A Method and System for Evaluating the Nonlinear Strength of Insulating Materials Based on High-Frequency Component Analysis

Abstract

This disclosure relates to the field of insulating material testing, including a method and system for evaluating the nonlinear strength of insulating materials based on high-frequency component analysis. The method involves applying an excitation electrical signal of a first preset frequency to the insulating material under test; acquiring the response signal obtained by the insulating material in response to the excitation electrical signal based on a second preset frequency; performing time-frequency transformation on the response signal to obtain the frequency characteristics of various preset higher harmonic components; and determining the evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of these higher harmonic components. This method allows for obtaining the evaluation result of the nonlinear strength with a single excitation and response acquisition; it eliminates the need for multi-voltage point step testing in traditional techniques, shortening the testing cycle, improving testing efficiency, and enabling efficient, accurate, and standardized determination of the nonlinear strength evaluation result.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of insulation material testing, and particularly to an insulation material nonlinear strength evaluation method and system based on high-frequency component analysis. BACKGROUND

[0002] The core components of a rotating electrical machine, such as a hydroelectric generator, a steam turbine generator, and a large motor, include a stator and a rotor. The stator bar (also known as winding bar) embedded in the stator core slot is a key conductive component that bears high voltage and large current. During the operation of the rotating electrical machine, the stator bar, especially the end region extending out of the core, is under extremely high working voltage. Due to structural mutations and proximity effects, the electric field distribution in this region is uneven, and there is a phenomenon of electric field concentration. This high-intensity electric field can induce continuous local corona discharge, not only causing energy loss, but also causing electrical corrosion, aging, and degradation of the insulation material, which may eventually cause the problem of main insulation breakdown, seriously threatening the reliability of the electrical machine operation and shortening its service life.

[0003] To effectively suppress the electric field concentration and corona discharge phenomenon at the end of the stator bar, a corona prevention band made of a semiconductor or a nonlinear conductive composite material can be provided at the end of the stator bar. The electrical conductivity (or resistivity) of the material of the corona prevention band will exhibit nonlinear changes with the increase of the electric field strength, so as to provide a higher electrical conductivity in the high electric field region, thereby dispersing the electric field and reducing the local electric field strength; and maintain a lower electrical conductivity in the low electric field region to reduce the leakage current loss. The strength of the nonlinear characteristics of the corona prevention band determines its voltage equalization effect and anti-corona performance, and therefore, the nonlinear strength of the corona prevention band needs to be evaluated.

[0004] Currently, the nonlinear strength evaluation methods for insulation materials include:

[0005] 1. Direct current conductivity test method: The electrical conductivity of the insulation material is measured under a constant electric field. By using specific detection equipment under specific test conditions, the electrical parameters of the insulation material are detected to ensure the insulation performance of the material.

[0006] However, this method only obtains the electrical conductivity value under a specific electric field strength, and it is difficult to capture the dynamic nonlinear behavior of the material under the actual operating high electric field, resulting in the inability to accurately reflect the nonlinear characteristic curve of the material. At the same time, the direct current test method cannot simulate the alternating current electric field environment of the material under actual operating conditions, which will result in a deviation between the test results and the actual working performance of the material, and the evaluation results are not accurate.

[0007] 2. Step voltage response test method: By applying different amplitude step voltages to the insulation material, the current response of the insulation material under different electric field strengths is measured, and then the electrical conductivity is calculated.

[0008] Although this method can obtain data of multiple electric field strength points, the test process is time-consuming, usually taking several hours or even longer, and the test efficiency is low, which cannot meet the rapid iteration demand of material research and development, and is difficult to adapt to the quality control requirements on the production line, seriously affecting the industrialization process of the anti-corona belt material. In addition, since only the conductivity values of discrete electric field strength points can be obtained, it is difficult to accurately depict the complete nonlinear characteristic curve of the material, and the nonlinear conductivity characteristics of the polymer composite material in the electric field gradient application require comprehensive and dynamic evaluation of its performance, which cannot identify and distinguish the nonlinear type of the material (such as polynomial relationship, exponential relationship, power law relationship, etc.), resulting in the problem of being unable to quantitatively evaluate the size of the nonlinear strength. This qualitative evaluation method cannot provide accurate guidance for the formula optimization and performance improvement of the material. At the same time, affected by factors such as material polarization effect, temperature drift, and electrode contact state, the reproducibility and stability of the test results are poor. Under high electric field conditions, the polarization effect of the material will significantly affect the current response, resulting in greater dispersion of the test data, making it difficult to obtain reliable evaluation results.

[0009] 3. AC impedance spectroscopy test method: the electrical properties of insulating materials are evaluated by measuring the impedance characteristics of the insulating materials at different frequencies.

[0010] This method is mainly suitable for analyzing the equivalent impedance characteristics of linear insulating materials, and for nonlinear anti-corona materials with significant changes in conductivity with electric field strength, the method is difficult to capture the high-order harmonic components generated under the action of alternating electric field, and thus cannot effectively reveal the nonlinear conduction mechanism of the material, nor can it realize the quantitative characterization of the nonlinear characteristics.

[0011] In addition, the above-mentioned methods cannot deeply analyze the physical mechanism of the nonlinear characteristics of the material, and cannot distinguish the contribution of different nonlinear mechanisms to the overall nonlinear behavior of the material. SUMMARY

[0012] Therefore, the present disclosure proposes an insulating material nonlinear strength evaluation method and system based on high-frequency component analysis, which can efficiently, accurately and standardizedly determine the evaluation results of nonlinear strength, and can effectively solve the problems of low test efficiency, poor reproducibility of results, insufficient quantitative ability, and inability to simulate actual alternating working conditions of the existing methods.

[0013] According to an aspect of the present disclosure, an insulating material nonlinear strength evaluation method based on high-frequency component analysis is provided, the method comprising:

[0014] applying an excitation electric signal of a first preset frequency to the insulating material to be tested;

[0015] collecting a response signal obtained by the insulating material responding to the excitation electric signal based on a second preset frequency;

[0016] performing time-frequency transformation on the response signal to obtain frequency characteristics of a plurality of preset high-order harmonic components;

[0017] determine the evaluation result of the nonlinear strength of the insulation material based on the frequency characteristics of the various high-order harmonic components.

[0018] In a possible implementation, the time-frequency transformation on the response signal to obtain the frequency characteristics of the plurality of preset high-order harmonic components comprises:

[0019] obtain a spectrum diagram obtained by time-frequency transformation on the response signal;

[0020] extract at least one frequency characteristic of each high-order harmonic component based on the spectrum diagram, the frequency characteristic comprising at least one of the following: amplitude of each high-order harmonic component, amplitude ratio, spectral steepness, energy distribution.

[0021] In a possible implementation, the determination of the evaluation result of the nonlinear strength of the insulation material based on the frequency characteristics of the various high-order harmonic components comprises:

[0022] input a feature vector composed of the frequency characteristics of the various high-order harmonic components into a pre-trained machine learning model to obtain the nonlinear type;

[0023] and / or,

[0024] determine the nonlinear strength of the insulation material based on the amplitude ratio indicated by the frequency characteristics of each high-order harmonic component.

[0025] In a possible implementation, the application of the excitation electrical signal of the first preset frequency to the insulation material to be tested comprises:

[0026] determine the first preset frequency and the signal amplitude based on the electric field frequency of the alternating electric field environment in which the insulation material actually works, generate and apply the excitation electrical signal of the first preset frequency and the signal amplitude to the insulation material.

[0027] In a possible implementation, the second preset frequency is determined based on the highest frequency in the plurality of high-order harmonic components.

[0028] In a possible implementation, the collection time length of the response signal is determined based on the first preset frequency.

[0029] In a possible implementation, the insulation material is a corona shield material of an end portion of a stator bar of a rotating electrical machine.

[0030] According to another aspect of the present disclosure, there is provided an insulation material nonlinear strength evaluation system based on high-frequency component analysis, comprising: an evaluation device, comprising:

[0031] a signal generation module configured to apply an excitation electrical signal of a first preset frequency to an insulation material to be tested;

[0032] a signal acquisition module configured to acquire a response signal obtained by the insulation material in response to the excitation electrical signal based on a second preset frequency;

[0033] a signal processing module configured to perform time-frequency transformation on the response signal to obtain frequency characteristics of a plurality of preset high-order harmonic components;

[0034] a nonlinear evaluation module configured to determine an evaluation result of the nonlinear strength of the insulation material based on the frequency characteristics of the various high-order harmonic components.

[0035] In a possible implementation, the system further comprises a testing device, wherein the testing device comprises:

[0036] an electrode configured to transmit the excitation electrical signal output by the signal generation module to the insulation material and transmit a response signal obtained by the insulation material in response to the excitation electrical signal; and

[0037] a shield configured to shield the system from electromagnetic interference from the external environment.

[0038] According to another aspect of the present disclosure, there is provided an insulation material nonlinear strength evaluation device based on high-frequency component analysis, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0039] According to another aspect of the present disclosure, there is provided a non-volatile computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the above method.

[0040] According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program, or a non-volatile computer readable storage medium carrying the computer program, wherein the computer program is executed by a processor to implement the steps of the above method.

[0041] The nonlinear strength of the insulating material can be evaluated by applying an excitation electrical signal of a first preset frequency to the insulating material to be tested, collecting a response signal obtained by the insulating material in response to the excitation electrical signal based on a second preset frequency, performing time-frequency transformation on the response signal to obtain frequency characteristics of a plurality of preset high harmonic components, and determining an evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of the high harmonic components. The evaluation result of the nonlinear strength can be obtained by single excitation and response collection, and the test cycle can be shortened and the test efficiency can be improved without the multi-voltage point step test in the traditional technology.

[0042] Other features and aspects of the present disclosure will become apparent from the following detailed description of example embodiments with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate example embodiments, features, and aspects of the present disclosure and serve to explain the principles of the present disclosure.

[0044] Figure 1 A schematic diagram of an insulating material nonlinear strength evaluation system based on high-frequency component analysis according to an embodiment of the present disclosure is shown;

[0045] Figure 2 A schematic diagram of an electrode according to an embodiment of the present disclosure is shown;

[0046] Figure 3 A frequency spectrum diagram of anti-corona belt materials with different nonlinear strengths according to an embodiment of the present disclosure is shown;

[0047] Figure 4 A flowchart of an insulating material nonlinear strength evaluation method based on high-frequency component analysis according to an embodiment of the present disclosure is shown;

[0048] Figure 5 A block diagram of an insulating material nonlinear strength evaluation device based on high-frequency component analysis according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0049] Various example embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the drawings represent functionally the same or similar elements. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0050] As used herein, the terms "comprise", "contain", "have", or variants thereof are open, and include one or more stated features, integers, elements, steps, components or functions, but do not exclude the presence or addition of one or more other features, integers, elements, steps, components, functions or groups thereof.

[0051] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0052] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another. Therefore, without departing from the teachings of the inventive concept, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0053] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0054] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0055] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0056] As discussed above, traditional AC impedance spectroscopy is primarily used to analyze the equivalent impedance characteristics of linear insulating materials. During the analysis, the conductivity of the linear insulating material... The conductivity is usually assumed to be constant, resulting in a linear relationship between the electric field E and the current density J. However, in nonlinear insulating materials, the conductivity... The conductivity changes with the magnitude of the electric field strength E, causing the current density J to exhibit nonlinear response behavior. In this case, traditional AC impedance spectroscopy is no longer applicable. Typically, the conductivity of nonlinear insulating materials (such as corona materials) is... There exists a nonlinear exponential relationship between the electric field strength E and the electric field intensity E, expressed by the following formula:

[0057] ;

[0058] in, This represents the initial conductivity of a nonlinear insulating material in its initial state. The coefficient represents the nonlinearity, and E represents the electric field strength applied to the nonlinear insulating material. (E) represents the conductivity as a function of the electric field strength E.

[0059] For example, if the electric field applied to the nonlinear insulating material is a sinusoidal electric field Where E(t) represents the electric field strength at any time t, E0 represents the amplitude of the electric field, and ω represents the angular frequency of the electric field; then the nonlinear conductivity... This introduces harmonic components into the current density J. Specifically, the conductivity is expanded using Taylor series. The exponent term of (E) yields:

[0060] ;

[0061] sinusoidal electric field Substituting into the above expansion, the current density J(t) is obtained as:

[0062] .

[0063] From the power-reduction formula for trigonometric functions, we can obtain: , Based on this, the current density J(t) can also be expressed as:

[0064] .

[0065] According to the above equation, the second-order nonlinear term of the current density J(t) Second harmonic component appears cubic nonlinear term Third harmonic component appears That is, the nonlinear terms of conductivity correspond to the generation of harmonic components of corresponding orders. For example, the second-order nonlinear term induces the second harmonic component, the third-order nonlinear term induces the third harmonic component, and so on. This indicates that the generation of higher-order harmonic components is due to the nonlinear characteristics of the insulating material (i.e., the non-constant conductivity). Conversely, by quantitatively measuring the intensity and distribution of higher-order harmonic components, the degree of nonlinearity of the insulating material can be effectively inferred, thereby achieving an accurate characterization of the nonlinear coefficient.

[0066] Based on the above principles, this application provides the following method and system for evaluating the nonlinear strength of insulating materials based on high-frequency component analysis.

[0067] Figure 1 A schematic diagram of a nonlinear strength evaluation system for insulating materials based on high-frequency component analysis according to an embodiment of the present disclosure is shown. Figure 1 As shown, the system includes a testing device 110 and an evaluation device 120.

[0068] The testing device 110 can fix the insulating material to be tested. In this application, the insulating material to be tested has nonlinear characteristics, that is, the conductivity changes nonlinearly with the electric field strength. Optionally, the insulating material to be tested can be the anti-corona tape material at the end of the stator bar in a rotating electric machine, wherein the rotating electric machine includes, but is not limited to, hydro-generators, steam turbine generators, and electric motors, etc. This embodiment does not limit the type of rotating electric machine. At this time, by evaluating the nonlinear strength of the anti-corona tape material at the end of the stator bar, the evaluation result can be used to assist in optimizing the electric field distribution design at the end of the bar, effectively suppressing local corona discharge, and improving the insulation reliability and life of the equipment operation; at the same time, it can be used for the research and development and quality control of anti-corona tape materials, providing a quantitative evaluation means for the formulation optimization and production process control of anti-corona materials; and for the quality control of motor manufacturing, providing standardized testing methods and judgment criteria for the incoming inspection of materials by motor manufacturers. In other embodiments, the insulating material to be tested can also be an insulating material with nonlinear characteristics used in other scenarios, and this embodiment does not limit the application scenario of the insulating material. For example: the insulation material to be tested is the anti-corona tape material at the end of the stator bar of a large motor, with a thickness of 0.1-1mm.

[0069] The evaluation device 120 includes: a signal generation module 121, a signal acquisition module 122, a signal processing module 123, and a nonlinear evaluation module 124.

[0070] The signal generation module 121 is used to apply an excitation electrical signal of a first preset frequency to the insulating material to be tested.

[0071] In one example, the signal generation module 121 is specifically used to determine a first preset frequency and a signal amplitude based on the electric field frequency of the alternating electric field environment in which the insulating material is actually working, and to generate and apply an excitation electrical signal with the first preset frequency and signal amplitude to the insulating material.

[0072] For example, the electric field frequency of the alternating electric field environment in which the insulating material is actually operating is equal to the first preset frequency. For instance, if the electric field frequency of the alternating electric field environment in which the insulating material is actually operating is 50Hz, then the first preset frequency is 50Hz. In other application scenarios, the first preset frequency can also vary to 60Hz or other values ​​depending on the electric field frequency of the alternating electric field environment. This embodiment does not limit the value of the first preset frequency.

[0073] The amplitude of the excitation signal (i.e., the voltage amplitude) is adjustable. For example, the range of variation of the signal amplitude in the alternating electric field environment where the insulating material is actually operating is consistent with the range of variation of the excitation signal amplitude. For instance, if the range of variation of the signal amplitude in the alternating electric field environment where the insulating material is actually operating is [0, 1000] V, then the range of variation of the excitation signal amplitude is also [0, 1000] V.

[0074] Optionally, the environmental parameters of the test environment for the insulating material are consistent with the environmental parameters of the actual working environment. For example, if the actual working environment has a temperature of 25°C and a humidity of 50%, then the test environment for the insulating material will also have a temperature of 25°C and a humidity of 50%. If the actual working environment of the insulating material includes multiple environmental parameters, then the nonlinear strength can be evaluated separately for each environmental parameter to obtain the evaluation result of the nonlinear strength corresponding to each environmental parameter.

[0075] Optionally, the excitation signal type can be a sine wave, and / or a square wave, and / or a triangular wave. When the excitation signal includes at least two signal types, the evaluation device 120 can analyze the nonlinear response of the insulating material under excitation signals of different signal types, thereby verifying the robustness of the nonlinear characteristics.

[0076] Optionally, the duration of the excitation electrical signal applied by the signal generation module 121 is at least one cycle of the excitation electrical signal, such as 1 minute. This embodiment does not limit the value of the duration.

[0077] The signal acquisition module 122 is used to acquire the response signal obtained by the insulating material responding to the excitation electrical signal based on the second preset frequency.

[0078] In one example, the second preset frequency is determined based on the highest frequency among a set of preset higher harmonic components. Exemplarily, the second preset frequency is greater than or equal to twice the highest frequency among the higher harmonic components. In other embodiments, the second preset frequency may also be greater than or equal to 20 times the first preset frequency. For example, the first preset frequency ω is 50Hz, and the higher harmonic components include: a harmonic component with a frequency of 2ω (i.e., frequency = 100Hz), a harmonic component with a frequency of 3ω (i.e., frequency = 150Hz), a harmonic component with a frequency of 4ω (i.e., frequency = 200Hz), a harmonic component with a frequency of 5ω (i.e., frequency = 250Hz), and a harmonic component with a frequency of 6ω (i.e., frequency = 300Hz), and the second preset frequency is at least greater than 300 × 2 = 600Hz, and the second preset frequency is greater than or equal to 50 × 20 = 1kHz. For example, the second preset frequency is 10kHz.

[0079] In one example, the acquisition duration of the response signal is determined based on a first preset frequency. For instance, to ensure that the response signal can capture sufficient harmonic information, the acquisition duration is a preset multiple of the period corresponding to the first preset frequency. For example, if the first preset frequency is 50Hz, then the period corresponding to the first preset frequency is 0.02s, and if the preset multiple is 50, then the acquisition duration of the response signal is 0.02 × 50 = 1s.

[0080] For example, the signal acquisition module 122 includes a signal acquisition sensor and a data acquisition card connected to the signal acquisition sensor. Optionally, the signal acquisition sensor can be an ammeter, a Hall effect device, or other device capable of acquiring current; this embodiment does not limit the implementation of the signal acquisition sensor. The data acquisition card is connected to the signal acquisition sensor and is used to acquire the response signal acquired by the signal acquisition sensor. The second preset frequency can be used as the sampling frequency for acquiring the response signal, such as the sampling frequency of the acquisition sensor.

[0081] Optionally, after acquiring the response signal, the signal acquisition module 122 can further preprocess the response signal. Preprocessing methods include, but are not limited to, amplification and / or filtering. This embodiment does not limit the preprocessing method. Correspondingly, the signal acquisition module 122 also includes a signal preprocessing circuit, such as an amplifier and a filter. Subsequent modules process the preprocessed response signal.

[0082] The signal processing module 123 is used to perform time-frequency transformation on the response signal to obtain the frequency characteristics of various preset high-order harmonic components.

[0083] Optionally, the time-frequency transformation of the response signal may include, but is not limited to, the following time-frequency transformation algorithms that can obtain multiple higher harmonic components: Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), wavelet transform, etc. This embodiment does not limit the time-frequency transformation method.

[0084] Because the insulating material in this application has nonlinear conductivity, its current-voltage relationship is no longer linear. This nonlinearity distorts the current waveform, which should be sinusoidal, resulting in a periodically distorted waveform. According to Fourier analysis, the periodically distorted waveform can be decomposed into a fundamental wave and a series of sine waves with frequencies that are integer multiples of the fundamental wave frequency. The series of sine waves with frequencies that are integer multiples of the fundamental wave frequency are the higher harmonic components, and the fundamental wave frequency is the first preset frequency.

[0085] Higher harmonics generally refer to the collective term for second and higher harmonic components. Optionally, the various higher harmonic components in this embodiment include, but are not limited to, higher harmonic components with frequencies of 2ω, 3ω, 4ω, and 5ω, where ω is a first preset frequency. In other embodiments, the various higher harmonic components can be higher harmonic components with more or fewer frequencies. This embodiment does not limit the implementation method of the various higher harmonic components.

[0086] Optionally, the signal processing module 123 performs time-frequency transformation on the response signal to obtain frequency characteristics of various preset higher harmonic components, including: acquiring a spectrum obtained by performing time-frequency transformation on the response signal; and extracting at least one frequency characteristic of each higher harmonic component based on the spectrum, wherein the frequency characteristics include at least one of the following: amplitude, amplitude ratio, spectral steepness, and energy distribution of each higher harmonic component.

[0087] After converting the response signal from the time domain to the frequency domain using a time-frequency transformation algorithm, the amplitude and phase of all higher harmonic components are obtained. Based on the correspondence between the frequency and amplitude of the higher harmonic components, the spectrum of the response signal can be obtained.

[0088] For example, extracting at least one frequency feature of each higher harmonic component based on the spectrum diagram includes: extracting the amplitude corresponding to each preset higher harmonic component in the spectrum diagram; and / or, determining the ratio of the sum of the amplitudes corresponding to each preset higher harmonic component to the fundamental frequency amplitude to obtain the amplitude ratio; and / or, determining the logarithm log(ω) of the frequency of each preset higher harmonic component. n ), and the logarithm (A) of the amplitude of the higher harmonic component. n ), log(ω) with respect to frequency n ) and the logarithm of the magnitude log(A) n Fitting the numerical pairs formed by ) yields log(A) n = α + β·log(ω) n This involves obtaining the spectral steepness β, and / or determining the power corresponding to each higher harmonic component based on its amplitude in the spectrum, and determining the energy distribution corresponding to each preset higher harmonic component based on the power corresponding to each preset higher harmonic component and the sum of the powers corresponding to each higher harmonic component in the spectrum. For example, the energy distribution is obtained by dividing the power corresponding to each preset higher harmonic component by the sum of the powers corresponding to each higher harmonic component in the spectrum.

[0089] In other implementations, the frequency characteristics can also be other indicators determined based on the spectrum. This embodiment does not limit the implementation method of the frequency characteristics.

[0090] Optionally, the signal processing module 123 may include an embedded processor or a dedicated digital signal processor (DSP) to perform time-frequency transformation algorithms and frequency feature extraction processes to obtain the frequency features corresponding to the response signal.

[0091] The nonlinear evaluation module 124 is used to determine the evaluation results of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components.

[0092] In one example, the nonlinear evaluation module 124 determines the evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components, including: inputting a feature vector composed of the frequency characteristics of various higher harmonic components into a pre-trained machine learning model to obtain the nonlinear type; and / or, determining the nonlinear strength of the insulating material based on the amplitude proportion indicated by the frequency characteristics of each higher harmonic component.

[0093] Optionally, the pre-trained machine learning model can be a machine learning-based classification algorithm such as Support Vector Machine (SVM), Random Forest, or Deep Neural Network. This embodiment does not limit the implementation method of the machine learning model.

[0094] Furthermore, this application does not involve improvements to existing machine learning models, but rather a pre-trained machine learning model obtained by training an existing machine learning model using a training set suitable for nonlinear type classification. The training set includes multiple sets of training data. Each set includes frequency feature samples corresponding to the response signal samples generated when an insulating material responds to an excitation electrical signal sample, and a nonlinear type label for the insulating material. The extraction method and data type of the frequency feature samples are consistent with those described above. The type indicated by the nonlinear type label is consistent with the nonlinear types described above. During training, the frequency feature samples can be input into the machine learning model. The loss function value is calculated based on the machine learning model and the nonlinear type label. The parameters of the machine learning model are then adjusted based on the loss function value to obtain the trained machine learning model.

[0095] Optionally, the nonlinear type includes, but is not limited to, strong type (or exponential type), weak type (or polynomial type), etc. In other embodiments, the nonlinear type can also be set to other types as needed. This embodiment does not limit the way nonlinear types are divided.

[0096] Optionally, the machine learning model outputs labels corresponding to feature vectors composed of the frequency characteristics of various higher harmonic components. Correspondingly, the nonlinear evaluation module 124 obtains the correspondence between the labels and the nonlinear types, determining the nonlinear type indicated by the label. For example, machine learning model output 1 indicates a strong nonlinear type; machine learning model output 2 indicates a weak nonlinear type.

[0097] In other embodiments, the evaluation device 120 may further include an output module for outputting the evaluation results of the nonlinear intensity. Optionally, the output module includes, but is not limited to, a display, an audio player, and / or communication components, etc. This embodiment does not limit the implementation of the output module.

[0098] The testing device 110 includes electrodes. The electrodes are a pair of conductive devices between the evaluation device 120 and the insulating material, used to transmit the excitation electrical signal output by the signal generation module 121 to the insulating material, and to transmit the response signal obtained by the insulating material in response to the excitation electrical signal.

[0099] Optionally, the electrode can be a flat plate electrode, a cylindrical electrode, or a needle-plate electrode. The electrode can adopt different shapes depending on the shape of the insulating material. This embodiment does not limit the implementation method of the electrode. (See reference) Figure 2 , Figure 2 The following explanation uses an example where the upper electrode 21 is a cylindrical electrode and the lower electrode 22 is a flat plate electrode.

[0100] In one example, the signal generation module 121 is connected to the test device 110 (specifically to the electrodes of the test device 110) via a high-voltage cable. The electrodes are also connected to the signal acquisition module 122 via a high-voltage cable, specifically to the signal acquisition sensor of the signal acquisition module 122. The signal acquisition module 122 transmits the response signal to the signal processing module 123 for processing via a high-speed data line to obtain the frequency characteristics. The nonlinear evaluation module 124 performs a nonlinear evaluation on the frequency characteristics to obtain the evaluation result of the nonlinear strength of the insulating material.

[0101] Optionally, the test apparatus 110 also includes a shielding cover to isolate the system from electromagnetic interference from the external environment.

[0102] In other embodiments, the testing device 110 may also include other components, such as support components for supporting and fixing insulating materials, etc., which will not be described in detail here.

[0103] In summary, the nonlinear strength evaluation system for insulating materials based on high-frequency component analysis provided in this application includes: a signal generation module for applying an excitation electrical signal of a first preset frequency to the insulating material under test; a signal acquisition module for acquiring the response signal obtained by the insulating material in response to the excitation electrical signal based on a second preset frequency; a signal processing module for performing time-frequency transformation on the response signal to obtain the frequency characteristics of various preset higher harmonic components; and a nonlinear evaluation module for determining the evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components. This system can achieve the evaluation result of nonlinear strength with a single excitation and response acquisition. It eliminates the need for multi-voltage point step testing in traditional technologies, shortening the testing cycle (from several hours to several minutes), improving testing efficiency, and meeting the high-throughput screening needs of material research and development as well as the rapid evaluation requirements of motor manufacturers for the acceptance of anti-corona materials upon arrival at the factory.

[0104] In addition, by extracting the higher harmonic components in the response signal through time-frequency transformation, and constructing feature vectors based on the frequency characteristics of various higher harmonic components, nonlinear types such as power-law, exponential, and polynomial response mechanisms can be automatically distinguished. This solves the problem that traditional methods cannot identify nonlinear characteristics and realizes the identification of nonlinear characteristics.

[0105] In addition, by determining the nonlinear strength of insulating materials, the nonlinear strength can be quantified, thereby supporting the horizontal comparison, vertical tracking and R&D trend judgment of the material properties of insulating materials, overcoming the shortcomings of existing methods that can only obtain discrete conductivity data and cannot output continuous strength quantification indicators.

[0106] In addition, unlike traditional DC or step voltage tests, determining the first preset frequency based on the electric field frequency of the alternating electric field environment in which the insulating material is actually operating can restore the electric field environment in which the insulating material is operating. The current response of the material is more representative. When the insulating material is the anti-corona tape material at the end of the stator bar in a rotating motor, it helps to evaluate its actual effectiveness in suppressing corona and improves the consistency between the test and the actual application.

[0107] In addition, the shielding introduced into the system can enhance the anti-interference and stability of the test data, effectively improving the repeatability and engineering adaptability of the test results.

[0108] In addition, the evaluation system proposed in this application has a unified operating procedure and outputs evaluation results of nonlinear strength. It can serve as a quality evaluation standard interface between material research and development institutions, manufacturing enterprises and users, establish a performance database and classification system for insulating materials, thereby providing quantitative support for manufacturers of insulating materials to optimize structural design, upgrade formulas and manage production quality, and promote industrial technological progress.

[0109] Furthermore, this application is applicable to the testing of anti-corona belt materials in various types of large rotating electrical machines (such as hydro generators, steam turbine generators, and electric motors), possessing good versatility and applicability. It brings significant economic and social benefits in improving equipment insulation reliability, extending motor life, and reducing maintenance frequency, and is particularly suitable for the operation and maintenance support of large-scale national hydropower and thermal power projects.

[0110] To better understand the nonlinear strength evaluation system for insulating materials based on high-frequency component analysis proposed in this application, an example is provided below. In this example, the insulating material is an anti-corona tape material at the end of the stator bars in a rotating electric motor. The thickness of the anti-corona tape film is 0.5 mm, and its dimensions are 10 mm × 10 mm. The signal generation module of the evaluation device applies a 50 Hz sinusoidal excitation signal with an amplitude of 500 V to the insulating material under test. The test environment for the anti-corona tape material is at a temperature of 25°C and a humidity of 50%.

[0111] During the evaluation process, the anti-halo tape material was fixed between the electrodes of the testing device to ensure good contact. The signal generation module continuously outputs an excitation electrical signal for 1 second; the signal acquisition module acquires the response signal (current signal) at a frequency of 20kHz (i.e., the second preset frequency) for 0.2 seconds. The signal acquisition module sends the acquired response signal to the signal processing module, which performs time-frequency conversion to generate a spectrum diagram. From the spectrum diagram, the amplitudes of higher harmonic components such as 100Hz, 150Hz, 200Hz, 250Hz, and 300Hz are extracted; frequency characteristics are obtained based on these amplitudes; the nonlinear evaluation module extracts the feature vector formed by the frequency characteristics and inputs it into a machine learning model to identify the nonlinearity type; and calculates the nonlinearity intensity based on the amplitude. Assuming the spectrum diagrams of anti-halo tape materials with different nonlinear intensities are as follows... Figure 3 As shown, after extracting the amplitudes (i.e., the normalized current amplitudes) of higher harmonic components such as 100Hz, 150Hz, 200Hz, 250Hz and 300Hz from the spectrum and determining the corresponding feature vectors, the classification results of weak nonlinearity type, medium nonlinearity type and strong nonlinearity type are obtained.

[0112] The following describes the nonlinear strength evaluation method for insulating materials based on high-frequency component analysis proposed in this application. This embodiment uses this method for... Figure 1 The evaluation device shown is used as an example for illustration. Figure 4 A flowchart illustrating a method for evaluating the nonlinear strength of insulating materials based on high-frequency component analysis according to an embodiment of this disclosure is shown. Figure 4 As shown, the method includes:

[0113] Step 401: Apply an excitation electrical signal of a first preset frequency to the insulating material to be tested.

[0114] For example, applying an excitation electrical signal of a first preset frequency to the insulating material to be tested includes: determining the first preset frequency and the signal amplitude based on the electric field frequency of the alternating electric field environment in which the insulating material is actually working, generating and applying an excitation electrical signal of the first preset frequency and the signal amplitude to the insulating material.

[0115] Step 402: Collect the response signal obtained by the insulating material responding to the excitation electrical signal based on the second preset frequency.

[0116] For example, the second preset frequency is determined based on the highest frequency among multiple higher harmonic components. The acquisition duration of the response signal is determined based on the first preset frequency.

[0117] Step 403: Perform time-frequency transformation on the response signal to obtain the frequency characteristics of various preset higher harmonic components.

[0118] For example, the response signal is subjected to time-frequency transformation to obtain the frequency characteristics of various preset higher harmonic components, including:

[0119] Obtain the spectrum obtained by performing time-frequency transformation on the response signal; extract at least one frequency feature for each higher harmonic component based on the spectrum, the frequency feature including at least one of the following: amplitude, amplitude ratio, spectral steepness, and energy distribution of each higher harmonic component.

[0120] Step 404: Based on the frequency characteristics of various higher harmonic components, determine the evaluation results of the nonlinear strength of the insulating material.

[0121] For example, determining the evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components includes: inputting a feature vector composed of the frequency characteristics of various higher harmonic components into a pre-trained machine learning model to obtain the nonlinear type; and / or, determining the nonlinear strength of the insulating material based on the amplitude proportion indicated by the frequency characteristics of each higher harmonic component.

[0122] For details, please refer to the above system implementation examples.

[0123] In summary, the nonlinear strength evaluation method for insulating materials based on high-frequency component analysis provided in this embodiment applies an excitation electrical signal of a first preset frequency to the insulating material under test; acquires the response signal obtained by the insulating material in response to the excitation electrical signal based on a second preset frequency; performs time-frequency transformation on the response signal to obtain the frequency characteristics of various preset higher harmonic components; and determines the evaluation result of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components. This method can achieve the evaluation result of nonlinear strength with a single excitation and response acquisition; it eliminates the need for multi-voltage point step testing in traditional techniques, thus shortening the testing cycle and improving testing efficiency.

[0124] This disclosure also provides an insulating material nonlinear strength evaluation device based on high-frequency component analysis, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0125] This disclosure also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0126] This disclosure also provides a computer program product, including a computer program or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program, when executed by a processor, implements the steps of the above method.

[0127] Figure 5 This is a block diagram illustrating a nonlinear strength assessment device 1900 for insulating materials based on high-frequency component analysis, according to an exemplary embodiment. For example, the device 1900 can be provided as a server or terminal device. (Refer to...) Figure 5 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0128] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output interface 1958 (I / O interface). Device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM macOS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0129] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0131] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for evaluating the nonlinear strength of insulating materials based on high-frequency component analysis, characterized in that, The method includes: An excitation electrical signal of a first preset frequency is applied to the insulating material to be tested; The response signal obtained by collecting the response of the insulating material to the excitation electrical signal based on the second preset frequency; The response signal is subjected to time-frequency transformation to obtain the frequency characteristics of various preset higher harmonic components; The evaluation results of the nonlinear strength of the insulating material are determined based on the frequency characteristics of various higher harmonic components.

2. The method according to claim 1, characterized in that, The time-frequency transformation of the response signal yields frequency characteristics of various preset higher harmonic components, including: Obtain the spectrum of the response signal by performing a time-frequency transformation; Based on the spectrum, at least one frequency feature of each higher harmonic component is extracted, and the frequency feature includes at least one of the following: amplitude, amplitude ratio, spectral steepness, and energy distribution of each higher harmonic component.

3. The method according to claim 1, characterized in that, The evaluation results for determining the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components include: The feature vector composed of the frequency characteristics of the various higher harmonic components is input into a pre-trained machine learning model to obtain the nonlinear type. And / or, The nonlinear strength of the insulating material is determined based on the amplitude proportion indicated by the frequency characteristics of each higher harmonic component.

4. The method according to claim 1, characterized in that, The process of applying an excitation electrical signal of a first preset frequency to the insulating material to be tested includes: The first preset frequency and the signal amplitude are determined based on the electric field frequency of the alternating electric field environment in which the insulating material is actually working, and an excitation electrical signal with the first preset frequency and the signal amplitude is generated and applied to the insulating material.

5. The method according to claim 1, characterized in that, The second preset frequency is determined based on the highest frequency among multiple higher harmonic components.

6. The method according to claim 1, characterized in that, The acquisition duration of the response signal is determined based on the first preset frequency.

7. The method according to any one of claims 1 to 6, characterized in that, The insulating material is the anti-corona tape material at the end of the stator bars in a rotating electric motor.

8. A nonlinear strength evaluation system for insulating materials based on high-frequency component analysis, characterized in that, The system includes: an evaluation device, comprising: The signal generation module is used to apply an excitation electrical signal of a first preset frequency to the insulating material to be tested; The signal acquisition module is used to acquire the response signal obtained by the insulating material responding to the excitation electrical signal based on a second preset frequency; The signal processing module is used to perform time-frequency transformation on the response signal to obtain the frequency characteristics of various preset higher harmonic components; The nonlinear evaluation module is used to determine the evaluation results of the nonlinear strength of the insulating material based on the frequency characteristics of various higher harmonic components.

9. The system according to claim 8, characterized in that, The system further includes: a testing device, the testing device comprising: Electrodes are used to transmit the excitation electrical signal output by the signal generation module to the insulating material, and to transmit the response signal obtained by the insulating material in response to the excitation electrical signal; and, A shielding cover is used to isolate the system from electromagnetic interference from the external environment.

10. A nonlinear strength evaluation device for insulating materials based on high-frequency component analysis, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

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