Switch cabinet contact surface simulation method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a switch cabinet contact surface simulation method and device, equipment and a storage medium, and the method comprises the steps: generating a two-dimensional white noise signal through Gaussian distribution based on randomly generated noise, carrying out the Fourier transformation of the two-dimensional white noise signal, obtaining an initial frequency domain signal, and carrying out the Fourier transformation of the initial frequency domain signal; according to a pre-acquired surface roughness parameter and a preset target power spectral density, a filter transfer function is designed, an initial frequency domain signal is processed based on the filter transfer function to obtain a filtered frequency domain signal, inverse Fourier transform is performed on the filtered frequency domain signal to generate a surface height distribution function of the contact surface, and the surface height distribution function of the contact surface is calculated. And dynamically adjusting the surface roughness parameter, and repeating the operation to obtain a surface height distribution function of the contact surface under different working conditions. According to the method, through frequency domain filtering and multi-scale iteration, the limitation of a traditional single-scale model is broken through, precise modeling of the contact surface microstructure is achieved, and the operation efficiency and long-term reliability of equipment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission and distribution equipment, and particularly relates to a switch cabinet contact surface simulation method, device, equipment and storage medium. BACKGROUND

[0002] With the rapid development of modern power systems, the safety and reliability of switch cabinets as core equipment in power transmission and distribution systems directly affect the stability of the entire power network. In the switch cabinet, the performance of the electrical contact surface not only affects the conduction efficiency of electric energy, but also determines the mechanical stability and long-term reliability of the equipment. However, the microstructure of the switch cabinet contact surface is complex, usually showing multi-scale roughness characteristics, which significantly affect from nanometers to microns to macroscopic scales. These roughness characteristics determine the actual contact area, contact resistance and thermodynamic performance, and will dynamically change under working load, current conduction and environmental effects, which significantly affect the contact performance of the equipment.

[0003] Current roughness modeling techniques have been applied in many engineering fields, but there are still obvious deficiencies in the specific modeling needs of switch cabinet contact surfaces. Traditional roughness modeling methods are usually based on ideal assumptions, such as assuming that the contact surface height distribution is normally distributed, or ignoring the interaction of roughness at different scales.

[0004] However, the above methods have certain theoretical guiding significance, but are difficult to truly reflect the contact behavior of the micro-rough surface under complex working conditions, especially the performance evolution under high load, variable temperature environment or long-term operation. SUMMARY

[0005] The embodiments of the present application provide a switch cabinet contact surface simulation method, device, equipment and storage medium, which can effectively analyze the change rule of contact impedance and provide reliable basis for the design and optimization of switch cabinet contact surfaces, thereby improving the operation efficiency and long-term reliability of the equipment.

[0006] In a first aspect, the embodiments of the present application provide a switch cabinet contact surface simulation method, comprising:

[0007] Step 1, based on randomly generated noise, generating a two-dimensional white noise signal through Gaussian distribution, and performing Fourier transform on the two-dimensional white noise signal to obtain an initial frequency domain signal;

[0008] Step 2, designing a filter transfer function according to pre-acquired surface roughness parameters and pre-set target power spectral density, wherein the surface roughness parameters include roughness root mean square value, autocorrelation length and multi-scale amplitude distribution;

[0009] Step 3: Processing the initial frequency domain signal based on the filter transfer function to obtain a filtered frequency domain signal;

[0010] Step 4, performing an inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface, wherein the height distribution function represents a microscopic relief feature of the contact surface in a vertical direction;

[0011] Step 5: Dynamically adjust the surface roughness parameters and repeat steps 2 to 4 to obtain the surface height distribution function of the contact surface under different working conditions.

[0012] In one possible implementation, the method further includes:

[0013] For each working condition, the surface height distribution function under the working condition is decomposed in the frequency domain to extract the asperity density and curvature radius of each frequency domain segment;

[0014] Based on the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material, the actual contact area of ​​the contact surface under the working condition is obtained through iterative calculation;

[0015] According to the contact radius corresponding to the actual contact area under each working condition, the contact resistance is calculated in combination with the material resistivity, and the contact inductance is calculated in combination with the magnetic permeability and geometric parameters;

[0016] A contact surface impedance database is constructed based on the contact resistance and contact inductance of the contact surface under all working conditions.

[0017] In one possible implementation, the method further includes:

[0018] The target power spectrum density is established based on the autocorrelation function characteristics of the contact surface.

[0019] In a possible implementation, the filter transfer function is designed based on the pre-acquired surface roughness parameter and the pre-set target power spectrum density, including:

[0020] determining a transfer function amplitude-frequency characteristic according to a ratio of the target power spectrum density to a square root of a normalization constant;

[0021] Calculating the total energy of the output signal based on the amplitude-frequency characteristic of the transfer function;

[0022] According to the predetermined actual total energy and the total energy of the output signal, a normalization constant is adjusted and the filter transfer function is determined.

[0023] In one possible implementation, the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus, and yield strength characteristics of the contact material, are used to iteratively calculate the actual contact area of ​​the contact surface under the working condition, including:

[0024] Step a: for each working condition, initializing the ideal contact area of ​​the contact surface and setting an initial frequency band index;

[0025] Step b, allocating a local contact load that a single asperity can withstand according to the contact load and the total number of asperities indexed by the current frequency band;

[0026] Step c, determining, for each micro-asperity, a deformation mode of the micro-asperity based on the local contact load that the micro-asperity can withstand, the elastic modulus, and the yield strength characteristics;

[0027] Step d, determining the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities;

[0028] Step e, adding up the contact areas of all asperities in the current frequency band to obtain the total contact area of ​​the current frequency band;

[0029] Step f, determining the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band;

[0030] Step g: increment the frequency band index and repeat steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

[0031] In a possible implementation, determining the deformation mode of the micro-asperities based on the local contact load that the micro-asperities can withstand, the elastic modulus, and the yield strength characteristics includes:

[0032] For each micro-asperity, if the local contact load that the micro-asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the micro-asperity;

[0033] If the local contact load that the micro-asperities can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the micro-asperities.

[0034] In a possible implementation, determining the contact area of ​​the micro-protrusion based on the deformation mode of the micro-protrusion includes:

[0035] For each micro-asperity, a contact radius of the micro-asperity is calculated based on the deformation mode of the micro-asperity;

[0036] The contact area of ​​the micro-protrusion is calculated according to the contact radius of the micro-protrusion.

[0037] In a second aspect, an embodiment of the present application provides a switch cabinet contact surface simulation device, comprising:

[0038] a transform module, configured to generate a two-dimensional white noise signal through a Gaussian distribution based on the randomly generated noise, and perform Fourier transform on the two-dimensional white noise signal to obtain an initial frequency domain signal;

[0039] a design module for designing a filter transfer function based on pre-acquired surface roughness parameters and pre-set target power spectral density, wherein the surface roughness parameters include a root mean square value of roughness, an autocorrelation length, and a multi-scale amplitude distribution;

[0040] a filtering module, configured to process the initial frequency domain signal based on the filter transfer function to obtain a filtered frequency domain signal;

[0041] an inverse transform module, configured to perform an inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface, wherein the height distribution function represents a microscopic relief feature of the contact surface in a vertical direction;

[0042] The dynamic adjustment module is used to dynamically adjust the surface roughness parameters and repeat the above operations to obtain the surface height distribution function of the contact surface under different working conditions.

[0043] In a possible implementation, the device further includes:

[0044] An extraction module is used to perform frequency domain decomposition on the surface height distribution function under each working condition, and extract the asperity density and curvature radius of each frequency domain segment;

[0045] A first calculation module is configured to obtain an actual contact area of ​​the contact surface under the working condition through iterative calculation based on the asperity density and curvature radius of each frequency domain segment, in combination with the contact load, the elastic modulus and the yield strength characteristics of the contact material;

[0046] The second calculation module is used to calculate the contact resistance based on the contact radius corresponding to the actual contact area under each working condition in combination with the material resistivity, and to calculate the contact inductance in combination with the magnetic permeability and geometric parameters;

[0047] A construction module is used to construct a contact surface impedance database based on the contact resistance and contact inductance of the contact surface under all working conditions.

[0048] In a possible implementation, the device further includes:

[0049] An establishing module is used to establish the target power spectrum density based on the autocorrelation function characteristics of the contact surface.

[0050] In a possible implementation, the design module is specifically used to:

[0051] determining a transfer function amplitude-frequency characteristic according to a ratio of the target power spectrum density to a square root of a normalization constant;

[0052] Calculating the total energy of the output signal based on the amplitude-frequency characteristic of the transfer function;

[0053] According to the predetermined actual total energy and the total energy of the output signal, a normalization constant is adjusted and the filter transfer function is determined.

[0054] In a possible implementation, the first calculation module is specifically configured to:

[0055] Step a: for each working condition, initializing the ideal contact area of ​​the contact surface and setting an initial frequency band index;

[0056] Step b, allocating a local contact load that a single asperity can withstand according to the contact load and the total number of asperities indexed by the current frequency band;

[0057] Step c, determining, for each micro-asperity, a deformation mode of the micro-asperity based on the local contact load that the micro-asperity can withstand, the elastic modulus, and the yield strength characteristics;

[0058] Step d, determining the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities;

[0059] Step e, adding up the contact areas of all asperities in the current frequency band to obtain the total contact area of ​​the current frequency band;

[0060] Step f, determining the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band;

[0061] Step g: increment the frequency band index and repeat steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

[0062] In a possible implementation, the first calculation module determines the deformation mode of the asperity based on the local contact load that the asperity can withstand, the elastic modulus, and the yield strength characteristics, specifically including:

[0063] For each micro-asperity, if the local contact load that the micro-asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the micro-asperity;

[0064] If the local contact load that the micro-asperities can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the micro-asperities.

[0065] In a possible implementation, the first calculation module determines the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities, specifically including:

[0066] For each micro-asperity, a contact radius of the micro-asperity is calculated based on the deformation mode of the micro-asperity;

[0067] The contact area of ​​the micro-protrusion is calculated according to the contact radius of the micro-protrusion.

[0068] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0069] The memory stores computer-executable instructions;

[0070] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0071] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0072] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0073] The switchgear contact surface simulation method, apparatus, device, and storage medium provided in the embodiments of the present application generate a two-dimensional white noise signal through a Gaussian distribution based on randomly generated noise. The two-dimensional white noise signal is Fourier transformed to obtain an initial frequency domain signal. A filter transfer function is designed based on pre-acquired surface roughness parameters and a pre-set target power spectral density. The initial frequency domain signal is processed based on the filter transfer function to obtain a filtered frequency domain signal. The filtered frequency domain signal is inversely Fourier transformed to generate a surface height distribution function of the contact surface. The surface roughness parameters are dynamically adjusted and the above operation is repeated to obtain the surface height distribution function of the contact surface under different operating conditions. The above method, through frequency domain filtering and multi-scale iteration, breaks through the limitations of traditional single-scale models, achieves accurate modeling of the contact surface micromorphology, and improves the operating efficiency and long-term reliability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The accompanying drawings, which are incorporated herein and constitute part of this specification, illustrate embodiments consistent with the application and, together with the description, further serve to explain the principles of the application.

[0075] Figure 1 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 1 ;

[0076] Figure 2 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 2 ;

[0077] Figure 3 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 3 ;

[0078] Figure 4 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 4 ;

[0079] Figure 5 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 5 ;

[0080] Figure 6 Flowchart of the switchgear contact surface simulation method provided in the present application Figure 6 ;

[0081] Figure 7 Contact surface height distribution function image

[0082] Figure 8 Rough surface contact model schematic diagram

[0083] Figure 9 Contact inductance measured value and calculated value comparison schematic diagram

[0084] Figure 10 Contact resistance measured value and calculated value comparison schematic diagram

[0085] Figure 11 Structure schematic diagram of the switchgear contact surface simulation device provided in the present application

[0086] Figure 12 Structure schematic diagram of the electronic device provided in the present application.

[0087] The specific embodiments of the present application have been shown in the above drawings, and will be described in more detail hereinafter. These drawings and written descriptions are not intended to limit the scope of the concept of the present application by any means, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0088] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0089] With the rapid development of modern power systems, switchgear, as a core component of power transmission and distribution systems, has a safety and reliability that is directly related to the stability of the entire power network. In switchgear, the performance of the electrical contact surface not only affects the efficiency of power transmission but also determines the mechanical stability and long-term reliability of the equipment. However, the microstructure of the switchgear contact surface is complex, often exhibiting multi-scale roughness, with significant effects from nanometers to micrometers to macroscales. These roughness characteristics determine the actual contact area, contact resistance, and thermodynamic properties, and they change dynamically under load, current conduction, and environmental influences, significantly affecting the contact performance of the equipment.

[0090] Current roughness modeling techniques have been applied in many engineering fields, but they still face significant deficiencies in addressing the specific modeling needs of switchgear contact surfaces. Traditional roughness modeling methods often rely on idealistic assumptions, such as a normal distribution of contact surface height or ignoring the interactions between roughness at different scales. While these methods offer some theoretical guidance, they struggle to accurately reflect the contact behavior of microscopic roughness surfaces under complex operating conditions, particularly under high loads, fluctuating temperatures, or under long-term operation.

[0091] To address the above-mentioned issues, the present application provides a switchgear contact surface simulation method, apparatus, device, and storage medium. These methods can effectively analyze the variation patterns of contact impedance and provide a reliable basis for the design and optimization of switchgear contact surfaces, thereby improving the equipment's operating efficiency and long-term reliability. Specifically, current roughness modeling techniques primarily include fractal theory, spectral analysis, and statistical methods. Fractal theory describes rough surface characteristics through self-similarity and can effectively capture the multi-scale characteristics of roughness, but its computational efficiency is low when dealing with complex contact topologies. Spectral analysis methods, such as fast Fourier transforms or wavelet transforms, can perform frequency domain decomposition of rough surfaces and extract multi-scale information, but they struggle to account for both topographical details and dynamic changes. Statistical methods, which establish probability distribution models by fitting experimental data, are suitable for describing common roughness characteristics, but are insufficient for describing roughness variations caused by non-Gaussian distributions or multi-physics field coupling. With these issues in mind, the inventors investigated whether a multi-scale modeling approach could be used to comprehensively describe the roughness characteristics of contact surfaces, thereby constructing a contact surface impedance database. This technology accurately simulates multi-scale contact surface topologies and compares them with measured contact surface impedance data to predict the actual electrical performance of the contact surface. This not only improves the scientific nature of switchgear design and manufacturing, but also provides a reliable basis for equipment operation and maintenance, thereby significantly improving the operating efficiency, stability, and lifespan of the switchgear. Based on this, the solution of this application is proposed.

[0092] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0093] Figure 1 Schematic diagram of the process of the switch cabinet contact surface simulation method provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0094] Step 1: Based on the randomly generated noise, a two-dimensional white noise signal is generated through Gaussian distribution, and the two-dimensional white noise signal is Fourier transformed to obtain an initial frequency domain signal.

[0095] In this step, in order to provide a basic signal for subsequent frequency domain filtering and accurately simulate the randomness of the contact surface micromorphology, randomly generated noise can be input into the Gaussian distribution to generate a two-dimensional white noise signal, where the mean of the two-dimensional white noise signal is 0, the variance is 1, and its frequency domain energy is uniformly distributed, which can be expressed by the formula η(x,y)~N(0,1).

[0096] It should be noted that the two-dimensional white noise signal is generated based on the mathematical laws of the Gaussian distribution. This Gaussian distribution is a purely mathematical probability distribution that imparts randomness to the signal. The generated white noise signal exhibits irregular fluctuations in the spatial domain. Essentially, it is a sequence of numbers that follows a specific probability distribution. It has no direct connection to the actual switchgear contact surface and serves only as a basic input for subsequent operations.

[0097] Then perform Fourier transform on the two-dimensional white noise signal to obtain the initial frequency domain signal A(ω x ,ω y ), can be expressed as A(ω x ,ω y )=F[η(x,y)].

[0098] The randomness is generated by white noise in order to accurately simulate the natural disorder of the contact surface micromorphology. The frequency domain signal provides a unified basis for subsequent filtering, which can facilitate the subsequent multi-scale feature injection.

[0099] It should be noted that the obtained two-dimensional white noise signal is subjected to a Fourier transform. The Fourier transform is a mathematical transformation tool that can convert a white noise signal in the spatial domain (describing the changes in the signal's spatial position) into the frequency domain (describing which different frequency components the signal is composed of) to obtain an initial frequency domain signal. The initial frequency domain signal at this time has a flat power spectrum density in the frequency domain, that is, the energy of each frequency component is relatively evenly distributed, but this is still only a mathematical signal processing result and does not yet involve the characteristics of the switch cabinet contact surface. It is only to provide a basis for accurately representing the actual microscopic morphology of the contact surface in the future, so that it can accurately reflect the frequency domain characteristic requirements of the switch cabinet contact surface after filtering, and then generate a contact surface morphology that conforms to reality.

[0100] In summary, this step uses mathematical methods (Gaussian distribution and Fourier transform) to generate a purely random frequency domain signal basis, which is then used for subsequent filtering through the filter transfer function to introduce contact surface related features, thereby accurately obtaining the actual microscopic morphology of the contact surface.

[0101] Step 2: Design a filter transfer function based on the pre-acquired surface roughness parameters and the pre-set target power spectrum density.

[0102] In this step, to accurately match the statistical characteristics of the actual contact surface of the switchgear, the filter design is performed based on the target power spectral density and surface roughness parameters. Surface roughness parameters include the root mean square value of the roughness, the autocorrelation length, and the multi-scale amplitude distribution.

[0103] Specifically, the target power spectrum density needs to be designed first, which can be designed based on the autocorrelation function characteristics of the contact surface.

[0104] The filter transfer function is determined by the square root ratio of the target power spectral density and a normalization constant, which is used to match the energy distribution of the filtered signal to the actual contact surface characteristics.

[0105] Optionally, the method further includes establishing a target power spectrum density based on the autocorrelation function characteristics of the contact surface.

[0106] Among them, the autocorrelation function R(τ x ,τ y ), for R(τ x ,τ y ) is Fourier transformed to obtain the target power spectrum density G(ω x ,ω y ).

[0107] The autocorrelation function can be expressed as:

[0108]

[0109] Where σ is the root mean square value of roughness, β x and β y Represents the autocorrelation length.

[0110] The final filter transfer function H(ω x ,ω y ) can be expressed by the following formula:

[0111]

[0112] Where C represents the normalization constant.

[0113] Step 3: Process the initial frequency domain signal based on the filter transfer function to obtain a filtered frequency domain signal.

[0114] In this step, after the filter is designed, it is applied to the initial frequency domain signal in step 1 to obtain a filtered frequency domain signal. The filter adjusts the spectral distribution of the initial frequency domain signal to meet the target power spectral density requirements.

[0115] Specifically, through the filter transfer function H(ω x ,ω y ) for the initial frequency domain signal A(ω x ,ω y ) is processed to obtain the filtered frequency domain signal Z(ω x ,ω y ) can be expressed as:

[0116] Z(ω x ,ωy )=A(ω x ,ω y )·H(ω x ,ω y ) (3)

[0117] Step 4: Perform inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface.

[0118] In this step, after obtaining the filtered frequency domain signal, the frequency domain signal is converted back to the spatial domain to obtain a three-dimensional height distribution of the contact surface with multi-scale characteristics.

[0119] Specifically, the filtered frequency domain signal Z(ω x ,ω y ) is inverse Fourier transformed to obtain the surface height distribution function z(x,y) of the contact surface, which can be expressed as z(x,y)=F -1 [Z(ω x ,ω y )].

[0120] Discretize it and express it as:

[0121]

[0122] Step 5: By dynamically adjusting the surface roughness parameters, repeat steps 2 to 4 to obtain the surface height distribution function of the contact surface under different working conditions.

[0123] In this step, in order to simulate the morphological evolution of the contact surface during long-term operation or under different environments (such as wear, oxidation, and temperature change), the surface roughness parameters can be adjusted and the above steps can be repeated to simulate the surface height distribution function of the switchgear contact surface under different working conditions.

[0124] Specifically, the RMS roughness value, or the standard deviation of the surface height distribution, characterizes the absolute height fluctuation of microscopic undulations. A larger RMS roughness value indicates a rougher surface. For example, a worn hoe's surface will have a significantly increased RMS roughness value. A smaller RMS roughness value indicates a smoother surface.

[0125] The autocorrelation length is the spatial correlation scale of surface height changes, reflecting the correlation distance between the height values ​​of adjacent points. The larger the autocorrelation length, the slower the height changes and the surface is gently undulating. The smaller the autocorrelation length, the more drastic the height changes and the surface is randomly peaked.

[0126] The multi-scale amplitude distribution is the contribution weight of different spatial scales (frequency bands) to the total roughness. The high-frequency band (short wavelength) has a large amplitude, and the surface contains a large number of nano-scale micro-protrusions. The low-frequency band (long wavelength) has a large amplitude, and the surface contains macroscopic undulations.

[0127] Alternatively, surface roughness parameters can be obtained by scanning the three-dimensional topography of the contact surface and then calculating the parameters to extract the multi-scale amplitude distribution. The amplitude weights of each frequency band can be decomposed through Fourier transform. Alternatively, parameters can be queried through empirical values ​​or a database.

[0128] The present application provides a method for measuring the contact impedance of a switchgear circuit. Based on randomly generated noise, a two-dimensional white noise signal is generated through a Gaussian distribution, and the two-dimensional white noise signal is Fourier transformed to obtain an initial frequency domain signal. According to the pre-acquired surface roughness parameters and the pre-set target power spectrum density, a filter transfer function is designed. The initial frequency domain signal is processed based on the filter transfer function to obtain a filtered frequency domain signal. The filtered frequency domain signal is inversely Fourier transformed to generate a surface height distribution function of the contact surface. By dynamically adjusting the surface roughness parameters and repeating the above operation, the surface height distribution function of the contact surface under different working conditions is obtained. The above method, through frequency domain filtering and multi-scale iteration, breaks through the limitations of the traditional single-scale model, realizes the precise modeling of the microscopic morphology of the contact surface, and improves the operating efficiency and long-term reliability of the equipment.

[0129] Figure 2 Schematic diagram of the process of the switch cabinet contact surface simulation method provided in this application Figure 2 ,like Figure 2 The method further comprises:

[0130] S201: For each working condition, perform frequency domain decomposition on the surface height distribution function under the working condition, and extract the asperity density and curvature radius of each frequency domain segment.

[0131] In this step, multi-scale characteristic parameters (micro-asperity density, curvature radius) are extracted from the three-dimensional micromorphology of the contact surface to provide basic data for subsequent contact area and impedance calculations.

[0132] Specifically, for each operating condition, the surface height distribution function under that condition is subjected to a fast Fourier transform or wavelet transform to decompose it into multiple frequency band components. Each frequency band corresponds to micro-asperities of a specific scale (e.g., low frequencies correspond to macroscopic undulations, and high frequencies correspond to nanoscale micro-asperities). The asperity density and curvature radius of each frequency band are then extracted.

[0133] Among them, the specific formulas of asperity density and curvature radius are expressed as follows:

[0134] η i =2f i 2 (5)

[0135]

[0136] Among them, ηi represents the asperity density, r i represents the radius of curvature, f i Indicates frequency, the reciprocal of wavelength, β i Indicates the amplitude corresponding to a given frequency.

[0137] S202: Based on the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material, the actual contact area of ​​the contact surface under the working condition is obtained through iterative calculation.

[0138] In this step, the actual contact area is calculated step by step by combining the contact load, material properties (elastic modulus, yield strength) and multi-scale micro-asperity parameters to reflect the influence of micro-morphology on contact performance.

[0139] Specifically, step a, for each working condition, initializes the ideal contact area of ​​the contact surface and sets the initial frequency band index; step b, allocates the local contact load that a single micro-asperity can withstand according to the contact load and the total number of micro-asperities of the current frequency band index; step c, for each micro-asperity, determines the deformation mode of the micro-asperity based on the local contact load, elastic modulus and yield strength characteristics that the micro-asperity can withstand; step d, determines the contact area of ​​the micro-asperity based on the deformation mode of the micro-asperity; step e, accumulates the contact areas of all micro-asperities in the current frequency band to obtain the total contact area of ​​the current frequency band; step f, determines the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band; step g, increments the frequency band index, repeats steps b to f, until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

[0140] The specific formula is:

[0141]

[0142] Among them, A r represents the actual contact area, F represents the contact load, A n is the ideal contact area, i represents the frequency band index, i max Indicates the highest frequency band, and They are the single bump contact area and single bump contact force at a certain frequency level.

[0143] S203: Calculate the contact resistance based on the contact radius corresponding to the actual contact area under each working condition in combination with the material resistivity, and calculate the contact inductance in combination with the magnetic permeability and geometric parameters.

[0144] In this step, the contact resistance and inductance are calculated based on the actual contact area to provide data support for the construction of the impedance database.

[0145] Specifically, the calculation formula is expressed as:

[0146]

[0147] Among them, R 总 Indicates contact resistance, L 总 Represents contact inductance, R i represents the contact resistance of the ith frequency band, L i represents the contact inductance of the i-th frequency band.

[0148] Optionally, the contact resistance calculation formula for each frequency band is expressed as:

[0149]

[0150] The calculation formula of contact inductance in each frequency band is expressed as:

[0151] L i =[1.545μ(ra i )-0.533μr]10 -7 (12)

[0152] Where ρ represents the surface resistivity, a i represents the contact radius of the i-th frequency band, μ represents the magnetic permeability, r represents the curvature radius,

[0153] Optionally, the calculation formula for the contact radius of the i-th frequency band can be expressed as:

[0154]

[0155] S204: Construct a contact surface impedance database based on the contact resistance and contact inductance of the contact surface under all working conditions.

[0156] In this step, the impedance data under different working conditions are integrated to support the design optimization and condition monitoring of the switchgear contact surface.

[0157] Specifically, based on the combination of different surface roughness parameters and working conditions, the contact resistance and contact inductance under different working conditions are obtained, and then the combination parameters and impedance data are stored as a relational database table.

[0158] Optionally, the measured impedance data is matched with the optimal parameter combination in the database to invert the microscopic features of the actual contact surface, such as the density of asperities and the radius of curvature.

[0159] The switch cabinet contact surface simulation method provided by the embodiment of the present application performs frequency domain decomposition on the surface height distribution function under each working condition, extracts the micro-convex body density and curvature radius of each frequency domain segment, and obtains the actual contact area of ​​the contact surface under the working condition through iterative calculation based on the micro-convex body density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material. According to the contact radius corresponding to the actual contact area under each working condition, the contact resistance is calculated in combination with the material resistivity, and the contact inductance is calculated in combination with the magnetic permeability and geometric parameters. Based on the contact resistance and contact inductance of the contact surface under all working conditions, a contact surface impedance database is constructed. The above method realizes accurate prediction from micro-morphology to macro-electrical performance through the combination of multi-scale modeling and database technology. Through frequency domain decomposition and step-by-step iterative calculation, it accurately simulates the influence of micro-convex bodies of different scales on the contact area, breaking through the limitations of the traditional single-scale model. Significantly improve the operating efficiency and life of the equipment.

[0160] Figure 3 Schematic diagram of the process of the switch cabinet contact surface simulation method provided in this application Figure 3 ,like Figure 3 As shown, based on the above embodiment, step 2 specifically includes:

[0161] S301: Determine the amplitude-frequency characteristic of a transfer function according to a ratio of a target power spectrum density to a square root of a normalization constant.

[0162] S302: Calculate the total energy of the output signal based on the amplitude-frequency characteristic of the transfer function.

[0163] S303: According to the predetermined actual total energy and the total energy of the output signal, adjust the normalization constant and determine the filter transfer function.

[0164] Based on the target power spectral density and the normalization constant, the amplitude-frequency characteristics of the filter transfer function are designed to ensure that the energy distribution of the generated frequency domain signal is consistent with the target power spectral density.

[0165] The target power spectrum density is obtained by performing Fourier transform based on the autocorrelation function of the contact surface, and then the ratio of the target power spectrum density to the square root of the normalization constant is determined as the amplitude-frequency characteristic of the transfer function.

[0166] Verify whether the filtered frequency domain signal under the current transfer function meets the target total energy requirement, provide a basis for subsequent adjustments, and then calculate the total energy of the output signal.

[0167] Multiply the initial frequency domain signal and the transfer function to obtain the filtered frequency domain signal, and calculate the total energy of the filtered signal, which can be expressed as:

[0168]

[0169] By iteratively adjusting the normalization constant, the total energy of the filtered signal is made consistent with the target total energy, ensuring that the generated surface morphology conforms to physical reality.

[0170] Exemplarily, if the total energy of the filtered signal is less than the target total energy, the normalization constant is increased and the amplitude-frequency characteristic of the transfer function is reduced, thereby increasing the energy of the filtered signal.

[0171] If the total energy of the filtered signal is greater than the target total energy, the normalization constant is reduced and the amplitude-frequency characteristic of the transfer function is improved, thereby reducing the energy of the filtered signal.

[0172] Optionally, the iteration may be performed based on Newton's method or bisection method until the total energy of the filtered signal converges to the target total energy, thereby obtaining the filter transfer function.

[0173] The switchgear contact surface simulation method provided in this embodiment determines the transfer function amplitude-frequency characteristic based on the ratio of the target power spectral density to the square root of a normalization constant. The total energy of the output signal is calculated based on the transfer function amplitude-frequency characteristic. The normalization constant is adjusted based on the predetermined actual total energy and the total energy of the output signal, and the filter transfer function is determined. This method avoids energy overshoot or undershoot, optimizes computational efficiency, and achieves precise control from frequency-domain characteristics to spatial-domain topography.

[0174] Figure 4 Schematic diagram of the process of the switchgear contact surface simulation method provided in the application Figure 4 ,like Figure 4 Based on the above embodiments, step S202 specifically includes:

[0175] Step a: For each working condition, initialize the ideal contact area of ​​the contact surface and set the initial frequency band index.

[0176] In this step, for each working condition, it is first necessary to provide initial conditions for the multi-scale iterative calculation and determine the macroscopic nominal contact area and the starting analysis frequency band.

[0177] Initialize the ideal contact area of ​​the contact surface. The ideal contact area is the nominal macroscopic area of ​​the contact surface, not accounting for microscopic roughness. It is typically set to the square of the scan length, L, where the scan length is the side length of the simulation or measurement area. Set the initial frequency band index, i.e., the index can be set to i, starting at 0, for subsequent iterations, proceeding from low to high frequencies.

[0178] Step b: allocating the local contact load that a single asperity can bear according to the contact load and the total number of asperities indexed by the current frequency band.

[0179] In this step, in order to determine the local contact load that each micro-asperity can withstand, the total number of micro-asperities in the current frequency band i is calculated by the micro-asperity density and the ideal contact area of ​​the previous frequency band. The local contact load that a single micro-asperity can withstand is the ratio of the contact load to the total number of micro-asperities.

[0180] Step c: for each micro-asperity, determining the deformation mode of the micro-asperity based on the local contact load, elastic modulus and yield strength characteristics that the micro-asperity can withstand.

[0181] In this step, in order to determine the actual contact area, calculations need to be performed based on the contact radius, and thus a deformation mode for calculating the contact radius needs to be determined in advance.

[0182] Specifically, for each asperity, if the local contact load that the asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the asperity. If the local contact load that the asperity can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the asperity.

[0183] Step d: determining the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities.

[0184] In this step, after the deformation mode is determined, the contact radius is calculated based on the deformation mode, and then the contact area of ​​the asperities is calculated, thereby providing basic data for subsequent accumulation.

[0185] Step e: adding up the contact areas of all asperities in the current frequency band to obtain the total contact area of ​​the current frequency band.

[0186] In this step, the contact areas of all asperities in the current frequency band are summed to obtain the total contact area at this scale (current frequency band).

[0187] Step f: The smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band is determined as the ideal contact area of ​​the next frequency band.

[0188] In this step, in order to avoid repeated calculation of contact areas of different scales and ensure physical consistency, the ideal contact area needs to be corrected.

[0189] To prevent the contact area of ​​the high-frequency band (microscale) from exceeding the actual contact area of ​​the low-frequency band (macroscale), reflecting the hierarchical dependency of multi-scale contact behavior, the total contact area of ​​the current frequency band is compared with the contact area of ​​the previous frequency band, and the smaller area is determined as the ideal contact area for the next frequency band.

[0190] Step g: increment the frequency band index and repeat steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

[0191] After processing the current frequency band, the frequency band index is incremented and the iterative calculation of the next frequency band is continued until the calculation of all frequency bands is completed. Finally, the contact area of ​​each frequency band is added together to obtain the actual contact area of ​​the contact surface.

[0192] The switch cabinet contact surface simulation method provided in the embodiment of the present application includes: step a, initializing the ideal contact area of ​​the contact surface for each working condition, and setting the initial frequency band index. Step b, allocating the local contact load that a single micro-protrusion can withstand based on the contact load and the total number of micro-protrusions of the current frequency band index. Step c, determining the deformation mode of each micro-protrusion based on the local contact load, elastic modulus and yield strength characteristics that the micro-protrusion can withstand. Step d, determining the contact area of ​​the micro-protrusion based on the deformation mode of the micro-protrusion. Step e, adding up the contact areas of all micro-protrusions in the current frequency band to obtain the total contact area of ​​the current frequency band. Step f, determining the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band. Step g, incrementing the frequency band index, repeating steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition. The above method avoids repeated calculation of contact areas of different scales by correcting the nominal area step by step, ensuring physical consistency. The step-by-step processing from low frequency to high frequency conforms to the physical law that actual contact behavior penetrates from large scale to small scale, reduces the computational complexity of global optimization, and accurately simulates the contribution of micro-asperities of different scales to the contact area.

[0193] Figure 5 Schematic diagram of the process of the switch cabinet contact surface simulation method provided in this application Figure 5 ,like Figure 5 It is shown that, based on the above embodiments, step c specifically includes:

[0194] S501: For each micro-asperity, if the local contact load that the micro-asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the micro-asperity.

[0195] S502: If the local contact load that the asperity can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the asperity.

[0196] When the local contact load is low (less than the material yield strength), the contact radius is calculated using elastic deformation theory, reflecting the reversible deformation characteristics of the micro-asperity. When the local contact load is high (greater than or equal to the material yield strength), the contact radius is calculated using plastic deformation theory, reflecting the irreversible deformation characteristics of the micro-asperity.

[0197] The local contact load and yield strength that the asperity can withstand are compared to determine the deformation mode.

[0198] The switchgear contact surface simulation method provided in the embodiments of the present application, for each asperity, determines the deformation mode of the asperity using elastic deformation theory if the local contact load the asperity can withstand is less than the yield strength; and uses plastic deformation theory if the local contact load the asperity can withstand is greater than or equal to the yield strength. This method adaptively selects the elastic / plastic model by comparing local stress with yield strength, ensuring the physical consistency of multi-scale contact behavior. This method achieves precise modeling of multi-scale asperity contact behavior, breaking through the limitations of traditional single-scale models and significantly improving the accuracy and practicality of contact performance predictions.

[0199] Figure 6 Schematic diagram of the process of the switch cabinet contact surface simulation method provided in this application Figure 6 ,like Figure 6 As shown, based on the above embodiments, step d specifically includes:

[0200] S601: For each asperity, a contact radius of the asperity is calculated based on the deformation mode of the asperity.

[0201] S602: Calculate the contact area of ​​the micro-asperities according to the contact radius of the micro-asperities.

[0202] According to the deformation mode (elasticity / plasticity) of the micro-convex body, an applicable mechanical model is selected to calculate the contact radius, providing basic parameters for subsequent contact area calculation.

[0203] For example, the contact radius in the elastic deformation mode is calculated based on the Hertz contact theory, and the contact radius in the plastic deformation mode is calculated based on the plastic flow theory.

[0204] After the contact radius is calculated, the contact area of ​​a single micro-asperity is calculated based on the contact radius, providing basic data for the step-by-step accumulation of multi-scale contact areas.

[0205] The switchgear contact surface simulation method provided in this application embodiment calculates the contact radius of each asperity based on its deformation pattern, and then calculates its contact area based on the asperity's contact radius. This method calculates contact radius and area in frequency bands, covering the full range of scales, from macroscopic undulations to nanoscale asperities, overcoming the limitations of traditional single-scale models.

[0206] For example, Figure 7 Contact surface height distribution function image, Figure 8 Schematic diagram of the rough surface contact model. Figure 9 Schematic diagram comparing the measured and calculated values ​​of contact inductance. Figure 10Schematic diagram comparing the measured and calculated values ​​of contact resistance, combined with Figure 7 and Figure 8 , conduct corrosion tests on the actual switch cabinet contact structure, measure its impedance, and record the contact resistance and contact inductance data under different degradation cycles. Compare the measured contact resistance and contact inductance data with the database to extract the corresponding surface roughness parameters. The methods of the above embodiments use these parameters to generate equivalent three-dimensional contact surface data such as Figure 7 As shown, Figure 7 The X-axis and Y-axis are used to determine the position of each point on the contact surface, and the Z-axis determines the height of each point. The units of the coordinate axes are all length units, which shows the complex undulations of the microscopic morphology of the contact surface. And import it into the simulation software for simulation. Figure 8 The contact resistance and contact inductance data extracted by simulation are compared with the measured values. Figure 9 、 Figure 10 As shown, the results show that the error between the simulation data and the measured data does not exceed 10%, thereby verifying the effectiveness of the methods of the above embodiments.

[0207] Figure 11 The schematic diagram of the structure of the switch cabinet contact surface simulation device provided in this application is as follows: Figure 11 As shown, the switch cabinet contact surface simulation device 1100 includes:

[0208] The transformation module 1101 is configured to generate a two-dimensional white noise signal through Gaussian distribution based on the randomly generated noise, and perform Fourier transform on the two-dimensional white noise signal to obtain an initial frequency domain signal.

[0209] The design module 1102 is used to design a filter transfer function based on pre-acquired surface roughness parameters and a pre-set target power spectrum density. The surface roughness parameters include the root mean square value of roughness, autocorrelation length, and multi-scale amplitude distribution.

[0210] The filtering module 1103 is configured to process the initial frequency domain signal based on a filter transfer function to obtain a filtered frequency domain signal.

[0211] The inverse transform module 1104 is used to perform inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface. The height distribution function represents the microscopic relief characteristics of the contact surface in the vertical direction.

[0212] The dynamic adjustment module 1105 is used to dynamically adjust the surface roughness parameters and repeat the above operations to obtain the surface height distribution function of the contact surface under different working conditions.

[0213] In one possible implementation, the switch cabinet contact surface simulation device 1100 further includes:

[0214] The extraction module 1106 is used to perform frequency domain decomposition on the surface height distribution function under each working condition, and extract the asperity density and curvature radius of each frequency domain segment.

[0215] The first calculation module 1107 is used to obtain the actual contact area of ​​the contact surface under the working condition through iterative calculation based on the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material.

[0216] The second calculation module 1108 is used to calculate the contact resistance based on the contact radius corresponding to the actual contact area under each working condition in combination with the material resistivity, and calculate the contact inductance in combination with the magnetic permeability and geometric parameters.

[0217] The construction module 1109 is used to construct a contact surface impedance database based on the contact resistance and contact inductance of the contact surface under all working conditions.

[0218] In one possible implementation, the switch cabinet contact surface simulation device 1100 further includes:

[0219] The establishing module 1110 is used to establish a target power spectrum density based on the autocorrelation function characteristics of the contact surface.

[0220] In one possible implementation, the design module 1102 is specifically configured to:

[0221] The amplitude-frequency characteristic of the transfer function is determined according to the square root ratio of the target power spectrum density and the normalization constant;

[0222] Calculate the total energy of the output signal based on the amplitude-frequency characteristics of the transfer function;

[0223] According to the predetermined actual total energy and the total energy of the output signal, the normalization constant is adjusted and the filter transfer function is determined.

[0224] In a possible implementation, the first calculation module 1107 is specifically configured to:

[0225] Step a: for each working condition, initialize the ideal contact area of ​​the contact surface and set the initial frequency band index;

[0226] Step b, allocating the local contact load that a single asperity can withstand according to the contact load and the total number of asperities indexed by the current frequency band;

[0227] Step c, for each micro-asperity, determining a deformation mode of the micro-asperity based on the local contact load, elastic modulus, and yield strength characteristics that the micro-asperity can withstand;

[0228] Step d, determining the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities;

[0229] Step e, adding up the contact areas of all asperities in the current frequency band to obtain the total contact area of ​​the current frequency band;

[0230] Step f, determining the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band;

[0231] Step g: increment the frequency band index and repeat steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

[0232] In a possible implementation, the first calculation module 1107 determines the deformation mode of the asperities based on the local contact load, elastic modulus, and yield strength characteristics that the asperities can withstand, specifically including:

[0233] For each micro-asperity, if the local contact load that the micro-asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the micro-asperity;

[0234] If the local contact load that the asperity can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the asperity.

[0235] In a possible implementation, the first calculation module 1107 determines the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities, specifically including:

[0236] For each micro-asperity, the contact radius of the micro-asperity is calculated based on the deformation mode of the micro-asperity;

[0237] The contact area of ​​the micro-asperities is calculated based on the contact radius of the micro-asperities.

[0238] Figure 12 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 12 As shown, the electronic device 1200 provided in this embodiment includes: at least one processor 1201 and a memory 1202. Optionally, the electronic device 1200 further includes a communication component 1203. The processor 1201, the memory 1202, and the communication component 1203 are connected via a bus 1204.

[0239] During the specific implementation process, at least one processor 1201 executes the computer-executable instructions stored in the memory 1202, so that the at least one processor 1201 executes the methods of the above-mentioned embodiments.

[0240] The specific implementation process of the processor 1201 can be found in the above-mentioned various method embodiments. The implementation principles and technical effects are similar and will not be repeated here in this embodiment.

[0241] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented by a hardware processor or implemented by a combination of hardware and software modules in the processor.

[0242] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0243] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0244] The present application also provides a computer program product, including a computer program, which implements the methods of the above embodiments when executed by a processor.

[0245] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the methods of the above-mentioned embodiments are implemented.

[0246] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0247] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0248] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, for example, combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, whether electrical, mechanical, or otherwise, through some interface.

[0249] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0250] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0251] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0252] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0253] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A switch cabinet contact surface simulation method, characterized in that: include: Step 1: generating a two-dimensional white noise signal through Gaussian distribution based on randomly generated noise, and performing Fourier transform on the two-dimensional white noise signal to obtain an initial frequency domain signal; Step 2: designing a filter transfer function based on pre-acquired surface roughness parameters and a pre-set target power spectral density, wherein the surface roughness parameters include a root mean square value of roughness, an autocorrelation length, and a multi-scale amplitude distribution; Step 3: Processing the initial frequency domain signal based on the filter transfer function to obtain a filtered frequency domain signal; Step 4, performing an inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface, wherein the height distribution function represents a microscopic relief feature of the contact surface in a vertical direction; Step 5: Dynamically adjust the surface roughness parameters and repeat steps 2 to 4 to obtain the surface height distribution function of the contact surface under different working conditions.

2. The method according to claim 1, characterized in that The method further comprises: For each working condition, the surface height distribution function under the working condition is decomposed in the frequency domain to extract the asperity density and curvature radius of each frequency domain segment; Based on the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material, the actual contact area of ​​the contact surface under the working condition is obtained through iterative calculation; According to the contact radius corresponding to the actual contact area under each working condition, the contact resistance is calculated in combination with the material resistivity, and the contact inductance is calculated in combination with the magnetic permeability and geometric parameters; A contact surface impedance database is constructed based on the contact resistance and contact inductance of the contact surface under all working conditions.

3. The method according to claim 1, characterized in that The method further comprises: The target power spectrum density is established based on the autocorrelation function characteristics of the contact surface.

4. The method according to claim 1, wherein The filter transfer function is designed based on the pre-acquired surface roughness parameters and the pre-set target power spectrum density, including: determining a transfer function amplitude-frequency characteristic according to a ratio of the target power spectrum density to a square root of a normalization constant; Calculating the total energy of the output signal based on the amplitude-frequency characteristic of the transfer function; According to the predetermined actual total energy and the total energy of the output signal, a normalization constant is adjusted and the filter transfer function is determined.

5. The method according to claim 2, characterized in that The actual contact area of ​​the contact surface under the working condition is obtained by iterative calculation based on the asperity density and curvature radius of each frequency domain segment, combined with the contact load, elastic modulus and yield strength characteristics of the contact material, including: Step a: for each working condition, initializing the ideal contact area of ​​the contact surface and setting an initial frequency band index; Step b, allocating a local contact load that a single asperity can withstand according to the contact load and the total number of asperities indexed by the current frequency band; Step c, determining, for each micro-asperity, a deformation mode of the micro-asperity based on the local contact load that the micro-asperity can withstand, the elastic modulus, and the yield strength characteristics; Step d, determining the contact area of ​​the micro-asperities based on the deformation mode of the micro-asperities; Step e, adding up the contact areas of all asperities in the current frequency band to obtain the total contact area of ​​the current frequency band; Step f, determining the smaller contact area between the total contact area of ​​the current frequency band and the ideal contact area of ​​the previous frequency band as the ideal contact area of ​​the next frequency band; Step g: increment the frequency band index and repeat steps b to f until all frequency bands are traversed to obtain the actual contact area of ​​the contact surface under the working condition.

6. The method according to claim 5, characterized in that The step of determining the deformation mode of the micro-asperities based on the local contact load that the micro-asperities can withstand, the elastic modulus, and the yield strength characteristics includes: For each micro-asperity, if the local contact load that the micro-asperity can withstand is less than the yield strength, the elastic deformation theory is determined as the deformation mode of the micro-asperity; If the local contact load that the micro-asperities can withstand is greater than or equal to the yield strength, the plastic deformation theory is determined as the deformation mode of the micro-asperities.

7. The method according to claim 5, characterized in that The determining of the contact area of ​​the micro-protrusion based on the deformation mode of the micro-protrusion comprises: For each micro-asperity, a contact radius of the micro-asperity is calculated based on the deformation mode of the micro-asperity; The contact area of ​​the micro-protrusion is calculated according to the contact radius of the micro-protrusion.

8. A switch cabinet contact surface simulation device, characterized in that: include: a transform module, configured to generate a two-dimensional white noise signal through a Gaussian distribution based on the randomly generated noise, and perform Fourier transform on the two-dimensional white noise signal to obtain an initial frequency domain signal; A design module is used to design a filter transfer function based on pre-acquired surface roughness parameters and pre-set target power spectral density, wherein the surface roughness parameters include a root mean square value of roughness, an autocorrelation length, and a multi-scale amplitude distribution; A filtering module, configured to process the initial frequency domain signal based on the filter transfer function to obtain a filtered frequency domain signal; an inverse transform module, configured to perform an inverse Fourier transform on the filtered frequency domain signal to generate a surface height distribution function of the contact surface, wherein the height distribution function represents a microscopic relief feature of the contact surface in a vertical direction; The dynamic adjustment module is used to dynamically adjust the surface roughness parameters and repeat the above operations to obtain the surface height distribution function of the contact surface under different working conditions.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the switch cabinet contact surface simulation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the switch cabinet contact surface simulation method according to any one of claims 1 to 7.

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