Method, system, medium and equipment for evaluating fatigue degree of high-voltage circuit breaker spring

Abstract

The embodiment of the application discloses a kind of high-voltage circuit breaker spring fatigue degree evaluation methods, the method comprises: the particle model of high-voltage circuit breaker is constructed, the particle model includes several to be measured particles;The vibration signal of the several to be measured particles is collected;According to ensemble empirical mode decomposition, the vibration signal is decomposed, obtains several to be measured vibration signals;According to the vibration energy of the several to be measured vibration signals and its corresponding weight coefficient, the spring energy storage function corresponding to the several to be measured particles is determined;According to the spring energy storage function, the energy storage detection value of high-voltage circuit breaker spring is determined, and the energy storage detection value is used to characterize the fatigue degree of spring.The application is realized to the accurate evaluation of high-voltage circuit breaker spring fatigue degree by constructing particle model, collecting vibration signal and decomposing, determining spring energy storage function, not only improves the accuracy and reliability of evaluation, also provides effective technical support for the maintenance and management of circuit breaker.

Description

Technical Field

[0001] This invention relates to the field of high-voltage equipment testing technology, and in particular to a method, system, medium, and equipment for evaluating the fatigue degree of high-voltage circuit breaker springs. Background Technology

[0002] As a key piece of equipment in the power system, high-voltage circuit breakers bear the important responsibility of protecting and controlling circuits. Their stable operation is crucial to ensuring the safety and reliability of the power system. However, in actual operation, high-voltage circuit breakers often face a series of problems caused by spring fatigue.

[0003] As the core component of the operating mechanism of a high-voltage circuit breaker, the performance of the spring directly affects the closing and opening operations of the circuit breaker. When the spring becomes fatigued due to long-term operation or harsh operating environment, it may lead to accidents such as incomplete closing or long opening time. As the operating time of the high-voltage circuit breaker accumulates, the failure rate caused by spring fatigue gradually increases, posing a potential threat to the stable operation of the power system.

[0004] To address the fatigue problem of springs in high-voltage circuit breakers, existing technologies have studied the dynamic characteristics of high-voltage circuit breakers under spring fatigue conditions and performed qualitative diagnosis of mechanical faults such as spring fatigue from the perspective of pattern recognition. However, qualitative diagnosis alone is insufficient to accurately reflect the degree of spring fatigue and cannot provide precise decision support for the maintenance of high-voltage circuit breakers. Summary of the Invention

[0005] Therefore, it is necessary to propose a method for evaluating the fatigue level of high-voltage circuit breaker springs to address the above-mentioned problems.

[0006] A method for evaluating the fatigue level of a high-voltage circuit breaker spring, the method comprising the following steps:

[0007] Construct a mass point model of a high-voltage circuit breaker, wherein the mass point model includes several mass points to be measured;

[0008] The vibration signals of the several particles to be measured are collected;

[0009] The vibration signal is decomposed according to the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0010] Based on the vibration energy of the several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to the several particles to be measured.

[0011] The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring.

[0012] In the above scheme, the step of decomposing the vibration signal according to ensemble empirical mode decomposition to obtain several vibration signals to be measured specifically includes:

[0013] The vibration signals of the plurality of test particles are cleaned and filtered to obtain the first vibration signal of the plurality of test particles;

[0014] Empirical mode decomposition is performed on the first vibration signal to obtain several corresponding IMF components;

[0015] Select specific groups of IMF components, perform weighted summation, and reconstruct the corresponding vibration signals to be measured.

[0016] In the above scheme, determining the spring energy storage function corresponding to the plurality of test particles based on the vibration energy of the plurality of test vibration signals and their corresponding weighting coefficients specifically includes:

[0017] The vibration energy of the several test particles is determined based on the several test vibration signals;

[0018] The weighting coefficient h of the energy of the several particles to be measured is determined using the nonlinear least squares method. i ;

[0019] Based on the vibration energy of the plurality of particles to be measured and the weighting coefficient h of the energy of the plurality of particles to be measured. i Determine the energy transfer function of the high-voltage circuit breaker:

[0020]

[0021] In the formula, S d Stores energy for the tripping spring of the high-voltage circuit breaker; S b Store energy for the buffer spring of the high-voltage circuit breaker; h i S represents the weighting coefficients for the energies of several particles to be measured; i The vibrational energy of several particles to be measured;

[0022] Based on the energy transfer function, determine the spring energy storage function corresponding to several particles to be measured:

[0023]

[0024] In the formula, S(x) is the spring energy storage function; h0 is the initial energy value of several particles to be measured; and S... i h represents the vibrational energy of several particles to be measured. i The weighting coefficients are used to determine the energy of several particles to be measured.

[0025] In the above scheme, determining the vibration energy of the plurality of test particles based on the plurality of test vibration signals specifically includes:

[0026] Determine the mass of the plurality of particles to be tested;

[0027] Collect the velocity and acceleration of the several particles to be measured;

[0028] The vibrational energy of the plurality of particles to be measured is determined based on their mass, velocity, and acceleration.

[0029]

[0030] In the formula, m i v is the mass of the i-th particle to be measured; i Let a be the velocity of the i-th particle to be measured; i τ is the acceleration of the i-th particle to be measured; τ is the sampling time; X is the number of sampling points.

[0031] In the above scheme, determining the mass of the plurality of test particles specifically includes:

[0032] The mass of the several test points is determined based on the three-dimensional dimensions of the high-voltage circuit breaker and the material specifications of the parts.

[0033] In the above scheme, the weighting coefficient h for determining the energy of the plurality of particles to be measured using the nonlinear least squares method is... i Specifically, it includes:

[0034] Obtain the objective function of the nonlinear least squares method, wherein the objective function is:

[0035]

[0036] In the formula, The actual value of energy stored in the trip spring; S d The calculated value of the energy stored in the trip spring; n is the number of measurements;

[0037] The optimization criterion for the nonlinear least squares method is obtained, and the optimization criterion is:

[0038]

[0039] Where x,x 2 ,···,x n Let a be a linearly independent function within the domain of the error function δ; j The coefficients are the coefficients corresponding to the linearly independent functions, 1≤j≤k, where k is a constant;

[0040] Solving the objective function and the optimization criterion yields the weighting coefficient h of the energy of the plurality of particles to be measured. i .

[0041] In the above scheme, after determining the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function, it further includes:

[0042] The fatigue state of the high-voltage circuit breaker spring is identified based on the spring energy storage detection value;

[0043] The fatigue states include: normal state, mild fatigue state, moderate fatigue state, severe fatigue state, and failure state.

[0044] In the above scheme, identifying the fatigue state of the high-voltage circuit breaker spring based on the spring energy storage detection value includes:

[0045] Obtain the normal range of spring energy storage value;

[0046] When the spring energy storage detection value is within 90%-100% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a normal state.

[0047] When the spring energy storage detection value is within 80%-89% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a state of mild fatigue.

[0048] When the spring energy storage detection value is within 50%-79% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a general fatigue state.

[0049] When the spring energy storage detection value is within 25%-49% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a state of severe fatigue.

[0050] When the detected value of the spring energy storage is less than 25% of the normal range of the spring energy storage, the high-voltage circuit breaker spring is determined to be in a failed state.

[0051] In the above scheme, when the high-voltage circuit breaker spring is in a state of severe fatigue or failure, a prompt message is sent to remind the user to replace the spring.

[0052] This application also proposes a high-voltage circuit breaker spring fatigue assessment system, the system comprising: a model building unit, a signal acquisition unit, a signal processing unit, and a spring fatigue assessment unit;

[0053] The model building unit is used to build a mass point model of a high-voltage circuit breaker, which includes several mass points to be measured.

[0054] The signal acquisition unit is used to acquire the vibration signals of the 100 particles to be measured.

[0055] The signal processing unit is used to decompose the vibration signal according to the set empirical mode decomposition to obtain several vibration signals to be measured.

[0056] The spring fatigue assessment unit is used to determine the energy transfer function and spring energy storage function corresponding to the plurality of test particles based on the vibration energy and weighting coefficients of the plurality of test vibration signals; and to determine the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function, wherein the energy storage detection value is used to characterize the fatigue degree of the spring.

[0057] This application also proposes a readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0058] Construct a mass point model of a high-voltage circuit breaker, wherein the mass point model includes several mass points to be measured;

[0059] The vibration signals of the several particles to be measured are collected;

[0060] The vibration signal is decomposed according to the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0061] Based on the vibration energy of the several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to the several particles to be measured.

[0062] The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring.

[0063] This application also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor in the following steps:

[0064] Construct a mass point model of a high-voltage circuit breaker, wherein the mass point model includes several mass points to be measured;

[0065] The vibration signals of the several particles to be measured are collected;

[0066] The vibration signal is decomposed according to the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0067] Based on the vibration energy of the several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to the several particles to be measured.

[0068] The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring.

[0069] The embodiments of this invention have the following beneficial effects: First, a mass point model of a high-voltage circuit breaker is constructed, including several mass points to be measured; vibration signals of these mass points are collected; the vibration signals are decomposed according to ensemble empirical mode decomposition to obtain several vibration signals to be measured; the spring energy storage function corresponding to the several vibration signals to be measured is determined based on the vibration energy of the several vibration signals to be measured and their corresponding weighting coefficients; the energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring. This invention, by constructing a mass point model, collecting and decomposing vibration signals, and determining the spring energy storage function, can accurately detect the stored energy value of the spring, achieving quantitative online monitoring of the spring and realizing accurate assessment of the fatigue degree of the high-voltage circuit breaker spring. This not only improves the accuracy and reliability of the assessment but also provides effective technical support for the maintenance and management of circuit breakers. Attached Figure Description

[0070] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0071] in:

[0072] Figure 1 This is a schematic diagram of a method for assessing the fatigue level of a high-voltage circuit breaker spring in one embodiment.

[0073] Figure 2 This is a schematic diagram of the mass point model structure of a high-voltage circuit breaker. Detailed Implementation

[0074] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0075] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention; however, it will be apparent to those skilled in the art that the invention may be practiced without one or more of these details; in other instances, certain technical features well-known in the art have not been described in order to avoid confusion with the invention. It should be understood that the invention can be practiced in different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided to make the disclosure thorough and complete and to fully convey the scope of the invention to those skilled in the art.

[0076] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms, unless the context clearly indicates otherwise. The terms “comprising” and / or “including,” when used in this specification, identify the presence of said features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0077] To fully understand the present invention, a detailed structure will be presented in the following description in order to illustrate the technical solution proposed by the present invention; optional embodiments of the present invention are described in detail below, however, in addition to these detailed descriptions, the present invention may have other embodiments.

[0078] like Figure 1 As shown, in one embodiment, a method for evaluating the fatigue level of a high-voltage circuit breaker spring is provided. This method includes steps S101 to S105, detailed below:

[0079] S101. Construct a mass point model of the high-voltage circuit breaker, which includes several mass points to be measured.

[0080] By establishing a mass point model of a high-voltage circuit breaker, the complex physical system can be simplified, facilitating subsequent analysis and processing. The mass points to be measured in the mass point model represent key parts of the circuit breaker, and the vibration of these parts can reflect the working state and fatigue degree of the spring.

[0081] like Figure 2As shown, considering the mechanical structure of the high-voltage circuit breaker, the entire high-voltage circuit breaker is simplified into a mass model, which includes 7 mass points to be measured. The mass of each mass point to be measured is defined as m1 to m7. The mass of each mass point to be measured can be calculated according to the three-dimensional dimensions of the high-voltage circuit breaker and the specifications of the parts materials. According to the energy transfer mechanism of the high-voltage circuit breaker and combined with the law of conservation of energy, during the opening process, the energy stored in the spring will eventually be converted into the vibration energy of the 7 mass points to be measured.

[0082] S102. Collect vibration signals from several particles to be measured;

[0083] Collecting vibration signals from the test particle is the basic data for assessing the fatigue level of a spring. These signals contain vibration information generated by the spring during operation. By analyzing this information, the energy storage and fatigue state of the spring can be inferred.

[0084] S103. Decompose the vibration signal according to the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0085] Ensemble Empirical Mode Decomposition (EEMD) is an effective signal processing technique that can decompose complex vibration signals into multiple intrinsic mode functions (IMFs), thereby extracting different frequency components in the signal. This method helps to separate specific vibration modes related to spring fatigue from the original vibration signal.

[0086] In some embodiments, the vibration signal is decomposed according to ensemble empirical mode decomposition to obtain several vibration signals to be measured, specifically including:

[0087] The vibration signals of several particles to be measured are cleaned and filtered to obtain the first vibration signal of several particles to be measured.

[0088] Empirical mode decomposition (EMD) is performed on the first vibration signal to obtain several corresponding IMF components;

[0089] Select a specific set of IMF components, perform weighted summation, and reconstruct the corresponding vibration signals to be measured.

[0090] Specifically, by selecting specific IMF components for weighted summation, vibration signals reflecting the vibration characteristics of the particle under test can be reconstructed. These signals are clearer and more accurate, which is beneficial for subsequent vibration analysis and fault diagnosis.

[0091] S104. Based on the vibration energy of several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to several particles to be measured.

[0092] By analyzing the energy and weighting coefficients of the vibration signal, the energy storage function of the spring can be constructed. This function can quantify the energy storage capacity of the spring under different vibration modes, thus reflecting the fatigue state of the spring. The introduction of weighting coefficients can more accurately assess the contribution of different vibration modes to the energy storage of the spring.

[0093] In some embodiments, the spring energy storage function corresponding to several test particles is determined based on the vibration energy of several vibration signals to be measured and their corresponding weighting coefficients, specifically including:

[0094] The vibration energy of several particles to be measured is determined based on several vibration signals to be measured.

[0095] The weighting coefficient h of the energy of several particles to be measured is determined using the nonlinear least squares method. i ;

[0096] Based on the vibrational energy of several particles to be measured and the weighting coefficient h of the energy of several particles to be measured. i Determine the energy transfer function of the high-voltage circuit breaker:

[0097]

[0098] In the formula, S d Stores energy for the tripping spring of the high-voltage circuit breaker; S b Store energy for the buffer spring of the high-voltage circuit breaker; h i S represents the weighting coefficients for the energies of several particles to be measured; i The vibrational energy of several particles to be measured;

[0099] Determine the spring storage function corresponding to several particles to be measured based on the energy transfer function:

[0100]

[0101] In the formula, S(x) is the spring energy storage function; h0 is the initial energy value of several particles to be measured; and S... i h represents the vibrational energy of several particles to be measured. i The weighting coefficients are used to determine the energy of several particles to be measured.

[0102] As can be seen, based on the energy transfer function, combined with the initial value of the energy of the particle under test and the vibration energy, as well as the weighting coefficient, the spring energy storage function corresponding to several particles under test was determined. Through this function, the spring energy storage situation of each particle can be intuitively understood, providing strong support for subsequent analysis and decision-making.

[0103] In some embodiments, determining the vibration energy of several test particles based on several test vibration signals specifically includes:

[0104] Determine the mass of several particles to be measured;

[0105] Collect the velocity and acceleration of several particles to be measured;

[0106] The vibrational energy of several particles to be measured is determined based on their mass, velocity, and acceleration.

[0107]

[0108] In the formula, m i v is the mass of the i-th particle to be measured; i Let a be the velocity of the i-th particle to be measured; i τ is the acceleration of the i-th particle to be measured; τ is the sampling time; X is the number of sampling points.

[0109] like Figure 2 As shown, taking the first particle to be tested in the particle model as an example:

[0110]

[0111] In the formula, m1 is the mass of the first particle to be measured; v1 is the velocity of the first particle to be measured; a1 is the acceleration of the first particle to be measured; τ is the sampling time; and X is the number of sampling points.

[0112] In some embodiments, determining the mass of a plurality of test particles specifically includes:

[0113] The mass of several test points is determined based on the three-dimensional dimensions of the high-voltage circuit breaker and the material specifications of the parts.

[0114] In some embodiments, the weighting coefficient h of the energies of several particles to be measured is determined using the nonlinear least squares method. i Specifically, it includes:

[0115] Obtain the objective function of the nonlinear least squares method. The objective function is:

[0116]

[0117] In the formula, The actual value of energy stored in the trip spring; S d The calculated value of the energy stored in the trip spring; n is the number of measurements;

[0118] The optimization criteria for nonlinear least squares method are as follows:

[0119]

[0120] Where x,x 2 ,···,x n Let a be a linearly independent function within the domain of the error function δ;j The coefficients are the coefficients corresponding to the linearly independent functions, 1≤j≤k, where k is a constant;

[0121] By solving the objective function and the optimization criteria, the weighting coefficients h of the energies of several particles to be measured are obtained. i .

[0122] Preferably, each coefficient a in the optimization criterion is adjusted according to the error function δ. j Find the partial derivative and set it to 0 to obtain the system of linear equations:

[0123]

[0124]

[0125] Where x,x 2 ,···,x n Let a be a linearly independent function within the domain of the error function δ; j The coefficients are the coefficients corresponding to the linearly independent functions, 1≤j≤k, where k is a constant;

[0126] Solving the above system of linear equations yields the weighting coefficients h of the energies of several particles to be measured. i The weighting coefficient h i By substituting the spring energy storage function into the spring energy storage function, the spring energy storage detection value can be calculated, thereby completing the online monitoring of the spring fatigue level.

[0127] S105. Determine the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function. The energy storage detection value is used to characterize the fatigue degree of the spring.

[0128] The energy storage detection value calculated by the spring energy storage function can directly reflect the fatigue degree of the high-voltage circuit breaker spring. This detection value can serve as an important indicator for evaluating the life and performance of the spring, providing a scientific basis for the maintenance and management of the circuit breaker.

[0129] In some embodiments, after determining the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function, the method further includes:

[0130] Identify the fatigue state of high-voltage circuit breaker springs based on spring energy storage test values;

[0131] Fatigue states include: normal state, mild fatigue state, moderate fatigue state, severe fatigue state, and failure state.

[0132] In some embodiments, identifying the fatigue state of a high-voltage circuit breaker spring based on spring energy storage detection values ​​includes:

[0133] Obtain the normal range of spring energy storage value;

[0134] When the spring energy storage test value is within 90%-100% of the normal range of spring energy storage value, the high-voltage circuit breaker spring is determined to be in normal condition.

[0135] When the spring energy storage test value is within 80%-89% of the normal range of spring energy storage, it is determined that the high-voltage circuit breaker spring is in a state of mild fatigue.

[0136] When the spring energy storage test value is within 50%-79% of the normal range of spring energy storage value, the high-voltage circuit breaker spring is determined to be in a general fatigue state.

[0137] When the spring energy storage test value is between 25% and 49% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a state of severe fatigue.

[0138] When the spring energy storage detection value is 25% lower than the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a failed state.

[0139] Among them, 100% of the normal energy storage value corresponds to 150J, and 0% of the normal energy storage value corresponds to the theoretical value of the spring having no energy storage at all.

[0140] Preferably, when it is detected that the high-voltage circuit breaker spring is in a state of severe fatigue or failure, a prompt message is sent to remind the user to replace the spring, so as to ensure the normal operation of the circuit breaker and the safety and stability of the power system.

[0141] In summary, this invention analyzes the energy transfer during the operation of a high-voltage circuit breaker. By using a mass point model to simplify the entire structure into a test mass point, the vibration signal of the test mass point is collected and the noise signal is filtered out. Then, by constructing the spring energy storage function of the high-voltage circuit breaker, the spring energy storage detection value is accurately obtained, thereby realizing online monitoring of the spring energy.

[0142] This application also proposes a high-voltage circuit breaker spring fatigue assessment system, which includes: a model building unit, a signal acquisition unit, a signal processing unit, and a spring fatigue assessment unit;

[0143] The model building unit is used to build a mass point model of a high-voltage circuit breaker, which includes several mass points to be measured.

[0144] The signal acquisition unit is used to acquire vibration signals from several particles under test.

[0145] The signal processing unit is used to decompose the vibration signal according to the ensemble empirical mode decomposition and obtain several vibration signals to be measured.

[0146] The spring fatigue assessment unit is used to determine the energy transfer function and spring energy storage function corresponding to several test particles based on the vibration energy and weighting coefficients of several test vibration signals; and to determine the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function. The energy storage detection value is used to characterize the fatigue degree of the spring.

[0147] This application also proposes a readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0148] Construct a mass point model of a high-voltage circuit breaker, which includes several mass points to be measured;

[0149] Collect vibration signals from several particles to be measured;

[0150] The vibration signal is decomposed based on the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0151] Based on the vibration energy of several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to several particles to be measured.

[0152] The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function. The energy storage detection value is used to characterize the fatigue degree of the spring.

[0153] This application also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor in the following steps:

[0154] Construct a mass point model of a high-voltage circuit breaker, which includes several mass points to be measured;

[0155] Collect vibration signals from several particles to be measured;

[0156] The vibration signal is decomposed based on the ensemble empirical mode decomposition to obtain several vibration signals to be measured;

[0157] Based on the vibration energy of several vibration signals to be measured and their corresponding weighting coefficients, determine the spring energy storage function corresponding to several particles to be measured.

[0158] The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function. The energy storage detection value is used to characterize the fatigue degree of the spring.

[0159] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be accomplished by instructing related hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0160] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0161] The embodiments described above are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application's patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. The embodiments disclosed above are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made according to the claims of this invention are still within the scope of this invention.

Claims

1. A method for evaluating the fatigue degree of a high-voltage circuit breaker spring, characterized in that, The method includes: Construct a mass point model of a high-voltage circuit breaker, wherein the mass point model includes several mass points to be measured; The vibration signals of the several particles to be measured are collected; The vibration signal is decomposed according to the ensemble empirical mode decomposition to obtain several vibration signals to be measured; Based on the vibration energy of the plurality of vibration signals to be measured and their corresponding weighting coefficients, the spring energy storage function corresponding to the plurality of particles to be measured is determined, specifically including: The vibration energy of the several test particles is determined based on the several test vibration signals; The weighting coefficients for the energies of the several particles to be measured are determined using the nonlinear least squares method. ; Based on the vibration energy of the plurality of particles to be measured and the weighting coefficients of the energy of the plurality of particles to be measured. Determine the energy transfer function of the high-voltage circuit breaker: In the formula, Store energy for the tripping spring of the high-voltage circuit breaker; To store energy for the buffer springs of high-voltage circuit breakers; These are the weighting coefficients for the energies of several particles to be measured; The vibrational energy of several particles to be measured; Based on the energy transfer function, determine the spring energy storage function corresponding to several particles to be measured: In the formula, Let be the energy storage function of the spring; The initial energy values ​​for several particles to be measured. The vibrational energy of several particles to be measured; These are the weighting coefficients for the energies of several particles to be measured; The energy storage detection value of the high-voltage circuit breaker spring is determined based on the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring.

2. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 1, characterized in that, The step of decomposing the vibration signal according to ensemble empirical mode decomposition to obtain several vibration signals to be measured specifically includes: The vibration signals of the plurality of test particles are cleaned and filtered to obtain the first vibration signal of the plurality of test particles; Empirical mode decomposition is performed on the first vibration signal to obtain several corresponding IMF components; Select specific groups of IMF components, perform weighted summation, and reconstruct the corresponding vibration signals to be measured.

3. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 1, characterized in that, The determination of the vibration energy of the plurality of test particles based on the plurality of test vibration signals specifically includes: Determine the mass of the plurality of particles to be tested; Collect the velocity and acceleration of the several particles to be measured; The vibrational energy of the plurality of particles to be measured is determined based on their mass, velocity, and acceleration. In the formula, Let be the mass of the i-th particle to be measured; Let be the velocity of the i-th particle to be measured; Let be the acceleration of the i-th particle to be measured; X represents the sampling time; X represents the number of sampling points.

4. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 3, characterized in that, Determining the mass of the plurality of test particles specifically includes: The mass of the several test points is determined based on the three-dimensional dimensions of the high-voltage circuit breaker and the material specifications of the parts.

5. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 1, characterized in that, The weighting coefficients for determining the energy of the plurality of particles to be measured are obtained by using the nonlinear least squares method. Specifically, it includes: Obtain the objective function of the nonlinear least squares method, wherein the objective function is: In the formula, The actual value of energy stored in the trip spring; The calculated value of the energy stored in the trip spring; n is the number of measurements; The optimization criterion for the nonlinear least squares method is obtained, and the optimization criterion is: in, Error function Linearly independent functions within the domain; The coefficients are those corresponding to linearly independent functions. k is a constant; By solving the objective function and the optimization criterion, the weighting coefficients of the energies of the plurality of particles to be measured are obtained. .

6. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 5, characterized in that, After determining the energy storage detection value of the high-voltage circuit breaker spring based on the spring energy storage function, the method further includes: The fatigue state of the high-voltage circuit breaker spring is identified based on the spring energy storage detection value; The fatigue states include: normal state, mild fatigue state, moderate fatigue state, severe fatigue state, and failure state.

7. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 6, characterized in that, The step of identifying the fatigue state of the high-voltage circuit breaker spring based on the spring energy storage detection value includes: Obtain the normal range of spring energy storage value; When the spring energy storage detection value is within 90%-100% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a normal state. When the spring energy storage detection value is within 80%-89% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a state of mild fatigue. When the spring energy storage detection value is within 50%-79% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a general fatigue state. When the spring energy storage detection value is within 25%-49% of the normal range of spring energy storage, the high-voltage circuit breaker spring is determined to be in a state of severe fatigue. When the detected value of the spring energy storage is less than 25% of the normal range of the spring energy storage, the high-voltage circuit breaker spring is determined to be in a failed state.

8. The method for evaluating the fatigue degree of high-voltage circuit breaker springs according to claim 7, characterized in that, Also includes: When the high-voltage circuit breaker spring is in a state of severe fatigue or failure, a prompt message is sent to remind the user to replace the spring.

9. A fatigue assessment system for high-voltage circuit breaker springs, characterized in that, The system includes: a model building unit, a signal acquisition unit, a signal processing unit, and a spring fatigue assessment unit; The model building unit is used to build a mass point model of a high-voltage circuit breaker, which includes several mass points to be measured. The signal acquisition unit is used to acquire the vibration signals of the 100 particles to be measured. The signal processing unit is used to decompose the vibration signal according to the set empirical mode decomposition to obtain several vibration signals to be measured. The spring fatigue assessment unit is used to determine the energy transfer function and spring energy storage function corresponding to the plurality of test particles based on the vibration energy and weighting coefficients of the plurality of test vibration signals. Specifically, this includes: determining the vibration energy of the plurality of test particles based on the plurality of test vibration signals; and determining the weighting coefficients of the energy of the plurality of test particles using a nonlinear least squares method. Based on the vibrational energy of the plurality of particles to be measured and the weighting coefficients of the energy of the plurality of particles to be measured. Determine the energy transfer function of the high-voltage circuit breaker: In the formula, Store energy for the tripping spring of the high-voltage circuit breaker; To store energy for the buffer springs of high-voltage circuit breakers; These are the weighting coefficients for the energies of several particles to be measured; The vibrational energy of several particles to be measured; Based on the energy transfer function, determine the spring energy storage function corresponding to several particles to be measured: In the formula, Let be the energy storage function of the spring; The initial energy values ​​for several particles to be measured. The vibrational energy of several particles to be measured; The weighting coefficients are used to determine the energy of several particles to be measured; the energy storage detection value of the high-voltage circuit breaker spring is determined according to the spring energy storage function, and the energy storage detection value is used to characterize the fatigue degree of the spring.

10. A readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 8.

11. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 8.

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