functions into pressure-intensity interference, comprising: The multi-field coupled stress modeling module is used to select key load-bearing components in vacuum-splitting GIS operating mechanisms and establish solid finite element models that integrate multiple loads based on three-dimensional geometric parameters. The material degradation function establishment module is used to establish a material degradation function based on the solid finite element model and according to the degradation mechanism of the material under temperature accumulation, electric field breakdown and stress cycle. The interference reliability calculation module is used to construct a pressure distribution function based on the material degradation function, combine it with the intensity distribution function, and calculate the reliability through interference integral. The parameter correction module is used to construct a comprehensive error objective function using the simulation data and experimental data of the solid finite element model, obtain the optimal solution of the comprehensive error objective function using the first optimization algorithm, and correct the parameters of the pressure distribution function and intensity distribution function using the optimal solution. A dynamic reliability evolution module is configured to discretize the service life interval of the component into multiple time steps, calculate the reliability at each time step based on the modified function, and verify the calculation results by using the Monte Carlo method.

[0017] In a third aspect, the present application provides an electronic device comprising a memory and a processor; the memory is configured to store computer executable instructions, and the processor is configured to implement the steps of a method for introducing material degradation function into pressure-strength interference of vacuum interrupter type GIS multi-field coupling when executing the computer executable instructions.

[0018] In a fourth aspect, the present application provides a computer readable storage medium storing computer executable instructions, and the computer executable instructions are configured to implement the steps of a method for introducing material degradation function into pressure-strength interference of vacuum interrupter type GIS multi-field coupling when executed by a processor.

[0019] Compared with the prior art, the present application has the following beneficial effects: by introducing the material degradation function into the pressure-strength interference theory, a dynamic reliability analysis model integrating thermal, electrical and force multi-field coupling is constructed, which can more realistically reflect the performance degradation and stress response of the key components in the actual service environment. The present application not only significantly improves the reliability prediction accuracy of the key components of the vacuum interrupter type GIS in the whole life cycle, but also improves the efficiency and global convergence of the model parameter identification by introducing the improved optimization algorithm, thereby providing more reliable theoretical basis and engineering support for the design optimization, life evaluation and operation decision of the equipment. In addition, the present application can quantify the comprehensive influence of micro-crack evolution, thermal fatigue and electrical aging on reliability, and has high engineering practicability. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Figure 1 The overall flow logic diagram of the method for introducing material degradation function into pressure-strength interference of vacuum interrupter type GIS multi-field coupling provided by an embodiment of the present application is shown.

[0022] Figure 2 The material degradation and strength time-varying evolution diagram of the method for introducing material degradation function into pressure-strength interference of vacuum interrupter type GIS multi-field coupling provided by an embodiment of the present application is shown.

[0023] Figure 3A particle swarm algorithm convergence curve diagram of a vacuum interrupter type GIS multi-field coupling method provided by an embodiment of the present application introduces a material degradation function into pressure-strength interference. DETAILED DESCRIPTION

[0024] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0025] Embodiment 1, Reference Figure 1 For an embodiment of the present application, a vacuum interrupter type GIS multi-field coupling method is provided, which introduces a material degradation function into pressure-strength interference, as shown in Figure 1 and specifically includes the following steps: S100: selecting a key load-bearing component in a vacuum interrupter type GIS operating mechanism, and establishing an entity finite element model integrating multiple loads according to three-dimensional geometric parameters; S200: based on the entity finite element model, establishing a material degradation function according to the degradation mechanism of the material under the action of temperature accumulation, electric field breakdown and stress cycle; S300: constructing a pressure distribution function according to the material degradation function, combining a strength distribution function, and calculating reliability through interference integration; S400: constructing a comprehensive error objective function using simulation data and experimental data of the entity finite element model, obtaining an optimal solution of the comprehensive error objective function by using a first optimization algorithm, and correcting parameters of the pressure distribution function and the strength distribution function through the optimal solution; S500: discretizing a component service life interval into multiple time steps, calculating reliability step by step based on the corrected function, and verifying the calculation results by using a Monte Carlo method.

[0026] It should be noted that, in order to solve the problem that the strength degradation and multi-field stress superposition effect of key components of vacuum interrupter type GIS in the service process cannot be accurately described in the prior art, the material degradation function is introduced into the pressure-strength interference theory to construct a dynamic reliability analysis model integrating thermal, electrical and force multi-field coupling, which can more truly reflect the performance degradation and stress response of the key components in the actual service environment. The present application not only significantly improves the reliability prediction accuracy of the key components of the vacuum interrupter type GIS in the whole life cycle, but also improves the efficiency and global convergence of model parameter identification by introducing an improved optimization algorithm, thereby providing more reliable theoretical basis and engineering support for design optimization, life evaluation and operation decision of the equipment. In addition, the present application can quantify the comprehensive influence of micro-crack evolution, thermal fatigue and electrical aging on reliability, and has high engineering practicability.

[0027] Embodiment 2, refer to Figure 2 and Figure 3 Based on the previous embodiment, the present embodiment provides a specific embodiment of a vacuum interrupter type GIS multi-field coupling method by introducing a material degradation function into pressure-strength interference, which is used to illustrate the technical means used in the method.

[0028] In the embodiment of the present application, the above-mentioned step S100 selects the key load-bearing component in the vacuum interrupter type GIS operating mechanism, and the establishment of the entity finite element model integrating multiple loads according to the three-dimensional geometric parameters includes the following sub-steps A1~A3: In A1: the entity finite element model is established according to the three-dimensional geometric parameters of the key load-bearing component, and the mesh refinement is implemented on the stress transmission path and the high stress concentration area of the model, and the mesh element size is required to be not greater than the set value; Specifically, the set value in the present embodiment is 0.2mm, which is to ensure the calculation accuracy in the high stress concentration area and the vicinity of the key contact pair, so as to accurately capture the local stress gradient change and micro contact behavior, thereby providing sufficient grid resolution support for subsequent multi-field coupling analysis and reliability evaluation.

[0029] In A2: the three types of boundary conditions of mechanical load, thermal load and electric field load are simultaneously applied on the entity finite element model, wherein the mechanical load includes the steady-state working pressure applied on the sealing ring contact surface and the contact pressure stress applied on the key contact pair, the thermal load includes the environmental temperature boundary applied on the outer surface of the shell and the exposed surface of the insulating part, and the electric field load is obtained by applying the rated voltage on the outer surface of the insulating part and solving the Poisson equation to obtain the electric potential distribution; Specifically, the mechanical load includes a steady-state working pressure applied on the finite element surface corresponding to the sealing ring contact surface, and the applied value is 0.4-0.8 MPa. The contact pressure stress is applied on the key contact pair, and the applied value is 30-80 MPa. The thermal load includes an environmental temperature boundary applied on the outer surface of the shell and the exposed surface of the insulation part, and the value ranges from 10 to 40 DEG C. The calculation of the electric field load is to apply a rated voltage U(t) to the outer surface of the insulation part, and the potential distribution is calculated by the Poisson equation: wherein, is a vector differential operator, is a dielectric constant, is a potential vector differential.

[0030] In A3, based on the applied load conditions, the stress response of the model under the multi-field coupling effect is solved by finite element analysis, and the dynamic load data of the key region is extracted.

[0031] In an optional embodiment, the construction of the solid finite element model can also adopt a modeling strategy based on adaptive mesh technology. After initial coarse mesh analysis, local mesh refinement is automatically performed on the high load variation region according to the stress gradient or error estimation, so as to improve the balance between calculation efficiency and accuracy.

[0032] In an optional embodiment, the construction of the solid finite element model can also adopt a step-by-step coupling or sequential coupling load application mode, that is, the electric field and temperature field distribution are solved first, and then the results are input as loads into the structure analysis, which is suitable for scenarios with weak field coupling effect or requiring stage verification, so as to enhance the flexibility and controllability of model construction.

[0033] It should be noted that the above step S100 realizes the fine simulation of the stress response of the key components of the vacuum breaking type GIS under the multi-physical field coupling effect by constructing a solid finite element model integrating mechanical, thermal and electric field loads according to the three-dimensional geometric parameters.

[0034] In the embodiment of the present application, the above step S200 establishes the material degradation function based on the solid finite element model and according to the degradation mechanism of the material under the action of temperature accumulation, electric field breakdown and stress cycle, including: The key mechanisms of material degradation are the organization softening caused by temperature accumulation, the micro-crack growth caused by electric field breakdown and the fatigue damage induced by stress cycle. The key mechanisms of material degradation are coupled to establish the material degradation function; Based on the material degradation function and the initial strength of the material, the instantaneous strength of the material at any time is calculated; Randomness is introduced on the basis of instantaneous strength, and it is assumed that the material strength obeys a normal distribution, wherein the mean value of the distribution is determined by the instantaneous strength, and the standard deviation is obtained according to experiments, and then a time-varying probability distribution of the material strength is constructed.

[0035] Specifically, as shown in the formula (1), the material degradation mechanism and mathematical expression are defined, and for metal and insulating composite materials, the main degradation factors include microstructure softening caused by temperature accumulation, microcrack growth caused by electric field breakdown, and fatigue damage induced by stress cycle, and the material degradation function is defined by comprehensively considering the three mechanisms, and the formula is expressed as: Figure 2 Among them, is the material degradation function, is the degradation coefficient, is a nonlinear index for controlling the degradation rate. On the basis of the material degradation function, the instantaneous strength of the material is: Among them, is the initial yield strength of the material.

[0036] Specifically, in order to consider randomness, it is assumed that the instantaneous strength obeys a normal distribution: Among them, s is the value of the instantaneous strength, is the standard deviation of the strength, is the mean value of the strength.

[0037] In an optional embodiment, the construction of the material degradation function can also be based on the damage mechanics framework, and the temperature accumulation, electric field breakdown and cyclic fatigue are modeled as independent damage variables, and then the nonlinear superposition is performed through a coupling equation to form a segmented or mechanism-based degradation evolution function.

[0038] In an optional embodiment, the construction of the material degradation function can also use a phenomenological model based on physical mechanisms, and by introducing a time-temperature-electric field equivalent factor, the multi-field degradation effects are mapped into a unified accelerated aging parameter, so as to simplify the degradation function form and facilitate experimental calibration.

[0039] It should be noted that the above step S200 quantitatively describes the time-varying attenuation process of the material strength by establishing a material degradation function that comprehensively considers the three degradation mechanisms of temperature accumulation, electric field breakdown and stress cycle. The function can truly reflect the degradation law of the material performance in the service process, and overcome the limitation that the strength is fixed in the traditional method.

[0040] ​In the embodiment of the present application, the step S300 described above constructs the pressure distribution function according to the material degradation function, combines the strength distribution function, and calculates the reliability through interference integral, which includes: The pressure distribution function is constructed according to the material degradation function, wherein it is assumed that the pressure obeys normal distribution, the mean value and the standard deviation change with time, and the formula is expressed as: Wherein, p is the value of instantaneous pressure, is the time-varying mean value of pressure load, is the time-varying standard deviation of pressure load; Based on the time-varying probability distribution of material strength, the strength distribution function is obtained; The pressure distribution function and the strength distribution function are interference integrated to obtain the reliability of the component at any given time, and the formula is expressed as: Wherein, is the strength distribution function, is the pressure distribution function.

[0041] It should be noted that the step S300 described above constructs the pressure distribution function based on the material degradation function, and performs pressure-strength interference integral calculation combined with the time-varying strength distribution to realize dynamic evaluation of the reliability of the component at any service time. Not only the randomness of load and strength is considered, but also the reliability calculation has continuity in time dimension through coupling degradation mechanism, which significantly improves the accuracy of evaluation.

[0042] In the embodiment of the present application, the step S400 described above utilizes the simulation data and experimental data of the entity finite element model to construct a comprehensive error objective function, adopts a first optimization algorithm to obtain the optimal solution of the comprehensive error objective function, and modifies the parameters of the pressure distribution function and the strength distribution function through the optimal solution, which includes: Specifically, the simulation data and experimental data of the entity finite element model are utilized to construct a comprehensive error objective function F(x), and the formula is expressed as: Wherein, and represent weight coefficients for balancing the relative importance of pressure and strength errors; m represents the number of pressure data points for fitting, and n represents the number of strength data points for fitting, represents the simulation pressure value of the model at time under the parameters x, represents the measured pressure value at time , represents the predicted strength of the model, represents the experimental strength data.

[0043] Specifically, as shown in Figure 3 , the first optimization algorithm for obtaining the optimal solution of the comprehensive error objective function comprises the following steps: Set the particle swarm size and randomly generate the initial position and velocity of each particle, wherein each particle represents a set of parameter combinations to be identified; In each iteration, update the velocity and position of each particle according to the historical optimal position of the particle itself and the historical optimal position of the group, combined with the adaptive inertia weight and learning factor; Monitor the diversity of the particle swarm. When the group diversity is lower than the first threshold ), apply adaptive mutation operation to some particles to avoid premature convergence to local optimum; Set the iteration termination condition. When the improvement rate of the objective function of consecutive generations is lower than the first threshold or the maximum iteration number is reached, output the current group historical optimal position as the optimal parameter solution.

[0044] In an optional embodiment, the first optimization algorithm can also use a quasi-Newton optimization method based on gradient information, which is suitable for cases where the objective function is continuously derivable and the parameter space is relatively smooth, by constructing a second-order approximation model of the objective function and iteratively updating the search direction.

[0045] In an optional embodiment, the first optimization algorithm can also use a genetic algorithm, which simulates the natural evolution process through selection, crossover and mutation operations, and shows good robustness and convergence in global optimization and multi-peak optimization problems.

[0046] In the embodiment of the application, the first optimization algorithm for obtaining the optimal solution of the comprehensive error objective function comprises the following steps: The particle swarm size N=50, the position is randomly distributed in the feasible region , , the initial velocity is a zero vector, and each particle represents a set of parameters to be identified; The velocity and position are updated, , , wherein the inertia weight is adaptively changed with the number of generations: wherein =0.9, =0.4, and c1=c2=2.0 are the upper and lower bounds of the inertia weight. c1=c2=2.0 are the learning factors. Wherein: is the parameter vector of the i-th particle in the k-th generation, is the velocity vector of the i-th particle in the k-th generation, is the historical best position of the i-th particle so far, The best position for the group history, The kth generation inertia weight, r 1、 R2 is an independent uniform random number generated in each iteration, , The maximum iteration number; When the group diversity is lower than the threshold value delta, that is, the variance of all particle objective functions is less than , randomly select part of the particles to perform Gaussian disturbance: To prevent premature convergence, where, The adaptive disturbance standard deviation; If the error improvement rate of 10 consecutive generations is less than Or reach the maximum number of generations =300 output the optimal solution .

[0047] It should be noted that the above step S400 utilizes finite element simulation data and experimental data to construct a comprehensive error objective function, and adopts an adaptive improved optimization algorithm for parameter identification and model calibration, which can efficiently and accurately fit the model parameters, improve the prediction consistency of the model, and ensure the applicability and reliability of the degradation function and the pressure response function under actual working conditions.

[0048] In the embodiment of the present application, the step S500 described above discretizes the component service life interval into multiple time steps, calculates the reliability step by step based on the corrected function, and verifies the calculation result by using the Monte Carlo method, including: In the embodiment of the present application, the component service life interval is discretized into multiple time steps, and the reliability is calculated step by step based on the corrected function, including: The component service life interval is discretized into a set number of time steps, and the probability distribution of strength and the probability distribution of pressure are recalculated at each time step based on the corrected material degradation function and the pressure distribution function; At each discrete time step, the pressure-strength interference integral calculation is performed to obtain the dynamic reliability corresponding to the time.

[0049] Specifically, the time discretization calculation is to discretize the service life interval [0, ] into N=1000 time steps, and calculate the reliability at each time: Specifically, in the Monte Carlo simulation verification, in order to verify the analytical result, random sample simulation is performed to generate and 10 5 groups of samples, satisfying , Where Z1Z2~N(0,1), the failure number N fail, the failure probability is obtained: wherein, is the total number of Monte Carlo samples, is the number of samples determined as failure.

[0050] For example, Table 1 is a comparison of the reliability evolution of the present application and two prior arts using Monte Carlo simulation (10 5 samples, N = 1000 time steps).

[0051] Table 1: Comparison of dynamic reliability.

[0052] In an optional embodiment, the verification of the calculation result can also use the importance sampling method, which significantly improves the simulation efficiency of low failure probability events by constructing a sampling distribution biased towards the failure region.

[0053] In an optional embodiment, the verification of the calculation result can also combine the subset simulation technique to decompose the entire reliability evaluation problem into a series of conditional probability products, gradually approaching the failure domain, suitable for the verification scenario of high reliability systems.

[0054] It should be noted that the above step S500 calculates the dynamic reliability by discretizing the entire life cycle into multiple time steps, and performs large-scale random verification by combining Monte Carlo simulation. Not only does it realize the full-process characterization of the evolution of component reliability over time, but also improves the confidence of the calculation result through statistical verification, providing a robust numerical basis for life prediction and risk assessment.

[0055] In embodiment 3, a vacuum interrupter type GIS multi-field coupling system is provided, which introduces a material degradation function into the pressure-strength interference, comprising: A multi-field coupling stress modeling module is used to select key load-bearing components in the vacuum interrupter type GIS operating mechanism, and to establish a solid finite element model integrating multiple loads according to three-dimensional geometric parameters; A material degradation function establishing module is used to establish a material degradation function based on the solid finite element model according to the degradation mechanism of the material under the action of temperature accumulation, electric field breakdown and stress cycle; An interference reliability calculation module is used to construct a pressure distribution function according to the material degradation function, combine a strength distribution function, and calculate the reliability through interference integration; A parameter correction module is used to construct a comprehensive error objective function using simulation data and experimental data of the solid finite element model, obtain an optimal solution of the comprehensive error objective function using a first optimization algorithm, and correct the parameters of the pressure distribution function and the strength distribution function through the optimal solution. A dynamic reliability evolution module is configured to discretize the component service life interval into a plurality of time steps, calculate the reliability at each time step based on the modified function, and verify the calculation results using a Monte Carlo method.

[0056] It should be noted that the technical scheme of introducing the material degradation function into the pressure-strength interference of the vacuum interrupter type GIS multi-field coupling system and the technical scheme of introducing the material degradation function into the pressure-strength interference of the vacuum interrupter type GIS multi-field coupling method described above belong to the same concept. The technical details of the technical scheme of introducing the material degradation function into the pressure-strength interference of the vacuum interrupter type GIS multi-field coupling system in the present embodiment are not described in detail, and can be seen from the description of the technical scheme of introducing the material degradation function into the pressure-strength interference of the vacuum interrupter type GIS multi-field coupling method described above.

[0057] The above-mentioned unit modules can be embedded in or independent of the processor in the electronic device in hardware form, or can be stored in the memory in the electronic device in software form, so as to call and execute the operations corresponding to the above-mentioned modules by the processor.

[0058] The present embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The communication interface of the electronic device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved through WIFI, operator network, NFC (Near Field Communication) or other technologies. The computer program is executed by the processor to implement a method of introducing a material degradation function into a pressure-strength interference of a vacuum interrupter type GIS multi-field coupling method. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen. The input device of the electronic device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0059] The present embodiment also provides a computer readable storage medium having a computer program stored thereon, which is executed by the processor to implement the method proposed in the above-mentioned embodiment.

[0060] The storage medium proposed in the present embodiment and the method proposed in the above-mentioned embodiment belong to the same inventive concept. The technical details not described in detail in the present embodiment can be seen from the above-mentioned embodiment, and the present embodiment has the same beneficial effects as the above-mentioned embodiment.

[0061] Those skilled in the art can clearly understand the present application by the description of the above embodiments, and the present application can be realized by software and necessary general hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a ROM, a RAM, a flash memory, a hard disk or an optical disk, and includes a number of instructions to make an electronic device (which can be a personal computer, a server, or a network device, etc.) execute the method of the embodiments of the present application.

[0062] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and all should be covered in the scope of the claims of the present application.

Claims

1. A vacuum-segmented GIS multi-field coupling method that incorporates material degradation functions into pressure-intensity interference, characterized in that, include: Key load-bearing components in the vacuum-switching GIS operating mechanism are selected, and a solid finite element model integrating multiple loads is established based on three-dimensional geometric parameters. Based on the aforementioned solid finite element model, a material degradation function is established according to the degradation mechanism of materials under temperature accumulation, electric field breakdown, and stress cycling. A pressure distribution function is constructed based on the material degradation function, and the reliability is calculated by interferometric integral in combination with the intensity distribution function. A comprehensive error objective function is constructed using simulation data and experimental data from the solid finite element model. The optimal solution of the comprehensive error objective function is obtained using a first optimization algorithm. The parameters of the pressure distribution function and intensity distribution function are then corrected using the optimal solution. The service life of the component is discretized into multiple time steps, and the reliability is calculated step by step based on the modified function. The Monte Carlo method is then used to verify the calculation results.

2. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 1, characterized in that, The establishment of the material degradation function includes: The key mechanisms of material degradation are identified as microstructure softening caused by temperature accumulation, microcrack growth caused by electric field breakdown, and fatigue damage induced by stress cycling. These key mechanisms of material degradation are coupled together to establish a material degradation function. Based on the material degradation function and the initial strength of the material, the instantaneous strength of the material at any given time is calculated; Based on the instantaneous strength, randomness is introduced, assuming that the material strength follows a normal distribution, where the mean of the distribution is determined by the instantaneous strength and the standard deviation is obtained from experimental statistics, thereby constructing a time-varying probability distribution of the material strength.

3. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 2, characterized in that, The step of constructing a pressure distribution function based on the material degradation function, combining it with the intensity distribution function, and calculating the reliability through interferometric integration includes: A pressure distribution function is constructed based on the material degradation function, where it is assumed that the pressure follows a normal distribution and that the mean and standard deviation change with time. Based on the time-varying probability distribution of the material strength, the strength distribution function is obtained; The reliability of the component at any given time is obtained by performing an interference integral calculation on the pressure distribution function and the intensity distribution function.

4. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 3, characterized in that, The step of discretizing the service life of a component into multiple time steps and calculating the reliability step-by-step based on the modified function includes: The service life of the component is discretized into a set number of time steps. Based on the modified material degradation function and pressure distribution function, the probability distribution of strength and the probability distribution of pressure are recalculated at each time step. At each discrete time step, the pressure-intensity interferometry integral is calculated to obtain the dynamic reliability at that time.

5. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 1, characterized in that, The establishment of a solid finite element model integrating multiple loads based on three-dimensional geometric parameters includes: A solid finite element model is established based on the three-dimensional geometric parameters of the key load-bearing component, and the mesh is refined for the force transmission path and high stress concentration area of ​​the model, requiring that the mesh element size is not greater than a set value; Three types of boundary conditions—mechanical load, thermal load, and electric field load—are simultaneously applied to the solid finite element model. The mechanical load includes the steady-state working pressure applied to the sealing ring contact surface and the contact compressive stress applied to the key contact pair. The thermal load includes the ambient temperature boundary applied to the outer surface of the shell and the exposed surface of the insulation component. The electric field load is obtained by applying a rated voltage to the outer surface of the insulation component and solving the Poisson equation to obtain the potential distribution. Based on the applied load conditions, the stress response of the model under multi-field coupling is obtained by solving the finite element method, and the dynamic load data of the key area is extracted.

6. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 5, characterized in that, The construction of the comprehensive error objective function includes: Using the simulation and experimental data from the aforementioned solid finite element model, a comprehensive error objective function F(x) is constructed, expressed as follows: in, and represents the weighting coefficient, used to balance the relative importance of pressure and strength errors; m represents the number of pressure data points used for fitting, and n represents the number of strength data points used for fitting. This indicates that the model at time x is in the parameter x. The simulated pressure value, Indicates at time The measured pressure value, Indicates the strength of the model's prediction. This represents the intensity data measured in the experiment.

7. The vacuum-severing GIS multi-field coupling method for incorporating material degradation functions into pressure-intensity interference as described in claim 6, characterized in that, The step of obtaining the optimal solution of the comprehensive error objective function using the first optimization algorithm includes: Set the particle swarm size and randomly generate the initial position and velocity of each particle, where each particle represents a set of parameter combinations to be identified. In each iteration, the velocity and position of each particle are updated based on its own historical best position and the group's historical best position, combined with adaptively changing inertial weights and learning factors. Monitor the diversity of the particle swarm. When the diversity of the swarm is lower than the first threshold, apply an adaptive mutation operation to some particles to avoid the algorithm from converging to a local optimum too early. Set an iteration termination condition: when the improvement rate of the objective function is lower than the first threshold or the maximum number of iterations is reached for several consecutive generations, output the current population's historical best position as the optimal parameter solution.

8. A vacuum-segmented GIS multi-field coupling system that incorporates a material degradation function into pressure-intensity interference, employing the vacuum-segmented GIS multi-field coupling method for incorporating a material degradation function into pressure-intensity interference as described in any one of claims 1 to 7, characterized in that, include: The multi-field coupled stress modeling module is used to select key load-bearing components in vacuum-splitting GIS operating mechanisms and establish solid finite element models that integrate multiple loads based on three-dimensional geometric parameters. The material degradation function establishment module is used to establish a material degradation function based on the solid finite element model and according to the degradation mechanism of the material under temperature accumulation, electric field breakdown and stress cycle. The interference reliability calculation module is used to construct a pressure distribution function based on the material degradation function, combine it with the intensity distribution function, and calculate the reliability through interference integral. The parameter correction module is used to construct a comprehensive error objective function using the simulation data and experimental data of the solid finite element model, obtain the optimal solution of the comprehensive error objective function using the first optimization algorithm, and correct the parameters of the pressure distribution function and intensity distribution function using the optimal solution. The dynamic reliability evolution module is used to discretize the service life of a component into multiple time steps, calculate the reliability step by step based on the modified function, and verify the calculation results using the Monte Carlo method.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and when the processor executes the computer-executable instructions, it implements the steps of the vacuum-severing GIS multi-field coupling method that introduces material degradation functions into pressure-intensity interference as described in any one of claims 1 to 7.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer-executable instructions are executed by the processor, they implement the steps of the vacuum-severing GIS multi-field coupling method according to any one of claims 1 to 7, which introduces the material degradation function into pressure-intensity interference.

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