High-frequency electric field distribution calculation method and device considering dielectric constant time characteristic

Abstract

The invention provides a high-frequency electric field distribution calculation method and device considering dielectric constant time characteristics, and belongs to the technical field of high-frequency electric field distribution calculation. The method comprises the following steps: processing an excitation signal by adopting continuous wavelet variation to obtain a wavelet quantity diagram of the excitation signal; determining an energy distribution concentration area of the excitation signal and the number of VMD decomposition layers; performing VMD decomposition on the excitation signal to obtain different IMF components; extracting the instantaneous frequency h (t) of each IMF component by using an HHT algorithm; extracting an instantaneous frequency peak distribution curve of each obtained IMF component; calculating instantaneous frequency distribution in a window function by adopting the window function; according to a calculation method for calculating the centroid, the amplitude of each IMF component is weighted, and then a synthetic instantaneous frequency is calculated; coupling the relation between the time and the instantaneous frequency and the relation curve of the dielectric constant changing along with the frequency to obtain a relation curve of the dielectric constant changing along with the time; and performing high-frequency electric field distribution calculation based on the relation curve of the dielectric constant changing with time.

Description

Technical Field

[0001] The present invention relates to the technical field of high-frequency electric field distribution calculation, and in particular to a method and device for calculating high-frequency electric field distribution taking into account the time characteristics of a dielectric constant. Background Art

[0002] The charged material of the dielectric will produce strain under the action of the electric field, and will produce charges opposite to the electrode polarity on the end face of the dielectric. This phenomenon is called dielectric polarization. The dielectric constant is used to describe the ability of the material to be polarized under the action of the electric field, that is, the relationship between the strength of the dielectric polarization and the electric field. The values ​​of the dielectric constants of various dielectrics are not the same, and the relationship between the dielectric constant and the temperature and power frequency is also inconsistent. This is because the types of microscopic polarization of different materials are not exactly the same. Common types of polarization include electronic polarization, ionic polarization and dipole polarization, as well as interlayer polarization and space polarization. Among them, dipole polarization is inelastic and takes a long time. Therefore, the relative dielectric constant of polar dielectrics is closely related to the power frequency. When the frequency is high, the dipole does not have time to rotate, and its relative dielectric constant will decrease.

[0003] During the operation of the power system, the equipment will be subjected to various voltage shocks, including lightning impulse voltage, fast transient overvoltage, etc. The equivalent frequency of these voltage waveforms is as high as several megahertz or even tens of megahertz. Within this frequency range, it is necessary to consider the relationship between the change of dielectric constant over time. Generally speaking, as the power frequency increases, the dielectric constant will decrease accordingly. In traditional electromagnetic simulation, the internal polarization establishment time of the material is often ignored, and the calculation is performed according to the constant dielectric constant. However, under the action of lightning impulse voltage or VFTO voltage, the polarization establishment time of the material cannot be directly ignored, which may easily lead to the calculated electric field failing to reflect the actual electric field strength and distribution; at the same time, for non-periodic power supply signals, there is a lack of effective decomposition methods, and Fourier approximation is often used to replace the actual frequency, which also leads to calculation errors in electric field simulation and cannot truly reflect the actual situation. Summary of the invention

[0004] In view of this, the present invention provides a method and device for calculating high-frequency electric field distribution taking into account the time characteristics of dielectric constant, providing effective dielectric constant change data for electric field calculation and improving the accuracy of electric field calculation.

[0005] The technical solution adopted by the embodiment of the present invention to solve the technical problem is:

[0006] A method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant, comprising:

[0007] Step S1, using continuous wavelet transform to process the excitation signal to obtain a wavelet quantity map of the excitation signal;

[0008] Step S2, determining the energy distribution concentration area of ​​the excitation signal and the VMD decomposition layer number I according to the wavelet volume map of the excitation signal;

[0009] Step S3, performing VMD decomposition on the excitation signal according to the obtained decomposition level I to obtain different IMF components;

[0010] Step S4, extracting the instantaneous frequency h(t) of each IMF component using the HHT algorithm;

[0011] Step S5, extracting the instantaneous frequency peak distribution curve of each of the obtained IMF components;

[0012] Step S6, using the window function to calculate the instantaneous frequency distribution within the window function;

[0013] Step S7, according to the method for calculating the centroid, weight the amplitudes of the respective IMF components and then calculate the synthetic instantaneous frequency;

[0014] Step S8, coupling the obtained relationship between time and instantaneous frequency with the relationship curve between dielectric constant and frequency to obtain a relationship curve between dielectric constant and time;

[0015] Step S9, calculating the high-frequency electric field distribution based on the dielectric constant versus time relationship curve.

[0016] Preferably, in step S1, the excitation signal f(t) is decomposed using Marr wavelet, and the expression of continuous wavelet change is:

[0017]

[0018]

[0019] Where Ψ(t) is the time domain expression of the basic wavelet function, Ψ(ω) is the frequency domain expression of the basic wavelet function, and WT f (a, b) are wavelet change coefficients, a is the scale parameter, b is the translation parameter, and t is time;

[0020] According to WT f (a, b) Expression f(t) is decomposed to obtain the wavelet quantity graph of the excitation signal f(t).

[0021] Preferably, the step S2 comprises:

[0022] The number of energy concentration regions in the wavelet volume map of the excitation signal f(t) is determined as the number of decomposition levels I required for VMD decomposition.

[0023] Preferably, the step S3 comprises:

[0024] Step S31, using Hilbert transform to obtain the single-sided spectrum corresponding to each mode for each modal component of the excitation signal f(t);

[0025] Step S32, by the translation factor e -jωit Adjust the unilateral spectrum of each mode to the estimated center frequency ω i Position, forming position signals of each mode;

[0026] Step S33, calculate the square of the gradient norm of the position signal, so as to estimate the bandwidth of the frequency-shifted component mode. The constrained variational model expression is:

[0027]

[0028] In the formula, {s i} and {ω i} are the modal component functions and corresponding center frequencies after decomposition; i is the number of decomposition levels;

[0029] Step S34, introduce the quadratic penalty factor α and the Lagrange multiplier ζ to achieve the conversion from the constrained problem to the unconstrained problem:

[0030]

[0031] Among them, L(.) is the augmented Lagrangian function;

[0032] Step S35, using the alternating direction multiplier algorithm (ADMM) method to solve the unconstrained problem function of step S34, the specific steps include:

[0033] Step S351, initialization n, and the initial value is zero, ^ represents the frequency domain form corresponding to the Fourier transform of the signal, and n is the number of iterations;

[0034] Step S352, according to Iterative formula, solve it in sequence

[0035]

[0036] In the formula, F -1 (.) is the inverse Fourier operation;

[0037] Step S353, iterative calculation The iteration formula is:

[0038]

[0039] Step S354, iterative update

[0040]

[0041] Step S355, loop the above steps until the cut-off condition is met, and the cut-off condition expression is:

[0042]

[0043] Where η is the convergence tolerance;

[0044] Iteration s i (t) is the time series Y(t) as the IMF component.

[0045] Preferably, the step S4 of extracting the IMF single-layer instantaneous frequency comprises:

[0046] Step S41, transforming the IMF time series Y(t) into an expression about X(t):

[0047]

[0048] Further transform the Y(t) signal into the analytical signal Z(t):

[0049] Z(t)=X(t)+jY(t)=a(t)e jθ(t)

[0050] According to the expression of Z(t), the instantaneous frequency h(t) is expressed as:

[0051]

[0052] Preferably, the step S7 weights the amplitudes of the respective IMF components and then calculates the synthetic instantaneous frequency according to the method for calculating the centroid, and includes:

[0053] The relationship between time, energy density and frequency is obtained after decomposition of each IMF component. Energy has different distributions at different times and frequencies. The superimposed instantaneous frequency is calculated according to the center of mass calculation principle in physics. The calculation formula is:

[0054]

[0055] Among them, f IMFn (t) represents IMF n The instantaneous frequency of E IMFn (t) represents IMF n The instantaneous energy and amplitude of , Fre(t) represents the synthetic instantaneous frequency, and represents the relationship between time and instantaneous frequency.

[0056] A high-frequency electric field distribution calculation device that takes into account the time characteristics of dielectric constant includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the aforementioned method.

[0057] It can be seen from the above technical scheme that the high-frequency electric field distribution calculation method and device considering the time characteristics of the dielectric constant provided by the embodiment of the present invention first use continuous wavelet change to process the excitation signal to obtain the wavelet quantity map of the excitation signal; determine the energy distribution concentration area of ​​the excitation signal and the number of VMD decomposition layers; perform VMD decomposition on the excitation signal to obtain different IMF components; use the HHT algorithm to extract the instantaneous frequency h(t) of each of the IMF components; extract the instantaneous frequency peak distribution curve of each of the obtained IMF components; use a window function to calculate the instantaneous frequency distribution within the window function; according to the calculation method of calculating the centroid, the amplitude of each of the IMF components is weighted and then the synthetic instantaneous frequency is calculated; the relationship between time and instantaneous frequency is coupled with the relationship curve of the dielectric constant changing with frequency to obtain the relationship curve of the dielectric constant changing with time; and the high-frequency electric field distribution is calculated based on the relationship curve of the dielectric constant changing with time. The present invention provides effective dielectric constant change data for electric field calculation, which can improve the accuracy of electric field calculation. In addition, it can also avoid the phenomenon of modal mixing that may occur in traditional calculation methods, solve the problem that similar frequencies cannot be decomposed, and improve calculation efficiency and frequency accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The figure is a flow chart of the method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant of the present invention.

[0059] Figure 2 The present invention is a block diagram of a device for implementing a method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The technical scheme and technical effects of the present invention are further elaborated in detail below in conjunction with the accompanying drawings of the present invention.

[0061] The present invention uses the energy centroid algorithm to extract the instantaneous frequency of the non-periodic voltage waveform encountered by the power system (such as lightning impulse voltage), couples the relative dielectric constant of the insulating medium with the frequency change characteristic, and accurately calculates the electric field distribution of different insulating materials as the power supply frequency changes. The present invention is suitable for maintaining the normal operation of power equipment, assessing the power insulation performance, and calculating the electric field distribution under different power supply excitations.

[0062] refer to Figure 1 As shown, the present invention provides a method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant, and the specific steps are:

[0063] A method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant, comprising:

[0064] Step S1, using continuous wavelet transform to process the excitation signal to obtain a wavelet quantity map of the excitation signal;

[0065] Step S2, determining the energy distribution concentration area of ​​the excitation signal and the VMD decomposition layer number I according to the wavelet volume map of the excitation signal; the number of energy concentration areas in the wavelet volume map of the excitation signal f(t) is used as the decomposition layer number I required for VMD decomposition, and the number of energy concentration areas can be obtained by manual or automatic identification;

[0066] Step S3, performing VMD decomposition on the excitation signal according to the obtained decomposition level I to obtain different IMF components;

[0067] Step S4, extracting the instantaneous frequency h(t) of each IMF component using the HHT algorithm;

[0068] Step S5, extracting the instantaneous frequency peak distribution curve of each obtained IMF component;

[0069] Step S6, using the window function to calculate the instantaneous frequency distribution within the window function;

[0070] Step S7, according to the calculation method of calculating the centroid, weight the amplitude of each IMF component and then calculate the synthetic instantaneous frequency;

[0071] Step S8, coupling the obtained relationship between time and instantaneous frequency with the relationship curve between dielectric constant and frequency to obtain a relationship curve between dielectric constant and time;

[0072] Step S9, calculating the high-frequency electric field distribution based on the dielectric constant versus time relationship curve.

[0073] In step S1, the principle of wavelet volume map extraction is: ψ(t)∈L 1 (R)∩L 2 (R), and Right now It is called a basic wavelet:

[0074]

[0075] Where Ψ(t) is the time domain expression of the basic wavelet function, a is the scale parameter, b is the translation parameter, and t is the time;

[0076] Marr wavelet is used to decompose the excitation signal f(t), and the expression of continuous wavelet change is:

[0077]

[0078] Where WT f (a, b) are wavelet variation coefficients; WT f (a, b) are characterized by exponential decay, non-tight support, and very good time-frequency localization characteristics;

[0079] According to WT f (a, b) Expression decomposition f(t) obtains the wavelet quantity graph of the excitation signal f(t).

[0080] Step S2 performs continuous wavelet decomposition on the signal to be analyzed to obtain the distribution of its wavelet quantity map. Generally speaking, different functions have different energy distributions. The concentrated areas are analyzed to obtain the number of decomposition layers required for VMD decomposition.

[0081] VMD is a new type of adaptive signal decomposition technology, and its main function is to decompose multi-component signals into multiple component modes with specific sparse characteristics. It requires that the center frequencies of the component signals do not overlap and have the closest bandwidth around their respective center frequencies. VMD separates the component signals through signal analysis methods such as Hilbert transform and frequency mixing under the constraint that the sum of the component signals after decomposition is equal to the original signal. Step S3 includes:

[0082] Step S31, using Hilbert transform to obtain the single-sided spectrum corresponding to each mode for each modal component of the excitation signal f(t);

[0083] Step S32, by the translation factor e -jωit Adjust the unilateral spectrum of each mode to the estimated center frequency ω i Position, forming position signals of each mode;

[0084] Step S33, calculate the square of the gradient norm of the position signal, so as to estimate the bandwidth of the component mode after frequency shift. The constrained variation model expression is:

[0085]

[0086] In the formula, {s i} and {ω i} are the modal component functions and corresponding center frequencies after decomposition; i is the number of decomposition levels;

[0087] Step S34, to solve equation (5), introduce the quadratic penalty factor α and the Lagrange multiplier ζ to achieve the transformation from the constrained problem to the unconstrained problem:

[0088]

[0089] Among them, L(.) is the augmented Lagrangian function;

[0090] Step S35, using the alternating direction multiplier algorithm (ADMM) method to solve the unconstrained problem function of step S34, the specific steps include:

[0091] Step S351, initialization n, and the initial value is zero, ^ represents the frequency domain form corresponding to the Fourier transform of the signal, n is the number of iterations, and the initial value is 1;

[0092] Step S352, iterate according to formula (7) and solve

[0093]

[0094] In the formula, F -1 (.) is the inverse Fourier operation;

[0095] Step S353, according to formula (8):

[0096]

[0097] Step S354, iterative update

[0098]

[0099] Step S355, loop the above steps until the cut-off condition is met, and the cut-off condition expression is:

[0100]

[0101] Where η is the convergence tolerance;

[0102] Iteration s i (t) is the time series Y(t) as the IMF component.

[0103] Step S4 extracting the IMF single-layer instantaneous frequency includes:

[0104] Step S41, transform the IMF time series Y(t) into an expression about X(t):

[0105]

[0106] Further transform the Y(t) signal into the analytical signal Z(t):

[0107] Z(t)=X(t)+jY(t)=a(t)e jθ(t) (12)

[0108] According to the expression of Z(t), the instantaneous frequency h(t) is expressed as:

[0109]

[0110] Step S7 weights the amplitudes of the various IMF components according to the centroid calculation method and then calculates the synthetic instantaneous frequency, including:

[0111] After decomposing different IMFs, we can get the relationship between time, energy density and frequency. Energy has different distributions at different times and frequencies. We can analyze the relationship between time and frequency by imitating the method of calculating the center of mass in physics. The principle formula for calculating the center of mass is:

[0112]

[0113] x, y are the corresponding horizontal and vertical coordinates.

[0114] According to formula (14), the calculation formula of superimposed instantaneous frequency is:

[0115]

[0116] Among them, f IMFn (t) represents IMF n The instantaneous frequency of E IMFn (t) represents IMF n The instantaneous energy and amplitude of , Fre(t) represents the synthetic instantaneous frequency, and represents the relationship between time and instantaneous frequency.

[0117] The instantaneous frequency after superposition using this method meets engineering requirements in terms of physical meaning and signal processing, and has good application value.

[0118] The high-frequency electric field distribution calculation method proposed in the present invention taking into account the time characteristics of the dielectric constant uses the energy centroid method to extract the instantaneous frequency of the voltage, couples the dielectric constant and the frequency characteristic curve, and accurately calculates the electric field distribution of the insulating material under non-periodic voltage excitation. Its benefits are:

[0119] 1) It fills the missing part of the dielectric constant changing with frequency in the electric field simulation calculation, and provides a new calculation method and idea for high-frequency electric field simulation. It improves the accuracy of electric field calculation.

[0120] 2) It provides a feasible method for extracting the instantaneous frequency of non-periodic power supply signals, and the calculation results meet objective reality and are true and effective.

[0121] 3) It solves the problem of modal overlapping that may occur in traditional calculation methods, solves the problem that similar frequencies cannot be decomposed, and improves calculation efficiency and frequency accuracy.

[0122] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0123] Figure 2 A schematic block diagram of an example electronic device 200 that can be used to implement an embodiment of the present disclosure 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 processing, cellular phones, smart phones, 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 disclosure described and / or claimed herein.

[0124] like Figure 2 As shown, the device 200 includes a computing unit 201, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 202 or a computer program loaded from a storage unit 208 into a random access memory (RAM) 203. In the RAM 203, various programs and data required for the operation of the device 200 can also be stored. The computing unit 201, the ROM 202, and the RAM 203 are connected to each other via a bus 204. An input / output (I / O) interface 205 is also connected to the bus 204.

[0125] A number of components in the device 200 are connected to the I / O interface 205, including: an input unit 206, such as a keyboard, a mouse, etc.; an output unit 207, such as various types of displays, speakers, etc.; a storage unit 208, such as a disk, an optical disk, etc.; and a communication unit 209, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 209 allows the device 200 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0126] The computing unit 201 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 201 performs the various methods and processes described above, such as the high-frequency electric field distribution calculation considering the time characteristics of the dielectric constant. For example, in some embodiments, the high-frequency electric field distribution calculation considering the time characteristics of the dielectric constant may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 208. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 200 via the ROM 202 and / or the communication unit 209. When the computer program is loaded into the RAM 203 and executed by the computing unit 201, one or more steps of the high-frequency electric field distribution calculation considering the time characteristics of the dielectric constant described above may be performed. Alternatively, in other embodiments, the calculation unit 201 may be configured in any other appropriate manner (eg, by means of firmware) to perform high-frequency electric field distribution calculation taking into account the time characteristic of the dielectric constant.

[0127] Various implementations of the systems and techniques described above 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), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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.

[0128] The program code for implementing the method disclosed in the present invention can be written in any combination of one or more programming languages. These program codes 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 the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0129] In the context disclosed by 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 equipment. 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, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0130] 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).

[0131] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend 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 backend components, middleware components, or frontend components. The components of the system may 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), a blockchain network, and the Internet.

[0132] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0133] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in the present disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document is not limited here.

[0134] What is disclosed above is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of rights of the present invention. A person skilled in the art can understand that all or part of the processes of the above embodiments and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant, characterized in that: include: Step S1, using continuous wavelet transform to process the excitation signal to obtain a wavelet quantity map of the excitation signal; Step S2, determining the energy distribution concentration area of ​​the excitation signal and the VMD decomposition layer number I according to the wavelet volume map of the excitation signal; Step S3, performing VMD decomposition on the excitation signal according to the obtained decomposition level I to obtain different IMF components; Step S4, extracting the instantaneous frequency h(t) of each IMF component using the HHT algorithm; Step S5, extracting the instantaneous frequency peak distribution curve of each of the obtained IMF components; Step S6, using the window function to calculate the instantaneous frequency distribution within the window function; Step S7, according to the method for calculating the centroid, weight the amplitudes of the respective IMF components and then calculate the synthetic instantaneous frequency; Step S8, coupling the obtained relationship between time and instantaneous frequency with the relationship curve between dielectric constant and frequency to obtain a relationship curve between dielectric constant and time; Step S9, calculating the high-frequency electric field distribution based on the dielectric constant versus time relationship curve.

2. The method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to claim 1, characterized in that: In step S1, the excitation signal f(t) is decomposed by using Marr wavelet, and the expression of continuous wavelet change is: Where Ψ(t) is the time domain expression of the basic wavelet function, Ψ(ω) is the frequency domain expression of the basic wavelet function, and WT f (a, b) are wavelet change coefficients, a is the scale parameter, b is the translation parameter, and t is time; According to WT f (a, b) Expression f(t) is decomposed to obtain the wavelet quantity graph of the excitation signal f(t).

3. The method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to claim 2, characterized in that: The step S2 comprises: The number of energy concentration regions in the wavelet volume map of the excitation signal f(t) is determined as the number of decomposition levels I required for VMD decomposition.

4. The method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to claim 3, characterized in that: The step S3 comprises: Step S31, using Hilbert transform to obtain the single-sided spectrum corresponding to each mode for each modal component of the excitation signal f(t); Step S32, by the translation factor e -jωit Adjust the unilateral spectrum of each mode to the estimated center frequency ω i Position, forming the position signal of each mode; Step S33, calculate the square of the gradient norm of the position signal, so as to estimate the bandwidth of the component mode after frequency shift. The constrained variation model expression is: In the formula, {s i } and {ω i } are the modal component functions and corresponding center frequencies after decomposition; i is the number of decomposition levels; Step S34, introduce the quadratic penalty factor α and the Lagrange multiplier ζ to achieve the conversion from the constrained problem to the unconstrained problem: Among them, L(.) is the augmented Lagrangian function; Step S35, using the alternating direction multiplier algorithm (ADMM) method to solve the unconstrained problem function of step S34, the specific steps include: Step S351, initialization n, and the initial value is zero, ^ represents the frequency domain form corresponding to the Fourier transform of the signal, and n is the number of iterations; Step S352, according to Iterative formula, solve it in sequence In the formula, F -1 (.) is the inverse Fourier operation; Step S353, iterative calculation The iteration formula is: Step S354, iterative update Step S355, loop the above steps until the cut-off condition is met, and the cut-off condition expression is: Where η is the convergence tolerance; Iteration s i (t) is the time series Y(t) as the IMF component.

5. The method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to claim 4, characterized in that: The step S4 of extracting the IMF single-layer instantaneous frequency comprises: Step S41, transforming the IMF time series Y(t) into an expression about X(t): Further transform the Y(t) signal into the analytical signal Z(t): Z(t)=X(t)+jY(t)=a(t)e jθ(t) According to the expression of Z(t), the instantaneous frequency h(t) is expressed as:

6. The method for calculating high-frequency electric field distribution considering the time characteristics of dielectric constant according to claim 5, characterized in that: The step S7 weights the amplitudes of the respective IMF components according to the method for calculating the centroid and then calculates the synthetic instantaneous frequency, including: The relationship between time, energy density and frequency is obtained after decomposition of each IMF component. Energy has different distributions at different times and frequencies. The superimposed instantaneous frequency is calculated according to the center of mass calculation principle in physics. The calculation formula is: Among them, f IMFn (t) represents IMF n The instantaneous frequency of E IMFn (t) represents IMF n The instantaneous energy and amplitude of , Fre(t) represents the synthetic instantaneous frequency, and represents the relationship between time and instantaneous frequency.

7. A high-frequency electric field distribution calculation device taking into account the time characteristics of dielectric constant, characterized in that: include: 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 instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 6.

8. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

9. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

Images