Method and system for determining physical properties of arc discharge plasma in transformer oil

Abstract

The present invention provides a method and system for determining the physical properties of arc discharge plasma in transformer oil, relating to the field of data processing technology. The implementation scheme comprises: performing a power-frequency arc discharge on the transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and collecting the radiation light from the power-frequency arc discharge; performing spectral analysis on the radiation light, and determining the particle type, heavy particle temperature, electron temperature, and excited-state temperature of the plasma in the transformer oil based on the spectral analysis results; iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited-state temperature of the plasma in the transformer oil to obtain a target particle concentration for each element; and determining the physical properties of the plasma in the transformer oil based on the target particle concentration for each element. This method can accurately describe the physical properties of the plasma in the transformer oil.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for determining physical properties of arc discharge plasma in transformer oil. Background Art

[0002] Ultra-high voltage transformers are known as the "heart" of the power grid, and their safety is directly related to the stable operation of the power system. However, due to insufficient understanding of high-energy arc discharge explosion protection technology, the risk of explosion in the event of internal failure is extremely high.

[0003] In-depth research on the arc characteristics in transformer oil, calculation of key plasma parameters, and subsequent development of arc pressure simulation models, along with the design of effective explosion-proof measures and verification, are crucial for ensuring the safe operation of transformers and protecting the lives and property of personnel. These studies will enhance equipment reliability and provide crucial data and theoretical foundations for preventing power grid accidents.

[0004] However, most current studies only focus on the calculation of arc discharge plasma components in vacuum or insulating gas, or on electric explosion plasma in water. In comparison, the understanding of arc discharge plasma in transformer oil only remains at the qualitative analysis level, and there is a lack of accurate modeling of plasma during the development and evolution of arc discharge in oil.

[0005] Therefore, a method for calculating the key parameters of arc discharge plasma in transformer oil is urgently needed to provide parameter support for building simulation models. This has important scientific value and engineering significance for revealing the macroscopic and microscopic development mechanisms of long-gap arc discharge in oil and exploring the characteristics and evolution of power-frequency high-energy arc discharge in oil. Summary of the Invention

[0006] The present invention provides a method and system for determining the physical properties of arc discharge plasma in transformer oil, which can solve at least one of the above technical problems.

[0007] According to one aspect of the present invention, a method for determining physical properties of arc discharge plasma in transformer oil is provided, comprising:

[0008] Performing power frequency arc discharge on transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and collecting radiation light from the power frequency arc discharge;

[0009] performing a spectral analysis on the radiation light, and determining the particle types, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil based on the spectral analysis results;

[0010] Iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain a target particle concentration of each element;

[0011] Based on the target particle concentration of each of the elements, physical properties of the plasma in the transformer oil are determined.

[0012] According to another aspect of the present invention, there is provided a device for determining physical properties of arc discharge plasma in transformer oil, the device comprising:

[0013] An arc discharge module is used to perform power frequency arc discharge on transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and to collect radiation light from the power frequency arc discharge;

[0014] a spectral analysis module, configured to perform spectral analysis on the radiated light and determine the particle types, heavy particle temperature, electron temperature, and excited state temperature of the plasma in the transformer oil based on the spectral analysis results;

[0015] a particle concentration determination module, configured to iteratively correct the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain a target particle concentration of each element;

[0016] The physical property determination module is used to determine the physical property of the plasma in the transformer oil based on the target particle concentration of each element.

[0017] According to another aspect of the present invention, a system for determining physical properties of arc discharge plasma in transformer oil is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the processing is configured to retrieve the instructions from the memory and execute the instructions, so that the at least one processor can perform the method for determining physical properties of arc discharge plasma in transformer oil according to any one of the embodiments of the present invention.

[0018] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are provided to a computer to instruct the computer to execute the method for determining physical properties of arc discharge plasma in transformer oil according to any one of the embodiments of the present invention.

[0019] According to the technical solution of the present invention, when power-frequency arc discharge is performed on transformer oil, the initial particle concentration of each element when a plasma channel is formed in the transformer oil is first determined, and the radiation light of the power-frequency arc discharge is collected and spectrally analyzed. Based on the spectral analysis results, the particle type, heavy particle temperature, electron temperature, and excited-state temperature in the plasma in the transformer oil are determined. The initial particle concentration of each element is iteratively corrected using the particle type, heavy particle temperature, electron temperature, and excited-state temperature in the plasma to obtain the target particle concentration of each element. Thus, the physical properties of the plasma in the transformer oil can be accurately described using the accurate particle concentration of each element.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are provided for a better understanding of the present invention and do not constitute a limitation of the present invention.

[0022] Figure 1 is a flow chart of a method for determining physical properties of arc discharge plasma in transformer oil according to one embodiment of the present invention;

[0023] Figure 2 1 is a block diagram of a device for determining physical properties of arc discharge plasma in transformer oil according to an embodiment of the present invention;

[0024] Figure 3 is a block diagram of an electronic device for implementing the method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, and various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0026] Figure 1 The present invention is a flowchart of a method for determining physical properties of arc discharge plasma in transformer oil according to an embodiment of the present invention.

[0027] like Figure 1 As shown, the method for determining the physical properties of the arc discharge plasma in the transformer oil may include:

[0028] S110, performing power frequency arc discharge on the transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and collecting radiation light from the power frequency arc discharge;

[0029] S120, performing spectral analysis on the radiated light, and determining the particle type, heavy particle temperature, electron temperature, and excited state temperature of the plasma in the transformer oil based on the spectral analysis results;

[0030] S130, iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain a target particle concentration of each element;

[0031] S140 , determining physical properties of the plasma in the transformer oil based on the target particle concentration of each element.

[0032] For example, the power frequency arc discharge in transformer oil occurs between the copper electrode, insulating oil, and insulating cardboard. Therefore, the discharge process involves three elements: copper, carbon, and hydrogen. In step S110, the initial particle concentrations of the three elements are determined.

[0033] Exemplarily, the plasma includes heavy particles and electrons, and the types of heavy particles include three main types: copper, carbon, and hydrogen, i.e., the types of particles mentioned above.

[0034] For example, the initial particle concentration of each element may be the concentration of the current ionized particles of the corresponding type of heavy particles at the first iteration.

[0035] According to the above embodiment, when power-frequency arc discharge is performed on transformer oil, the initial particle concentration of each element when a plasma channel is formed in the transformer oil is first determined, and the radiation light of the power-frequency arc discharge is collected and spectrally analyzed. Based on the spectral analysis results, the particle type, heavy particle temperature, electron temperature, and excited-state temperature in the plasma in the transformer oil are determined. The initial particle concentration of each element is iteratively corrected using the particle type, heavy particle temperature, electron temperature, and excited-state temperature in the plasma to obtain the target particle concentration of each element. Therefore, the accurate particle concentration of each element can be used to accurately describe the physical properties of the plasma in the transformer oil.

[0036] In one embodiment, the above-mentioned determining the initial particle concentration of each element when the plasma channel is formed in the transformer oil includes: determining the gas density of the power frequency arc discharge based on the vapor pressure, evaporation heat, gas temperature and gas volume of the power frequency arc discharge; and determining the initial particle concentration of the copper element when the plasma channel is formed in the transformer oil based on the gas density of the power frequency arc discharge.

[0037] In this example, the metal in the transformer oil exists as a vapor under high-temperature conditions, such as those caused by an electric arc. Therefore, the initial density of the copper element can be determined using the Clausius-Clapeyron equation and the ideal gas law.

[0038] Among them, the Clausius-Clapeyron equation is used to describe the relationship between the vapor pressure of a gas and the temperature of the gas, and its form is:

[0039] ;

[0040] in, represents the vapor pressure of copper metal gas, represents the temperature of copper metal gas, represents the heat of vaporization of copper metal gas, represents the gas constant.

[0041] Since the vapor pressure of copper metal gas can be determined based on the above formula, the initial particle concentration of copper element can be determined according to the following gas law.

[0042] ;

[0043] ;

[0044] .

[0045] in, represents the vapor pressure of copper metal gas, represents the volume of copper metal gas, represents the total number of molecules of copper metal gas, is the molar mass of the molecules in copper metal gas, is the initial particle concentration of copper metal gas, also known as gas density, represents the temperature of copper metal gas, represents the gas constant, is the amount density of copper metal gas per unit volume.

[0046] According to the above embodiment, the initial particle concentration of the copper element when the plasma channel is formed in the transformer oil can be determined.

[0047] In one embodiment, determining the initial particle concentration of each element when the plasma channel in the transformer oil is formed includes: determining the initial particle concentration of the carbon element and the initial particle concentration of the hydrogen element based on the volume of the plasma channel in the transformer oil and the proportion of the medium participating in the cracking reaction in the plasma channel.

[0048] Understandably, the length of the transformer's electrode gap corresponds to the length of the arc in the oil, and the arc channel's geometry is roughly cylindrical. Combining existing experimental measurements, the arc channel radius can be estimated. Given the high temperature and high energy environment of the arc in oil, the medium within the arc zone undergoes varying degrees of cracking reactions, such as the decomposition of mineral oil and cellulose, which in turn affects the concentrations of elements such as carbon and hydrogen.

[0049] Exemplarily, the plasma channel volume in transformer oil can be expressed as follows:

[0050] ;

[0051] in, represents the volume of the plasma channel in the transformer oil, represents the arc length in oil, i.e. the plasma channel length, Indicates the radius of the arc channel.

[0052] For example, within the effective area of the arc channel, about 10% of the volume of the medium participates in the cracking reaction generated by the high temperature of the arc, from which the initial density of the generated carbon and hydrogen elements, that is, the initial particle concentration, can be estimated.

[0053] According to the above embodiment, the initial particle concentration of carbon element and the initial particle concentration of hydrogen element when the plasma channel is formed in the transformer oil can be determined.

[0054] In one embodiment, based on the spectral analysis results, the particle types, heavy particle temperature, electron temperature and excited state temperature in the plasma in the transformer oil are determined, including: matching the spectral characteristics in the spectral analysis results with the spectral characteristics of each particle type to determine the particle types in the plasma in the transformer oil; determining the heavy particle temperature in the plasma based on the ion spectral line broadening in the spectral analysis results; determining the electron temperature in the plasma based on the heavy particle temperature in the plasma and the temperature relationship between the electron temperature and the heavy ion temperature; and determining the excited state temperature in the plasma based on the radiation intensity of the transition spectrum in the spectral analysis results.

[0055] Exemplarily, a high-resolution spectrometer is used to collect the radiation light generated by the arc discharge in real time, and the signal covers the ultraviolet, visible and near-infrared bands.

[0056] Exemplarily, spectral analysis of the radiation light includes: matching the spectral features in the radiation light with the spectral features of each candidate particle type to obtain a degree of matching between the spectral features in the radiation light and the spectral features of each candidate particle type, using this degree to determine the corresponding candidate particle type among each candidate particle type, and using the determined candidate particle type as the particle type in the plasma in the transformer oil.

[0057] For example, the collected spectral signals are decoded and the main particles produced during the discharge process, such as H, C, O atoms and molecular free radicals such as CH, are identified by matching the characteristic spectral lines.

[0058] For example, the main chemical reaction chain and product generation mechanism can be inferred by combining the detected particle types, concentrations, and energy distribution with the known reaction pathways of oil molecule cracking (such as the breakage of CH bonds and CC bonds, and free radical reactions).

[0059] For example, the heavy particle temperature can be indirectly inferred by observing ion line broadening, combined with spectral analysis results. Ion line broadening is typically caused by ion collisions and thermal motion. This line broadening is measured by measuring the full width at half maximum (FWHM) of the spectral line. Combined with kinetic energy theory, the heavy particle temperature can be estimated using the following formula.

[0060] ;

[0061] in, The spectral line broadening of copper particles, carbon particles or copper particles in the plasma, is the Boltzmann constant, is the heavy particle temperature of copper particles, carbon particles or copper particles in the plasma, represents the mass of copper particles, carbon particles or copper particles in the plasma, Represents the speed of light.

[0062] In this way, by inputting the spectral line broadening and mass of the corresponding particle into the above formula, the heavy particle temperature of the particle can be calculated.

[0063] For example, in an arc discharge plasma in transformer oil, the process of electrons approaching thermal equilibrium primarily involves collisions with various particles. The mathematical relationship between the electron temperature and the heavy particle temperature can be derived using the Coulomb collision model, which describes two-body elastic collisions between electrons and heavy particles.

[0064] For example, the mathematical relationship between the electron temperature and the heavy particle temperature can be expressed as follows:

[0065] ;

[0066] in, represents the electron temperature of the electrons in the plasma, represents the heavy particle temperature of copper particles, carbon particles or copper particles in plasma, represents the heavy particle temperature of copper particles, carbon particles or copper particles in plasma, represents the mass of electrons in the plasma, represents the electric field strength of the plasma, represents the mean free path, represents the Boltzmann constant.

[0067] According to the above formula, the corresponding electron temperature can be calculated based on the heavy particle temperature of each type of particle, and then the calculated electron temperatures can be averaged as the electron temperature of electrons in the plasma.

[0068] For example, according to the experimentally measured radiation intensity of the transition spectrum and the Boltzmann distribution formula, when multiple energy level data are known, a linear fit is performed, and the slope of the fitting line is , the excited state temperature can be obtained.

[0069] For example, the excited state temperature of each particle in the plasma can be calculated using the following formula:

[0070] ;

[0071] in, It represents the spectral line intensity of copper particles, carbon particles or copper particles in plasma from the initial energy level to the final energy level. represents the degeneracy of the copper, carbon or copper particles in the plasma at the initial energy level, represents the transition probability of copper particles, carbon particles or copper particles in plasma from the initial energy level to the final energy level, It represents the transition frequency of copper particles, carbon particles or copper particles in plasma from the initial energy level to the final energy level, represents the energy level of copper particles, carbon particles or copper particles in plasma, represents the excited state temperature of copper particles, carbon particles or copper particles in plasma, Indicates the total number of copper particles, carbon particles or copper particles in the plasma, The partition function represents the partition function of copper particles, carbon particles or copper particles in the plasma.

[0072] Thus, according to the above formula, the excited state temperature of copper particles, carbon particles or copper particles in the plasma can be calculated.

[0073] Through the above spectral analysis and related calculations, the heavy particle temperature, excited state temperature, and electron temperature of the copper, carbon, or copper particles in the plasma are obtained. Using this information, the concentration of copper, carbon, or copper particles in the plasma can be iteratively corrected to obtain the accurate stable concentration of copper, carbon, or copper particles in the plasma.

[0074] The Saha equation, part of the law of mass action, applies to plasmas in thermal equilibrium, where electrons follow the Maxwell-Boltzmann distribution. However, given that arc discharge in transformer oil is in a thermodynamically non-equilibrium state, the conventional Saha equation is not applicable. Embodiments of the present invention modify the plasma state by taking into account at least one or a combination of three aspects, such as the concentration of various particles.

[0075] 1. In a non-equilibrium state, interparticle interactions cannot be ignored. Therefore, the temperature of heavy particles is introduced to form a dual-temperature model and the excited-state temperature is calculated, rather than approximating the temperature by using the electron temperature. The effect of temperature gradients on the degree of ionization is also considered. In this embodiment of the present invention, heavy particles refer to any type of particle other than electrons.

[0076] 2. The Debye screening effect and collision effect in arc discharge in transformer oil will reduce the ionization energy. The decrease in ionization energy should be taken into account in the ionization equation.

[0077] 3. Considering that high-energy electrons do not follow the Maxwell-Boltzmann distribution, the Kappa distribution is introduced to correct the ionization process, obtaining an ionization process that is more consistent with the plasma distribution characteristics in transformer oil.

[0078] In one embodiment, iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain the target particle concentration of each element includes: using a first formula, iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain the target particle concentration of each element;

[0079] Among them, the first formula is:

[0080] ;

[0081] ;

[0082] in, represents the electron density, represents the concentration of the next ionized particle, Indicates the current concentration of ionized particles, represents the distribution function of the current ionized particles, represents the distribution function of the next ionized particle, represents the ionization energy of the current ionized particle, represents the ionization energy of the next ionized particle, represents the mass of the electron, represents Planck's constant, represents the electron temperature in the plasma, The excited state temperature in the plasma, It represents the ionization energy drop difference between the ionization energy of the current ionized particle and the ionization energy of the next ionized particle. represents the correction factor, represents the Boltzmann constant.

[0083] In one embodiment, it further includes:

[0084] Use the second formula to calculate the ionization energy drop difference;

[0085] Among them, the second formula is:

[0086] ;

[0087] ;

[0088] in, represents the energy level of the current ionized particle, represents the dielectric constant, represents the Debye length, represents the total number of particle types in the plasma, Indicates the The amount of charge on the particles, Indicates the The total number of particles, represents the heavy particle temperature.

[0089] In one embodiment, the dissociation reaction is typically larger than the ionization reaction, which cannot be ignored. Therefore, the Guldberg-Wagge dissociation equation from the law of mass action can be incorporated into the calculation of plasma composition. To accommodate arc discharge in transformer oil, the temperature is corrected. Specifically, the excited state temperature is introduced, which more accurately describes the energy distribution between dissociation products and molecules. Furthermore, due to the plasma discharge effect, local temperatures in the plasma can vary significantly, affecting the dissociation dynamic equilibrium. Therefore, a temperature gradient term is incorporated into the calculation of plasma composition. The corrected dissociation equation is shown below.

[0090] ;

[0091] in, The original particle before dissociation The total number of Represents particles before dissociation The total number of Particles involved in dissociation The total number of For particles The partition function of For particles The partition function of For the original particle The partition function of Represents particles quality, Represents particles quality, Represents the primary particle quality.

[0092] In this way, the modified Saha equation and the Guldberg-Wagge dissociation equation are alternately iteratively updated starting from the initial concentration of each element until a relatively stable composition result is obtained, completing the calculation of the power frequency arc discharge plasma composition in transformer oil.

[0093] In one embodiment, determining physical properties of the plasma in the transformer oil based on target particle concentrations of the respective elements includes determining specific heat capacity, thermal conductivity, electrical conductivity, carrier mobility, and diffusion coefficient of the plasma in the transformer oil based on the target particle concentrations of the respective elements.

[0094] For example, a gas model is used to calculate the specific heat capacity of an arc discharge plasma in oil, fully accounting for the physical properties of the different particle components in the plasma and their influence on thermodynamic properties. Because ions have a much larger mass than electrons and relatively few degrees of freedom, their specific heat capacity is typically significantly smaller than that of electrons. Therefore, when calculating the specific heat capacity, the contributions of electrons and ions are calculated separately, and then the specific heat capacities of the two are weighted to obtain the total specific heat capacity.

[0095] ;

[0096] ;

[0097] ;

[0098] in, is the electron concentration, , and are the particle concentrations of copper ions, carbon ions, and hydrogen ions in the plasma, respectively. is the total specific heat capacity, is the electronic specific heat capacity, is the specific heat capacity of the particle, is the Boltzmann constant.

[0099] For example, thermal conductivity in oil arc plasma is primarily composed of contributions from electrons and ions. At low pressure and low temperature, electrons dominate the overall thermal conductivity; however, at high pressure and high density, the contribution from ions increases. The Spitzer-Härm equation is used to describe the thermal conductivity of oil arc plasma.

[0100] ;

[0101] in, is the effective charge number, is the Lorentz factor, for example, it takes a value of 10, is the thermal conductivity, It's the temperature.

[0102] The Spitzer-Härm equation is based on the current transport equation and plasma collision theory. It assumes that electron diffusion in plasma follows a model similar to gas molecular motion and that multiple interactions occur during collisions, including electron-ion collisions and electron-neutral particle collisions. Furthermore, to more accurately calculate the thermal conductivity of a plasma, the contribution of all particles must be considered. The effective charge of a plasma is used to reflect the effective number of charged particles in the plasma and to describe the total charge state of a plasma composed of various ions and neutral atoms.

[0103] ;

[0104] in, is the charge of copper electrons, is the charge number of carbon electrons, is the charge of hydrogen electrons, is the number of copper ion particles, is the number of carbon ion particles, is the number of hydrogen ion particles.

[0105] For example, in the case of arc discharge plasma in transformer oil, conductivity is affected by the concentration of ions and free electrons, temperature, and the frequency of collisions between them. Plasma conductivity is typically dominated by the conductive contribution of electrons. The movement and collisions of electrons determine their response characteristics under the action of an electric field, which in turn affects conductivity. This is expressed as follows:

[0106] ;

[0107] in, is the electronic conductivity, is the electron collision time, is the mass of the electron, is the number of electrons.

[0108] The collision frequency of electrons is It can be approximately calculated by the following formula:

[0109] .

[0110] The above two formulas can be combined to calculate the arc plasma conductivity in transformer oil.

[0111] For example, consider carrier mobility and diffusion coefficient. The diffusion coefficient is a key parameter determining plasma uniformity, and its magnitude is affected by temperature, particle density, and electric field strength. Given that carriers not only diffuse but also drift in a directional manner under the influence of an electric field, the diffusion coefficient of arc discharge plasma in oil is calculated using carrier mobility.

[0112] In plasma, charged particles (such as electrons and ions) migrate from areas of high concentration to areas of low concentration according to the concentration gradient. This migration is called diffusion. According to Fick's law, the diffusion rate is proportional to the concentration gradient. According to Einstein's law, the diffusion coefficient and mobility are related as follows:

[0113] ;

[0114] in, is the carrier mobility, is the diffusion coefficient.

[0115] Through the laboratory's high-temperature and high-field carrier mobility measurement platform based on the barrier layer electroacoustic pulse (PEA) method, the measured values of transformer oil carrier mobility at 20-80°C were obtained. Different fitting methods were used and the average value was taken to obtain the transformer oil carrier mobility at a specific temperature. The diffusion coefficient model of plasma was established by combining the Einstein relationship and the above-mentioned carrier mobility formula.

[0116] ;

[0117] in, for The carrier mobility at time t, For the upper electrode The total charge injected at time , For the interface of the double-layer dielectric The charge accumulated at all times, is the sample thickness of the dielectric layer, is the length of the barrier layer between the upper and lower electrodes.

[0118] According to the above embodiment, the specific heat capacity, thermal conductivity, electrical conductivity, carrier mobility and diffusion coefficient of the plasma in the transformer oil can be calculated.

[0119] Figure 2 The present invention is a block diagram of a device for determining physical properties of arc discharge plasma in transformer oil according to an embodiment of the present invention.

[0120] like Figure 2 As shown, the device for determining the physical properties of arc discharge plasma in transformer oil comprises:

[0121] The arc discharge module 210 is used to perform power frequency arc discharge on the transformer oil to determine the initial particle concentration of each element when the plasma channel is formed in the transformer oil, and to collect the radiation light of the power frequency arc discharge;

[0122] a spectrum analysis module 220 for performing spectrum analysis on the radiation light and determining the particle type, heavy particle temperature, electron temperature, and excited state temperature of the plasma in the transformer oil based on the spectrum analysis results;

[0123] a particle concentration determination module 230 for iteratively correcting the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil to obtain a target particle concentration for each element;

[0124] The physical property determination module 240 is configured to determine the physical properties of the plasma in the transformer oil based on the target particle concentration of each element.

[0125] In one embodiment, the arc discharge module 210 includes:

[0126] a gas density determining unit, configured to determine the gas density of the power frequency arc discharge based on the vapor pressure, evaporation heat, gas temperature, and gas volume of the power frequency arc discharge;

[0127] The first concentration determination unit is configured to determine, based on the gas density of the power frequency arc discharge, the initial particle concentration of the copper element when the plasma channel in the transformer oil is formed.

[0128] In one embodiment, the arc discharge module 210 includes:

[0129] The second concentration determination unit is used to determine the initial particle concentration of carbon element and the initial particle concentration of hydrogen element based on the volume of the plasma channel in the transformer oil and the proportion of the medium participating in the cracking reaction in the plasma channel.

[0130] In one embodiment, the spectrum analysis module 220 includes:

[0131] a particle type determination unit, configured to match the spectral characteristics in the spectral analysis result with the spectral characteristics of each particle type to determine the particle type in the plasma in the transformer oil;

[0132] a particle temperature determination unit, configured to determine a heavy particle temperature in the plasma based on ion line broadening in the spectrum analysis result;

[0133] an electron temperature determining unit, configured to determine the electron temperature in the plasma based on the temperature of heavy particles in the plasma and a temperature relationship between the electron temperature and the heavy ion temperature;

[0134] The excited state temperature determining unit is configured to determine the excited state temperature in the plasma based on the radiation intensity of the transition spectrum in the spectrum analysis result.

[0135] In one embodiment, the particle concentration determination module 230 is specifically configured to:

[0136] Using a first formula, based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil, the initial particle concentration of each element is iteratively corrected to obtain a target particle concentration of each element;

[0137] Among them, the first formula is:

[0138] ;

[0139] ;

[0140] in, represents the electron density, represents the concentration of the next ionized particle, Indicates the current concentration of ionized particles, represents the distribution function of the current ionized particles, represents the distribution function of the next ionized particle, represents the ionization energy of the current ionized particle, represents the ionization energy of the next ionized particle, represents the mass of the electron, represents Planck's constant, represents the electron temperature in the plasma, The excited state temperature in the plasma, It represents the ionization energy drop difference between the ionization energy of the current ionized particle and the ionization energy of the next ionized particle. represents the correction factor, represents the Boltzmann constant.

[0141] In one embodiment, the particle concentration determination module 230 is further configured to:

[0142] Using the second formula, the ionization energy drop difference is calculated;

[0143] Wherein, the second formula is:

[0144] ;

[0145] ;

[0146] in, represents the energy level of the current ionized particle, represents the dielectric constant, represents the Debye length, represents the total number of particle types in the plasma, represents the amount of charge on the t-th particle, represents the total number of the t-th particle, represents the heavy particle temperature.

[0147] In one embodiment, the physical property determination module 240 is specifically configured to determine the specific heat capacity, thermal conductivity, electrical conductivity, carrier mobility, and diffusion coefficient of the plasma in the transformer oil based on the target particle concentration of each element.

[0148] For the description of specific functions and examples of each module and submodule of the system in the embodiment of the present invention, please refer to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0149] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0150] According to an embodiment of the present invention, the present invention further provides a system and a readable storage medium.

[0151] Figure 3 A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0152] like Figure 3 As shown, electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. RAM 803 may also store various programs and data required for the operation of electronic device 800. Computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0153] Multiple components in the electronic device 800 are connected to the I / O interface 805, including an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0154] The computing unit 801 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above, such as the method for determining physical properties of arc discharge plasma in transformer oil. For example, in some embodiments, the method for determining physical properties of arc discharge plasma in transformer oil can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed into the electronic device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the method for determining physical properties of arc discharge plasma in transformer oil described above can be performed. Alternatively, in other embodiments, the computing unit 801 may be configured in any other appropriate manner (eg, by means of firmware) to execute the method for determining the physical properties of arc discharge plasma in transformer oil.

[0155] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0156] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0157] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0158] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0159] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0160] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0161] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. This is not limited herein.

[0162] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for determining the physical properties of arc discharge plasma in transformer oil, characterized in that: include: Performing power frequency arc discharge on transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and collecting radiation light from the power frequency arc discharge; performing a spectral analysis on the radiation light, and determining the particle types, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil based on the spectral analysis results; Using a first formula, based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil, the initial particle concentration of each element is iteratively corrected to obtain a target particle concentration of each element; determining a physical property of the plasma in the transformer oil based on the target particle concentration of each of the elements; Among them, the first formula is: ； ； in, represents the electron density, represents the concentration of the next ionized particle, Indicates the current concentration of ionized particles, represents the distribution function of the current ionized particles, represents the distribution function of the next ionized particle, represents the ionization energy of the current ionized particle, represents the ionization energy of the next ionized particle, represents the mass of the electron, represents Planck's constant, represents the electron temperature in the plasma, The excited state temperature in the plasma, It represents the ionization energy drop difference between the ionization energy of the current ionized particle and the ionization energy of the next ionized particle. represents the correction factor, represents the Boltzmann constant.

2. The method according to claim 1, characterized in that Determining the initial particle concentration of each element when the plasma channel in the transformer oil is formed includes: determining a gas density of the power frequency arc discharge based on a vapor pressure, vaporization heat, gas temperature, and gas volume of the power frequency arc discharge; Based on the gas density of the power frequency arc discharge, the initial particle concentration of the copper element when the plasma channel in the transformer oil is formed is determined.

3. The method according to claim 1, characterized in that Determining the initial particle concentration of each element when the plasma channel in the transformer oil is formed includes: The initial particle concentration of the carbon element and the initial particle concentration of the hydrogen element are determined based on the volume of the plasma channel in the transformer oil and the proportion of the medium participating in the cracking reaction in the plasma channel.

4. The method according to claim 1, wherein The determining of the particle types, heavy particle temperature, electron temperature and excited state temperature in the plasma in the transformer oil based on the spectral analysis results includes: Matching the spectral characteristics in the spectral analysis results with the spectral characteristics of each particle type to determine the particle types in the plasma in the transformer oil; determining a heavy particle temperature in the plasma based on ion line broadening in the spectral analysis result; Determining the electron temperature in the plasma based on the heavy particle temperature in the plasma and the temperature relationship between the electron temperature and the heavy ion temperature; The excited state temperature in the plasma is determined based on the radiation intensity of the transition spectrum in the spectrum analysis result.

5. The method according to claim 1, wherein Also includes: Using the second formula, the ionization energy drop difference is calculated; Wherein, the second formula is: ； ； in, represents the energy level of the current ionized particle, represents the dielectric constant, represents the Debye length, represents the total number of particle types in the plasma, Indicates the The amount of charge on the particles, Indicates the The total number of particles, represents the heavy particle temperature.

6. The method according to claim 1, characterized in that Determining the physical properties of the plasma in the transformer oil based on the target particle concentration of each of the elements includes: Based on the target particle concentration of each of the elements, the specific heat capacity, thermal conductivity, electrical conductivity, carrier mobility and diffusion coefficient of the plasma in the transformer oil are determined.

7. A device for determining the physical properties of arc discharge plasma in transformer oil, characterized in that: include: An arc discharge module is used to perform power frequency arc discharge on transformer oil to determine the initial particle concentration of each element when a plasma channel is formed in the transformer oil, and to collect radiation light from the power frequency arc discharge; a spectral analysis module, configured to perform spectral analysis on the radiated light and determine the particle types, heavy particle temperature, electron temperature, and excited state temperature of the plasma in the transformer oil based on the spectral analysis results; a particle concentration determination module, configured to iteratively correct the initial particle concentration of each element based on the particle type, heavy particle temperature, electron temperature, and excited state temperature in the plasma in the transformer oil using a first formula to obtain a target particle concentration of each element; a physical property determination module, configured to determine the physical properties of the plasma in the transformer oil based on the target particle concentration of each element; Among them, the first formula is: ； ； in, represents the electron density, represents the concentration of the next ionized particle, Indicates the current concentration of ionized particles, represents the distribution function of the current ionized particles, represents the distribution function of the next ionized particle, represents the ionization energy of the current ionized particle, represents the ionization energy of the next ionized particle, represents the mass of the electron, represents Planck's constant, represents the electron temperature in the plasma, The excited state temperature in the plasma, It represents the ionization energy drop difference between the ionization energy of the current ionized particle and the ionization energy of the next ionized particle. represents the correction factor, represents the Boltzmann constant.

8. A system for determining physical properties of arc discharge plasma in transformer oil, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the process is used to obtain the instructions from the memory and execute the instructions, so that the at least one processor can execute the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to be provided to a computer to instruct the computer to execute the method according to any one of claims 1 to 6.

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